diff --git a/examples/jupyter_notebooks/Monet-analysis-example-plots-wrfChemexample_develop_aircraft_Latest.ipynb b/examples/jupyter_notebooks/Monet-analysis-example-plots-wrfChemexample_develop_aircraft_Latest.ipynb
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@@ -0,0 +1,7596 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "4834b5df",
+   "metadata": {},
+   "source": [
+    "# MONET-analysis dev \n",
+    "\n",
+    "First lets just import the driver to see how it happens and so we can play around with it a little "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "90856e9f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from melodies_monet import driver"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "25a873f0",
+   "metadata": {},
+   "source": [
+    "### Driver class\n",
+    "\n",
+    "Now lets create an instance of the python driver analysis class. It consists of 4 main parts; model instances, observation instances, a paired instance of both.  This will allow us to move things around the plotting function for spatial and overlays and more complex plots."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "323c4b19",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "an = driver.analysis()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "645d5473",
+   "metadata": {},
+   "source": [
+    "### Control File\n",
+    "\n",
+    "set the yaml control file and begin by reading the file"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "1de6f34b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'analysis': {'start_time': '2019-09-05-12:00:00',\n",
+       "  'end_time': '2019-09-06-00:00:00',\n",
+       "  'output_dir': '/wrk/qrasool/output_testaircraft_PR189_uptoviolin_multiplemodels',\n",
+       "  'debug': True},\n",
+       " 'model': {'wrfchem_v4.2': {'files': '/wrk/qrasool/firex_mech_qzhu/run_CONUS_fv19_BEIS_1.0xISO_RACM_v4.2.2_racm_berk_vcp_noI_phot_soa/0905/*',\n",
+       "   'mod_type': 'wrfchem',\n",
+       "   'mod_kwargs': {'mech': 'racm_esrl_vcp'},\n",
+       "   'radius_of_influence': 12000,\n",
+       "   'mapping': {'firexaq': {'no2': 'NO2_CL_RYERSON',\n",
+       "     'no': 'NO_CL_RYERSON',\n",
+       "     'o3': 'O3_CL_RYERSON'}},\n",
+       "   'variables': {'pres_pa_mid': {'rename': 'pressure_model',\n",
+       "     'unit_scale': 1,\n",
+       "     'unit_scale_method': '*'},\n",
+       "    'temperature_k': {'rename': 'temp_model',\n",
+       "     'unit_scale': 1,\n",
+       "     'unit_scale_method': '*'}},\n",
+       "   'projection': 'None',\n",
+       "   'plot_kwargs': {'color': 'dodgerblue', 'marker': '^', 'linestyle': ':'}},\n",
+       "  'wrfchem_v4.2_test': {'files': '/wrk/qrasool/firex_mech_qzhu/run_CONUS_fv19_BEIS_1.0xISO_RACM_v4.2.2_racm_berk_vcp_noI_phot_soa/0905/*',\n",
+       "   'mod_type': 'wrfchem',\n",
+       "   'mod_kwargs': {'mech': 'racm_esrl_vcp'},\n",
+       "   'radius_of_influence': 12000,\n",
+       "   'mapping': {'firexaq': {'no2': 'NO2_CL_RYERSON',\n",
+       "     'no': 'NO_CL_RYERSON',\n",
+       "     'o3': 'O3_CL_RYERSON'}},\n",
+       "   'variables': {'pres_pa_mid': {'rename': 'pressure_model',\n",
+       "     'unit_scale': 1,\n",
+       "     'unit_scale_method': '*'},\n",
+       "    'temperature_k': {'rename': 'temp_model',\n",
+       "     'unit_scale': 1,\n",
+       "     'unit_scale_method': '*'},\n",
+       "    'no2': {'unit_scale': 2, 'unit_scale_method': '*'},\n",
+       "    'no': {'unit_scale': 2, 'unit_scale_method': '*'},\n",
+       "    'o3': {'unit_scale': 2, 'unit_scale_method': '*'}},\n",
+       "   'projection': 'None',\n",
+       "   'plot_kwargs': {'color': 'goldenrod', 'marker': 's', 'linestyle': '-'}}},\n",
+       " 'obs': {'firexaq': {'filename': '/wrk/d2/rschwantes/obs/firex-aq/R1/10s_merge/firexaq-mrg10-dc8_merge_20190905_R1.ict',\n",
+       "   'obs_type': 'aircraft',\n",
+       "   'variables': {'O3_CL_RYERSON': {'unit_scale': 1,\n",
+       "     'unit_scale_method': '*',\n",
+       "     'nan_value': -777777,\n",
+       "     'LLOD_value': -888888,\n",
+       "     'LLOD_setvalue': 0.0,\n",
+       "     'ylabel_plot': 'Ozone (ppbv)',\n",
+       "     'vmin_plot': 15.0,\n",
+       "     'vmax_plot': 55.0,\n",
+       "     'vdiff_plot': 20.0},\n",
+       "    'NO_CL_RYERSON': {'nan_value': -777777,\n",
+       "     'LLOD_value': -888888,\n",
+       "     'LLOD_setvalue': 0.0,\n",
+       "     'ylabel_plot': 'NO (ppbv)',\n",
+       "     'vmin_plot': 0.0,\n",
+       "     'vmax_plot': 20.0,\n",
+       "     'vdiff_plot': 15.0,\n",
+       "     'nlevels_plot': 21},\n",
+       "    'NO2_CL_RYERSON': {'nan_value': -777777,\n",
+       "     'LLOD_value': -888888,\n",
+       "     'LLOD_setvalue': 0.0,\n",
+       "     'ylabel_plot': 'NO2 (ppbv)',\n",
+       "     'vmin_plot': 0.0,\n",
+       "     'vmax_plot': 20.0,\n",
+       "     'vdiff_plot': 15.0,\n",
+       "     'nlevels_plot': 21},\n",
+       "    'Latitude_YANG': {'rename': 'latitude',\n",
+       "     'unit_scale': 1,\n",
+       "     'unit_scale_method': '*'},\n",
+       "    'Longitude_YANG': {'rename': 'longitude',\n",
+       "     'unit_scale': 1,\n",
+       "     'unit_scale_method': '*'},\n",
+       "    'P_BUI': {'rename': 'pressure_obs',\n",
+       "     'unit_scale': 100,\n",
+       "     'unit_scale_method': '*'},\n",
+       "    'MSL_GPS_Altitude_YANG': {'rename': 'altitude',\n",
+       "     'unit_scale': 1,\n",
+       "     'unit_scale_method': '*'}}}},\n",
+       " 'plots': {'plot_grp1': {'type': 'timeseries',\n",
+       "   'fig_kwargs': {'figsize': [12, 6]},\n",
+       "   'default_plot_kwargs': {'linewidth': 2.0, 'markersize': 10.0},\n",
+       "   'text_kwargs': {'fontsize': 18.0},\n",
+       "   'domain_type': ['all'],\n",
+       "   'domain_name': ['CONUS'],\n",
+       "   'data': ['firexaq_wrfchem_v4.2', 'firexaq_wrfchem_v4.2_test'],\n",
+       "   'data_proc': {'rem_obs_nan': True,\n",
+       "    'ts_select_time': 'time',\n",
+       "    'ts_avg_window': None,\n",
+       "    'set_axis': False,\n",
+       "    'altitude_yax2': {'altitude_variable': 'altitude',\n",
+       "     'altitude_ticks': 1000,\n",
+       "     'ylabel2': 'Altitude (m)',\n",
+       "     'plot_kwargs_y2': {'color': 'g'},\n",
+       "     'altitude_unit': 'm',\n",
+       "     'altitude_scaling_factor': 1,\n",
+       "     'filter_dict': {'altitude': {'oper': 'between',\n",
+       "       'value': [2000, 8000]}}}}},\n",
+       "  'plot_grp2': {'type': 'vertprofile',\n",
+       "   'fig_kwargs': {'figsize': [10, 14]},\n",
+       "   'default_plot_kwargs': {'linewidth': 4.0, 'markersize': 10.0},\n",
+       "   'text_kwargs': {'fontsize': 18.0},\n",
+       "   'domain_type': ['all'],\n",
+       "   'domain_name': ['CONUS'],\n",
+       "   'data': ['firexaq_wrfchem_v4.2', 'firexaq_wrfchem_v4.2_test'],\n",
+       "   'data_proc': {'rem_obs_nan': True,\n",
+       "    'set_axis': False,\n",
+       "    'interquartile_style': 'shading'},\n",
+       "   'altitude_variable': 'altitude',\n",
+       "   'vertprofile_bins': [0,\n",
+       "    1000,\n",
+       "    2000,\n",
+       "    3000,\n",
+       "    4000,\n",
+       "    5000,\n",
+       "    6000,\n",
+       "    7000,\n",
+       "    8000,\n",
+       "    9000,\n",
+       "    10000,\n",
+       "    11000,\n",
+       "    12000],\n",
+       "   'vmin': None,\n",
+       "   'vmax': None},\n",
+       "  'plot_grp3': {'type': 'violin',\n",
+       "   'fig_kwargs': {'figsize': [10, 8]},\n",
+       "   'text_kwargs': {'fontsize': 25.0},\n",
+       "   'domain_type': ['all'],\n",
+       "   'domain_name': ['CONUS'],\n",
+       "   'data': ['firexaq_wrfchem_v4.2', 'firexaq_wrfchem_v4.2_test'],\n",
+       "   'data_proc': {'rem_obs_nan': True, 'set_axis': False}},\n",
+       "  'plot_grp4': {'type': 'scatter_density',\n",
+       "   'fig_kwargs': {'figsize': [10, 10]},\n",
+       "   'default_plot_kwargs': {'linewidth': 4.0, 'markersize': 10.0},\n",
+       "   'text_kwargs': {'fontsize': 18.0},\n",
+       "   'domain_type': ['all'],\n",
+       "   'domain_name': ['CONUS'],\n",
+       "   'data': ['firexaq_wrfchem_v4.2', 'firexaq_wrfchem_v4.2_test'],\n",
+       "   'data_proc': {'rem_obs_nan': True,\n",
+       "    'set_axis': False,\n",
+       "    'vmin_x': None,\n",
+       "    'vmax_x': None,\n",
+       "    'vmin_y': None,\n",
+       "    'vmax_y': None},\n",
+       "   'color_map': {'colors': ['royalblue', 'cyan', 'yellow', 'orange'],\n",
+       "    'over': 'red',\n",
+       "    'under': 'blue'},\n",
+       "   'xlabel': 'Model',\n",
+       "   'ylabel': 'Observation',\n",
+       "   'title': 'Scatter Density Plot',\n",
+       "   'fill': True,\n",
+       "   'shade_lowest': True,\n",
+       "   'vcenter': None,\n",
+       "   'extensions': ['min', 'max']},\n",
+       "  'plot_grp5': {'type': 'taylor',\n",
+       "   'fig_kwargs': {'figsize': [8, 8]},\n",
+       "   'default_plot_kwargs': {'linewidth': 2.0, 'markersize': 10.0},\n",
+       "   'text_kwargs': {'fontsize': 16.0},\n",
+       "   'domain_type': ['all'],\n",
+       "   'domain_name': ['CONUS'],\n",
+       "   'data': ['firexaq_wrfchem_v4.2', 'firexaq_wrfchem_v4.2_test'],\n",
+       "   'data_proc': {'rem_obs_nan': True, 'set_axis': True}},\n",
+       "  'plot_grp6': {'type': 'boxplot',\n",
+       "   'fig_kwargs': {'figsize': [8, 6]},\n",
+       "   'text_kwargs': {'fontsize': 20.0},\n",
+       "   'domain_type': ['all'],\n",
+       "   'domain_name': ['CONUS'],\n",
+       "   'data': ['firexaq_wrfchem_v4.2', 'firexaq_wrfchem_v4.2_test'],\n",
+       "   'data_proc': {'rem_obs_nan': True, 'set_axis': False}}},\n",
+       " 'stats': {'stat_list': ['MB', 'MdnB', 'R2', 'RMSE'],\n",
+       "  'round_output': 2,\n",
+       "  'output_table': False,\n",
+       "  'output_table_kwargs': {'figsize': [7, 3],\n",
+       "   'fontsize': 12.0,\n",
+       "   'xscale': 1.4,\n",
+       "   'yscale': 1.4,\n",
+       "   'edges': 'horizontal'},\n",
+       "  'domain_type': ['all'],\n",
+       "  'domain_name': ['CONUS'],\n",
+       "  'data': ['firexaq_wrfchem_v4.2', 'firexaq_wrfchem_v4.2_test']}}"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "an.control = '../yaml/control_wrfchem_aircraft_Latestfor_develop_aircraft_testmultiplemodelgroups.yaml'\n",
+    "                #'MELODIES-MONET/examples/yaml/control_wrfchem_aircraft.yaml' \n",
+    "               #'control_wrfchem_aircraft_test2.yaml'\n",
+    "                \n",
+    "an.read_control() \n",
+    "an.control_dict   "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9d4d5be4",
+   "metadata": {},
+   "source": [
+    "### Loading the model data \n",
+    "\n",
+    "driver will automatically loop through the \"models\" found in the model section of the yaml file and create an instance of the driver.model class for each that includes the label, mapping information, and xarray object as well as the filenames.  Note it can open multiple files easily by including hot keys "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "a5474cf2",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "NOTE: model.wrfchem_v4.2.projection is 'None' (str), but we assume you want `None` (Python null sentinel). To avoid this warning, update your control file to remove the projection setting or set to `~` or `null` if you want null value in YAML.\n",
+      "/wrk/qrasool/firex_mech_qzhu/run_CONUS_fv19_BEIS_1.0xISO_RACM_v4.2.2_racm_berk_vcp_noI_phot_soa/0905/*\n",
+      "**** Reading WRF-Chem model output...\n",
+      "NOTE: model.wrfchem_v4.2_test.projection is 'None' (str), but we assume you want `None` (Python null sentinel). To avoid this warning, update your control file to remove the projection setting or set to `~` or `null` if you want null value in YAML.\n",
+      "/wrk/qrasool/firex_mech_qzhu/run_CONUS_fv19_BEIS_1.0xISO_RACM_v4.2.2_racm_berk_vcp_noI_phot_soa/0905/*\n",
+      "**** Reading WRF-Chem model output...\n"
+     ]
+    }
+   ],
+   "source": [
+    "an.open_models()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "55185914",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'wrfchem_v4.2': model(\n",
+       "     model='wrfchem',\n",
+       "     radius_of_influence=12000,\n",
+       "     mod_kwargs={'mech': 'racm_esrl_vcp', 'var_list': ['no', 'o3', 'no2', 'pres', 'height', 'tk', 'height_agl', 'PSFC']},\n",
+       "     file_str='/wrk/qrasool/firex_mech_qzhu/run_CONUS_fv19_BEIS_1.0xISO_RACM_v4.2.2_racm_berk_vcp_noI_phot_soa/0905/*',\n",
+       "     label='wrfchem_v4.2',\n",
+       "     obj=...,\n",
+       "     mapping={'firexaq': {'no2': 'NO2_CL_RYERSON', 'no': 'NO_CL_RYERSON', 'o3': 'O3_CL_RYERSON'}},\n",
+       "     label='wrfchem_v4.2',\n",
+       "     ...\n",
+       " ),\n",
+       " 'wrfchem_v4.2_test': model(\n",
+       "     model='wrfchem',\n",
+       "     radius_of_influence=12000,\n",
+       "     mod_kwargs={'mech': 'racm_esrl_vcp', 'var_list': ['no', 'o3', 'no2', 'pres', 'height', 'tk', 'height_agl', 'PSFC']},\n",
+       "     file_str='/wrk/qrasool/firex_mech_qzhu/run_CONUS_fv19_BEIS_1.0xISO_RACM_v4.2.2_racm_berk_vcp_noI_phot_soa/0905/*',\n",
+       "     label='wrfchem_v4.2_test',\n",
+       "     obj=...,\n",
+       "     mapping={'firexaq': {'no2': 'NO2_CL_RYERSON', 'no': 'NO_CL_RYERSON', 'o3': 'O3_CL_RYERSON'}},\n",
+       "     label='wrfchem_v4.2_test',\n",
+       "     ...\n",
+       " )}"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "an.models"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "cdbcd6e7",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
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+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: '►';\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: '▼';\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
+       "Dimensions:         (y: 284, x: 440, time: 31, z: 50)\n",
+       "Coordinates:\n",
+       "    longitude       (y, x) float32 -122.3 -122.2 -122.1 ... -60.68 -60.52 -60.37\n",
+       "    latitude        (y, x) float32 21.19 21.22 21.24 21.27 ... 50.28 50.24 50.2\n",
+       "  * time            (time) datetime64[ns] 2019-09-05 ... 2019-09-06T06:00:00\n",
+       "Dimensions without coordinates: y, x, z\n",
+       "Data variables:\n",
+       "    no              (time, z, y, x) float32 0.004484 0.004511 ... 5.302e-09\n",
+       "    o3              (time, z, y, x) float32 28.46 28.46 ... 1.971e+03 1.971e+03\n",
+       "    no2             (time, z, y, x) float32 0.01467 0.01473 ... 0.08481 0.08481\n",
+       "    pressure_model  (time, z, y, x) float32 1.007e+05 1.007e+05 ... 5.584e+03\n",
+       "    alt_msl_m_mid   (time, z, y, x) float32 11.4 11.39 ... 2.016e+04 2.016e+04\n",
+       "    temp_model      (time, z, y, x) float32 297.0 296.9 296.8 ... 220.5 220.4\n",
+       "    alt_agl_m_mid   (time, z, y, x) float32 11.41 11.4 ... 2.015e+04 2.016e+04\n",
+       "    surfpres_pa     (time, y, x) float32 1.008e+05 1.008e+05 ... 1.007e+05\n",
+       "Attributes: (12/15)\n",
+       "    FieldType:                 104\n",
+       "    MemoryOrder:               XYZ\n",
+       "    description:               NO mixing ratio\n",
+       "    units:                     ppmv\n",
+       "    stagger:                   \n",
+       "    coordinates:               XLONG XLAT XTIME\n",
+       "    ...                        ...\n",
+       "    MOAD_CEN_LAT:              39.617638\n",
+       "    STAND_LON:                 -97.0\n",
+       "    MAP_PROJ:                  1\n",
+       "    CEN_LAT:                   39.617638\n",
+       "    CEN_LON:                   -97.77487\n",
+       "    mapping_tables_to_airnow:  {&#x27;OZONE&#x27;: &#x27;o3&#x27;, &#x27;PM2.5&#x27;: &#x27;PM2_5_DRY&#x27;, &#x27;PM10&#x27;: ...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-33b62cd0-eee6-4f99-85ef-fc3a2ccaece9' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-33b62cd0-eee6-4f99-85ef-fc3a2ccaece9' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>y</span>: 284</li><li><span>x</span>: 440</li><li><span class='xr-has-index'>time</span>: 31</li><li><span>z</span>: 50</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-a3f70d6d-37d8-44ce-ac71-bd5b3885b1bf' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a3f70d6d-37d8-44ce-ac71-bd5b3885b1bf' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-122.3 -122.2 ... -60.52 -60.37</div><input id='attrs-6fbe1aaa-512d-424a-8c74-1573a8ac0c28' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6fbe1aaa-512d-424a-8c74-1573a8ac0c28' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-02530e7e-a9a6-46fe-a2d6-033ff4c13604' class='xr-var-data-in' type='checkbox'><label for='data-02530e7e-a9a6-46fe-a2d6-033ff4c13604' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>TRUELAT1 :</span></dt><dd>33.0</dd><dt><span>TRUELAT2 :</span></dt><dd>45.0</dd><dt><span>MOAD_CEN_LAT :</span></dt><dd>39.617638</dd><dt><span>STAND_LON :</span></dt><dd>-97.0</dd><dt><span>MAP_PROJ :</span></dt><dd>1</dd><dt><span>CEN_LAT :</span></dt><dd>39.617638</dd><dt><span>CEN_LON :</span></dt><dd>-97.77487</dd></dl></div><div class='xr-var-data'><pre>array([[-122.282745, -122.17581 , -122.0688  , ...,  -73.00513 ,\n",
+       "         -72.8974  ,  -72.789795],\n",
+       "       [-122.31329 , -122.20625 , -122.09914 , ...,  -72.97595 ,\n",
+       "         -72.86813 ,  -72.760376],\n",
+       "       [-122.34393 , -122.236786, -122.12955 , ...,  -72.94672 ,\n",
+       "         -72.838776,  -72.730896],\n",
+       "       ...,\n",
+       "       [-135.0139  , -134.86354 , -134.71295 , ...,  -60.804962,\n",
+       "         -60.65219 ,  -60.499634],\n",
+       "       [-135.08081 , -134.93024 , -134.77945 , ...,  -60.74051 ,\n",
+       "         -60.587524,  -60.434753],\n",
+       "       [-135.14793 , -134.99716 , -134.84618 , ...,  -60.675873,\n",
+       "         -60.522675,  -60.36969 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>21.19 21.22 21.24 ... 50.24 50.2</div><input id='attrs-79191838-c9c7-4b2a-871c-8d9ffd2225e0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-79191838-c9c7-4b2a-871c-8d9ffd2225e0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-40d3d646-7cfd-4165-bc20-4cf0a61c8c3f' class='xr-var-data-in' type='checkbox'><label for='data-40d3d646-7cfd-4165-bc20-4cf0a61c8c3f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>TRUELAT1 :</span></dt><dd>33.0</dd><dt><span>TRUELAT2 :</span></dt><dd>45.0</dd><dt><span>MOAD_CEN_LAT :</span></dt><dd>39.617638</dd><dt><span>STAND_LON :</span></dt><dd>-97.0</dd><dt><span>MAP_PROJ :</span></dt><dd>1</dd><dt><span>CEN_LAT :</span></dt><dd>39.617638</dd><dt><span>CEN_LON :</span></dt><dd>-97.77487</dd></dl></div><div class='xr-var-data'><pre>array([[21.18737 , 21.215775, 21.244072, ..., 21.520782, 21.493614,\n",
+       "        21.466347],\n",
+       "       [21.287056, 21.315514, 21.343864, ..., 21.621033, 21.593834,\n",
+       "        21.566513],\n",
+       "       [21.386795, 21.41529 , 21.443687, ..., 21.721321, 21.694077,\n",
+       "        21.66671 ],\n",
+       "       ...,\n",
+       "       [49.581253, 49.624477, 49.667526, ..., 50.08878 , 50.047417,\n",
+       "        50.005882],\n",
+       "       [49.678635, 49.721916, 49.76504 , ..., 50.18683 , 50.145416,\n",
+       "        50.103832],\n",
+       "       [49.775967, 49.819294, 49.862473, ..., 50.28482 , 50.24335 ,\n",
+       "        50.20171 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-09-05 ... 2019-09-06T06:00:00</div><input id='attrs-81d2c523-710a-4804-9ae1-f122ae4263a5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-81d2c523-710a-4804-9ae1-f122ae4263a5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-90969736-d454-479d-a1e7-c5167ae551c6' class='xr-var-data-in' type='checkbox'><label for='data-90969736-d454-479d-a1e7-c5167ae551c6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>TRUELAT1 :</span></dt><dd>33.0</dd><dt><span>TRUELAT2 :</span></dt><dd>45.0</dd><dt><span>MOAD_CEN_LAT :</span></dt><dd>39.617638</dd><dt><span>STAND_LON :</span></dt><dd>-97.0</dd><dt><span>MAP_PROJ :</span></dt><dd>1</dd><dt><span>CEN_LAT :</span></dt><dd>39.617638</dd><dt><span>CEN_LON :</span></dt><dd>-97.77487</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-09-05T00:00:00.000000000&#x27;, &#x27;2019-09-05T01:00:00.000000000&#x27;,\n",
+       "       &#x27;2019-09-05T02:00:00.000000000&#x27;, &#x27;2019-09-05T03:00:00.000000000&#x27;,\n",
+       "       &#x27;2019-09-05T04:00:00.000000000&#x27;, &#x27;2019-09-05T05:00:00.000000000&#x27;,\n",
+       "       &#x27;2019-09-05T06:00:00.000000000&#x27;, &#x27;2019-09-05T07:00:00.000000000&#x27;,\n",
+       "       &#x27;2019-09-05T08:00:00.000000000&#x27;, &#x27;2019-09-05T09:00:00.000000000&#x27;,\n",
+       "       &#x27;2019-09-05T10:00:00.000000000&#x27;, &#x27;2019-09-05T11:00:00.000000000&#x27;,\n",
+       "       &#x27;2019-09-05T12:00:00.000000000&#x27;, &#x27;2019-09-05T13:00:00.000000000&#x27;,\n",
+       "       &#x27;2019-09-05T14:00:00.000000000&#x27;, &#x27;2019-09-05T15:00:00.000000000&#x27;,\n",
+       "       &#x27;2019-09-05T16:00:00.000000000&#x27;, &#x27;2019-09-05T17:00:00.000000000&#x27;,\n",
+       "       &#x27;2019-09-05T18:00:00.000000000&#x27;, &#x27;2019-09-05T19:00:00.000000000&#x27;,\n",
+       "       &#x27;2019-09-05T20:00:00.000000000&#x27;, &#x27;2019-09-05T21:00:00.000000000&#x27;,\n",
+       "       &#x27;2019-09-05T22:00:00.000000000&#x27;, &#x27;2019-09-05T23:00:00.000000000&#x27;,\n",
+       "       &#x27;2019-09-06T00:00:00.000000000&#x27;, &#x27;2019-09-06T01:00:00.000000000&#x27;,\n",
+       "       &#x27;2019-09-06T02:00:00.000000000&#x27;, &#x27;2019-09-06T03:00:00.000000000&#x27;,\n",
+       "       &#x27;2019-09-06T04:00:00.000000000&#x27;, &#x27;2019-09-06T05:00:00.000000000&#x27;,\n",
+       "       &#x27;2019-09-06T06:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c8966802-4186-4c2f-8549-b77232258513' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c8966802-4186-4c2f-8549-b77232258513' class='xr-section-summary' >Data variables: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>no</span></div><div class='xr-var-dims'>(time, z, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.004484 0.004511 ... 5.302e-09</div><input id='attrs-8050890e-72f7-4c15-9f47-b6965ff1ae43' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8050890e-72f7-4c15-9f47-b6965ff1ae43' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6c6e14c3-92c0-4102-bcdd-3f31614e96b8' class='xr-var-data-in' type='checkbox'><label for='data-6c6e14c3-92c0-4102-bcdd-3f31614e96b8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd></dl></div><div class='xr-var-data'><pre>array([[[[4.48352797e-03, 4.51092282e-03, 4.71630553e-03, ...,\n",
+       "          3.89743276e-04, 1.16604002e-04, 3.14356803e-05],\n",
+       "         [4.48922534e-03, 4.50808462e-03, 4.58325492e-03, ...,\n",
+       "          5.54059079e-06, 2.12863742e-04, 9.52260137e-08],\n",
+       "         [4.65722848e-03, 4.67358157e-03, 4.59262542e-03, ...,\n",
+       "          2.51346421e-07, 5.90306008e-05, 8.77960247e-08],\n",
+       "         ...,\n",
+       "         [3.16438526e-02, 3.18967737e-02, 4.20151576e-02, ...,\n",
+       "          1.33096194e-02, 1.09915184e-02, 2.17261373e-07],\n",
+       "         [4.17759791e-02, 4.39619236e-02, 4.91272584e-02, ...,\n",
+       "          6.27219561e-04, 3.65893985e-03, 1.75882107e-07],\n",
+       "         [4.04302478e-02, 4.07214016e-02, 4.72229682e-02, ...,\n",
+       "          2.21720446e-04, 9.29756905e-04, 1.26779592e-03]],\n",
+       "\n",
+       "        [[4.50818194e-03, 4.52949293e-03, 4.69338661e-03, ...,\n",
+       "          1.93041167e-04, 6.22087973e-05, 2.02766005e-05],\n",
+       "         [4.51386347e-03, 4.52735741e-03, 4.60344926e-03, ...,\n",
+       "          2.89745708e-06, 1.01125443e-04, 9.51351637e-08],\n",
+       "         [4.66857897e-03, 4.66694403e-03, 4.59684990e-03, ...,\n",
+       "          1.75344042e-07, 2.89718646e-05, 8.76234125e-08],\n",
+       "...\n",
+       "          6.10064488e-09, 6.06382233e-09, 6.06377615e-09],\n",
+       "         [6.54032206e-09, 9.59562294e-06, 3.59380238e-07, ...,\n",
+       "          6.14246831e-09, 6.12300299e-09, 6.12296081e-09],\n",
+       "         [9.57991415e-06, 9.57553220e-06, 3.59108924e-07, ...,\n",
+       "          6.14218854e-09, 6.12269568e-09, 6.12280049e-09]],\n",
+       "\n",
+       "        [[2.95271763e-09, 2.95218117e-09, 2.95060931e-09, ...,\n",
+       "          8.03064104e-09, 7.27653005e-09, 7.27670280e-09],\n",
+       "         [5.28374330e-05, 5.28011697e-05, 5.29554382e-05, ...,\n",
+       "          8.03076450e-09, 7.27718419e-09, 3.20829630e-09],\n",
+       "         [2.71064641e-06, 2.70836586e-06, 2.70908959e-06, ...,\n",
+       "          8.03441758e-09, 7.28479765e-09, 3.20945803e-09],\n",
+       "         ...,\n",
+       "         [8.21414314e-09, 3.41795044e-06, 1.05223990e-07, ...,\n",
+       "          5.26658939e-09, 5.09401321e-09, 5.09401010e-09],\n",
+       "         [8.21570278e-09, 3.04853847e-06, 8.13067871e-08, ...,\n",
+       "          5.51147661e-09, 5.30260102e-09, 5.30255750e-09],\n",
+       "         [3.04342302e-06, 3.04182754e-06, 8.12193051e-08, ...,\n",
+       "          5.51125101e-09, 5.30236566e-09, 5.30246025e-09]]]],\n",
+       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>o3</span></div><div class='xr-var-dims'>(time, z, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>28.46 28.46 ... 1.971e+03 1.971e+03</div><input id='attrs-4646737b-89c8-4740-af30-0310a1da583e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4646737b-89c8-4740-af30-0310a1da583e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eb1abd43-acd3-47cd-87e3-62bb4f9c2706' class='xr-var-data-in' type='checkbox'><label for='data-eb1abd43-acd3-47cd-87e3-62bb4f9c2706' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd></dl></div><div class='xr-var-data'><pre>array([[[[  28.461918,   28.460806,   27.890722, ...,   30.844538,\n",
+       "            30.63243 ,   30.645164],\n",
+       "         [  28.461508,   28.456303,   27.886086, ...,   31.03633 ,\n",
+       "            30.617105,   30.031328],\n",
+       "         [  28.702957,   28.696598,   28.136173, ...,   30.730406,\n",
+       "            30.416647,   29.827269],\n",
+       "         ...,\n",
+       "         [  24.212223,   24.21073 ,   24.417244, ...,   29.011135,\n",
+       "            30.232214,   31.576689],\n",
+       "         [  24.160465,   24.150948,   24.185417, ...,   27.652838,\n",
+       "            29.02698 ,   30.448254],\n",
+       "         [  24.164972,   24.160227,   24.194767, ...,   27.802938,\n",
+       "            29.029522,   29.011948]],\n",
+       "\n",
+       "        [[  28.480263,   28.479702,   27.91234 , ...,   31.030422,\n",
+       "            30.70334 ,   30.715847],\n",
+       "         [  28.479708,   28.47905 ,   27.909008, ...,   31.09924 ,\n",
+       "            30.685825,   30.057844],\n",
+       "         [  28.720932,   28.720545,   28.160027, ...,   30.790312,\n",
+       "            30.480305,   29.8513  ],\n",
+       "...\n",
+       "         [1177.938   , 1171.0818  , 1167.5234  , ..., 1488.2415  ,\n",
+       "          1480.2834  , 1480.2834  ],\n",
+       "         [1185.967   , 1182.5833  , 1176.6971  , ..., 1496.9712  ,\n",
+       "          1485.5243  , 1485.5243  ],\n",
+       "         [1182.5831  , 1182.5834  , 1176.6971  , ..., 1496.9711  ,\n",
+       "          1485.5243  , 1485.5243  ]],\n",
+       "\n",
+       "        [[1228.5924  , 1229.3324  , 1230.011   , ..., 1125.4436  ,\n",
+       "          1126.2831  , 1126.2831  ],\n",
+       "         [1230.3696  , 1230.3696  , 1230.3693  , ..., 1125.4436  ,\n",
+       "          1126.2831  , 1127.1045  ],\n",
+       "         [1230.4044  , 1230.4044  , 1230.41    , ..., 1124.7418  ,\n",
+       "          1126.3569  , 1127.6458  ],\n",
+       "         ...,\n",
+       "         [1785.8556  , 1784.9581  , 1785.7219  , ..., 1982.914   ,\n",
+       "          1990.4944  , 1990.4944  ],\n",
+       "         [1791.1445  , 1791.6699  , 1790.6383  , ..., 1940.3529  ,\n",
+       "          1970.5532  , 1970.5532  ],\n",
+       "         [1791.6699  , 1791.6699  , 1790.6383  , ..., 1940.3529  ,\n",
+       "          1970.5532  , 1970.5532  ]]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>no2</span></div><div class='xr-var-dims'>(time, z, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.01467 0.01473 ... 0.08481 0.08481</div><input id='attrs-1752a0af-3595-4e9d-b731-2db14e9f9436' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1752a0af-3595-4e9d-b731-2db14e9f9436' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-acba78f3-e545-4546-9760-3f0036238687' class='xr-var-data-in' type='checkbox'><label for='data-acba78f3-e545-4546-9760-3f0036238687' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd></dl></div><div class='xr-var-data'><pre>array([[[[0.0146713 , 0.01473413, 0.01500142, ..., 0.0498601 ,\n",
+       "          0.05344776, 0.0530177 ],\n",
+       "         [0.01466483, 0.01464844, 0.0146572 , ..., 0.04878013,\n",
+       "          0.05394015, 0.0534546 ],\n",
+       "         [0.01521287, 0.01520134, 0.01473507, ..., 0.0444545 ,\n",
+       "          0.04823257, 0.05023834],\n",
+       "         ...,\n",
+       "         [0.07055512, 0.07107425, 0.09335505, ..., 0.47129953,\n",
+       "          0.35520932, 0.19248094],\n",
+       "         [0.09127434, 0.09432675, 0.10663554, ..., 0.31403798,\n",
+       "          0.2787688 , 0.17906879],\n",
+       "         [0.08935987, 0.09001682, 0.10405079, ..., 0.30077162,\n",
+       "          0.26228178, 0.2749267 ]],\n",
+       "\n",
+       "        [[0.01464196, 0.0146923 , 0.01488151, ..., 0.04913152,\n",
+       "          0.05241894, 0.05212831],\n",
+       "         [0.01463551, 0.01462378, 0.01463614, ..., 0.04851838,\n",
+       "          0.05274872, 0.0528254 ],\n",
+       "         [0.01514442, 0.01511282, 0.01467667, ..., 0.0443302 ,\n",
+       "          0.04767425, 0.04965715],\n",
+       "...\n",
+       "         [0.26594782, 0.25918618, 0.25624153, ..., 0.0993861 ,\n",
+       "          0.09891113, 0.09891116],\n",
+       "         [0.2647122 , 0.25743043, 0.25417268, ..., 0.09847514,\n",
+       "          0.0981034 , 0.09810342],\n",
+       "         [0.25743017, 0.2574301 , 0.25417253, ..., 0.09847502,\n",
+       "          0.09810326, 0.09810332]],\n",
+       "\n",
+       "        [[0.3155686 , 0.31509677, 0.31462678, ..., 0.30466434,\n",
+       "          0.30502987, 0.30502984],\n",
+       "         [0.3093899 , 0.30938983, 0.309105  , ..., 0.30466425,\n",
+       "          0.30502978, 0.3055648 ],\n",
+       "         [0.30606237, 0.30606222, 0.30580154, ..., 0.30449325,\n",
+       "          0.30484608, 0.30538806],\n",
+       "         ...,\n",
+       "         [0.2863115 , 0.27792963, 0.27944568, ..., 0.08666716,\n",
+       "          0.08281111, 0.08281111],\n",
+       "         [0.28511542, 0.27649722, 0.2785407 , ..., 0.08867354,\n",
+       "          0.08480635, 0.08480634],\n",
+       "         [0.27649692, 0.27649683, 0.27854046, ..., 0.08867337,\n",
+       "          0.08480621, 0.08480628]]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure_model</span></div><div class='xr-var-dims'>(time, z, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.007e+05 1.007e+05 ... 5.584e+03</div><input id='attrs-b1963965-8384-4152-8f18-421f50daf594' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b1963965-8384-4152-8f18-421f50daf594' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-083b9cd0-e99a-4c03-9587-1cd480f8f00e' class='xr-var-data-in' type='checkbox'><label for='data-083b9cd0-e99a-4c03-9587-1cd480f8f00e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XYZ</dd><dt><span>description :</span></dt><dd>pressure</dd><dt><span>units :</span></dt><dd>Pa</dd><dt><span>stagger :</span></dt><dd></dd><dt><span>coordinates :</span></dt><dd>XLONG XLAT XTIME</dd><dt><span>projection :</span></dt><dd>LambertConformal(stand_lon=-97.0, moad_cen_lat=39.617637634277344, truelat1=33.0, truelat2=45.0, pole_lat=90.0, pole_lon=0.0)</dd><dt><span>TRUELAT1 :</span></dt><dd>33.0</dd><dt><span>TRUELAT2 :</span></dt><dd>45.0</dd><dt><span>MOAD_CEN_LAT :</span></dt><dd>39.617638</dd><dt><span>STAND_LON :</span></dt><dd>-97.0</dd><dt><span>MAP_PROJ :</span></dt><dd>1</dd><dt><span>CEN_LAT :</span></dt><dd>39.617638</dd><dt><span>CEN_LON :</span></dt><dd>-97.77487</dd></dl></div><div class='xr-var-data'><pre>array([[[[100695.47  , 100689.26  , 100682.42  , ..., 101406.11  ,\n",
+       "          101405.414 , 101404.5   ],\n",
+       "         [100701.8   , 100695.72  , 100688.96  , ..., 101413.66  ,\n",
+       "          101412.93  , 101412.46  ],\n",
+       "         [100708.14  , 100701.734 , 100695.56  , ..., 101421.39  ,\n",
+       "          101420.98  , 101420.76  ],\n",
+       "         ...,\n",
+       "         [101906.36  , 101913.96  , 101921.    , ..., 100865.484 ,\n",
+       "          100891.89  , 100919.57  ],\n",
+       "         [101907.18  , 101914.93  , 101922.52  , ..., 100859.25  ,\n",
+       "          100901.984 , 100931.55  ],\n",
+       "         [101907.97  , 101916.08  , 101923.12  , ..., 100739.65  ,\n",
+       "          100836.24  , 100902.734 ]],\n",
+       "\n",
+       "        [[100423.98  , 100417.74  , 100410.984 , ..., 101131.2   ,\n",
+       "          101130.57  , 101129.71  ],\n",
+       "         [100430.3   , 100424.195 , 100417.49  , ..., 101138.75  ,\n",
+       "          101138.07  , 101137.6   ],\n",
+       "         [100436.58  , 100430.266 , 100424.15  , ..., 101146.55  ,\n",
+       "          101146.09  , 101145.89  ],\n",
+       "...\n",
+       "         [  6809.747 ,   6809.615 ,   6809.5645, ...,   6810.289 ,\n",
+       "            6810.175 ,   6809.7515],\n",
+       "         [  6809.7515,   6809.456 ,   6809.489 , ...,   6810.19  ,\n",
+       "            6809.901 ,   6809.758 ],\n",
+       "         [  6809.7456,   6809.7515,   6809.747 , ...,   6809.7524,\n",
+       "            6809.751 ,   6809.7554]],\n",
+       "\n",
+       "        [[  5584.2515,   5584.247 ,   5584.246 , ...,   5584.248 ,\n",
+       "            5584.2515,   5584.247 ],\n",
+       "         [  5584.246 ,   5584.633 ,   5585.0054, ...,   5583.936 ,\n",
+       "            5583.914 ,   5584.245 ],\n",
+       "         [  5584.2544,   5584.7065,   5584.9233, ...,   5583.509 ,\n",
+       "            5583.6606,   5584.246 ],\n",
+       "         ...,\n",
+       "         [  5584.2544,   5583.984 ,   5584.089 , ...,   5583.7695,\n",
+       "            5583.8877,   5584.2495],\n",
+       "         [  5584.2524,   5584.0435,   5583.96  , ...,   5583.7227,\n",
+       "            5583.842 ,   5584.249 ],\n",
+       "         [  5584.2524,   5584.2495,   5584.2495, ...,   5584.246 ,\n",
+       "            5584.2534,   5584.2544]]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>alt_msl_m_mid</span></div><div class='xr-var-dims'>(time, z, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>11.4 11.39 ... 2.016e+04 2.016e+04</div><input id='attrs-cd88856c-76f0-4020-9d15-76a687801f38' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cd88856c-76f0-4020-9d15-76a687801f38' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e11cc573-7fee-41b1-b87f-fb49c2087095' class='xr-var-data-in' type='checkbox'><label for='data-e11cc573-7fee-41b1-b87f-fb49c2087095' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XYZ</dd><dt><span>description :</span></dt><dd>model height - [MSL] (mass grid)</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>stagger :</span></dt><dd></dd><dt><span>coordinates :</span></dt><dd>XLONG XLAT XTIME</dd><dt><span>projection :</span></dt><dd>LambertConformal(stand_lon=-97.0, moad_cen_lat=39.617637634277344, truelat1=33.0, truelat2=45.0, pole_lat=90.0, pole_lon=0.0)</dd><dt><span>TRUELAT1 :</span></dt><dd>33.0</dd><dt><span>TRUELAT2 :</span></dt><dd>45.0</dd><dt><span>MOAD_CEN_LAT :</span></dt><dd>39.617638</dd><dt><span>STAND_LON :</span></dt><dd>-97.0</dd><dt><span>MAP_PROJ :</span></dt><dd>1</dd><dt><span>CEN_LAT :</span></dt><dd>39.617638</dd><dt><span>CEN_LON :</span></dt><dd>-97.77487</dd></dl></div><div class='xr-var-data'><pre>array([[[[1.13956261e+01, 1.13915205e+01, 1.13885164e+01, ...,\n",
+       "          1.17076454e+01, 1.17046232e+01, 1.17031908e+01],\n",
+       "         [1.13917227e+01, 1.13889999e+01, 1.13874235e+01, ...,\n",
+       "          1.17069454e+01, 1.17042618e+01, 1.17041187e+01],\n",
+       "         [1.13890944e+01, 1.13880882e+01, 1.13865299e+01, ...,\n",
+       "          1.17068577e+01, 1.17055378e+01, 1.17033911e+01],\n",
+       "         ...,\n",
+       "         [1.10290060e+01, 1.10270195e+01, 1.10245380e+01, ...,\n",
+       "          9.21303368e+00, 9.13495445e+00, 9.13425636e+00],\n",
+       "         [1.10262518e+01, 1.10237560e+01, 1.10156584e+01, ...,\n",
+       "          1.10823402e+01, 9.57869911e+00, 9.21612263e+00],\n",
+       "         [1.10237846e+01, 1.10201750e+01, 1.10143795e+01, ...,\n",
+       "          2.27575455e+01, 1.69050579e+01, 1.31301870e+01]],\n",
+       "\n",
+       "        [[3.50668907e+01, 3.50537491e+01, 3.50467453e+01, ...,\n",
+       "          3.60334091e+01, 3.60235062e+01, 3.60189362e+01],\n",
+       "         [3.50553055e+01, 3.50460167e+01, 3.50400810e+01, ...,\n",
+       "          3.60306015e+01, 3.60224533e+01, 3.60222549e+01],\n",
+       "         [3.50468102e+01, 3.50438957e+01, 3.50388527e+01, ...,\n",
+       "          3.60302315e+01, 3.60265198e+01, 3.60199242e+01],\n",
+       "...\n",
+       "          1.88702012e+04, 1.88717520e+04, 1.88734863e+04],\n",
+       "         [1.89748027e+04, 1.89757480e+04, 1.89756777e+04, ...,\n",
+       "          1.88703477e+04, 1.88720566e+04, 1.88730840e+04],\n",
+       "         [1.89753691e+04, 1.89756230e+04, 1.89752539e+04, ...,\n",
+       "          1.88703164e+04, 1.88720098e+04, 1.88726465e+04]],\n",
+       "\n",
+       "        [[2.01392070e+04, 2.01399590e+04, 2.01408359e+04, ...,\n",
+       "          2.01314082e+04, 2.01314316e+04, 2.01312148e+04],\n",
+       "         [2.01406582e+04, 2.01415586e+04, 2.01423125e+04, ...,\n",
+       "          2.01325215e+04, 2.01324219e+04, 2.01315605e+04],\n",
+       "         [2.01414531e+04, 2.01429160e+04, 2.01440371e+04, ...,\n",
+       "          2.01335625e+04, 2.01333125e+04, 2.01322051e+04],\n",
+       "         ...,\n",
+       "         [2.02459512e+04, 2.02457500e+04, 2.02453418e+04, ...,\n",
+       "          2.01555137e+04, 2.01574668e+04, 2.01593828e+04],\n",
+       "         [2.02446172e+04, 2.02455488e+04, 2.02454434e+04, ...,\n",
+       "          2.01569785e+04, 2.01590039e+04, 2.01602695e+04],\n",
+       "         [2.02456758e+04, 2.02460977e+04, 2.02453164e+04, ...,\n",
+       "          2.01582695e+04, 2.01603496e+04, 2.01604922e+04]]]],\n",
+       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_model</span></div><div class='xr-var-dims'>(time, z, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>297.0 296.9 296.8 ... 220.5 220.4</div><input id='attrs-ff1377c9-960c-4502-bfe7-2fc1cdadb6f5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ff1377c9-960c-4502-bfe7-2fc1cdadb6f5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-04ea3bc7-9e48-4dbe-83ed-b4a88e5a3aa0' class='xr-var-data-in' type='checkbox'><label for='data-04ea3bc7-9e48-4dbe-83ed-b4a88e5a3aa0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XYZ</dd><dt><span>description :</span></dt><dd>temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>stagger :</span></dt><dd></dd><dt><span>coordinates :</span></dt><dd>XLONG XLAT XTIME</dd><dt><span>projection :</span></dt><dd>LambertConformal(stand_lon=-97.0, moad_cen_lat=39.617637634277344, truelat1=33.0, truelat2=45.0, pole_lat=90.0, pole_lon=0.0)</dd><dt><span>TRUELAT1 :</span></dt><dd>33.0</dd><dt><span>TRUELAT2 :</span></dt><dd>45.0</dd><dt><span>MOAD_CEN_LAT :</span></dt><dd>39.617638</dd><dt><span>STAND_LON :</span></dt><dd>-97.0</dd><dt><span>MAP_PROJ :</span></dt><dd>1</dd><dt><span>CEN_LAT :</span></dt><dd>39.617638</dd><dt><span>CEN_LON :</span></dt><dd>-97.77487</dd></dl></div><div class='xr-var-data'><pre>array([[[[296.97205, 296.86508, 296.79016, ..., 302.5541 , 302.55164,\n",
+       "          302.62527],\n",
+       "         [296.906  , 296.82993, 296.78992, ..., 302.6153 , 302.60834,\n",
+       "          302.6495 ],\n",
+       "         [296.86908, 296.8604 , 296.8119 , ..., 302.65732, 302.64978,\n",
+       "          302.64087],\n",
+       "         ...,\n",
+       "         [289.73105, 289.61404, 289.44296, ..., 286.38535, 286.66254,\n",
+       "          286.83255],\n",
+       "         [289.60068, 289.46143, 289.1941 , ..., 285.8716 , 286.03766,\n",
+       "          286.4102 ],\n",
+       "         [289.49515, 289.32498, 289.1979 , ..., 286.1651 , 285.74582,\n",
+       "          285.8759 ]],\n",
+       "\n",
+       "        [[296.64935, 296.54797, 296.4859 , ..., 302.31732, 302.31705,\n",
+       "          302.38876],\n",
+       "         [296.57715, 296.49564, 296.44696, ..., 302.37662, 302.36786,\n",
+       "          302.41095],\n",
+       "         [296.53397, 296.53766, 296.48813, ..., 302.42032, 302.4144 ,\n",
+       "          302.4066 ],\n",
+       "...\n",
+       "         [217.9952 , 217.93852, 217.8611 , ..., 220.48944, 220.55513,\n",
+       "          220.6146 ],\n",
+       "         [217.97198, 217.95184, 217.93994, ..., 220.7582 , 220.81654,\n",
+       "          220.86664],\n",
+       "         [218.05624, 218.08582, 217.98973, ..., 221.01776, 221.10216,\n",
+       "          221.01006]],\n",
+       "\n",
+       "        [[207.38243, 207.39938, 207.4022 , ..., 205.74452, 205.74385,\n",
+       "          205.76181],\n",
+       "         [207.33502, 207.39427, 207.41719, ..., 205.79208, 205.81308,\n",
+       "          205.7903 ],\n",
+       "         [207.32344, 207.39595, 207.42216, ..., 205.82893, 205.85112,\n",
+       "          205.82451],\n",
+       "         ...,\n",
+       "         [217.31105, 217.28731, 217.25253, ..., 220.06215, 220.13676,\n",
+       "          220.14354],\n",
+       "         [217.2861 , 217.28287, 217.28043, ..., 220.24535, 220.292  ,\n",
+       "          220.33716],\n",
+       "         [217.37062, 217.3985 , 217.3508 , ..., 220.45004, 220.50061,\n",
+       "          220.42236]]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>alt_agl_m_mid</span></div><div class='xr-var-dims'>(time, z, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>11.41 11.4 ... 2.015e+04 2.016e+04</div><input id='attrs-fa3ae76b-b06e-4d24-be39-14e7b32ea958' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fa3ae76b-b06e-4d24-be39-14e7b32ea958' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4b3a1c4a-ec74-490f-a8e6-b7934a78465c' class='xr-var-data-in' type='checkbox'><label for='data-4b3a1c4a-ec74-490f-a8e6-b7934a78465c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XYZ</dd><dt><span>description :</span></dt><dd>model height - [AGL] (mass grid)</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>stagger :</span></dt><dd></dd><dt><span>coordinates :</span></dt><dd>XLONG XLAT XTIME</dd><dt><span>projection :</span></dt><dd>LambertConformal(stand_lon=-97.0, moad_cen_lat=39.617637634277344, truelat1=33.0, truelat2=45.0, pole_lat=90.0, pole_lon=0.0)</dd><dt><span>TRUELAT1 :</span></dt><dd>33.0</dd><dt><span>TRUELAT2 :</span></dt><dd>45.0</dd><dt><span>MOAD_CEN_LAT :</span></dt><dd>39.617638</dd><dt><span>STAND_LON :</span></dt><dd>-97.0</dd><dt><span>MAP_PROJ :</span></dt><dd>1</dd><dt><span>CEN_LAT :</span></dt><dd>39.617638</dd><dt><span>CEN_LON :</span></dt><dd>-97.77487</dd></dl></div><div class='xr-var-data'><pre>array([[[[1.14056015e+01, 1.14014959e+01, 1.13984919e+01, ...,\n",
+       "          1.17176208e+01, 1.17145987e+01, 1.17131662e+01],\n",
+       "         [1.14016981e+01, 1.13989754e+01, 1.13973989e+01, ...,\n",
+       "          1.17169209e+01, 1.17142372e+01, 1.17140942e+01],\n",
+       "         [1.13990698e+01, 1.13980637e+01, 1.13965054e+01, ...,\n",
+       "          1.17168331e+01, 1.17155132e+01, 1.17133665e+01],\n",
+       "         ...,\n",
+       "         [1.10389814e+01, 1.10369949e+01, 1.10345135e+01, ...,\n",
+       "          1.08857241e+01, 1.08972111e+01, 1.09042320e+01],\n",
+       "         [1.10362272e+01, 1.10337315e+01, 1.10256338e+01, ...,\n",
+       "          1.08606272e+01, 1.08685665e+01, 1.08849478e+01],\n",
+       "         [1.10337601e+01, 1.10301504e+01, 1.10243549e+01, ...,\n",
+       "          1.08716812e+01, 1.08541861e+01, 1.08599854e+01]],\n",
+       "\n",
+       "        [[3.50768661e+01, 3.50637245e+01, 3.50567207e+01, ...,\n",
+       "          3.60433846e+01, 3.60334816e+01, 3.60289116e+01],\n",
+       "         [3.50652809e+01, 3.50559921e+01, 3.50500565e+01, ...,\n",
+       "          3.60405769e+01, 3.60324287e+01, 3.60322304e+01],\n",
+       "         [3.50567856e+01, 3.50538712e+01, 3.50488281e+01, ...,\n",
+       "          3.60402069e+01, 3.60364952e+01, 3.60298996e+01],\n",
+       "...\n",
+       "          1.88718730e+04, 1.88735137e+04, 1.88752559e+04],\n",
+       "         [1.89748125e+04, 1.89757578e+04, 1.89756875e+04, ...,\n",
+       "          1.88701250e+04, 1.88733457e+04, 1.88747520e+04],\n",
+       "         [1.89753789e+04, 1.89756328e+04, 1.89752637e+04, ...,\n",
+       "          1.88584297e+04, 1.88659590e+04, 1.88703770e+04]],\n",
+       "\n",
+       "        [[2.01392168e+04, 2.01399688e+04, 2.01408457e+04, ...,\n",
+       "          2.01314180e+04, 2.01314414e+04, 2.01312246e+04],\n",
+       "         [2.01406680e+04, 2.01415684e+04, 2.01423223e+04, ...,\n",
+       "          2.01325312e+04, 2.01324316e+04, 2.01315703e+04],\n",
+       "         [2.01414629e+04, 2.01429258e+04, 2.01440469e+04, ...,\n",
+       "          2.01335723e+04, 2.01333223e+04, 2.01322148e+04],\n",
+       "         ...,\n",
+       "         [2.02459609e+04, 2.02457598e+04, 2.02453516e+04, ...,\n",
+       "          2.01571855e+04, 2.01592285e+04, 2.01611523e+04],\n",
+       "         [2.02446270e+04, 2.02455586e+04, 2.02454531e+04, ...,\n",
+       "          2.01567559e+04, 2.01602930e+04, 2.01619375e+04],\n",
+       "         [2.02456855e+04, 2.02461074e+04, 2.02453262e+04, ...,\n",
+       "          2.01463828e+04, 2.01542988e+04, 2.01582227e+04]]]],\n",
+       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>surfpres_pa</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.008e+05 1.008e+05 ... 1.007e+05</div><input id='attrs-b936b487-aed3-40d5-8b2b-687f60ee97fc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b936b487-aed3-40d5-8b2b-687f60ee97fc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0bf6fd76-b543-4362-bf51-727b929de9e8' class='xr-var-data-in' type='checkbox'><label for='data-0bf6fd76-b543-4362-bf51-727b929de9e8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>SFC PRESSURE</dd><dt><span>units :</span></dt><dd>Pa</dd><dt><span>stagger :</span></dt><dd></dd><dt><span>coordinates :</span></dt><dd>XLONG XLAT XTIME</dd><dt><span>projection :</span></dt><dd>LambertConformal(stand_lon=-97.0, moad_cen_lat=39.617637634277344, truelat1=33.0, truelat2=45.0, pole_lat=90.0, pole_lon=0.0)</dd><dt><span>TRUELAT1 :</span></dt><dd>33.0</dd><dt><span>TRUELAT2 :</span></dt><dd>45.0</dd><dt><span>MOAD_CEN_LAT :</span></dt><dd>39.617638</dd><dt><span>STAND_LON :</span></dt><dd>-97.0</dd><dt><span>MAP_PROJ :</span></dt><dd>1</dd><dt><span>CEN_LAT :</span></dt><dd>39.617638</dd><dt><span>CEN_LON :</span></dt><dd>-97.77487</dd></dl></div><div class='xr-var-data'><pre>array([[[100828.64 , 100822.56 , 100815.87 , ..., 101541.86 ,\n",
+       "         101541.15 , 101540.2  ],\n",
+       "        [100834.94 , 100828.94 , 100822.34 , ..., 101549.48 ,\n",
+       "         101548.69 , 101548.14 ],\n",
+       "        [100841.195, 100834.89 , 100828.84 , ..., 101557.27 ,\n",
+       "         101556.72 , 101556.45 ],\n",
+       "        ...,\n",
+       "        [102039.99 , 102047.61 , 102054.68 , ..., 100997.39 ,\n",
+       "         101023.836, 101051.53 ],\n",
+       "        [102040.87 , 102048.61 , 102056.23 , ..., 100991.12 ,\n",
+       "         101033.92 , 101063.555],\n",
+       "        [102041.63 , 102049.77 , 102056.76 , ..., 100871.32 ,\n",
+       "         100968.   , 101034.664]],\n",
+       "\n",
+       "       [[100859.95 , 100853.39 , 100846.39 , ..., 101551.414,\n",
+       "         101550.836, 101549.88 ],\n",
+       "        [100866.39 , 100855.78 , 100848.42 , ..., 101556.125,\n",
+       "         101554.15 , 101557.43 ],\n",
+       "        [100872.8  , 100862.02 , 100854.99 , ..., 101565.13 ,\n",
+       "         101562.805, 101564.945],\n",
+       "...\n",
+       "        [101614.23 , 101637.055, 101654.53 , ..., 100824.   ,\n",
+       "         100817.5  , 100786.3  ],\n",
+       "        [101611.234, 101633.89 , 101651.086, ..., 100772.375,\n",
+       "         100782.3  , 100756.336],\n",
+       "        [101608.266, 101626.84 , 101644.1  , ..., 100578.35 ,\n",
+       "         100643.75 , 100684.01 ]],\n",
+       "\n",
+       "       [[100635.48 , 100589.75 , 100543.39 , ..., 101577.15 ,\n",
+       "         101579.87 , 101582.875],\n",
+       "        [100588.84 , 100528.03 , 100466.58 , ..., 101569.51 ,\n",
+       "         101575.62 , 101587.37 ],\n",
+       "        [100540.85 , 100438.81 , 100362.266, ..., 101571.414,\n",
+       "         101578.26 , 101592.76 ],\n",
+       "        ...,\n",
+       "        [101595.76 , 101619.016, 101636.94 , ..., 100828.66 ,\n",
+       "         100819.836, 100789.13 ],\n",
+       "        [101592.734, 101615.75 , 101633.31 , ..., 100778.52 ,\n",
+       "         100786.13 , 100760.77 ],\n",
+       "        [101589.72 , 101609.125, 101627.086, ..., 100586.22 ,\n",
+       "         100650.766, 100689.89 ]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b7193cd9-03d8-49b7-8ef3-7dbd7e293984' class='xr-section-summary-in' type='checkbox'  ><label for='section-b7193cd9-03d8-49b7-8ef3-7dbd7e293984' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-20e62777-8036-4c4e-ab87-31c990635473' class='xr-index-data-in' type='checkbox'/><label for='index-20e62777-8036-4c4e-ab87-31c990635473' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2019-09-05 00:00:00&#x27;, &#x27;2019-09-05 01:00:00&#x27;,\n",
+       "               &#x27;2019-09-05 02:00:00&#x27;, &#x27;2019-09-05 03:00:00&#x27;,\n",
+       "               &#x27;2019-09-05 04:00:00&#x27;, &#x27;2019-09-05 05:00:00&#x27;,\n",
+       "               &#x27;2019-09-05 06:00:00&#x27;, &#x27;2019-09-05 07:00:00&#x27;,\n",
+       "               &#x27;2019-09-05 08:00:00&#x27;, &#x27;2019-09-05 09:00:00&#x27;,\n",
+       "               &#x27;2019-09-05 10:00:00&#x27;, &#x27;2019-09-05 11:00:00&#x27;,\n",
+       "               &#x27;2019-09-05 12:00:00&#x27;, &#x27;2019-09-05 13:00:00&#x27;,\n",
+       "               &#x27;2019-09-05 14:00:00&#x27;, &#x27;2019-09-05 15:00:00&#x27;,\n",
+       "               &#x27;2019-09-05 16:00:00&#x27;, &#x27;2019-09-05 17:00:00&#x27;,\n",
+       "               &#x27;2019-09-05 18:00:00&#x27;, &#x27;2019-09-05 19:00:00&#x27;,\n",
+       "               &#x27;2019-09-05 20:00:00&#x27;, &#x27;2019-09-05 21:00:00&#x27;,\n",
+       "               &#x27;2019-09-05 22:00:00&#x27;, &#x27;2019-09-05 23:00:00&#x27;,\n",
+       "               &#x27;2019-09-06 00:00:00&#x27;, &#x27;2019-09-06 01:00:00&#x27;,\n",
+       "               &#x27;2019-09-06 02:00:00&#x27;, &#x27;2019-09-06 03:00:00&#x27;,\n",
+       "               &#x27;2019-09-06 04:00:00&#x27;, &#x27;2019-09-06 05:00:00&#x27;,\n",
+       "               &#x27;2019-09-06 06:00:00&#x27;],\n",
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a7c1868d-c722-49ad-972d-c62775ebaf02' class='xr-section-summary-in' type='checkbox'  ><label for='section-a7c1868d-c722-49ad-972d-c62775ebaf02' class='xr-section-summary' >Attributes: <span>(15)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XYZ</dd><dt><span>description :</span></dt><dd>NO mixing ratio</dd><dt><span>units :</span></dt><dd>ppmv</dd><dt><span>stagger :</span></dt><dd></dd><dt><span>coordinates :</span></dt><dd>XLONG XLAT XTIME</dd><dt><span>projection :</span></dt><dd>LambertConformal(stand_lon=-97.0, moad_cen_lat=39.617637634277344, truelat1=33.0, truelat2=45.0, pole_lat=90.0, pole_lon=0.0)</dd><dt><span>TRUELAT1 :</span></dt><dd>33.0</dd><dt><span>TRUELAT2 :</span></dt><dd>45.0</dd><dt><span>MOAD_CEN_LAT :</span></dt><dd>39.617638</dd><dt><span>STAND_LON :</span></dt><dd>-97.0</dd><dt><span>MAP_PROJ :</span></dt><dd>1</dd><dt><span>CEN_LAT :</span></dt><dd>39.617638</dd><dt><span>CEN_LON :</span></dt><dd>-97.77487</dd><dt><span>mapping_tables_to_airnow :</span></dt><dd>{&#x27;OZONE&#x27;: &#x27;o3&#x27;, &#x27;PM2.5&#x27;: &#x27;PM2_5_DRY&#x27;, &#x27;PM10&#x27;: &#x27;PM10&#x27;, &#x27;CO&#x27;: &#x27;co&#x27;, &#x27;SO2&#x27;: &#x27;so2&#x27;, &#x27;NO&#x27;: &#x27;no&#x27;, &#x27;NO2&#x27;: &#x27;no2&#x27;}</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset>\n",
+       "Dimensions:         (y: 284, x: 440, time: 31, z: 50)\n",
+       "Coordinates:\n",
+       "    longitude       (y, x) float32 -122.3 -122.2 -122.1 ... -60.68 -60.52 -60.37\n",
+       "    latitude        (y, x) float32 21.19 21.22 21.24 21.27 ... 50.28 50.24 50.2\n",
+       "  * time            (time) datetime64[ns] 2019-09-05 ... 2019-09-06T06:00:00\n",
+       "Dimensions without coordinates: y, x, z\n",
+       "Data variables:\n",
+       "    no              (time, z, y, x) float32 0.004484 0.004511 ... 5.302e-09\n",
+       "    o3              (time, z, y, x) float32 28.46 28.46 ... 1.971e+03 1.971e+03\n",
+       "    no2             (time, z, y, x) float32 0.01467 0.01473 ... 0.08481 0.08481\n",
+       "    pressure_model  (time, z, y, x) float32 1.007e+05 1.007e+05 ... 5.584e+03\n",
+       "    alt_msl_m_mid   (time, z, y, x) float32 11.4 11.39 ... 2.016e+04 2.016e+04\n",
+       "    temp_model      (time, z, y, x) float32 297.0 296.9 296.8 ... 220.5 220.4\n",
+       "    alt_agl_m_mid   (time, z, y, x) float32 11.41 11.4 ... 2.015e+04 2.016e+04\n",
+       "    surfpres_pa     (time, y, x) float32 1.008e+05 1.008e+05 ... 1.007e+05\n",
+       "Attributes: (12/15)\n",
+       "    FieldType:                 104\n",
+       "    MemoryOrder:               XYZ\n",
+       "    description:               NO mixing ratio\n",
+       "    units:                     ppmv\n",
+       "    stagger:                   \n",
+       "    coordinates:               XLONG XLAT XTIME\n",
+       "    ...                        ...\n",
+       "    MOAD_CEN_LAT:              39.617638\n",
+       "    STAND_LON:                 -97.0\n",
+       "    MAP_PROJ:                  1\n",
+       "    CEN_LAT:                   39.617638\n",
+       "    CEN_LON:                   -97.77487\n",
+       "    mapping_tables_to_airnow:  {'OZONE': 'o3', 'PM2.5': 'PM2_5_DRY', 'PM10': ..."
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "an.models['wrfchem_v4.2'].obj"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "91ae5876-0e1a-4dde-8db7-4f2259c01ca6",
+   "metadata": {},
+   "outputs": [
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+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;alt_msl_m_mid&#x27; (time: 31, z: 50, y: 284, x: 440)&gt;\n",
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+       "    longitude  (y, x) float32 -122.3 -122.2 -122.1 ... -60.68 -60.52 -60.37\n",
+       "    latitude   (y, x) float32 21.19 21.22 21.24 21.27 ... 50.33 50.28 50.24 50.2\n",
+       "  * time       (time) datetime64[ns] 2019-09-05 ... 2019-09-06T06:00:00\n",
+       "Dimensions without coordinates: z, y, x\n",
+       "Attributes: (12/14)\n",
+       "    FieldType:     104\n",
+       "    MemoryOrder:   XYZ\n",
+       "    description:   model height - [MSL] (mass grid)\n",
+       "    units:         m\n",
+       "    stagger:       \n",
+       "    coordinates:   XLONG XLAT XTIME\n",
+       "    ...            ...\n",
+       "    TRUELAT2:      45.0\n",
+       "    MOAD_CEN_LAT:  39.617638\n",
+       "    STAND_LON:     -97.0\n",
+       "    MAP_PROJ:      1\n",
+       "    CEN_LAT:       39.617638\n",
+       "    CEN_LON:       -97.77487</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'alt_msl_m_mid'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 31</li><li><span>z</span>: 50</li><li><span>y</span>: 284</li><li><span>x</span>: 440</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-8e983e9c-2068-47b4-bc8e-fa820293d0c4' class='xr-array-in' type='checkbox' checked><label for='section-8e983e9c-2068-47b4-bc8e-fa820293d0c4' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>11.4 11.39 11.39 11.39 ... 2.016e+04 2.016e+04 2.016e+04 2.016e+04</span></div><div class='xr-array-data'><pre>array([[[[1.13956261e+01, 1.13915205e+01, 1.13885164e+01, ...,\n",
+       "          1.17076454e+01, 1.17046232e+01, 1.17031908e+01],\n",
+       "         [1.13917227e+01, 1.13889999e+01, 1.13874235e+01, ...,\n",
+       "          1.17069454e+01, 1.17042618e+01, 1.17041187e+01],\n",
+       "         [1.13890944e+01, 1.13880882e+01, 1.13865299e+01, ...,\n",
+       "          1.17068577e+01, 1.17055378e+01, 1.17033911e+01],\n",
+       "         ...,\n",
+       "         [1.10290060e+01, 1.10270195e+01, 1.10245380e+01, ...,\n",
+       "          9.21303368e+00, 9.13495445e+00, 9.13425636e+00],\n",
+       "         [1.10262518e+01, 1.10237560e+01, 1.10156584e+01, ...,\n",
+       "          1.10823402e+01, 9.57869911e+00, 9.21612263e+00],\n",
+       "         [1.10237846e+01, 1.10201750e+01, 1.10143795e+01, ...,\n",
+       "          2.27575455e+01, 1.69050579e+01, 1.31301870e+01]],\n",
+       "\n",
+       "        [[3.50668907e+01, 3.50537491e+01, 3.50467453e+01, ...,\n",
+       "          3.60334091e+01, 3.60235062e+01, 3.60189362e+01],\n",
+       "         [3.50553055e+01, 3.50460167e+01, 3.50400810e+01, ...,\n",
+       "          3.60306015e+01, 3.60224533e+01, 3.60222549e+01],\n",
+       "         [3.50468102e+01, 3.50438957e+01, 3.50388527e+01, ...,\n",
+       "          3.60302315e+01, 3.60265198e+01, 3.60199242e+01],\n",
+       "...\n",
+       "          1.88702012e+04, 1.88717520e+04, 1.88734863e+04],\n",
+       "         [1.89748027e+04, 1.89757480e+04, 1.89756777e+04, ...,\n",
+       "          1.88703477e+04, 1.88720566e+04, 1.88730840e+04],\n",
+       "         [1.89753691e+04, 1.89756230e+04, 1.89752539e+04, ...,\n",
+       "          1.88703164e+04, 1.88720098e+04, 1.88726465e+04]],\n",
+       "\n",
+       "        [[2.01392070e+04, 2.01399590e+04, 2.01408359e+04, ...,\n",
+       "          2.01314082e+04, 2.01314316e+04, 2.01312148e+04],\n",
+       "         [2.01406582e+04, 2.01415586e+04, 2.01423125e+04, ...,\n",
+       "          2.01325215e+04, 2.01324219e+04, 2.01315605e+04],\n",
+       "         [2.01414531e+04, 2.01429160e+04, 2.01440371e+04, ...,\n",
+       "          2.01335625e+04, 2.01333125e+04, 2.01322051e+04],\n",
+       "         ...,\n",
+       "         [2.02459512e+04, 2.02457500e+04, 2.02453418e+04, ...,\n",
+       "          2.01555137e+04, 2.01574668e+04, 2.01593828e+04],\n",
+       "         [2.02446172e+04, 2.02455488e+04, 2.02454434e+04, ...,\n",
+       "          2.01569785e+04, 2.01590039e+04, 2.01602695e+04],\n",
+       "         [2.02456758e+04, 2.02460977e+04, 2.02453164e+04, ...,\n",
+       "          2.01582695e+04, 2.01603496e+04, 2.01604922e+04]]]],\n",
+       "      dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-1f6661fa-f424-4abc-9167-5404059fc0d3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1f6661fa-f424-4abc-9167-5404059fc0d3' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-122.3 -122.2 ... -60.52 -60.37</div><input id='attrs-3b5b4ac3-ae56-4e5f-ad97-ea880fd424d0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3b5b4ac3-ae56-4e5f-ad97-ea880fd424d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-59b67e57-2f65-4235-907b-7231eaa22e89' class='xr-var-data-in' type='checkbox'><label for='data-59b67e57-2f65-4235-907b-7231eaa22e89' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>TRUELAT1 :</span></dt><dd>33.0</dd><dt><span>TRUELAT2 :</span></dt><dd>45.0</dd><dt><span>MOAD_CEN_LAT :</span></dt><dd>39.617638</dd><dt><span>STAND_LON :</span></dt><dd>-97.0</dd><dt><span>MAP_PROJ :</span></dt><dd>1</dd><dt><span>CEN_LAT :</span></dt><dd>39.617638</dd><dt><span>CEN_LON :</span></dt><dd>-97.77487</dd></dl></div><div class='xr-var-data'><pre>array([[-122.282745, -122.17581 , -122.0688  , ...,  -73.00513 ,\n",
+       "         -72.8974  ,  -72.789795],\n",
+       "       [-122.31329 , -122.20625 , -122.09914 , ...,  -72.97595 ,\n",
+       "         -72.86813 ,  -72.760376],\n",
+       "       [-122.34393 , -122.236786, -122.12955 , ...,  -72.94672 ,\n",
+       "         -72.838776,  -72.730896],\n",
+       "       ...,\n",
+       "       [-135.0139  , -134.86354 , -134.71295 , ...,  -60.804962,\n",
+       "         -60.65219 ,  -60.499634],\n",
+       "       [-135.08081 , -134.93024 , -134.77945 , ...,  -60.74051 ,\n",
+       "         -60.587524,  -60.434753],\n",
+       "       [-135.14793 , -134.99716 , -134.84618 , ...,  -60.675873,\n",
+       "         -60.522675,  -60.36969 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>21.19 21.22 21.24 ... 50.24 50.2</div><input id='attrs-ac009a22-3610-4053-81d3-0aed88a6f9d4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ac009a22-3610-4053-81d3-0aed88a6f9d4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d8dc9ea2-79df-4b44-8224-9eb1be0e717f' class='xr-var-data-in' type='checkbox'><label for='data-d8dc9ea2-79df-4b44-8224-9eb1be0e717f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>TRUELAT1 :</span></dt><dd>33.0</dd><dt><span>TRUELAT2 :</span></dt><dd>45.0</dd><dt><span>MOAD_CEN_LAT :</span></dt><dd>39.617638</dd><dt><span>STAND_LON :</span></dt><dd>-97.0</dd><dt><span>MAP_PROJ :</span></dt><dd>1</dd><dt><span>CEN_LAT :</span></dt><dd>39.617638</dd><dt><span>CEN_LON :</span></dt><dd>-97.77487</dd></dl></div><div class='xr-var-data'><pre>array([[21.18737 , 21.215775, 21.244072, ..., 21.520782, 21.493614,\n",
+       "        21.466347],\n",
+       "       [21.287056, 21.315514, 21.343864, ..., 21.621033, 21.593834,\n",
+       "        21.566513],\n",
+       "       [21.386795, 21.41529 , 21.443687, ..., 21.721321, 21.694077,\n",
+       "        21.66671 ],\n",
+       "       ...,\n",
+       "       [49.581253, 49.624477, 49.667526, ..., 50.08878 , 50.047417,\n",
+       "        50.005882],\n",
+       "       [49.678635, 49.721916, 49.76504 , ..., 50.18683 , 50.145416,\n",
+       "        50.103832],\n",
+       "       [49.775967, 49.819294, 49.862473, ..., 50.28482 , 50.24335 ,\n",
+       "        50.20171 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-09-05 ... 2019-09-06T06:00:00</div><input id='attrs-c979a2bb-8685-4088-9567-c406e89404b0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c979a2bb-8685-4088-9567-c406e89404b0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-46d22c4e-bf09-4dcc-a60f-3d09c6fd3962' class='xr-var-data-in' type='checkbox'><label for='data-46d22c4e-bf09-4dcc-a60f-3d09c6fd3962' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>TRUELAT1 :</span></dt><dd>33.0</dd><dt><span>TRUELAT2 :</span></dt><dd>45.0</dd><dt><span>MOAD_CEN_LAT :</span></dt><dd>39.617638</dd><dt><span>STAND_LON :</span></dt><dd>-97.0</dd><dt><span>MAP_PROJ :</span></dt><dd>1</dd><dt><span>CEN_LAT :</span></dt><dd>39.617638</dd><dt><span>CEN_LON :</span></dt><dd>-97.77487</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-09-05T00:00:00.000000000&#x27;, &#x27;2019-09-05T01:00:00.000000000&#x27;,\n",
+       "       &#x27;2019-09-05T02:00:00.000000000&#x27;, &#x27;2019-09-05T03:00:00.000000000&#x27;,\n",
+       "       &#x27;2019-09-05T04:00:00.000000000&#x27;, &#x27;2019-09-05T05:00:00.000000000&#x27;,\n",
+       "       &#x27;2019-09-05T06:00:00.000000000&#x27;, &#x27;2019-09-05T07:00:00.000000000&#x27;,\n",
+       "       &#x27;2019-09-05T08:00:00.000000000&#x27;, &#x27;2019-09-05T09:00:00.000000000&#x27;,\n",
+       "       &#x27;2019-09-05T10:00:00.000000000&#x27;, &#x27;2019-09-05T11:00:00.000000000&#x27;,\n",
+       "       &#x27;2019-09-05T12:00:00.000000000&#x27;, &#x27;2019-09-05T13:00:00.000000000&#x27;,\n",
+       "       &#x27;2019-09-05T14:00:00.000000000&#x27;, &#x27;2019-09-05T15:00:00.000000000&#x27;,\n",
+       "       &#x27;2019-09-05T16:00:00.000000000&#x27;, &#x27;2019-09-05T17:00:00.000000000&#x27;,\n",
+       "       &#x27;2019-09-05T18:00:00.000000000&#x27;, &#x27;2019-09-05T19:00:00.000000000&#x27;,\n",
+       "       &#x27;2019-09-05T20:00:00.000000000&#x27;, &#x27;2019-09-05T21:00:00.000000000&#x27;,\n",
+       "       &#x27;2019-09-05T22:00:00.000000000&#x27;, &#x27;2019-09-05T23:00:00.000000000&#x27;,\n",
+       "       &#x27;2019-09-06T00:00:00.000000000&#x27;, &#x27;2019-09-06T01:00:00.000000000&#x27;,\n",
+       "       &#x27;2019-09-06T02:00:00.000000000&#x27;, &#x27;2019-09-06T03:00:00.000000000&#x27;,\n",
+       "       &#x27;2019-09-06T04:00:00.000000000&#x27;, &#x27;2019-09-06T05:00:00.000000000&#x27;,\n",
+       "       &#x27;2019-09-06T06:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-923d8cf9-699b-472e-85e4-95cfa898edb4' class='xr-section-summary-in' type='checkbox'  ><label for='section-923d8cf9-699b-472e-85e4-95cfa898edb4' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-17c986a3-a077-4bcf-8eb3-c3b75b68c096' class='xr-index-data-in' type='checkbox'/><label for='index-17c986a3-a077-4bcf-8eb3-c3b75b68c096' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2019-09-05 00:00:00&#x27;, &#x27;2019-09-05 01:00:00&#x27;,\n",
+       "               &#x27;2019-09-05 02:00:00&#x27;, &#x27;2019-09-05 03:00:00&#x27;,\n",
+       "               &#x27;2019-09-05 04:00:00&#x27;, &#x27;2019-09-05 05:00:00&#x27;,\n",
+       "               &#x27;2019-09-05 06:00:00&#x27;, &#x27;2019-09-05 07:00:00&#x27;,\n",
+       "               &#x27;2019-09-05 08:00:00&#x27;, &#x27;2019-09-05 09:00:00&#x27;,\n",
+       "               &#x27;2019-09-05 10:00:00&#x27;, &#x27;2019-09-05 11:00:00&#x27;,\n",
+       "               &#x27;2019-09-05 12:00:00&#x27;, &#x27;2019-09-05 13:00:00&#x27;,\n",
+       "               &#x27;2019-09-05 14:00:00&#x27;, &#x27;2019-09-05 15:00:00&#x27;,\n",
+       "               &#x27;2019-09-05 16:00:00&#x27;, &#x27;2019-09-05 17:00:00&#x27;,\n",
+       "               &#x27;2019-09-05 18:00:00&#x27;, &#x27;2019-09-05 19:00:00&#x27;,\n",
+       "               &#x27;2019-09-05 20:00:00&#x27;, &#x27;2019-09-05 21:00:00&#x27;,\n",
+       "               &#x27;2019-09-05 22:00:00&#x27;, &#x27;2019-09-05 23:00:00&#x27;,\n",
+       "               &#x27;2019-09-06 00:00:00&#x27;, &#x27;2019-09-06 01:00:00&#x27;,\n",
+       "               &#x27;2019-09-06 02:00:00&#x27;, &#x27;2019-09-06 03:00:00&#x27;,\n",
+       "               &#x27;2019-09-06 04:00:00&#x27;, &#x27;2019-09-06 05:00:00&#x27;,\n",
+       "               &#x27;2019-09-06 06:00:00&#x27;],\n",
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-137826ec-cbdf-480c-ba24-22b19994d08a' class='xr-section-summary-in' type='checkbox'  ><label for='section-137826ec-cbdf-480c-ba24-22b19994d08a' class='xr-section-summary' >Attributes: <span>(14)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XYZ</dd><dt><span>description :</span></dt><dd>model height - [MSL] (mass grid)</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>stagger :</span></dt><dd></dd><dt><span>coordinates :</span></dt><dd>XLONG XLAT XTIME</dd><dt><span>projection :</span></dt><dd>LambertConformal(stand_lon=-97.0, moad_cen_lat=39.617637634277344, truelat1=33.0, truelat2=45.0, pole_lat=90.0, pole_lon=0.0)</dd><dt><span>TRUELAT1 :</span></dt><dd>33.0</dd><dt><span>TRUELAT2 :</span></dt><dd>45.0</dd><dt><span>MOAD_CEN_LAT :</span></dt><dd>39.617638</dd><dt><span>STAND_LON :</span></dt><dd>-97.0</dd><dt><span>MAP_PROJ :</span></dt><dd>1</dd><dt><span>CEN_LAT :</span></dt><dd>39.617638</dd><dt><span>CEN_LON :</span></dt><dd>-97.77487</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.DataArray 'alt_msl_m_mid' (time: 31, z: 50, y: 284, x: 440)>\n",
+       "array([[[[1.13956261e+01, 1.13915205e+01, 1.13885164e+01, ...,\n",
+       "          1.17076454e+01, 1.17046232e+01, 1.17031908e+01],\n",
+       "         [1.13917227e+01, 1.13889999e+01, 1.13874235e+01, ...,\n",
+       "          1.17069454e+01, 1.17042618e+01, 1.17041187e+01],\n",
+       "         [1.13890944e+01, 1.13880882e+01, 1.13865299e+01, ...,\n",
+       "          1.17068577e+01, 1.17055378e+01, 1.17033911e+01],\n",
+       "         ...,\n",
+       "         [1.10290060e+01, 1.10270195e+01, 1.10245380e+01, ...,\n",
+       "          9.21303368e+00, 9.13495445e+00, 9.13425636e+00],\n",
+       "         [1.10262518e+01, 1.10237560e+01, 1.10156584e+01, ...,\n",
+       "          1.10823402e+01, 9.57869911e+00, 9.21612263e+00],\n",
+       "         [1.10237846e+01, 1.10201750e+01, 1.10143795e+01, ...,\n",
+       "          2.27575455e+01, 1.69050579e+01, 1.31301870e+01]],\n",
+       "\n",
+       "        [[3.50668907e+01, 3.50537491e+01, 3.50467453e+01, ...,\n",
+       "          3.60334091e+01, 3.60235062e+01, 3.60189362e+01],\n",
+       "         [3.50553055e+01, 3.50460167e+01, 3.50400810e+01, ...,\n",
+       "          3.60306015e+01, 3.60224533e+01, 3.60222549e+01],\n",
+       "         [3.50468102e+01, 3.50438957e+01, 3.50388527e+01, ...,\n",
+       "          3.60302315e+01, 3.60265198e+01, 3.60199242e+01],\n",
+       "...\n",
+       "          1.88702012e+04, 1.88717520e+04, 1.88734863e+04],\n",
+       "         [1.89748027e+04, 1.89757480e+04, 1.89756777e+04, ...,\n",
+       "          1.88703477e+04, 1.88720566e+04, 1.88730840e+04],\n",
+       "         [1.89753691e+04, 1.89756230e+04, 1.89752539e+04, ...,\n",
+       "          1.88703164e+04, 1.88720098e+04, 1.88726465e+04]],\n",
+       "\n",
+       "        [[2.01392070e+04, 2.01399590e+04, 2.01408359e+04, ...,\n",
+       "          2.01314082e+04, 2.01314316e+04, 2.01312148e+04],\n",
+       "         [2.01406582e+04, 2.01415586e+04, 2.01423125e+04, ...,\n",
+       "          2.01325215e+04, 2.01324219e+04, 2.01315605e+04],\n",
+       "         [2.01414531e+04, 2.01429160e+04, 2.01440371e+04, ...,\n",
+       "          2.01335625e+04, 2.01333125e+04, 2.01322051e+04],\n",
+       "         ...,\n",
+       "         [2.02459512e+04, 2.02457500e+04, 2.02453418e+04, ...,\n",
+       "          2.01555137e+04, 2.01574668e+04, 2.01593828e+04],\n",
+       "         [2.02446172e+04, 2.02455488e+04, 2.02454434e+04, ...,\n",
+       "          2.01569785e+04, 2.01590039e+04, 2.01602695e+04],\n",
+       "         [2.02456758e+04, 2.02460977e+04, 2.02453164e+04, ...,\n",
+       "          2.01582695e+04, 2.01603496e+04, 2.01604922e+04]]]],\n",
+       "      dtype=float32)\n",
+       "Coordinates:\n",
+       "    longitude  (y, x) float32 -122.3 -122.2 -122.1 ... -60.68 -60.52 -60.37\n",
+       "    latitude   (y, x) float32 21.19 21.22 21.24 21.27 ... 50.33 50.28 50.24 50.2\n",
+       "  * time       (time) datetime64[ns] 2019-09-05 ... 2019-09-06T06:00:00\n",
+       "Dimensions without coordinates: z, y, x\n",
+       "Attributes: (12/14)\n",
+       "    FieldType:     104\n",
+       "    MemoryOrder:   XYZ\n",
+       "    description:   model height - [MSL] (mass grid)\n",
+       "    units:         m\n",
+       "    stagger:       \n",
+       "    coordinates:   XLONG XLAT XTIME\n",
+       "    ...            ...\n",
+       "    TRUELAT2:      45.0\n",
+       "    MOAD_CEN_LAT:  39.617638\n",
+       "    STAND_LON:     -97.0\n",
+       "    MAP_PROJ:      1\n",
+       "    CEN_LAT:       39.617638\n",
+       "    CEN_LON:       -97.77487"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "an.models['wrfchem_v4.2'].obj['alt_msl_m_mid']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "527eab21",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "wrfchem_v4.2\n",
+      "{'firexaq': {'no2': 'NO2_CL_RYERSON', 'no': 'NO_CL_RYERSON', 'o3': 'O3_CL_RYERSON'}}\n"
+     ]
+    }
+   ],
+   "source": [
+    "#All the info in the model class can be called here.\n",
+    "print(an.models['wrfchem_v4.2'].label)\n",
+    "print(an.models['wrfchem_v4.2'].mapping)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "c648be31",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2019-09-05 12:00:00\n",
+      "2019-09-06 00:00:00\n"
+     ]
+    }
+   ],
+   "source": [
+    "#All the info in the analysis class can also be called.\n",
+    "print(an.start_time)\n",
+    "print(an.end_time)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5165f204",
+   "metadata": {},
+   "source": [
+    "### Open Obs\n",
+    "\n",
+    "Now for monet-analysis we will open preprocessed data in either netcdf icartt or some other format.  We will not be retrieving data like monetio does for some observations (ie aeronet, airnow, etc....).  Instead we will provide utitilies to do this so that users can add more data easily.\n",
+    "\n",
+    "Like models we list all obs objects in the yaml file and it will loop through and create driver.observation instances that include the model type, file, objects (i.e. data object) and label  "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "bd807787",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "an.open_obs()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "52f31e54",
+   "metadata": {},
+   "outputs": [
+    {
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+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
+       "Dimensions:                                       (time: 2007)\n",
+       "Coordinates:\n",
+       "  * time                                          (time) datetime64[ns] 2019-...\n",
+       "Data variables: (12/642)\n",
+       "    Time_Stop                                     (time) float64 6.34e+04 ......\n",
+       "    Day_Of_Year_YANG                              (time) float64 248.0 ... 248.0\n",
+       "    latitude                                      (time) float64 38.81 ... 34.63\n",
+       "    longitude                                     (time) float64 -97.65 ... -...\n",
+       "    altitude                                      (time) float64 383.7 ... 771.0\n",
+       "    HAE_GPS_Altitude_YANG                         (time) float64 356.1 ... 737.3\n",
+       "    ...                                            ...\n",
+       "    smoke_age_HOLMES                              (time) float64 nan nan ... nan\n",
+       "    smoke_age_corr_HOLMES                         (time) float64 nan nan ... nan\n",
+       "    smoke_age_rise_HOLMES                         (time) float64 nan nan ... nan\n",
+       "    smoke_rise_HOLMES                             (time) float64 nan nan ... nan\n",
+       "    fire_distance_HOLMES                          (time) float64 nan nan ... nan\n",
+       "    smoke_agemethod_HOLMES                        (time) float64 nan nan ... nan\n",
+       "Attributes: (12/23)\n",
+       "    source:               Merged Flight#20190905, on the DC8 platform. Data i...\n",
+       "    Date Revised:         2022-02-11 00:00:00\n",
+       "    mission:              FIREXAQ\n",
+       "    organization:         NASA Langley Research Center\n",
+       "    PI:                   Suborbital Science Data for Atmospheric Composition\n",
+       "    PI_CONTACT_INFO:      gao.chen@nasa.gov, michael.shook@nasa.gov, ali.a.ak...\n",
+       "    ...                   ...\n",
+       "    PROJECT_INFO:         FIREXAQ\n",
+       "    STIPULATIONS_ON_USE:  N/A\n",
+       "    OTHER_COMMENTS:       This merge was created using the SSD-AC online merg...\n",
+       "    REVISION:             R1\n",
+       "    R1:                   File generated from data submitted before 2022, 2, ...\n",
+       "    R0:                   File was generated using the online merge tool.</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-4df09d32-703c-4664-990e-004ffc020981' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-4df09d32-703c-4664-990e-004ffc020981' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 2007</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-fd203dfa-6fda-4a6b-8b8e-a2a3a1fe4085' class='xr-section-summary-in' type='checkbox'  checked><label for='section-fd203dfa-6fda-4a6b-8b8e-a2a3a1fe4085' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-09-05T17:36:25 ... 2019-09-...</div><input id='attrs-d77cb5bf-bb2e-405b-bd2c-410f4746772d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d77cb5bf-bb2e-405b-bd2c-410f4746772d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f0b38884-4f92-4baa-ac52-5174d348e5b5' class='xr-var-data-in' type='checkbox'><label for='data-f0b38884-4f92-4baa-ac52-5174d348e5b5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-09-05T17:36:25.000000000&#x27;, &#x27;2019-09-05T17:36:35.000000000&#x27;,\n",
+       "       &#x27;2019-09-05T17:36:45.000000000&#x27;, ..., &#x27;2019-09-05T23:10:25.000000000&#x27;,\n",
+       "       &#x27;2019-09-05T23:10:35.000000000&#x27;, &#x27;2019-09-05T23:10:45.000000000&#x27;],\n",
+       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8b58878e-65ac-4492-8eb1-dda1b5eb7cf5' class='xr-section-summary-in' type='checkbox'  ><label for='section-8b58878e-65ac-4492-8eb1-dda1b5eb7cf5' class='xr-section-summary' >Data variables: <span>(642)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>Time_Stop</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.34e+04 6.34e+04 ... 8.346e+04</div><input id='attrs-4083ed97-29fd-44cb-9385-fbe157ddcc23' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4083ed97-29fd-44cb-9385-fbe157ddcc23' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3ecdc99c-09cd-4381-90f1-073ce397b368' class='xr-var-data-in' type='checkbox'><label for='data-3ecdc99c-09cd-4381-90f1-073ce397b368' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>seconds</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([63395., 63405., 63415., ..., 83435., 83445., 83455.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Day_Of_Year_YANG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>248.0 248.0 248.0 ... 248.0 248.0</div><input id='attrs-1dbd0dd1-ee2e-46ea-8aca-3c764d5e2c8a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1dbd0dd1-ee2e-46ea-8aca-3c764d5e2c8a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a6a1ecdd-840d-4b9a-8270-680edbc0e6ca' class='xr-var-data-in' type='checkbox'><label for='data-a6a1ecdd-840d-4b9a-8270-680edbc0e6ca' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>day</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([248., 248., 248., ..., 248., 248., 248.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>38.81 38.81 38.8 ... 34.63 34.63</div><input id='attrs-a7033f05-5667-4b5e-b3da-eb2ba6ed0576' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a7033f05-5667-4b5e-b3da-eb2ba6ed0576' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-25661519-bb31-4bff-93e4-fc9bb80edd2b' class='xr-var-data-in' type='checkbox'><label for='data-25661519-bb31-4bff-93e4-fc9bb80edd2b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([38.808306, 38.805232, 38.800498, ..., 34.626705, 34.626136,\n",
+       "       34.625921])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-97.65 -97.65 ... -118.1 -118.1</div><input id='attrs-a3a34c2b-8d83-4c56-b4f6-c2e7f7eb4831' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a3a34c2b-8d83-4c56-b4f6-c2e7f7eb4831' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2e56f85c-6fe3-4f9b-8862-4c7cda7555b2' class='xr-var-data-in' type='checkbox'><label for='data-2e56f85c-6fe3-4f9b-8862-4c7cda7555b2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([ -97.645956,  -97.645961,  -97.645946, ..., -118.076759,\n",
+       "       -118.077723, -118.077854])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>altitude</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>383.7 383.3 384.2 ... 771.3 771.0</div><input id='attrs-31f0ab35-e938-4f47-adc3-5a45e742ebb3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-31f0ab35-e938-4f47-adc3-5a45e742ebb3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a2952983-65b0-4219-a4d5-dd600bb1c314' class='xr-var-data-in' type='checkbox'><label for='data-a2952983-65b0-4219-a4d5-dd600bb1c314' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([383.7, 383.3, 384.2, ..., 770.6, 771.3, 771. ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HAE_GPS_Altitude_YANG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>356.1 356.1 357.0 ... 737.0 737.3</div><input id='attrs-e347ca07-cb8b-4e76-aaf8-b846449e8e3f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e347ca07-cb8b-4e76-aaf8-b846449e8e3f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2e78d69e-2c4d-4cd0-8864-92f7d33531fa' class='xr-var-data-in' type='checkbox'><label for='data-2e78d69e-2c4d-4cd0-8864-92f7d33531fa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([356.07, 356.14, 357.04, ..., 736.43, 737.04, 737.3 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Pressure_Altitude_YANG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.172e+03 1.168e+03 ... 2.448e+03</div><input id='attrs-e216c96c-d31f-4cdf-bd22-1e426530a871' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e216c96c-d31f-4cdf-bd22-1e426530a871' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c1a8616a-b088-4ccc-b9c0-0c265833fd6e' class='xr-var-data-in' type='checkbox'><label for='data-c1a8616a-b088-4ccc-b9c0-0c265833fd6e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ft</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([1171.5, 1167.8, 1160.9, ..., 2443.9, 2447.5, 2448.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Radar_Altitude_YANG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... 4.65 3.95 3.5</div><input id='attrs-4d9dd97a-52be-4c2f-8de3-b7007e6618f8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4d9dd97a-52be-4c2f-8de3-b7007e6618f8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a5f80da5-1c73-45cc-ba7f-9b80d644dab3' class='xr-var-data-in' type='checkbox'><label for='data-a5f80da5-1c73-45cc-ba7f-9b80d644dab3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ft</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([ nan,  nan,  nan, ..., 4.65, 3.95, 3.5 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Ground_Speed_YANG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>24.11 43.75 61.0 ... 6.727 3.69</div><input id='attrs-2c73c9b9-ce61-4bcd-9626-02e0e5ac57be' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2c73c9b9-ce61-4bcd-9626-02e0e5ac57be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-505cc8f2-8bb3-47a8-8f0f-a62c3f0cd5d7' class='xr-var-data-in' type='checkbox'><label for='data-505cc8f2-8bb3-47a8-8f0f-a62c3f0cd5d7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([24.112, 43.747, 60.999, ..., 15.711,  6.727,  3.69 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>True_Air_Speed_YANG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-8.889e+05 107.4 ... -8.889e+05</div><input id='attrs-d400ed56-276a-436a-98a4-a1d789f91d8c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d400ed56-276a-436a-98a4-a1d789f91d8c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8d0bcd89-f61b-462a-978c-888d862b2d23' class='xr-var-data-in' type='checkbox'><label for='data-8d0bcd89-f61b-462a-978c-888d862b2d23' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>kts</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([-8.88888e+05,  1.07365e+02,  1.30939e+02, ..., -8.88888e+05,\n",
+       "       -8.88888e+05, -8.88888e+05])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Indicated_Air_Speed_YANG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>60.7 95.25 ... -8.889e+05</div><input id='attrs-5d5df40f-9e93-4558-a2d4-622477f4d0f6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5d5df40f-9e93-4558-a2d4-622477f4d0f6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-da6ccfbc-eb3a-4447-b9ca-956d61f51d7d' class='xr-var-data-in' type='checkbox'><label for='data-da6ccfbc-eb3a-4447-b9ca-956d61f51d7d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>kts</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([ 6.07010e+01,  9.52510e+01,  1.24051e+02, ...,  3.99367e+01,\n",
+       "       -8.88888e+05, -8.88888e+05])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Mach_Number_YANG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.1103 0.1473 ... -8.889e+05</div><input id='attrs-8d8b7e09-e1fb-4235-bde5-b48c98b44f09' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8d8b7e09-e1fb-4235-bde5-b48c98b44f09' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2a359497-b0ca-40c0-8931-ee205482f208' class='xr-var-data-in' type='checkbox'><label for='data-2a359497-b0ca-40c0-8931-ee205482f208' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>mach</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([ 1.10330e-01,  1.47300e-01,  1.92400e-01, ..., -8.88888e+05,\n",
+       "       -8.88888e+05, -8.88888e+05])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Vertical_Speed_YANG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.02 0.02 0.13 ... 0.1 0.04 -0.05</div><input id='attrs-4c10fc51-4993-45ff-be53-13c52fb9ceba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4c10fc51-4993-45ff-be53-13c52fb9ceba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-95f4af12-41da-462c-bc09-66e46dd29208' class='xr-var-data-in' type='checkbox'><label for='data-95f4af12-41da-462c-bc09-66e46dd29208' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([ 0.02,  0.02,  0.13, ...,  0.1 ,  0.04, -0.05])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>True_Heading_YANG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>180.1 180.0 180.0 ... 229.5 195.0</div><input id='attrs-c0194b4c-9606-4186-8f83-44ae175df300' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c0194b4c-9606-4186-8f83-44ae175df300' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b1c6d7b0-27af-4bba-b0ec-b2501de988b4' class='xr-var-data-in' type='checkbox'><label for='data-b1c6d7b0-27af-4bba-b0ec-b2501de988b4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>deg 0-360</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([180.077, 179.99 , 180.014, ..., 235.726, 229.54 , 195.045])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Track_Angle_YANG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>180.1 179.9 179.9 ... 219.7 138.2</div><input id='attrs-0ffde9e5-66d6-42c3-9a4e-5f97d80b6b16' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0ffde9e5-66d6-42c3-9a4e-5f97d80b6b16' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b7109255-1471-4f29-8720-67cb27d87c3c' class='xr-var-data-in' type='checkbox'><label for='data-b7109255-1471-4f29-8720-67cb27d87c3c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>deg 0-360</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([180.064 , 179.941 , 179.863 , ..., 235.737 , 219.7077, 138.205 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Drift_Angle_YANG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.03 -0.04 -0.14 ... -10.67 -56.85</div><input id='attrs-c58bf85a-06a9-4ea5-b838-74260ca34769' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c58bf85a-06a9-4ea5-b838-74260ca34769' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2880bb26-1326-48f0-88a9-0e70cb766dea' class='xr-var-data-in' type='checkbox'><label for='data-2880bb26-1326-48f0-88a9-0e70cb766dea' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>deg +-180</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([-3.000e-02, -4.000e-02, -1.400e-01, ...,  2.000e-02, -1.067e+01,\n",
+       "       -5.685e+01])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Pitch_Angle_YANG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>359.5 359.6 359.9 ... 359.5 359.9</div><input id='attrs-3cfd98f9-5cc9-4195-8935-1f5ae154d5c2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3cfd98f9-5cc9-4195-8935-1f5ae154d5c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8eb11cf4-55ab-4efe-a1a9-f868281b63eb' class='xr-var-data-in' type='checkbox'><label for='data-8eb11cf4-55ab-4efe-a1a9-f868281b63eb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>deg +-180</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([359.519, 359.626, 359.901, ..., 359.418, 359.51 , 359.85 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Roll_Angle_YANG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.695 0.672 0.574 ... 1.107 0.81</div><input id='attrs-3e4caf85-9461-471b-a1a3-8a204b21d013' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3e4caf85-9461-471b-a1a3-8a204b21d013' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2532c716-e0a0-4c95-970a-3867966fec84' class='xr-var-data-in' type='checkbox'><label for='data-2532c716-e0a0-4c95-970a-3867966fec84' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>deg +-180</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([0.695, 0.672, 0.574, ..., 0.969, 1.107, 0.81 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Static_Air_Temp_YANG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>32.31 32.38 32.57 ... 34.87 34.82</div><input id='attrs-79e974ff-d86d-4f73-8955-797b57722902' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-79e974ff-d86d-4f73-8955-797b57722902' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7f198ada-6950-4111-a64d-78b57dca20d9' class='xr-var-data-in' type='checkbox'><label for='data-7f198ada-6950-4111-a64d-78b57dca20d9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees Celcius</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([32.31 , 32.384, 32.571, ..., 34.995, 34.869, 34.82 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Potential_Temp_YANG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>308.1 308.1 308.3 ... 314.8 314.7</div><input id='attrs-8185a755-7219-473a-8ede-d741c3245cb3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8185a755-7219-473a-8ede-d741c3245cb3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aebe9d54-01f5-4a47-921c-403e387a9b20' class='xr-var-data-in' type='checkbox'><label for='data-aebe9d54-01f5-4a47-921c-403e387a9b20' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Kelvin</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([308.05, 308.09, 308.26, ..., 314.91, 314.79, 314.7 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Dew_Point_YANG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>19.8 19.8 19.85 ... 12.9 12.86 12.8</div><input id='attrs-4ea4c44f-af48-4055-86b3-694667e29b30' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4ea4c44f-af48-4055-86b3-694667e29b30' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c1b2a9b6-15c0-4554-9a7b-7cb1bcc5088e' class='xr-var-data-in' type='checkbox'><label for='data-c1b2a9b6-15c0-4554-9a7b-7cb1bcc5088e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees Celcius</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([19.8 , 19.8 , 19.85, ..., 12.9 , 12.86, 12.8 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Total_Air_Temp_YANG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>32.86 33.72 34.86 ... 34.92 34.8</div><input id='attrs-a1ff0b8f-678b-42cd-ab63-7ee4b0ab088d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a1ff0b8f-678b-42cd-ab63-7ee4b0ab088d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9168741e-cee6-4e81-961e-35d20358bc31' class='xr-var-data-in' type='checkbox'><label for='data-9168741e-cee6-4e81-961e-35d20358bc31' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees Celcius</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([32.86, 33.72, 34.86, ..., 35.27, 34.92, 34.8 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>IR_Surf_Temp_YANG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>34.54 34.56 34.42 ... 32.7 32.7</div><input id='attrs-0ec66631-93d8-472e-bc60-03ca96a95864' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0ec66631-93d8-472e-bc60-03ca96a95864' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-83d1de2d-464a-4470-86b3-9e01271035a9' class='xr-var-data-in' type='checkbox'><label for='data-83d1de2d-464a-4470-86b3-9e01271035a9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees Celcius</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([34.54, 34.56, 34.42, ..., 32.7 , 32.7 , 32.7 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Static_Pressure_YANG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>971.1 971.2 971.5 ... 926.8 926.8</div><input id='attrs-af4ec7cb-7a04-4570-bc65-95596368cb9a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-af4ec7cb-7a04-4570-bc65-95596368cb9a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-37a55c14-d78f-48f9-8637-8bf0c4e98fdf' class='xr-var-data-in' type='checkbox'><label for='data-37a55c14-d78f-48f9-8637-8bf0c4e98fdf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>hPa</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([971.081, 971.214, 971.457, ..., 926.906, 926.785, 926.75 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Cabin_Pressure_YANG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>980.5 981.3 981.9 ... 936.3 936.2</div><input id='attrs-a90af1ef-65b0-46c8-8af2-70f39db728a4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a90af1ef-65b0-46c8-8af2-70f39db728a4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2fb2f51a-0d1a-42ae-8123-d795395f3494' class='xr-var-data-in' type='checkbox'><label for='data-2fb2f51a-0d1a-42ae-8123-d795395f3494' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>hPa</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([980.55, 981.3 , 981.92, ..., 936.65, 936.27, 936.25])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Wind_Speed_YANG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.63 7.89 6.37 ... 7.71 3.95 3.15</div><input id='attrs-c65276f4-61f8-495d-a4a8-4cdf9e40e737' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c65276f4-61f8-495d-a4a8-4cdf9e40e737' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-98e4658d-3718-4ed4-8422-95fcbe743105' class='xr-var-data-in' type='checkbox'><label for='data-98e4658d-3718-4ed4-8422-95fcbe743105' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([8.63, 7.89, 6.37, ..., 7.71, 3.95, 3.15])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Wind_Direction_YANG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>180.1 180.4 181.5 ... 242.6 290.2</div><input id='attrs-6ce6094f-538d-417a-aafe-7d5415e708a4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6ce6094f-538d-417a-aafe-7d5415e708a4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1804682a-5f8a-4f89-a844-73b807dbdc29' class='xr-var-data-in' type='checkbox'><label for='data-1804682a-5f8a-4f89-a844-73b807dbdc29' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>deg 0-360 cw from +y</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([180.1399, 180.3548, 181.4729, ..., 235.6525, 242.601 , 290.2224])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Solar_Zenith_Angle_YANG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>34.3 34.3 34.3 ... 53.48 53.5 53.5</div><input id='attrs-90d8a3ff-35b3-413a-a713-d1f51bf39aec' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-90d8a3ff-35b3-413a-a713-d1f51bf39aec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-22c2c70a-abab-4065-837d-e7c09b347e98' class='xr-var-data-in' type='checkbox'><label for='data-22c2c70a-abab-4065-837d-e7c09b347e98' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>deg</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([34.3 , 34.3 , 34.3 , ..., 53.48, 53.5 , 53.5 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Aircraft_Sun_Elevation_YANG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>55.91 55.82 55.66 ... 37.16 37.1</div><input id='attrs-fe6d19a9-aa69-4712-b16d-3ec8ded195fe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fe6d19a9-aa69-4712-b16d-3ec8ded195fe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ecde2381-8afa-4902-b7f8-1a5c84c1215c' class='xr-var-data-in' type='checkbox'><label for='data-ecde2381-8afa-4902-b7f8-1a5c84c1215c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>deg</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([55.91, 55.82, 55.66, ..., 37.15, 37.16, 37.1 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Sun_Azimuth_YANG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>155.7 155.8 155.9 ... 250.3 250.4</div><input id='attrs-24051a39-e8ea-4eb3-9b4f-dc8da77b0658' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-24051a39-e8ea-4eb3-9b4f-dc8da77b0658' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e5258130-fcfb-4477-9bd7-d7ac78ff34e8' class='xr-var-data-in' type='checkbox'><label for='data-e5258130-fcfb-4477-9bd7-d7ac78ff34e8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>deg</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([155.74, 155.8 , 155.9 , ..., 250.3 , 250.35, 250.4 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Aircraft_Sun_Azimuth_YANG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-24.99 -24.8 -24.45 ... 19.83 52.7</div><input id='attrs-ee0e272c-4f69-4a3b-b32f-766a6e44de01' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ee0e272c-4f69-4a3b-b32f-766a6e44de01' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5d9548ec-63d8-4efd-aad1-59a86248ed2d' class='xr-var-data-in' type='checkbox'><label for='data-5d9548ec-63d8-4efd-aad1-59a86248ed2d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>deg</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([-24.99, -24.8 , -24.45, ...,  14.38,  19.83,  52.7 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Mixing_Ratio_YANG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>15.31 15.33 15.35 ... 10.22 10.19</div><input id='attrs-6186166a-d3ca-44b6-a193-73df3a5e9382' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6186166a-d3ca-44b6-a193-73df3a5e9382' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6a6ecc37-3f39-4be3-b256-6aefb31ae2cf' class='xr-var-data-in' type='checkbox'><label for='data-6a6ecc37-3f39-4be3-b256-6aefb31ae2cf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>g/kg</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([15.307, 15.327, 15.35 , ..., 10.227, 10.218, 10.19 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Part_Press_Water_Vapor_YANG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>23.33 23.36 23.4 ... 14.98 14.94</div><input id='attrs-7356fd0b-a874-44f6-b418-5609edda8e74' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7356fd0b-a874-44f6-b418-5609edda8e74' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-465f9e83-3ae4-4e05-b8f9-8534729da4b6' class='xr-var-data-in' type='checkbox'><label for='data-465f9e83-3ae4-4e05-b8f9-8534729da4b6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>hPa</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([23.326, 23.358, 23.397, ..., 14.991, 14.98 , 14.94 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Sat_Vapor_Press_H2O_YANG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>48.86 49.06 49.59 ... 56.36 56.2</div><input id='attrs-8c4a588f-ed46-4ba2-bf4f-2b5fe0f498cb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8c4a588f-ed46-4ba2-bf4f-2b5fe0f498cb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-076fd938-13fd-44b2-a024-c294f1380598' class='xr-var-data-in' type='checkbox'><label for='data-076fd938-13fd-44b2-a024-c294f1380598' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>hPa</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([48.857, 49.057, 49.59 , ..., 56.764, 56.361, 56.2  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Sat_Vapor_Press_Ice_YANG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>66.56 66.87 67.72 ... 78.64 78.37</div><input id='attrs-c31c217c-d373-4940-9b03-aab05de581ef' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c31c217c-d373-4940-9b03-aab05de581ef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2406fd80-6b78-4437-8a01-9aa72d66ef1e' class='xr-var-data-in' type='checkbox'><label for='data-2406fd80-6b78-4437-8a01-9aa72d66ef1e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>hPa</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([66.556, 66.872, 67.723, ..., 79.296, 78.635, 78.37 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Relative_Humidity_YANG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>47.76 47.62 47.2 ... 26.59 26.59</div><input id='attrs-3f82e0b3-fb33-4abf-ab1b-a8437140783e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3f82e0b3-fb33-4abf-ab1b-a8437140783e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d373e069-d312-4ae0-bed4-7d2753995357' class='xr-var-data-in' type='checkbox'><label for='data-d373e069-d312-4ae0-bed4-7d2753995357' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>percent</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([47.756, 47.625, 47.203, ..., 26.428, 26.586, 26.59 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure_obs</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-c8988928-d27f-4646-a65b-46245edcc829' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c8988928-d27f-4646-a65b-46245edcc829' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-412299fa-192e-440d-bd4f-df55224113b5' class='xr-var-data-in' type='checkbox'><label for='data-412299fa-192e-440d-bd4f-df55224113b5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>hPa</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>T_BUI</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-d11c2e17-9b39-4853-8748-6641d347119d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d11c2e17-9b39-4853-8748-6641d347119d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f2a01b8b-b4a4-4266-9be6-f99d9695f40e' class='xr-var-data-in' type='checkbox'><label for='data-f2a01b8b-b4a4-4266-9be6-f99d9695f40e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>K</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TAS_BUI</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-bf39dedf-793c-4c08-a0e0-68ce460a5c79' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bf39dedf-793c-4c08-a0e0-68ce460a5c79' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3ccebd6b-954d-4761-88e9-6394a0fbddb1' class='xr-var-data-in' type='checkbox'><label for='data-3ccebd6b-954d-4761-88e9-6394a0fbddb1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>U_BUI</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-7b3bf82d-a97e-4a70-8548-0297a228c461' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7b3bf82d-a97e-4a70-8548-0297a228c461' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4d3d3b1e-2a1b-4d5e-8699-beadf37ce65c' class='xr-var-data-in' type='checkbox'><label for='data-4d3d3b1e-2a1b-4d5e-8699-beadf37ce65c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>V_BUI</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-1f2feb88-6efb-452e-a0fa-deb8da370f4f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1f2feb88-6efb-452e-a0fa-deb8da370f4f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-38679f74-bec3-4114-bbcf-d9afb90a5c60' class='xr-var-data-in' type='checkbox'><label for='data-38679f74-bec3-4114-bbcf-d9afb90a5c60' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>W_BUI</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-80704648-0b1a-45eb-b410-92feff62c169' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-80704648-0b1a-45eb-b410-92feff62c169' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6ea5face-3c51-4e75-a683-f7582e1767ca' class='xr-var-data-in' type='checkbox'><label for='data-6ea5face-3c51-4e75-a683-f7582e1767ca' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TEDR_BUI</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-200a230d-852c-42e3-99ec-6dd1d2aef060' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-200a230d-852c-42e3-99ec-6dd1d2aef060' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b8bc8d3f-fafa-4c02-8ddd-0a21221c0766' class='xr-var-data-in' type='checkbox'><label for='data-b8bc8d3f-fafa-4c02-8ddd-0a21221c0766' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>kW/kg</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>REYN_BUI</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-a7936327-1f96-4e2c-8dec-701b8caf1bf2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a7936327-1f96-4e2c-8dec-701b8caf1bf2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-639d9630-772b-4a77-a91e-4ee85a6f9ed0' class='xr-var-data-in' type='checkbox'><label for='data-639d9630-772b-4a77-a91e-4ee85a6f9ed0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/m</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>POT_BUI</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-6e4e5fcf-a14b-4259-b78c-94294220c294' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6e4e5fcf-a14b-4259-b78c-94294220c294' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dcf75c4d-7dce-4624-9369-a32e93a97402' class='xr-var-data-in' type='checkbox'><label for='data-dcf75c4d-7dce-4624-9369-a32e93a97402' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>K</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ROLL_BUI</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-4d91f5f7-7aa8-4d94-862c-99bba94f43aa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4d91f5f7-7aa8-4d94-862c-99bba94f43aa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-679f7635-bc81-49a7-acba-5cc5ccb82cbc' class='xr-var-data-in' type='checkbox'><label for='data-679f7635-bc81-49a7-acba-5cc5ccb82cbc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>deg</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HDG_BUI</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-61f57ae0-2a5f-45de-9a9a-98e5112cdfaa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-61f57ae0-2a5f-45de-9a9a-98e5112cdfaa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1abfad9b-eff3-46b6-97b6-5e43a065aea2' class='xr-var-data-in' type='checkbox'><label for='data-1abfad9b-eff3-46b6-97b6-5e43a065aea2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>deg</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PITCH_BUI</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-0e0f292b-d80d-451e-98ba-84a26aeb1482' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0e0f292b-d80d-451e-98ba-84a26aeb1482' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e9e3fc98-86b6-48ee-9c46-cad246ebf7d6' class='xr-var-data-in' type='checkbox'><label for='data-e9e3fc98-86b6-48ee-9c46-cad246ebf7d6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>deg</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>YAW_BUI</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-c1396a7a-9e11-4a5b-88ad-1f24abceab0f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c1396a7a-9e11-4a5b-88ad-1f24abceab0f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ff54b87a-e67a-410c-9d62-2a3adea3ee19' class='xr-var-data-in' type='checkbox'><label for='data-ff54b87a-e67a-410c-9d62-2a3adea3ee19' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>deg</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>AOA_BUI</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-5b3b7b03-8926-475b-8fc4-4de78c893e8c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5b3b7b03-8926-475b-8fc4-4de78c893e8c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-72d33dd6-4c1f-40bf-b2f6-4afe6a867c45' class='xr-var-data-in' type='checkbox'><label for='data-72d33dd6-4c1f-40bf-b2f6-4afe6a867c45' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>deg</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Smoke_flag_SCHWARZ</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-a56eb0d1-db59-43bd-8ed4-fffe84a594c7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a56eb0d1-db59-43bd-8ed4-fffe84a594c7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-39849765-183e-4601-80b1-f432fc158992' class='xr-var-data-in' type='checkbox'><label for='data-39849765-183e-4601-80b1-f432fc158992' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>none</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transect_type_SCHWARZ</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-0f3743f7-da17-489d-9ed1-7cc877f05ff4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0f3743f7-da17-489d-9ed1-7cc877f05ff4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d7db742b-019d-4797-a1f2-8b312bab5a6c' class='xr-var-data-in' type='checkbox'><label for='data-d7db742b-019d-4797-a1f2-8b312bab5a6c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>none</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fire_id_SCHWARZ</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-aa30c35d-2d21-48bd-95c1-c76604ea5752' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aa30c35d-2d21-48bd-95c1-c76604ea5752' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-29b9442d-f9ac-438d-a338-d426f3c405d3' class='xr-var-data-in' type='checkbox'><label for='data-29b9442d-f9ac-438d-a338-d426f3c405d3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>none</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Background_flag_SCHWARZ</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-d0775152-5a5c-4430-8602-6cf4c7c61477' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d0775152-5a5c-4430-8602-6cf4c7c61477' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bca76721-fa8e-49f8-b8ac-5c2ad02c729f' class='xr-var-data-in' type='checkbox'><label for='data-bca76721-fa8e-49f8-b8ac-5c2ad02c729f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>integer</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transect_smoke_age_SCHWARZ</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-f7f318ce-8ccc-42fd-b147-b08a96ff1a11' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f7f318ce-8ccc-42fd-b147-b08a96ff1a11' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2fb518e7-da1e-4bd6-9103-08c807596805' class='xr-var-data-in' type='checkbox'><label for='data-2fb518e7-da1e-4bd6-9103-08c807596805' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>seconds</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transect_smoke_MCE_SCHWARZ</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-5de8e7b5-6e79-45a1-ab40-b998bc536145' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5de8e7b5-6e79-45a1-ab40-b998bc536145' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e22438ad-fd9b-4382-8781-b696144ffe97' class='xr-var-data-in' type='checkbox'><label for='data-e22438ad-fd9b-4382-8781-b696144ffe97' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>none</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transect_number_SCHWARZ</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-0fb51d2b-612a-4db7-a8a0-a13b78825d2d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0fb51d2b-612a-4db7-a8a0-a13b78825d2d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-62c24e2c-64e5-4d7d-833b-c92c822c2673' class='xr-var-data-in' type='checkbox'><label for='data-62c24e2c-64e5-4d7d-833b-c92c822c2673' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>none</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transect_plume_number_SCHWARZ</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-045d0fe6-c3f6-4c4d-bb67-beacd04a4589' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-045d0fe6-c3f6-4c4d-bb67-beacd04a4589' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-93e539af-3f44-417e-99cf-dcd1d0465cf5' class='xr-var-data-in' type='checkbox'><label for='data-93e539af-3f44-417e-99cf-dcd1d0465cf5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>none</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transect_mce_ODR_SCHWARZ</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-3dafefcd-0320-41b5-9966-c1f49194c3e4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3dafefcd-0320-41b5-9966-c1f49194c3e4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-91bbe669-ae26-4c50-a526-2eed59bf80fe' class='xr-var-data-in' type='checkbox'><label for='data-91bbe669-ae26-4c50-a526-2eed59bf80fe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transect_mce_odr_chisq_SCHWARZ</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-1ed9e208-1f4a-4de1-b0ed-d4d3ff693496' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1ed9e208-1f4a-4de1-b0ed-d4d3ff693496' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e8cdc2d0-094a-4fd7-b1a0-5d2211f51b46' class='xr-var-data-in' type='checkbox'><label for='data-e8cdc2d0-094a-4fd7-b1a0-5d2211f51b46' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>none</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fire_distance_estimate_SCHWARZ</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-1b6a7387-64f1-4b07-8c21-e7471a2dfd5e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1b6a7387-64f1-4b07-8c21-e7471a2dfd5e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-060a3c23-b910-4252-8697-810a7c65f43e' class='xr-var-data-in' type='checkbox'><label for='data-060a3c23-b910-4252-8697-810a7c65f43e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>meters</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>H2O_DLH_DISKIN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan ... nan nan nan</div><input id='attrs-7711a5a0-10eb-4d36-ae3c-96ce9fa8306d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7711a5a0-10eb-4d36-ae3c-96ce9fa8306d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6427100e-ba04-4fb5-aba1-9211d5dfc27b' class='xr-var-data-in' type='checkbox'><label for='data-6427100e-ba04-4fb5-aba1-9211d5dfc27b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppmv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>RHi_DLH_DISKIN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-caaaf019-b5d5-433a-83da-df9bd0592046' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-caaaf019-b5d5-433a-83da-df9bd0592046' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d51212d6-5764-4151-8c72-59d49ff2cd63' class='xr-var-data-in' type='checkbox'><label for='data-d51212d6-5764-4151-8c72-59d49ff2cd63' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>percent</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>RHw_DLH_DISKIN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 40.49 ... nan nan nan</div><input id='attrs-431f9849-78d4-44bd-8b4b-8b06b5a55e4e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-431f9849-78d4-44bd-8b4b-8b06b5a55e4e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3a8174dc-841a-467b-9f71-20e2ed1f27ba' class='xr-var-data-in' type='checkbox'><label for='data-3a8174dc-841a-467b-9f71-20e2ed1f27ba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>percent</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>H2O_LGR_ppmv_PEISCHL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan ... nan nan nan</div><input id='attrs-1f29fdb5-02ae-4b4b-a77a-5d1a679e781a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1f29fdb5-02ae-4b4b-a77a-5d1a679e781a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-833fbce5-ce15-4b2e-a17c-542ac4de9d6f' class='xr-var-data-in' type='checkbox'><label for='data-833fbce5-ce15-4b2e-a17c-542ac4de9d6f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppmv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>O3_CL_RYERSON</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-cda02cf6-7b40-44a7-9471-4e0e5ad4871f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cda02cf6-7b40-44a7-9471-4e0e5ad4871f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ee9b8c55-c429-410e-a2e0-c23264a3168f' class='xr-var-data-in' type='checkbox'><label for='data-ee9b8c55-c429-410e-a2e0-c23264a3168f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NO_CL_RYERSON</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-3cb403b0-ceac-4380-b8b5-8bfc7af1352b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3cb403b0-ceac-4380-b8b5-8bfc7af1352b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-83557030-b898-4416-9bcb-fd9542381d73' class='xr-var-data-in' type='checkbox'><label for='data-83557030-b898-4416-9bcb-fd9542381d73' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NO2_CL_RYERSON</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-7573b1d1-8d63-4f4a-b2c7-66710b37a48a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7573b1d1-8d63-4f4a-b2c7-66710b37a48a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b060fc99-a509-405b-b9ce-71a7d54f453a' class='xr-var-data-in' type='checkbox'><label for='data-b060fc99-a509-405b-b9ce-71a7d54f453a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NOy_CL_RYERSON</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-21e950a1-523a-44e4-8bf1-adeb3cda0751' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-21e950a1-523a-44e4-8bf1-adeb3cda0751' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-58dc217e-a569-4790-8a4f-8d4b56b9af0b' class='xr-var-data-in' type='checkbox'><label for='data-58dc217e-a569-4790-8a4f-8d4b56b9af0b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>O3_ROZE_HANISCO</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>51.85 52.95 52.57 ... nan nan nan</div><input id='attrs-4fc68417-8068-46a0-b0a5-6415fd07e9f2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4fc68417-8068-46a0-b0a5-6415fd07e9f2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-680f4944-57d7-4d6c-84b2-267ce43397ca' class='xr-var-data-in' type='checkbox'><label for='data-680f4944-57d7-4d6c-84b2-267ce43397ca' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([51.85 , 52.953, 52.57 , ...,    nan,    nan,    nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NO_LIF_ROLLINS</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-f2dd447e-52aa-4da2-8a78-7960908b32f9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f2dd447e-52aa-4da2-8a78-7960908b32f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d04bc29-f630-448d-901b-19f489af548c' class='xr-var-data-in' type='checkbox'><label for='data-1d04bc29-f630-448d-901b-19f489af548c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NO2_ACES_WOMACK</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.398 ... nan nan nan</div><input id='attrs-b9f4792e-61e7-45d3-9774-425e76fc5faa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b9f4792e-61e7-45d3-9774-425e76fc5faa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-02c5a111-b11d-4970-a830-4fc6b822d9ec' class='xr-var-data-in' type='checkbox'><label for='data-02c5a111-b11d-4970-a830-4fc6b822d9ec' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NO2_CANOE_STCLAIR</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-06ee28be-63d9-4688-8ee2-d4ed1cc2dda3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-06ee28be-63d9-4688-8ee2-d4ed1cc2dda3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3f51b7af-7215-4c38-b010-c43834e265b2' class='xr-var-data-in' type='checkbox'><label for='data-3f51b7af-7215-4c38-b010-c43834e265b2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HNO2_NOAACIMS_VERES</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-b09c9df5-257b-4cae-9d77-0ec82c5382d1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b09c9df5-257b-4cae-9d77-0ec82c5382d1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eb62a080-db00-48f2-801a-e34de7487f34' class='xr-var-data-in' type='checkbox'><label for='data-eb62a080-db00-48f2-801a-e34de7487f34' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HNO2_ACES_WOMACK</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.19 ... nan nan nan</div><input id='attrs-eb7ce527-6797-4585-b5ba-b4e2d178e6e3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eb7ce527-6797-4585-b5ba-b4e2d178e6e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fb8cc510-3ae9-4b21-9dc0-0b6345c98268' class='xr-var-data-in' type='checkbox'><label for='data-fb8cc510-3ae9-4b21-9dc0-0b6345c98268' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HONO_SAGA_DIBB</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 48.0 ... nan nan nan</div><input id='attrs-61507df7-3597-4d95-b5c9-887935322871' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-61507df7-3597-4d95-b5c9-887935322871' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f3dae62e-ab66-490f-84ec-075904c5f3eb' class='xr-var-data-in' type='checkbox'><label for='data-f3dae62e-ab66-490f-84ec-075904c5f3eb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HNO3+submicron-NO3_SAGA_DIBB</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 552.0 ... nan nan nan</div><input id='attrs-19b729fb-e107-4924-a2be-817123ea7e5b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-19b729fb-e107-4924-a2be-817123ea7e5b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0adbe597-3401-4980-8af9-06937b5f2727' class='xr-var-data-in' type='checkbox'><label for='data-0adbe597-3401-4980-8af9-06937b5f2727' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Sulfate_lt_1um_SAGA_DIBB</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.752 ... nan nan nan</div><input id='attrs-50756714-8ced-4c40-9370-d1e1342c6cc7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-50756714-8ced-4c40-9370-d1e1342c6cc7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8ee1637b-a1d4-40ee-951e-8c9411e0ade2' class='xr-var-data-in' type='checkbox'><label for='data-8ee1637b-a1d4-40ee-951e-8c9411e0ade2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ug std m-3</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HNO3-1Hz_CIT_WENNBERG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>179.0 175.0 184.8 ... nan nan nan</div><input id='attrs-9e8f169e-d738-485d-8168-73bae89a50fa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9e8f169e-d738-485d-8168-73bae89a50fa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d5c05221-34f9-434e-8e93-81d54ea8210b' class='xr-var-data-in' type='checkbox'><label for='data-d5c05221-34f9-434e-8e93-81d54ea8210b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([179.0167, 175.04  , 184.83  , ...,      nan,      nan,      nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PAN_GTCIMS_HUEY</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-26b08fec-74e5-41cf-8246-554b371628ed' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-26b08fec-74e5-41cf-8246-554b371628ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4d0d4305-64ab-42b0-9de5-8ade2d74aa26' class='xr-var-data-in' type='checkbox'><label for='data-4d0d4305-64ab-42b0-9de5-8ade2d74aa26' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PPN_GTCIMS_HUEY</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-eefa152b-2e56-4ca1-8135-43299a4625bf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eefa152b-2e56-4ca1-8135-43299a4625bf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-614de674-ef7e-4d6d-a2bc-1d8b1dcb2c60' class='xr-var-data-in' type='checkbox'><label for='data-614de674-ef7e-4d6d-a2bc-1d8b1dcb2c60' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>APAN_GTCIMS_HUEY</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-4f4cc09d-e3a0-4792-8624-72898c5d5b84' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4f4cc09d-e3a0-4792-8624-72898c5d5b84' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-09238ae8-31ae-47be-8f7e-f826b7191afa' class='xr-var-data-in' type='checkbox'><label for='data-09238ae8-31ae-47be-8f7e-f826b7191afa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PBN_GTCIMS_HUEY</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e9b5cea3-3c84-47d0-82bc-2846d9241e76' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e9b5cea3-3c84-47d0-82bc-2846d9241e76' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d963cee1-adf7-4222-9086-e85408fb90c8' class='xr-var-data-in' type='checkbox'><label for='data-d963cee1-adf7-4222-9086-e85408fb90c8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NH3_UIOPTR_ppbV_WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ac4f5df4-a9d8-4425-ac01-39840ae4197a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ac4f5df4-a9d8-4425-ac01-39840ae4197a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-faf3acbc-d79a-43b2-bf03-bc0e97cca82d' class='xr-var-data-in' type='checkbox'><label for='data-faf3acbc-d79a-43b2-bf03-bc0e97cca82d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>N2O5_NOAACIMS_VERES</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.2476 ... nan nan nan</div><input id='attrs-98fb6902-8934-44e0-8de6-780a5bec229a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-98fb6902-8934-44e0-8de6-780a5bec229a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-077b64c5-090d-4248-be6e-b063cfb059d5' class='xr-var-data-in' type='checkbox'><label for='data-077b64c5-090d-4248-be6e-b063cfb059d5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>N2O_LGR_ppb_PEISCHL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 330.9 ... nan nan nan</div><input id='attrs-298059ed-f6b0-41b9-965f-83480b6c9fc2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-298059ed-f6b0-41b9-965f-83480b6c9fc2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dac1ae43-91cd-43df-86b8-c45ea6765142' class='xr-var-data-in' type='checkbox'><label for='data-dac1ae43-91cd-43df-86b8-c45ea6765142' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppb</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CO_DACOM_DISKIN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 141.6 ... nan nan nan</div><input id='attrs-f4c71089-6f1a-4af5-91b9-2a5cb26dded6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f4c71089-6f1a-4af5-91b9-2a5cb26dded6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b779114-2a93-4e11-8613-207c7f2ef530' class='xr-var-data-in' type='checkbox'><label for='data-9b779114-2a93-4e11-8613-207c7f2ef530' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH4_DACOM_DISKIN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan ... nan nan nan</div><input id='attrs-22b621b2-6622-4dd6-90b8-fe4a6e1c2d2a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-22b621b2-6622-4dd6-90b8-fe4a6e1c2d2a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ed454e9-8e0a-42c4-8e8d-ecc9452ad3b9' class='xr-var-data-in' type='checkbox'><label for='data-5ed454e9-8e0a-42c4-8e8d-ecc9452ad3b9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CO_LGR_ppb_PEISCHL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 138.3 ... nan nan nan</div><input id='attrs-b5edcc11-0526-491d-8084-7643923750d6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b5edcc11-0526-491d-8084-7643923750d6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5922bf34-aa91-443d-9f79-31a983b69527' class='xr-var-data-in' type='checkbox'><label for='data-5922bf34-aa91-443d-9f79-31a983b69527' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppb</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CO2_7000_ppm_DISKIN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 405.8 ... nan nan nan</div><input id='attrs-f994c244-544e-4513-8cc6-893ca08bd692' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f994c244-544e-4513-8cc6-893ca08bd692' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3a742e14-0603-445c-9775-7d2f8d018807' class='xr-var-data-in' type='checkbox'><label for='data-3a742e14-0603-445c-9775-7d2f8d018807' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppm</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>C2H6_CAMS_pptv_FRIED</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-51c0091b-84ab-4c81-a560-684de6c449b8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-51c0091b-84ab-4c81-a560-684de6c449b8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-29eee5ba-ec5a-4123-bfd0-4973120d2c42' class='xr-var-data-in' type='checkbox'><label for='data-29eee5ba-ec5a-4123-bfd0-4973120d2c42' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH2O_CAMS_pptv_FRIED</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-c61253bb-015a-4c28-93ab-b82687a44223' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c61253bb-015a-4c28-93ab-b82687a44223' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-719ecc9d-3e6c-4650-9541-60bec28f7181' class='xr-var-data-in' type='checkbox'><label for='data-719ecc9d-3e6c-4650-9541-60bec28f7181' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH2O_ISAF_HANISCO</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-83de30c8-075f-4971-98db-310d9ae05ee2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-83de30c8-075f-4971-98db-310d9ae05ee2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6aa93ccd-7330-407e-9394-7d0c8b7cad87' class='xr-var-data-in' type='checkbox'><label for='data-6aa93ccd-7330-407e-9394-7d0c8b7cad87' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH2O_UIOPTR_ppbV_WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-128c9071-1321-4006-bb0d-e919a0fa4d04' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-128c9071-1321-4006-bb0d-e919a0fa4d04' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-82cd1f1b-9e68-4a00-b3cd-36bb456d71a7' class='xr-var-data-in' type='checkbox'><label for='data-82cd1f1b-9e68-4a00-b3cd-36bb456d71a7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>OCS_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-58066f18-3d9a-4965-8ec6-fe9927399062' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-58066f18-3d9a-4965-8ec6-fe9927399062' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-82fcd292-c0ad-4f50-8f8e-89e2c201f2d2' class='xr-var-data-in' type='checkbox'><label for='data-82fcd292-c0ad-4f50-8f8e-89e2c201f2d2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>DMS_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-d0fd26cf-7ddf-4fc1-b94d-2adb2c192c2f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d0fd26cf-7ddf-4fc1-b94d-2adb2c192c2f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f1065008-f254-4842-a1d3-a72bee6ef87a' class='xr-var-data-in' type='checkbox'><label for='data-f1065008-f254-4842-a1d3-a72bee6ef87a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CFC12_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-d15f2085-f3e4-4886-a36b-7f7dbe66a6e3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d15f2085-f3e4-4886-a36b-7f7dbe66a6e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0a080719-62f7-4a24-a82c-bc5011997796' class='xr-var-data-in' type='checkbox'><label for='data-0a080719-62f7-4a24-a82c-bc5011997796' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CFC11_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-da1b71be-383d-4660-be4b-d4077b106ba6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-da1b71be-383d-4660-be4b-d4077b106ba6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-27ef5567-537f-4cdd-9f4f-5e24709f1577' class='xr-var-data-in' type='checkbox'><label for='data-27ef5567-537f-4cdd-9f4f-5e24709f1577' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CFC113_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-3e25b959-4bbc-4bb4-b2f6-1df6fdd0fa54' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3e25b959-4bbc-4bb4-b2f6-1df6fdd0fa54' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-612b4e3d-3949-4c99-9aac-f5c219cbe54e' class='xr-var-data-in' type='checkbox'><label for='data-612b4e3d-3949-4c99-9aac-f5c219cbe54e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CFC114_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-9d0b46be-5a6a-4838-8262-0cef2e7d3a41' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9d0b46be-5a6a-4838-8262-0cef2e7d3a41' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6e59082d-511b-472a-b51e-fd407c2eae70' class='xr-var-data-in' type='checkbox'><label for='data-6e59082d-511b-472a-b51e-fd407c2eae70' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HFC152a_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-592f9d02-952c-4ab8-8088-5100ceaa3735' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-592f9d02-952c-4ab8-8088-5100ceaa3735' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c08003ef-7874-442a-9a28-d8a69a7e1e93' class='xr-var-data-in' type='checkbox'><label for='data-c08003ef-7874-442a-9a28-d8a69a7e1e93' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HFC134a_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-b2a44ee1-733e-4bc6-a11f-06f5cb467d00' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b2a44ee1-733e-4bc6-a11f-06f5cb467d00' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2fb59ad9-8b66-47a0-b4d6-b38c80558be0' class='xr-var-data-in' type='checkbox'><label for='data-2fb59ad9-8b66-47a0-b4d6-b38c80558be0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HFC365mfc_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-bda9f4ed-5095-4590-895e-612f2d058ae7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bda9f4ed-5095-4590-895e-612f2d058ae7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a7d3b2cb-f025-47f2-96a4-abd6c251c2c9' class='xr-var-data-in' type='checkbox'><label for='data-a7d3b2cb-f025-47f2-96a4-abd6c251c2c9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HCFC22_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-50719b9f-8803-480c-beb2-b2b61dff084c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-50719b9f-8803-480c-beb2-b2b61dff084c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8931dfdf-6d7c-4f26-8c04-0dec8b09c253' class='xr-var-data-in' type='checkbox'><label for='data-8931dfdf-6d7c-4f26-8c04-0dec8b09c253' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HCFC142b_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-6e2e01ea-3abc-45da-be9e-20e9be8d0ba3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6e2e01ea-3abc-45da-be9e-20e9be8d0ba3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-482958d7-c28f-4104-bf44-c1f44ffd1e0a' class='xr-var-data-in' type='checkbox'><label for='data-482958d7-c28f-4104-bf44-c1f44ffd1e0a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HCFC141b_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-013d5cf0-cb49-4822-acbe-4afb79ca525f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-013d5cf0-cb49-4822-acbe-4afb79ca525f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-29bff82b-cca1-4c82-beea-69ef23a61929' class='xr-var-data-in' type='checkbox'><label for='data-29bff82b-cca1-4c82-beea-69ef23a61929' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>H1301_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ddb38e09-d0a0-41d6-9e5d-f596daef7115' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ddb38e09-d0a0-41d6-9e5d-f596daef7115' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b5c66fa4-c4c6-4251-aae4-641f25704a87' class='xr-var-data-in' type='checkbox'><label for='data-b5c66fa4-c4c6-4251-aae4-641f25704a87' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>H2402_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-b15d6142-ff32-4c5e-a8a8-a27229a6e5a1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b15d6142-ff32-4c5e-a8a8-a27229a6e5a1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9d15e1f5-54de-4524-883f-43428735665d' class='xr-var-data-in' type='checkbox'><label for='data-9d15e1f5-54de-4524-883f-43428735665d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>H1211_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-aa53b931-73c2-4b4c-b21a-3abd4f89cccd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aa53b931-73c2-4b4c-b21a-3abd4f89cccd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-90513ae5-bfc0-4b05-96f9-8da819fdc6c8' class='xr-var-data-in' type='checkbox'><label for='data-90513ae5-bfc0-4b05-96f9-8da819fdc6c8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH3CCl3_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e1090e62-92e5-466e-8d6c-1ba1c4142827' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e1090e62-92e5-466e-8d6c-1ba1c4142827' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-98fcf084-85c6-4436-a748-0849e186dcb8' class='xr-var-data-in' type='checkbox'><label for='data-98fcf084-85c6-4436-a748-0849e186dcb8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CCl4_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-dd5fadff-f710-4dea-9fdc-4b289b0c4759' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dd5fadff-f710-4dea-9fdc-4b289b0c4759' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-761f684c-1a7b-47f6-8814-7ae850cb3c41' class='xr-var-data-in' type='checkbox'><label for='data-761f684c-1a7b-47f6-8814-7ae850cb3c41' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CHCl3_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-d14d68c2-ad71-4f74-9815-ae0930e95e94' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d14d68c2-ad71-4f74-9815-ae0930e95e94' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e5d2c518-bdc9-4d9b-9de9-9215dff8f061' class='xr-var-data-in' type='checkbox'><label for='data-e5d2c518-bdc9-4d9b-9de9-9215dff8f061' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH2Cl2_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-b11e6ce1-5a64-46b3-9453-df7f1ff19073' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b11e6ce1-5a64-46b3-9453-df7f1ff19073' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-37571665-bd23-49d8-887a-57925c92a309' class='xr-var-data-in' type='checkbox'><label for='data-37571665-bd23-49d8-887a-57925c92a309' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>C2HCl3_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-cd28fcbc-0789-48b4-9b40-7e58612f900e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cd28fcbc-0789-48b4-9b40-7e58612f900e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-07498dbd-93c2-426b-a671-7ac4f084526c' class='xr-var-data-in' type='checkbox'><label for='data-07498dbd-93c2-426b-a671-7ac4f084526c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>C2Cl4_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-141874dc-ec6d-418d-be35-8938ba9227f3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-141874dc-ec6d-418d-be35-8938ba9227f3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ce544bd3-168a-4347-87d9-15275ddc5bc4' class='xr-var-data-in' type='checkbox'><label for='data-ce544bd3-168a-4347-87d9-15275ddc5bc4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH3Cl_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-df68657d-fb99-4aa7-ba0e-1caef1135156' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-df68657d-fb99-4aa7-ba0e-1caef1135156' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fbb98769-c3dd-44f7-9492-5cf39336ec3f' class='xr-var-data-in' type='checkbox'><label for='data-fbb98769-c3dd-44f7-9492-5cf39336ec3f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH3Br_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-dab3f12d-5676-4b98-973f-24a1f5e3c1f8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dab3f12d-5676-4b98-973f-24a1f5e3c1f8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3f2354dc-5a2a-4cc3-b0ce-0a7057afad91' class='xr-var-data-in' type='checkbox'><label for='data-3f2354dc-5a2a-4cc3-b0ce-0a7057afad91' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH3I_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-09ae8d77-68e0-460d-8531-75e691943649' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-09ae8d77-68e0-460d-8531-75e691943649' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-51a64472-c33f-4d42-86ea-93ba6f812640' class='xr-var-data-in' type='checkbox'><label for='data-51a64472-c33f-4d42-86ea-93ba6f812640' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH2Br2_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-47bb1cc0-6a12-4ca3-852b-d9fc7e154579' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-47bb1cc0-6a12-4ca3-852b-d9fc7e154579' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7d861fa8-67d1-48b2-999d-9279392dde12' class='xr-var-data-in' type='checkbox'><label for='data-7d861fa8-67d1-48b2-999d-9279392dde12' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CHBrCl2_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-001e191e-ffbc-4711-983e-64db66664f13' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-001e191e-ffbc-4711-983e-64db66664f13' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2e072445-6048-4479-8d14-1936af021fac' class='xr-var-data-in' type='checkbox'><label for='data-2e072445-6048-4479-8d14-1936af021fac' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CHBr2Cl_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-af492876-9825-496c-ba10-301c3cf7adf0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-af492876-9825-496c-ba10-301c3cf7adf0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-38512926-34be-4234-b95e-ae5ad03bceef' class='xr-var-data-in' type='checkbox'><label for='data-38512926-34be-4234-b95e-ae5ad03bceef' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CHBr3_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-dd5a96f7-870d-41f9-b862-3ad45a03c77d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dd5a96f7-870d-41f9-b862-3ad45a03c77d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-066075ff-f337-4b1b-8241-4597e11552d1' class='xr-var-data-in' type='checkbox'><label for='data-066075ff-f337-4b1b-8241-4597e11552d1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH2ClCH2Cl_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-bc647198-1032-4c39-bd93-b5e430b961ff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bc647198-1032-4c39-bd93-b5e430b961ff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-187765cc-d216-43ed-a536-50e448927ff3' class='xr-var-data-in' type='checkbox'><label for='data-187765cc-d216-43ed-a536-50e448927ff3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>C2H5Cl_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-4a20cbcc-5c1d-4993-a5c9-f5cc7068a843' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4a20cbcc-5c1d-4993-a5c9-f5cc7068a843' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cf79c990-5ce1-4583-837b-44a865b4a9c3' class='xr-var-data-in' type='checkbox'><label for='data-cf79c990-5ce1-4583-837b-44a865b4a9c3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MeONO2_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-c1e899a0-f1fd-46cd-a9e7-2ecdacb048e3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c1e899a0-f1fd-46cd-a9e7-2ecdacb048e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0f7e84b5-6af7-404a-8121-a251c04ba486' class='xr-var-data-in' type='checkbox'><label for='data-0f7e84b5-6af7-404a-8121-a251c04ba486' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>EthONO2_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-c3161b6a-0a74-4554-93e5-f144c7c5d48c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c3161b6a-0a74-4554-93e5-f144c7c5d48c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-45db1497-8fea-4162-a7eb-5de056c84f96' class='xr-var-data-in' type='checkbox'><label for='data-45db1497-8fea-4162-a7eb-5de056c84f96' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>iPropONO2_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-f3471c27-a345-43d7-917c-970a6e47ea9b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f3471c27-a345-43d7-917c-970a6e47ea9b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-84a2cc89-19fa-4fbd-92eb-96735f0376e1' class='xr-var-data-in' type='checkbox'><label for='data-84a2cc89-19fa-4fbd-92eb-96735f0376e1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nPropONO2_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-c78ca333-e5e2-4d18-a161-6ed6623bd171' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c78ca333-e5e2-4d18-a161-6ed6623bd171' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c8c9cbb0-aff4-457c-a196-cced923cd89f' class='xr-var-data-in' type='checkbox'><label for='data-c8c9cbb0-aff4-457c-a196-cced923cd89f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x2ButONO2_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-f5fd7656-7ac3-47b0-a444-faedfa12d7ef' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f5fd7656-7ac3-47b0-a444-faedfa12d7ef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-22cc5e5c-fac8-4f7b-94fa-5f1c0ef8365c' class='xr-var-data-in' type='checkbox'><label for='data-22cc5e5c-fac8-4f7b-94fa-5f1c0ef8365c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x3PentONO2_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-19a8b047-42fd-4f1f-91d3-a6a5f2c42838' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-19a8b047-42fd-4f1f-91d3-a6a5f2c42838' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4d56a5d2-59d1-485e-a9d0-cf719f27f5c4' class='xr-var-data-in' type='checkbox'><label for='data-4d56a5d2-59d1-485e-a9d0-cf719f27f5c4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x2PentONO2_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-a10c5a88-e480-41d5-a36d-299b73efecaa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a10c5a88-e480-41d5-a36d-299b73efecaa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d50d0fe4-0af1-4187-b7ce-0cba7b043adc' class='xr-var-data-in' type='checkbox'><label for='data-d50d0fe4-0af1-4187-b7ce-0cba7b043adc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x3Me2ButONO2_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-d08db304-a5bf-447a-8ac7-c510b06bdfd9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d08db304-a5bf-447a-8ac7-c510b06bdfd9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7858c94b-eac4-45b1-bde6-1050473ef349' class='xr-var-data-in' type='checkbox'><label for='data-7858c94b-eac4-45b1-bde6-1050473ef349' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Ethane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-32df2edb-01ed-4feb-a362-2194351400b2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-32df2edb-01ed-4feb-a362-2194351400b2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-edc3f42d-ff41-45c6-91fd-440692ff3e23' class='xr-var-data-in' type='checkbox'><label for='data-edc3f42d-ff41-45c6-91fd-440692ff3e23' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Ethene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-f244c247-0ad3-4a93-9df4-bef66c1a7fcf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f244c247-0ad3-4a93-9df4-bef66c1a7fcf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e738cd2f-e0ff-4304-894b-0f5a89c67a9b' class='xr-var-data-in' type='checkbox'><label for='data-e738cd2f-e0ff-4304-894b-0f5a89c67a9b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Ethyne_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-7b88b62d-6d6b-48b6-8b37-4cb5dcdc957c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7b88b62d-6d6b-48b6-8b37-4cb5dcdc957c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1c3a85fc-67e4-474a-8e00-7c6f563752c3' class='xr-var-data-in' type='checkbox'><label for='data-1c3a85fc-67e4-474a-8e00-7c6f563752c3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Propene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-aa77af0f-6f6e-46a4-b086-d42cffcb7bd6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aa77af0f-6f6e-46a4-b086-d42cffcb7bd6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f68369f5-1732-4e61-b28e-ccc63c470bb1' class='xr-var-data-in' type='checkbox'><label for='data-f68369f5-1732-4e61-b28e-ccc63c470bb1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Propane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-985bf0ce-2bee-4aa9-b42a-85224cf7043b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-985bf0ce-2bee-4aa9-b42a-85224cf7043b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a65a999c-d59c-4462-b14a-e7c1b7d4abec' class='xr-var-data-in' type='checkbox'><label for='data-a65a999c-d59c-4462-b14a-e7c1b7d4abec' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Propadiene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-5b6783e0-3370-4ff0-b7c7-ab171a8f4a8d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5b6783e0-3370-4ff0-b7c7-ab171a8f4a8d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b5f0c459-0b2a-48c4-afc9-3e2bd6d8abf1' class='xr-var-data-in' type='checkbox'><label for='data-b5f0c459-0b2a-48c4-afc9-3e2bd6d8abf1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Propyne_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-9af782e7-e96e-47e6-8aae-3daf61174024' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9af782e7-e96e-47e6-8aae-3daf61174024' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1e5a0acd-d4e7-4067-aa2d-8f53e9b48f91' class='xr-var-data-in' type='checkbox'><label for='data-1e5a0acd-d4e7-4067-aa2d-8f53e9b48f91' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>iButane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-fde0ada2-9732-419d-a05a-b911279bdf15' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fde0ada2-9732-419d-a05a-b911279bdf15' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1248c2b3-87e8-4a12-82b2-9b60b106567a' class='xr-var-data-in' type='checkbox'><label for='data-1248c2b3-87e8-4a12-82b2-9b60b106567a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nButane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-81a003d8-37f7-4574-be37-79105a7b169c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-81a003d8-37f7-4574-be37-79105a7b169c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-36bbc5c9-317a-413c-8659-b70fbb340562' class='xr-var-data-in' type='checkbox'><label for='data-36bbc5c9-317a-413c-8659-b70fbb340562' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x1Butene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-2a922372-cc4a-4984-9151-ae16a391a8f3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2a922372-cc4a-4984-9151-ae16a391a8f3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-08d1839a-83f8-480d-94f4-c8f0531eb2ad' class='xr-var-data-in' type='checkbox'><label for='data-08d1839a-83f8-480d-94f4-c8f0531eb2ad' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>iButene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-196ee37a-9d91-4a30-9f5f-cc361806ec29' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-196ee37a-9d91-4a30-9f5f-cc361806ec29' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-13d70063-738c-42b0-be1b-cf424f683c0b' class='xr-var-data-in' type='checkbox'><label for='data-13d70063-738c-42b0-be1b-cf424f683c0b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>t2Butene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-83b5c400-e224-4439-8836-59b77330d230' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-83b5c400-e224-4439-8836-59b77330d230' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4802686d-4084-42e7-a746-57051ceb2079' class='xr-var-data-in' type='checkbox'><label for='data-4802686d-4084-42e7-a746-57051ceb2079' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>c2Butene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-d2819d25-9e4d-462f-864c-f8414a17655b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d2819d25-9e4d-462f-864c-f8414a17655b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-646cf6b5-384d-49e7-b10e-018c6bacb70c' class='xr-var-data-in' type='checkbox'><label for='data-646cf6b5-384d-49e7-b10e-018c6bacb70c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x13Butadiene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e7baf3c6-f4b7-4067-8981-164ca4862493' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e7baf3c6-f4b7-4067-8981-164ca4862493' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9dbcd0ef-e5e7-4dbf-8995-e78e4f8d7331' class='xr-var-data-in' type='checkbox'><label for='data-9dbcd0ef-e5e7-4dbf-8995-e78e4f8d7331' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x12Butadiene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-485e6a65-bf8e-4347-8a4e-bf54903947e2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-485e6a65-bf8e-4347-8a4e-bf54903947e2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a0e882cf-920e-461c-8368-9133b01ff437' class='xr-var-data-in' type='checkbox'><label for='data-a0e882cf-920e-461c-8368-9133b01ff437' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x1Buten3yne_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-1a8c90ff-9095-42fe-ac99-7ce6dcae2bd6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1a8c90ff-9095-42fe-ac99-7ce6dcae2bd6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4b2b548f-b73e-4191-b103-c2bd9f32142a' class='xr-var-data-in' type='checkbox'><label for='data-4b2b548f-b73e-4191-b103-c2bd9f32142a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x13Butadyine_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-d6165097-988a-4a85-9be7-0c8c1f367000' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d6165097-988a-4a85-9be7-0c8c1f367000' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cbace0ff-ca5b-47be-8187-7b7320bf2c0f' class='xr-var-data-in' type='checkbox'><label for='data-cbace0ff-ca5b-47be-8187-7b7320bf2c0f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x1Butyne_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-271dacce-f02f-475a-836f-6b4f8bfea11d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-271dacce-f02f-475a-836f-6b4f8bfea11d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-880948d3-1c28-4848-be14-39201043696c' class='xr-var-data-in' type='checkbox'><label for='data-880948d3-1c28-4848-be14-39201043696c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x2Butyne_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-afc2308f-e773-44f3-8470-40f2ef12f81f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-afc2308f-e773-44f3-8470-40f2ef12f81f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d9ccea46-7292-4e10-ac8e-b4ba087eaabe' class='xr-var-data-in' type='checkbox'><label for='data-d9ccea46-7292-4e10-ac8e-b4ba087eaabe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>iPentane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e5b1d609-e174-474b-b392-5eab0eac1c79' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e5b1d609-e174-474b-b392-5eab0eac1c79' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9a4a45aa-4691-442c-bab5-45bf1a1bfcf2' class='xr-var-data-in' type='checkbox'><label for='data-9a4a45aa-4691-442c-bab5-45bf1a1bfcf2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nPentane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-d9915032-f412-4f0f-a6ff-a5c428acef41' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d9915032-f412-4f0f-a6ff-a5c428acef41' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-48cda8a0-675a-479c-8bf4-20a50012318f' class='xr-var-data-in' type='checkbox'><label for='data-48cda8a0-675a-479c-8bf4-20a50012318f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Isoprene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-8228a935-c85e-4dbc-88f1-985abd065371' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8228a935-c85e-4dbc-88f1-985abd065371' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b4ec0f9d-45a5-4375-a26a-7d15157040c9' class='xr-var-data-in' type='checkbox'><label for='data-b4ec0f9d-45a5-4375-a26a-7d15157040c9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x1Pentene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-f664388d-e1ce-45f4-94ff-59663d954729' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f664388d-e1ce-45f4-94ff-59663d954729' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-90301490-8725-40aa-b07f-f6de966b2029' class='xr-var-data-in' type='checkbox'><label for='data-90301490-8725-40aa-b07f-f6de966b2029' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>t2Pentene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-3246c9b9-2b86-4bbc-b31d-30bf4bad42ac' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3246c9b9-2b86-4bbc-b31d-30bf4bad42ac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-406ebe7b-d73f-48e3-a8de-85b296863d23' class='xr-var-data-in' type='checkbox'><label for='data-406ebe7b-d73f-48e3-a8de-85b296863d23' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>c2Pentene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ac36dc48-e2ac-429a-84ca-78f742d1e11a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ac36dc48-e2ac-429a-84ca-78f742d1e11a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-96a6e3f3-438f-4cf8-bee7-e4a09fe8aef6' class='xr-var-data-in' type='checkbox'><label for='data-96a6e3f3-438f-4cf8-bee7-e4a09fe8aef6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>3Me1Butene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-d368f2ff-12ba-490f-a81f-9f2016da4eba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d368f2ff-12ba-490f-a81f-9f2016da4eba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-64d50b6d-cddf-42f0-b21a-b151afc9540f' class='xr-var-data-in' type='checkbox'><label for='data-64d50b6d-cddf-42f0-b21a-b151afc9540f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>2Me1Butene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-b1372e23-05ce-42d3-9302-58cb3970f272' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b1372e23-05ce-42d3-9302-58cb3970f272' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-26fdf4d1-3eec-4290-b5da-79e0b0c2a3de' class='xr-var-data-in' type='checkbox'><label for='data-26fdf4d1-3eec-4290-b5da-79e0b0c2a3de' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>2Me2Butene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-11a97efe-97b8-482d-9558-60381de856fb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-11a97efe-97b8-482d-9558-60381de856fb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1da2fa6a-c5ce-497f-81fd-a6043613dd52' class='xr-var-data-in' type='checkbox'><label for='data-1da2fa6a-c5ce-497f-81fd-a6043613dd52' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x13Pentadienes_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-58633779-a4b2-4804-887d-5cd4bf188a8d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-58633779-a4b2-4804-887d-5cd4bf188a8d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-09a15459-2894-4a78-a3bb-8e50392a76c8' class='xr-var-data-in' type='checkbox'><label for='data-09a15459-2894-4a78-a3bb-8e50392a76c8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x3Me1PenteneAnd4Me1Pentene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-14385596-1a65-42d0-8330-de8e8519e269' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-14385596-1a65-42d0-8330-de8e8519e269' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ce113766-544f-4d49-97c3-06fb1c0fd833' class='xr-var-data-in' type='checkbox'><label for='data-ce113766-544f-4d49-97c3-06fb1c0fd833' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x1Hexene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-caa47650-1e95-4321-a622-ed69da5098f2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-caa47650-1e95-4321-a622-ed69da5098f2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2aa4c2f7-98e2-4250-848e-c22e81c0b98c' class='xr-var-data-in' type='checkbox'><label for='data-2aa4c2f7-98e2-4250-848e-c22e81c0b98c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x1Heptene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-0e308f92-7896-47fe-8400-bd4c1fbbf3ac' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0e308f92-7896-47fe-8400-bd4c1fbbf3ac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c49d2213-7264-4240-823f-ab408a54dca9' class='xr-var-data-in' type='checkbox'><label for='data-c49d2213-7264-4240-823f-ab408a54dca9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x1Octene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-6392d2c3-1285-46e5-8210-0f075b8aacaf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6392d2c3-1285-46e5-8210-0f075b8aacaf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1788b6a9-0cce-45c7-b671-a539b7517eb8' class='xr-var-data-in' type='checkbox'><label for='data-1788b6a9-0cce-45c7-b671-a539b7517eb8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x1Nonene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-94fc93a8-c946-4e8f-b539-55c2927640b4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-94fc93a8-c946-4e8f-b539-55c2927640b4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-349ed356-193d-42c7-ad29-37ba346bcd67' class='xr-var-data-in' type='checkbox'><label for='data-349ed356-193d-42c7-ad29-37ba346bcd67' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x1Decene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-8a9fde22-0827-47d3-bd12-537defacd57d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8a9fde22-0827-47d3-bd12-537defacd57d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4dd2f3dc-d228-46f8-843a-c6e09ea39e6f' class='xr-var-data-in' type='checkbox'><label for='data-4dd2f3dc-d228-46f8-843a-c6e09ea39e6f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nHexane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-0547af4a-a96f-4b5e-b16f-c00a5b84a9c9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0547af4a-a96f-4b5e-b16f-c00a5b84a9c9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-15bb0e15-2144-401f-a6bf-0f4e1e7d75fc' class='xr-var-data-in' type='checkbox'><label for='data-15bb0e15-2144-401f-a6bf-0f4e1e7d75fc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nHeptane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-79d7f245-78a4-4e97-8693-63fb12378337' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-79d7f245-78a4-4e97-8693-63fb12378337' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fe2ed3fb-6849-4669-9230-bec74f90763e' class='xr-var-data-in' type='checkbox'><label for='data-fe2ed3fb-6849-4669-9230-bec74f90763e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nOctane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-1e4f10ca-3357-4560-9372-914b2ae78052' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1e4f10ca-3357-4560-9372-914b2ae78052' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cfc70072-c8a5-436c-80fc-5dc2c7fd6d7c' class='xr-var-data-in' type='checkbox'><label for='data-cfc70072-c8a5-436c-80fc-5dc2c7fd6d7c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nNonane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-913cd460-48ff-4661-9514-0445811fda08' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-913cd460-48ff-4661-9514-0445811fda08' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-692fa6e8-fb9b-4bb3-a73a-b29ee3aef821' class='xr-var-data-in' type='checkbox'><label for='data-692fa6e8-fb9b-4bb3-a73a-b29ee3aef821' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nDecane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ae4dcaec-5302-42cb-9abc-130cc88cf0f6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ae4dcaec-5302-42cb-9abc-130cc88cf0f6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-011ccc78-e8d4-4615-b9e4-80182b95a852' class='xr-var-data-in' type='checkbox'><label for='data-011ccc78-e8d4-4615-b9e4-80182b95a852' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nUndecane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-49630b95-a425-4949-b437-6eb4a4ec8ef8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-49630b95-a425-4949-b437-6eb4a4ec8ef8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-56e4d077-06b8-479a-adc6-879baed08945' class='xr-var-data-in' type='checkbox'><label for='data-56e4d077-06b8-479a-adc6-879baed08945' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x22Dimebutane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-697e59f4-9478-4175-87e3-81f727277da2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-697e59f4-9478-4175-87e3-81f727277da2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c9ea29a-fea1-4ace-96b5-8206d5121fad' class='xr-var-data-in' type='checkbox'><label for='data-4c9ea29a-fea1-4ace-96b5-8206d5121fad' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x23Dimebutane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ed6f4793-d3fa-4b40-bb99-b3479a7350ed' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ed6f4793-d3fa-4b40-bb99-b3479a7350ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c9fa793a-3962-4f88-818d-98dcf7f9c881' class='xr-var-data-in' type='checkbox'><label for='data-c9fa793a-3962-4f88-818d-98dcf7f9c881' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x2MePentane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-8f7e6207-a71e-47ae-ba8d-11b273804ce8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8f7e6207-a71e-47ae-ba8d-11b273804ce8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-29c07e2b-b616-45cb-b4a5-7a2b4aa1fe03' class='xr-var-data-in' type='checkbox'><label for='data-29c07e2b-b616-45cb-b4a5-7a2b4aa1fe03' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x3MePentane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-0eb2f583-6fc4-4487-8743-86cc6e8545ed' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0eb2f583-6fc4-4487-8743-86cc6e8545ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b42b535f-600a-473e-8026-e508970b364e' class='xr-var-data-in' type='checkbox'><label for='data-b42b535f-600a-473e-8026-e508970b364e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x2MeHexane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-f09a2b72-02d5-45a3-a793-8b90e50b336a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f09a2b72-02d5-45a3-a793-8b90e50b336a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-693b616d-5f2b-43ea-a53b-4cf77a4c19ad' class='xr-var-data-in' type='checkbox'><label for='data-693b616d-5f2b-43ea-a53b-4cf77a4c19ad' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x3MeHexane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e5839822-1a4e-4b4f-bc39-00548d631c03' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e5839822-1a4e-4b4f-bc39-00548d631c03' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-62055465-3f71-41f5-b5c4-dead00bedc85' class='xr-var-data-in' type='checkbox'><label for='data-62055465-3f71-41f5-b5c4-dead00bedc85' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x23DimePentane_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-3eed4433-aeb9-4591-a20e-24a4f3441354' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3eed4433-aeb9-4591-a20e-24a4f3441354' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-10fb6161-60c8-4458-b1aa-c2a4b0590ed5' class='xr-var-data-in' type='checkbox'><label for='data-10fb6161-60c8-4458-b1aa-c2a4b0590ed5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x224TrimePentane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ae5afdc0-f091-495c-aaef-38caaed41704' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ae5afdc0-f091-495c-aaef-38caaed41704' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4f0c2be8-42ee-48b4-b875-0fc122efe1fc' class='xr-var-data-in' type='checkbox'><label for='data-4f0c2be8-42ee-48b4-b875-0fc122efe1fc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x234TrimePentane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-2ed9aa4e-5dfc-4759-b123-acb0512d96da' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2ed9aa4e-5dfc-4759-b123-acb0512d96da' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c62bb538-deb8-42e5-a6e7-b37921c361d7' class='xr-var-data-in' type='checkbox'><label for='data-c62bb538-deb8-42e5-a6e7-b37921c361d7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CycPentane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-8c31da6a-795c-4309-a306-e9ce2b2138a9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8c31da6a-795c-4309-a306-e9ce2b2138a9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cae614c1-9796-4b73-9156-d264fca99729' class='xr-var-data-in' type='checkbox'><label for='data-cae614c1-9796-4b73-9156-d264fca99729' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MeCycPentane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-5364a11a-a9ac-416a-896e-dedd78d2066c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5364a11a-a9ac-416a-896e-dedd78d2066c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ab514426-015a-4822-a614-77a226cc3be8' class='xr-var-data-in' type='checkbox'><label for='data-ab514426-015a-4822-a614-77a226cc3be8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CycHexane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-4c632314-fa03-4f69-af45-1a75a00a39f3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4c632314-fa03-4f69-af45-1a75a00a39f3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-92e87309-6eb2-4491-8311-ce1905f42d54' class='xr-var-data-in' type='checkbox'><label for='data-92e87309-6eb2-4491-8311-ce1905f42d54' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MeCycHexane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-5fb7996c-1ae7-4b2b-9eb4-1cc29d6cea48' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5fb7996c-1ae7-4b2b-9eb4-1cc29d6cea48' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-54771b48-da9b-4131-9394-103517a67df2' class='xr-var-data-in' type='checkbox'><label for='data-54771b48-da9b-4131-9394-103517a67df2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CycPentene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-6b71ca2a-3914-4830-baee-79cc83ace7b3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6b71ca2a-3914-4830-baee-79cc83ace7b3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5b400619-d8d7-45d5-bc91-893781b752df' class='xr-var-data-in' type='checkbox'><label for='data-5b400619-d8d7-45d5-bc91-893781b752df' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Benzene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-f917d645-c18d-47db-abb8-c76e5e81e62a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f917d645-c18d-47db-abb8-c76e5e81e62a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c695a9a3-7b6f-4f56-a48c-94f33625b708' class='xr-var-data-in' type='checkbox'><label for='data-c695a9a3-7b6f-4f56-a48c-94f33625b708' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Toluene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e3f5ba89-bf9c-4ddf-901e-86ee8ff4f337' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e3f5ba89-bf9c-4ddf-901e-86ee8ff4f337' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-882cff04-7166-48f2-acaf-0c6168a5c1a3' class='xr-var-data-in' type='checkbox'><label for='data-882cff04-7166-48f2-acaf-0c6168a5c1a3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>EthBenzene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-b580805a-f408-4fea-84ad-9290bd98a6e9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b580805a-f408-4fea-84ad-9290bd98a6e9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8189c114-70bd-4d04-b079-1d1e3293710a' class='xr-var-data-in' type='checkbox'><label for='data-8189c114-70bd-4d04-b079-1d1e3293710a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mpXylene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-a61af31e-aeda-4ca0-b90d-50b4ca1c769a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a61af31e-aeda-4ca0-b90d-50b4ca1c769a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-40843f77-2d73-4379-ae05-0696f6b94280' class='xr-var-data-in' type='checkbox'><label for='data-40843f77-2d73-4379-ae05-0696f6b94280' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>oXylene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-a28b38be-dfea-4851-8bce-c812c06a79df' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a28b38be-dfea-4851-8bce-c812c06a79df' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f8bafc73-1752-4cae-bd35-bf50b7666bea' class='xr-var-data-in' type='checkbox'><label for='data-f8bafc73-1752-4cae-bd35-bf50b7666bea' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Styrene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-63a16f3b-2b97-48fe-939d-2ba4306f146a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-63a16f3b-2b97-48fe-939d-2ba4306f146a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8ffa94fd-90ab-4519-bb5d-9384e894a64b' class='xr-var-data-in' type='checkbox'><label for='data-8ffa94fd-90ab-4519-bb5d-9384e894a64b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>EthynylBenzene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-9747932f-4452-4b1e-9059-e6bc3dc86c67' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9747932f-4452-4b1e-9059-e6bc3dc86c67' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3b71dcdb-d6fd-4dcf-b17c-95637fd86283' class='xr-var-data-in' type='checkbox'><label for='data-3b71dcdb-d6fd-4dcf-b17c-95637fd86283' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>iPropBenzene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-270f5351-9a97-4b61-aac3-90dc9ea0f636' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-270f5351-9a97-4b61-aac3-90dc9ea0f636' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9a7d8f86-d418-4b57-8e2a-899e3cfa64d4' class='xr-var-data-in' type='checkbox'><label for='data-9a7d8f86-d418-4b57-8e2a-899e3cfa64d4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nPropBenzene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-30af13f1-a181-4438-acd2-0f4d0177f1cb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-30af13f1-a181-4438-acd2-0f4d0177f1cb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-214917ec-3a4d-4d5b-a6b8-41cc14f2b5e1' class='xr-var-data-in' type='checkbox'><label for='data-214917ec-3a4d-4d5b-a6b8-41cc14f2b5e1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x3EthToluene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-2f590735-1ac3-45f4-96f7-87243914842d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2f590735-1ac3-45f4-96f7-87243914842d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-04d61969-dd51-4f35-9df1-9a8bf464ab99' class='xr-var-data-in' type='checkbox'><label for='data-04d61969-dd51-4f35-9df1-9a8bf464ab99' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x4EthToluene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-97c09fc0-e215-4713-90c5-2d649f360fad' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-97c09fc0-e215-4713-90c5-2d649f360fad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4b00aeed-9c46-4da2-85ba-71898b392173' class='xr-var-data-in' type='checkbox'><label for='data-4b00aeed-9c46-4da2-85ba-71898b392173' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x2EthToluene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-984222dd-f4b0-484f-abfd-c6328a9a7540' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-984222dd-f4b0-484f-abfd-c6328a9a7540' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-31727514-8a1d-4e71-9d48-ed24ee678aad' class='xr-var-data-in' type='checkbox'><label for='data-31727514-8a1d-4e71-9d48-ed24ee678aad' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x135rimeBenzene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-4f8d6d9b-f1f1-4ccf-9aee-38733e61a521' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4f8d6d9b-f1f1-4ccf-9aee-38733e61a521' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0f813bc6-50e7-4d2a-95c5-f337b07e53d2' class='xr-var-data-in' type='checkbox'><label for='data-0f813bc6-50e7-4d2a-95c5-f337b07e53d2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x124rimeBenzene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-7843e75f-009e-43c3-9de7-5453cadf58b2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7843e75f-009e-43c3-9de7-5453cadf58b2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-265d649e-9ead-4922-b49b-194ada11a710' class='xr-var-data-in' type='checkbox'><label for='data-265d649e-9ead-4922-b49b-194ada11a710' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ClBenzene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-87fdcc03-6c37-41e7-8f2a-18c23c27c648' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-87fdcc03-6c37-41e7-8f2a-18c23c27c648' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d8a4f627-3848-4239-9ff2-335acdeb348f' class='xr-var-data-in' type='checkbox'><label for='data-d8a4f627-3848-4239-9ff2-335acdeb348f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aPinene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-1246b210-dd8e-480b-a36a-2dce6f4f04ba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1246b210-dd8e-480b-a36a-2dce6f4f04ba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1b7c27a3-758c-4a49-834e-a84f8a182cee' class='xr-var-data-in' type='checkbox'><label for='data-1b7c27a3-758c-4a49-834e-a84f8a182cee' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>bPinene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-14bcc265-7189-4445-8c52-64b6c81b8524' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-14bcc265-7189-4445-8c52-64b6c81b8524' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-468983ac-37c1-4846-8847-d575ac42281c' class='xr-var-data-in' type='checkbox'><label for='data-468983ac-37c1-4846-8847-d575ac42281c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Tricyclene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-9f3fa81f-8109-4820-aea0-950f620c5a3b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9f3fa81f-8109-4820-aea0-950f620c5a3b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8e7f54f1-29da-41ea-b9e9-caf6d3206725' class='xr-var-data-in' type='checkbox'><label for='data-8e7f54f1-29da-41ea-b9e9-caf6d3206725' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Camphene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-48feb861-2c02-4176-adcc-29a89c2bd40a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-48feb861-2c02-4176-adcc-29a89c2bd40a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6d2b482e-1774-42c1-8ec2-8739c5ca8886' class='xr-var-data-in' type='checkbox'><label for='data-6d2b482e-1774-42c1-8ec2-8739c5ca8886' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Myrcene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-f50f575e-543a-459c-90b4-6d2eb870e569' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f50f575e-543a-459c-90b4-6d2eb870e569' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9ff946f7-063c-450c-89e5-95cb823b87ba' class='xr-var-data-in' type='checkbox'><label for='data-9ff946f7-063c-450c-89e5-95cb823b87ba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Limonene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-a3cf3ee1-adfc-42d0-b703-573c2873acb9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a3cf3ee1-adfc-42d0-b703-573c2873acb9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-10c93de6-1b6e-4f81-85cd-b3273eace815' class='xr-var-data-in' type='checkbox'><label for='data-10c93de6-1b6e-4f81-85cd-b3273eace815' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Furan_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e6bad44e-2c69-47b2-9f40-0a39fb1efff3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e6bad44e-2c69-47b2-9f40-0a39fb1efff3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9d32013a-e53e-4bac-b79d-3f648febe61e' class='xr-var-data-in' type='checkbox'><label for='data-9d32013a-e53e-4bac-b79d-3f648febe61e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x2MeFuran_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-b003062c-7ae0-4975-9d65-632c80aa3bc1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b003062c-7ae0-4975-9d65-632c80aa3bc1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-78de91ae-75a7-403e-b6b4-8b0f1edab696' class='xr-var-data-in' type='checkbox'><label for='data-78de91ae-75a7-403e-b6b4-8b0f1edab696' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x3MeFuran_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-d54d6e19-cefd-4d4c-b050-1973f6ba8639' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d54d6e19-cefd-4d4c-b050-1973f6ba8639' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dd831568-8c3b-4dfb-8c60-84b4a8e635a3' class='xr-var-data-in' type='checkbox'><label for='data-dd831568-8c3b-4dfb-8c60-84b4a8e635a3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>BenzFuran_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-3740afd5-5d92-4944-8a3a-4be891ded3ac' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3740afd5-5d92-4944-8a3a-4be891ded3ac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cd45e5e4-6cf2-4e86-b946-12145fcf1a79' class='xr-var-data-in' type='checkbox'><label for='data-cd45e5e4-6cf2-4e86-b946-12145fcf1a79' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>iButanal_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-4a644499-d2fa-47ac-a999-86977899c1bb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4a644499-d2fa-47ac-a999-86977899c1bb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3937f2b5-9aaf-4d04-8313-bd4a9e91499b' class='xr-var-data-in' type='checkbox'><label for='data-3937f2b5-9aaf-4d04-8313-bd4a9e91499b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Butanal_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-23cdc753-813c-4197-901c-c1a560542b8f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-23cdc753-813c-4197-901c-c1a560542b8f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-445c4fce-b2a5-4f7c-84c6-da188a56427f' class='xr-var-data-in' type='checkbox'><label for='data-445c4fce-b2a5-4f7c-84c6-da188a56427f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>AcetonePropanal_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-2365a1b1-1288-4d36-8d1a-3ff7ad8c116a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2365a1b1-1288-4d36-8d1a-3ff7ad8c116a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e4a95942-8a9f-4efc-bde8-1f695c0d3609' class='xr-var-data-in' type='checkbox'><label for='data-e4a95942-8a9f-4efc-bde8-1f695c0d3609' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MEK_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-a242cb7d-5c1b-450d-9cf9-c59b46827981' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a242cb7d-5c1b-450d-9cf9-c59b46827981' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1ae011b5-fa06-44ae-bb16-b02a89931493' class='xr-var-data-in' type='checkbox'><label for='data-1ae011b5-fa06-44ae-bb16-b02a89931493' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MAC_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-0d9b6a73-27bd-4101-b418-b948792522c0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0d9b6a73-27bd-4101-b418-b948792522c0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8cda5191-c3a5-4a07-a29b-e2b9f82b493e' class='xr-var-data-in' type='checkbox'><label for='data-8cda5191-c3a5-4a07-a29b-e2b9f82b493e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MVK_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-60a0fb0a-751a-4b72-bfe0-cbf13591627b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-60a0fb0a-751a-4b72-bfe0-cbf13591627b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-367a1de6-a3ab-4d7d-a29c-d684a99e9a0c' class='xr-var-data-in' type='checkbox'><label for='data-367a1de6-a3ab-4d7d-a29c-d684a99e9a0c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Acrolein_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-57a80749-6d75-4273-ba58-e141b8446197' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-57a80749-6d75-4273-ba58-e141b8446197' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-89b2669e-64d1-4a97-805a-a737bddd5832' class='xr-var-data-in' type='checkbox'><label for='data-89b2669e-64d1-4a97-805a-a737bddd5832' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>iPropanol_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-7420bcf5-aa23-4af3-a80d-76ad628a0707' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7420bcf5-aa23-4af3-a80d-76ad628a0707' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9c164974-0861-414f-a728-7f77cad99e41' class='xr-var-data-in' type='checkbox'><label for='data-9c164974-0861-414f-a728-7f77cad99e41' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Nitromethane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-3744b792-2075-4bfc-b612-28975c6fcdd1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3744b792-2075-4bfc-b612-28975c6fcdd1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d99f4b3-f191-48dd-ae5b-ea35226778a8' class='xr-var-data-in' type='checkbox'><label for='data-1d99f4b3-f191-48dd-ae5b-ea35226778a8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Acrylonitrile_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ac170b9d-1033-42b5-af48-c471a0b255d1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ac170b9d-1033-42b5-af48-c471a0b255d1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0a759d74-c77a-43ff-9828-a06091111411' class='xr-var-data-in' type='checkbox'><label for='data-0a759d74-c77a-43ff-9828-a06091111411' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PropNitrile_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-446bba24-0b7c-43fa-96aa-955e34361047' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-446bba24-0b7c-43fa-96aa-955e34361047' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-69adce32-7b0d-4632-b8b3-42d1e7203212' class='xr-var-data-in' type='checkbox'><label for='data-69adce32-7b0d-4632-b8b3-42d1e7203212' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MeAcetate_WAS_BLAKE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-a88ffd02-77be-47f7-b953-bcc542496ea1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a88ffd02-77be-47f7-b953-bcc542496ea1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b401ba4a-4004-41f4-a080-c2de676b389b' class='xr-var-data-in' type='checkbox'><label for='data-b401ba4a-4004-41f4-a080-c2de676b389b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HFC134a_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-9227dc1a-6d32-4b26-9426-895cdf58a186' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9227dc1a-6d32-4b26-9426-895cdf58a186' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-11b5cfa6-9f5a-42c7-abbd-67a50dbad178' class='xr-var-data-in' type='checkbox'><label for='data-11b5cfa6-9f5a-42c7-abbd-67a50dbad178' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HCFC141b_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-f4c4ddb3-2c00-463e-a7b1-a4bf455c4fba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f4c4ddb3-2c00-463e-a7b1-a4bf455c4fba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-02622aa2-dae5-4895-a7be-27efcba9c39d' class='xr-var-data-in' type='checkbox'><label for='data-02622aa2-dae5-4895-a7be-27efcba9c39d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>arbppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HCFC142b_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-2a316ea7-01b3-4686-8504-9c3e0db62af0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2a316ea7-01b3-4686-8504-9c3e0db62af0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8c006790-42e6-4d24-b0fc-342e90907e55' class='xr-var-data-in' type='checkbox'><label for='data-8c006790-42e6-4d24-b0fc-342e90907e55' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HCFC22_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-18e0f619-d2c4-4e92-9502-c440e1088912' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-18e0f619-d2c4-4e92-9502-c440e1088912' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e97a83d4-2677-427d-9eed-aa1fcf4f33ae' class='xr-var-data-in' type='checkbox'><label for='data-e97a83d4-2677-427d-9eed-aa1fcf4f33ae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH2Cl2_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-d6a5b310-a37c-48da-b483-41cd3f3a29d4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d6a5b310-a37c-48da-b483-41cd3f3a29d4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fe3b911b-dd8a-4ba4-af72-136ea789015e' class='xr-var-data-in' type='checkbox'><label for='data-fe3b911b-dd8a-4ba4-af72-136ea789015e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CHCl3_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-bf813ca6-0c3e-4a7d-a790-3aa77252bfae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bf813ca6-0c3e-4a7d-a790-3aa77252bfae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-79b463f2-f17a-4cdd-9519-917433ae0bca' class='xr-var-data-in' type='checkbox'><label for='data-79b463f2-f17a-4cdd-9519-917433ae0bca' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH2ClCH2Cl_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-803f23c7-d831-4d8d-9f6c-c3ce9befb1cc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-803f23c7-d831-4d8d-9f6c-c3ce9befb1cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3a3b3280-8ece-4fd2-8921-c37953956f8b' class='xr-var-data-in' type='checkbox'><label for='data-3a3b3280-8ece-4fd2-8921-c37953956f8b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH3CCl3_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-9ce4bdb6-70ee-4898-9719-f20cb5a9fff5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9ce4bdb6-70ee-4898-9719-f20cb5a9fff5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-56cb1ea7-fd3c-4b9c-9b33-1939807238c4' class='xr-var-data-in' type='checkbox'><label for='data-56cb1ea7-fd3c-4b9c-9b33-1939807238c4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>C2Cl4_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-098f27d3-ea77-476e-ae28-7bb5fba416ca' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-098f27d3-ea77-476e-ae28-7bb5fba416ca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c73e00ca-f6a4-4cc5-8854-35908abd5eaf' class='xr-var-data-in' type='checkbox'><label for='data-c73e00ca-f6a4-4cc5-8854-35908abd5eaf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ClBenzene_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-464c94de-86f4-4646-b042-20dd9c7874a4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-464c94de-86f4-4646-b042-20dd9c7874a4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fb67ee87-c743-4cb0-8aea-19b342f4b5dd' class='xr-var-data-in' type='checkbox'><label for='data-fb67ee87-c743-4cb0-8aea-19b342f4b5dd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CHBrCl2_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-d5075226-a75e-43f4-9bec-dab70ebf5def' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d5075226-a75e-43f4-9bec-dab70ebf5def' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-12a94d5a-2794-4329-8efe-a75e3462b313' class='xr-var-data-in' type='checkbox'><label for='data-12a94d5a-2794-4329-8efe-a75e3462b313' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CHBr2Cl_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-61d00399-6437-48fd-a0e9-9b262175b3bd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-61d00399-6437-48fd-a0e9-9b262175b3bd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-425ed897-8180-40f6-8625-9ec6c88c3a0d' class='xr-var-data-in' type='checkbox'><label for='data-425ed897-8180-40f6-8625-9ec6c88c3a0d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH3Br_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-73563277-6a89-4eea-af70-c82c7a154f49' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-73563277-6a89-4eea-af70-c82c7a154f49' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9bbb6214-8aa8-419e-bd5d-d080e59c82e1' class='xr-var-data-in' type='checkbox'><label for='data-9bbb6214-8aa8-419e-bd5d-d080e59c82e1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH2Br2_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-660a7324-c906-41fb-bb0b-721c7cc6bc60' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-660a7324-c906-41fb-bb0b-721c7cc6bc60' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3343fd42-9bc4-4b63-8950-890f30306d2f' class='xr-var-data-in' type='checkbox'><label for='data-3343fd42-9bc4-4b63-8950-890f30306d2f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CHBr3_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-8df13a1d-a78d-4078-9fb3-6daa440e22f4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8df13a1d-a78d-4078-9fb3-6daa440e22f4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d0d89731-1ded-4f8d-bad8-94f6120a03dd' class='xr-var-data-in' type='checkbox'><label for='data-d0d89731-1ded-4f8d-bad8-94f6120a03dd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH2ClI_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-36e30a30-f896-4d5f-95ff-723a49d2b7f0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-36e30a30-f896-4d5f-95ff-723a49d2b7f0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f7d59611-92ef-402c-b935-8fd0afcfd92c' class='xr-var-data-in' type='checkbox'><label for='data-f7d59611-92ef-402c-b935-8fd0afcfd92c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH3I_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-4241418a-b35e-46ea-a220-53199aaba645' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4241418a-b35e-46ea-a220-53199aaba645' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ab95f9fe-9a18-43bc-96c7-0b7e0a7675d5' class='xr-var-data-in' type='checkbox'><label for='data-ab95f9fe-9a18-43bc-96c7-0b7e0a7675d5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>arbppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CS2_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-90065915-a4d0-4a4b-bdc3-3d8db0e9dde0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-90065915-a4d0-4a4b-bdc3-3d8db0e9dde0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f48dc980-aa0d-4397-98e7-e5828ab5bcc0' class='xr-var-data-in' type='checkbox'><label for='data-f48dc980-aa0d-4397-98e7-e5828ab5bcc0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH3SH_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-94c53ce3-936d-427a-b196-a3cdc8aca7e6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-94c53ce3-936d-427a-b196-a3cdc8aca7e6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4f99e6c6-4643-4d01-9473-47bff41c316c' class='xr-var-data-in' type='checkbox'><label for='data-4f99e6c6-4643-4d01-9473-47bff41c316c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>arbppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>DMS_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-078af090-ce9f-4cb8-a916-5c08db75fca2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-078af090-ce9f-4cb8-a916-5c08db75fca2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c64bccd7-6e2b-4695-a266-6db15588619f' class='xr-var-data-in' type='checkbox'><label for='data-c64bccd7-6e2b-4695-a266-6db15588619f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Propane_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-8c056766-bc19-485c-9ee5-254960c6ccb3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8c056766-bc19-485c-9ee5-254960c6ccb3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ca782c7c-3a47-4038-b6f4-42d761434496' class='xr-var-data-in' type='checkbox'><label for='data-ca782c7c-3a47-4038-b6f4-42d761434496' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>iButane_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-1b6a3c6b-a821-4eb0-bbed-27867d00d276' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1b6a3c6b-a821-4eb0-bbed-27867d00d276' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-720ee01a-b87a-4773-b647-1b5152c6ffc2' class='xr-var-data-in' type='checkbox'><label for='data-720ee01a-b87a-4773-b647-1b5152c6ffc2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nButane_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-7233c192-018c-459d-816e-84e039889d12' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7233c192-018c-459d-816e-84e039889d12' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bdb65121-f04f-448d-9092-831cf3611c32' class='xr-var-data-in' type='checkbox'><label for='data-bdb65121-f04f-448d-9092-831cf3611c32' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>iPentane_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-6f075865-155b-4428-af4e-35f4a0f8ae68' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6f075865-155b-4428-af4e-35f4a0f8ae68' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e0ec255e-836d-4f59-acb1-ed795a636dab' class='xr-var-data-in' type='checkbox'><label for='data-e0ec255e-836d-4f59-acb1-ed795a636dab' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nPentane_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-77c65b1a-5c96-4098-9649-d68a7a1a4b6c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-77c65b1a-5c96-4098-9649-d68a7a1a4b6c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c42e0613-4a13-4a91-ad6d-4396335d946e' class='xr-var-data-in' type='checkbox'><label for='data-c42e0613-4a13-4a91-ad6d-4396335d946e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x2MePentane_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-eef5d7c7-c8bb-45c3-a74a-939e8cf5bf1b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eef5d7c7-c8bb-45c3-a74a-939e8cf5bf1b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-44620c7a-038b-4d07-9417-5e0215b0ddbd' class='xr-var-data-in' type='checkbox'><label for='data-44620c7a-038b-4d07-9417-5e0215b0ddbd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x3MePentane_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-816aae28-7d46-43e5-815b-d06a1c63e4d8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-816aae28-7d46-43e5-815b-d06a1c63e4d8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9cf7fee6-fbe3-47a2-9c9b-763f558b4e6e' class='xr-var-data-in' type='checkbox'><label for='data-9cf7fee6-fbe3-47a2-9c9b-763f558b4e6e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nHexane_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-dd69b44b-1093-4918-9ad8-3f4d5617eec7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dd69b44b-1093-4918-9ad8-3f4d5617eec7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9cc8b000-f02e-42b2-8c92-2a1f843b9a5a' class='xr-var-data-in' type='checkbox'><label for='data-9cc8b000-f02e-42b2-8c92-2a1f843b9a5a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x224TrimePentane_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-15ddfab3-5dd0-4c9c-bd83-7d63a6a4ab1c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-15ddfab3-5dd0-4c9c-bd83-7d63a6a4ab1c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-342cd6c1-1910-469e-a130-88e7e29d8f78' class='xr-var-data-in' type='checkbox'><label for='data-342cd6c1-1910-469e-a130-88e7e29d8f78' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nHeptane_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-2c19346b-ea09-46b3-8fa7-5d71c00a632a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2c19346b-ea09-46b3-8fa7-5d71c00a632a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eb90348c-d889-4984-901a-f92f6bd62a69' class='xr-var-data-in' type='checkbox'><label for='data-eb90348c-d889-4984-901a-f92f6bd62a69' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nOctane_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-9ebb6179-13df-4662-bcc4-bedcc098452d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9ebb6179-13df-4662-bcc4-bedcc098452d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f11390bd-e3ab-4d62-b9dc-3cfd7942a54e' class='xr-var-data-in' type='checkbox'><label for='data-f11390bd-e3ab-4d62-b9dc-3cfd7942a54e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Propene_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-750aa270-6501-4fe5-9379-e5237f4de863' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-750aa270-6501-4fe5-9379-e5237f4de863' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-11d5ba4e-9c21-4204-9721-230e5f80a2bc' class='xr-var-data-in' type='checkbox'><label for='data-11d5ba4e-9c21-4204-9721-230e5f80a2bc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>iButene1Butene_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-f7694e1c-682a-43b9-a206-62fa2ef0e127' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f7694e1c-682a-43b9-a206-62fa2ef0e127' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e742faa9-1c19-4ea3-9361-7f8b8b47f83a' class='xr-var-data-in' type='checkbox'><label for='data-e742faa9-1c19-4ea3-9361-7f8b8b47f83a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Isoprene_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-1f68f3df-923d-43fb-bfde-6d0d67126748' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1f68f3df-923d-43fb-bfde-6d0d67126748' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d4e3e7dc-55fd-4c75-a863-8516b43bff12' class='xr-var-data-in' type='checkbox'><label for='data-d4e3e7dc-55fd-4c75-a863-8516b43bff12' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Tricyclene_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-5eaf6e9a-63f9-4e31-a512-7be442f5dd73' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5eaf6e9a-63f9-4e31-a512-7be442f5dd73' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4313d881-d447-42c4-8ecc-6d2fa9dacc50' class='xr-var-data-in' type='checkbox'><label for='data-4313d881-d447-42c4-8ecc-6d2fa9dacc50' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aPinene_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-af4b278e-006d-4fd9-b3b7-f5ac64c88aed' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-af4b278e-006d-4fd9-b3b7-f5ac64c88aed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b612504c-d947-47a8-a8ca-c64e722be3f3' class='xr-var-data-in' type='checkbox'><label for='data-b612504c-d947-47a8-a8ca-c64e722be3f3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Camphene_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-85a27625-ded0-4d11-865b-622f05abf408' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-85a27625-ded0-4d11-865b-622f05abf408' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-123d7d3d-02dc-48ed-abc4-68158bc00c6a' class='xr-var-data-in' type='checkbox'><label for='data-123d7d3d-02dc-48ed-abc4-68158bc00c6a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>bPineneMyrcene_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-d164d23c-86b3-4adc-b37e-3eee9c0f6290' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d164d23c-86b3-4adc-b37e-3eee9c0f6290' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1943d5f1-1b34-48ae-972d-bf0c782b657a' class='xr-var-data-in' type='checkbox'><label for='data-1943d5f1-1b34-48ae-972d-bf0c782b657a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>LimoneneD3Carene_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-94e8226f-6a94-446c-91b3-bef61e7cbb5d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-94e8226f-6a94-446c-91b3-bef61e7cbb5d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ced80d06-9a00-474d-a384-6b1a4a537861' class='xr-var-data-in' type='checkbox'><label for='data-ced80d06-9a00-474d-a384-6b1a4a537861' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Benzene_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-d3e5731f-34db-45e0-8e99-36fec7c33be4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d3e5731f-34db-45e0-8e99-36fec7c33be4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7e69560b-1d7d-4bf0-b2a7-6ad449186dcf' class='xr-var-data-in' type='checkbox'><label for='data-7e69560b-1d7d-4bf0-b2a7-6ad449186dcf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Toluene_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-52109e1f-dc48-45ff-99d9-890c5d100aa4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-52109e1f-dc48-45ff-99d9-890c5d100aa4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f31bc709-0806-4d52-822e-485c3ef34be8' class='xr-var-data-in' type='checkbox'><label for='data-f31bc709-0806-4d52-822e-485c3ef34be8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>EthBenzene_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-b10500be-c948-4b5e-a150-369be22cad1c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b10500be-c948-4b5e-a150-369be22cad1c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-63c0da14-3def-4bc2-b991-98d6c5c42ad4' class='xr-var-data-in' type='checkbox'><label for='data-63c0da14-3def-4bc2-b991-98d6c5c42ad4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mpXylene_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-53bd5577-8ef7-42dc-825d-0df000332184' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-53bd5577-8ef7-42dc-825d-0df000332184' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b114fb92-4ccf-4423-bdf3-2979286c865c' class='xr-var-data-in' type='checkbox'><label for='data-b114fb92-4ccf-4423-bdf3-2979286c865c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>oXylene_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-34a3b0b5-cc51-4d25-9e3f-8f551b57cef5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-34a3b0b5-cc51-4d25-9e3f-8f551b57cef5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-28f819d6-4dcf-43a7-92c3-6c5b17615666' class='xr-var-data-in' type='checkbox'><label for='data-28f819d6-4dcf-43a7-92c3-6c5b17615666' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Styrene_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-b479072c-996a-4ec7-a65d-abca17e17e5f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b479072c-996a-4ec7-a65d-abca17e17e5f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9665da44-e0a0-47ea-b71c-6aad5f85fe0a' class='xr-var-data-in' type='checkbox'><label for='data-9665da44-e0a0-47ea-b71c-6aad5f85fe0a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>EthynylBenzene_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-89a62f3c-bcbd-40ab-9a58-862d4544cc9b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-89a62f3c-bcbd-40ab-9a58-862d4544cc9b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-620fd2c9-17ec-4e9b-92a2-813d25c618d6' class='xr-var-data-in' type='checkbox'><label for='data-620fd2c9-17ec-4e9b-92a2-813d25c618d6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>arbppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH2O_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-0a69220c-6479-4f16-a9b8-7e6269e1fa33' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0a69220c-6479-4f16-a9b8-7e6269e1fa33' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d713619-b6b1-46c5-836b-20346937dbce' class='xr-var-data-in' type='checkbox'><label for='data-1d713619-b6b1-46c5-836b-20346937dbce' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH3CHO_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-b9c4d5d7-8f3e-4581-b76a-1666a91b40f1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b9c4d5d7-8f3e-4581-b76a-1666a91b40f1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d78d86f4-8a54-42fd-b79e-5a753c62e921' class='xr-var-data-in' type='checkbox'><label for='data-d78d86f4-8a54-42fd-b79e-5a753c62e921' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Propanal_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-677146b0-a6d1-4e09-9d46-db88da302380' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-677146b0-a6d1-4e09-9d46-db88da302380' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f24a3b60-c996-47c9-ba95-b8662123bb72' class='xr-var-data-in' type='checkbox'><label for='data-f24a3b60-c996-47c9-ba95-b8662123bb72' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Butanal_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-4f49b06e-3978-450e-b766-b5f2cfbd4669' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4f49b06e-3978-450e-b766-b5f2cfbd4669' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a5d5b5fe-2ead-4b98-a7f2-88730809a27a' class='xr-var-data-in' type='checkbox'><label for='data-a5d5b5fe-2ead-4b98-a7f2-88730809a27a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>iButanal_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-d1d27d51-39b9-42eb-8d70-29882db9456a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d1d27d51-39b9-42eb-8d70-29882db9456a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4e3bcaa8-ad67-4c7a-a9b7-331736134292' class='xr-var-data-in' type='checkbox'><label for='data-4e3bcaa8-ad67-4c7a-a9b7-331736134292' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>arbppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Acrolein_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-983f2ee2-06e5-4565-b1b4-beb736999189' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-983f2ee2-06e5-4565-b1b4-beb736999189' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c8c94d23-1956-4a7e-afdb-772e0e42f02a' class='xr-var-data-in' type='checkbox'><label for='data-c8c94d23-1956-4a7e-afdb-772e0e42f02a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x2Butenals_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-d8193e77-e2ef-4ef7-894f-1f03c6df3074' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d8193e77-e2ef-4ef7-894f-1f03c6df3074' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e5bc2b64-9332-45c5-a308-e48eb5667b62' class='xr-var-data-in' type='checkbox'><label for='data-e5bc2b64-9332-45c5-a308-e48eb5667b62' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Acetone_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-5964ba5f-052e-4341-b434-e82aaeff9ca8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5964ba5f-052e-4341-b434-e82aaeff9ca8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7b94eb2e-14f1-4a18-844e-2b19d6e5aad2' class='xr-var-data-in' type='checkbox'><label for='data-7b94eb2e-14f1-4a18-844e-2b19d6e5aad2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MEK_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-3233bd90-8c2a-48ba-8e83-a25275df3eba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3233bd90-8c2a-48ba-8e83-a25275df3eba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-319228b9-5d29-475b-a7ed-44db3869eace' class='xr-var-data-in' type='checkbox'><label for='data-319228b9-5d29-475b-a7ed-44db3869eace' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH3OH_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-0ad0b708-5f59-4385-b597-a3b958e4e74b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0ad0b708-5f59-4385-b597-a3b958e4e74b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e9184492-8403-4105-b21e-4297527ab3d4' class='xr-var-data-in' type='checkbox'><label for='data-e9184492-8403-4105-b21e-4297527ab3d4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>C2H5OH_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e8d47d5d-ded9-42cb-b5c7-c0379e74757e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e8d47d5d-ded9-42cb-b5c7-c0379e74757e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e47645e8-c58b-4cc5-a49f-8bc576bcea46' class='xr-var-data-in' type='checkbox'><label for='data-e47645e8-c58b-4cc5-a49f-8bc576bcea46' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>iPropanol_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-64862b89-88e1-4e1b-a44c-859348e86c36' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-64862b89-88e1-4e1b-a44c-859348e86c36' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b856a88d-eaea-469f-8a94-a9700d288594' class='xr-var-data-in' type='checkbox'><label for='data-b856a88d-eaea-469f-8a94-a9700d288594' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MBO_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-3e185760-3e9a-407d-b666-a18836b54e34' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3e185760-3e9a-407d-b666-a18836b54e34' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8631c4b8-8148-4519-8921-d1f79384a85f' class='xr-var-data-in' type='checkbox'><label for='data-8631c4b8-8148-4519-8921-d1f79384a85f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>arbppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MAC_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-9c93ab4b-43a8-4f9c-9400-31104ef0b0ae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9c93ab4b-43a8-4f9c-9400-31104ef0b0ae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a03f311b-a745-4a4b-bdf7-86735f9853c2' class='xr-var-data-in' type='checkbox'><label for='data-a03f311b-a745-4a4b-bdf7-86735f9853c2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MVK_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-1a56c9f9-4bd9-4a2a-aeb1-0bb70baa6788' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1a56c9f9-4bd9-4a2a-aeb1-0bb70baa6788' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c1fbd691-41a4-4774-9921-a8061a4cf9ac' class='xr-var-data-in' type='checkbox'><label for='data-c1fbd691-41a4-4774-9921-a8061a4cf9ac' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MeFormate_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-5c9dd83d-eaff-40e5-a6df-c002e69c3a8c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5c9dd83d-eaff-40e5-a6df-c002e69c3a8c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-644318b2-f863-43a1-80ba-d2b96ac76789' class='xr-var-data-in' type='checkbox'><label for='data-644318b2-f863-43a1-80ba-d2b96ac76789' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>arbppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MeAcetate_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-5e8feefd-af52-46b1-af6f-087b5e0a1458' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5e8feefd-af52-46b1-af6f-087b5e0a1458' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cf98bc8e-3352-411d-9236-d513c3ed544b' class='xr-var-data-in' type='checkbox'><label for='data-cf98bc8e-3352-411d-9236-d513c3ed544b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>arbppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Furan_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-28500b61-8310-45d5-9f9b-1e499878663a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-28500b61-8310-45d5-9f9b-1e499878663a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f5e3ca8f-9494-4f5b-a7d2-77bd581ee28a' class='xr-var-data-in' type='checkbox'><label for='data-f5e3ca8f-9494-4f5b-a7d2-77bd581ee28a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x2MeFuran_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-73efd2cc-8c82-49b6-8ac1-ea78f723e891' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-73efd2cc-8c82-49b6-8ac1-ea78f723e891' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cb19f45f-425f-4ce6-98cd-145de10ecd62' class='xr-var-data-in' type='checkbox'><label for='data-cb19f45f-425f-4ce6-98cd-145de10ecd62' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x3MeFuran_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-cbb85eb1-a35d-4c87-a31b-d784f97c0728' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cbb85eb1-a35d-4c87-a31b-d784f97c0728' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-65eb4e9f-0138-4ebf-82db-50f64ddd5e1b' class='xr-var-data-in' type='checkbox'><label for='data-65eb4e9f-0138-4ebf-82db-50f64ddd5e1b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Furfural_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-881084c3-1bd0-4a8b-96de-990c90c608fa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-881084c3-1bd0-4a8b-96de-990c90c608fa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a1b76fd1-fcfd-47bb-9f5e-2d9faf55a077' class='xr-var-data-in' type='checkbox'><label for='data-a1b76fd1-fcfd-47bb-9f5e-2d9faf55a077' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>arbppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HCN_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-30beac01-69e3-4c85-832b-d107c15b7968' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-30beac01-69e3-4c85-832b-d107c15b7968' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a8ff869c-7403-4086-9172-a658b70194e9' class='xr-var-data-in' type='checkbox'><label for='data-a8ff869c-7403-4086-9172-a658b70194e9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH3CN_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-212b4cc7-d242-4a18-bc07-6d4512831950' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-212b4cc7-d242-4a18-bc07-6d4512831950' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0eef8688-bb35-47e0-9919-a00c33a12f87' class='xr-var-data-in' type='checkbox'><label for='data-0eef8688-bb35-47e0-9919-a00c33a12f87' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PropNitrile_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-6709142e-cf7d-4ad3-8a2f-a5e587f2553a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6709142e-cf7d-4ad3-8a2f-a5e587f2553a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2e2f1f1d-9939-4262-b4f8-440fed508e99' class='xr-var-data-in' type='checkbox'><label for='data-2e2f1f1d-9939-4262-b4f8-440fed508e99' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Acrylonitrile_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-0ba3f758-5784-4279-8d30-3c06038b8bcb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0ba3f758-5784-4279-8d30-3c06038b8bcb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-64b82801-c858-484f-8090-5dea85f66552' class='xr-var-data-in' type='checkbox'><label for='data-64b82801-c858-484f-8090-5dea85f66552' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MeAcrylonitrile_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-3e6008f7-240c-4149-8053-0059aa1f3225' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3e6008f7-240c-4149-8053-0059aa1f3225' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f6daa894-c1ed-45b5-83f9-0b586947bb3f' class='xr-var-data-in' type='checkbox'><label for='data-f6daa894-c1ed-45b5-83f9-0b586947bb3f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Pyrrole_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-26ddec03-89bb-42eb-92e3-94af1703d467' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-26ddec03-89bb-42eb-92e3-94af1703d467' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d2e9313d-ae6a-41b0-8b9e-21073d768d75' class='xr-var-data-in' type='checkbox'><label for='data-d2e9313d-ae6a-41b0-8b9e-21073d768d75' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>arbppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Nitromethane_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-d3b64d8c-a0cc-43d3-9e91-000a8beda096' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d3b64d8c-a0cc-43d3-9e91-000a8beda096' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-10be277a-a930-4a12-ae24-fd6aa9ca5d74' class='xr-var-data-in' type='checkbox'><label for='data-10be277a-a930-4a12-ae24-fd6aa9ca5d74' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>arbppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MeONO2_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-d1e058c4-746c-4f87-943b-8aa5343cd70d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d1e058c4-746c-4f87-943b-8aa5343cd70d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8b4d10a4-0764-4db9-b840-d71fd1451b7b' class='xr-var-data-in' type='checkbox'><label for='data-8b4d10a4-0764-4db9-b840-d71fd1451b7b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>arbppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>EthONO2_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-27150447-8311-46fb-a162-7b688669de05' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-27150447-8311-46fb-a162-7b688669de05' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-00fe4b54-433b-44b9-86fa-340939365be8' class='xr-var-data-in' type='checkbox'><label for='data-00fe4b54-433b-44b9-86fa-340939365be8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>arbppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>iPropONO2_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-d31a365c-5ab4-4f4f-a6cd-f7b04bd50f99' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d31a365c-5ab4-4f4f-a6cd-f7b04bd50f99' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8745f050-e909-4906-a5cd-c37610cf81b1' class='xr-var-data-in' type='checkbox'><label for='data-8745f050-e909-4906-a5cd-c37610cf81b1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x2ButONO2iButONO2_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-0ed1079c-c01c-4e5e-a4fb-53b03df6d53f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0ed1079c-c01c-4e5e-a4fb-53b03df6d53f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f31767e6-d81a-42e4-8ace-bba77768dde1' class='xr-var-data-in' type='checkbox'><label for='data-f31767e6-d81a-42e4-8ace-bba77768dde1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>UnknownC2H4O_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-36e45dcd-b121-4531-b69b-14135c69d6a5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-36e45dcd-b121-4531-b69b-14135c69d6a5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c798f04c-4b40-4af1-bd21-dc6611a81647' class='xr-var-data-in' type='checkbox'><label for='data-c798f04c-4b40-4af1-bd21-dc6611a81647' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>arbppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>C3O2_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-5d32d6c1-2eb3-4f21-a260-b375c1c33f0b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5d32d6c1-2eb3-4f21-a260-b375c1c33f0b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b5ff628-cbe5-495e-b075-1ad763b05f36' class='xr-var-data-in' type='checkbox'><label for='data-9b5ff628-cbe5-495e-b075-1ad763b05f36' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>arbppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>THF_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-b84818e7-a07b-4c93-8deb-d6e2d2ee6c38' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b84818e7-a07b-4c93-8deb-d6e2d2ee6c38' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2e3808c6-4060-4774-a08a-3f8279e143d2' class='xr-var-data-in' type='checkbox'><label for='data-2e3808c6-4060-4774-a08a-3f8279e143d2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>arbppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x23Butanedione_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e5dfe8e7-7aae-4887-a21a-b709fadd19c4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e5dfe8e7-7aae-4887-a21a-b709fadd19c4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fdbe710f-d52e-48c8-8a1d-6c96b5a387c4' class='xr-var-data-in' type='checkbox'><label for='data-fdbe710f-d52e-48c8-8a1d-6c96b5a387c4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>arbppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>EthAcetate_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ec07a2c4-ec23-47ce-a8c6-88b2f39a6ae1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ec07a2c4-ec23-47ce-a8c6-88b2f39a6ae1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a2b0d612-bbfe-42b8-ad07-0c34d2d68aa7' class='xr-var-data-in' type='checkbox'><label for='data-a2b0d612-bbfe-42b8-ad07-0c34d2d68aa7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>arbppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MePropionate_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-76696aed-8ed3-4073-92e2-254ecf383a93' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-76696aed-8ed3-4073-92e2-254ecf383a93' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aa88a1a9-3ea5-4846-bcd4-98a703d6a9da' class='xr-var-data-in' type='checkbox'><label for='data-aa88a1a9-3ea5-4846-bcd4-98a703d6a9da' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>arbppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x2EthFuran_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-46ed210f-55f4-4733-9200-70b4da56ebe5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-46ed210f-55f4-4733-9200-70b4da56ebe5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-71393274-96f7-4aa5-915f-834b15e2d317' class='xr-var-data-in' type='checkbox'><label for='data-71393274-96f7-4aa5-915f-834b15e2d317' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>arbppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>DimeFurans_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-92a0dd98-3144-4793-8437-4cb35ebc6a84' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-92a0dd98-3144-4793-8437-4cb35ebc6a84' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-56944e80-2a8f-41c8-8bf0-07b7e6ca30fa' class='xr-var-data-in' type='checkbox'><label for='data-56944e80-2a8f-41c8-8bf0-07b7e6ca30fa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>arbppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>UnknownC6H8O_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-f119e49d-958b-4ea9-9420-7741c7a9536b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f119e49d-958b-4ea9-9420-7741c7a9536b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b570f50a-c72a-421b-b9dc-ead286006865' class='xr-var-data-in' type='checkbox'><label for='data-b570f50a-c72a-421b-b9dc-ead286006865' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>arbppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>VinylFuranA_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-01019472-fdd5-44ef-a0f2-84eb2ad0abb8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-01019472-fdd5-44ef-a0f2-84eb2ad0abb8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d63bede4-3d6a-4301-9b45-4143bdd09394' class='xr-var-data-in' type='checkbox'><label for='data-d63bede4-3d6a-4301-9b45-4143bdd09394' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>arbppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>VinylFuranB_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-18271d7d-cfaa-4fb6-9c6e-7ad34a287184' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-18271d7d-cfaa-4fb6-9c6e-7ad34a287184' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-10a4ddc4-2054-400e-9185-d37442dd5d91' class='xr-var-data-in' type='checkbox'><label for='data-10a4ddc4-2054-400e-9185-d37442dd5d91' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>arbppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x3Furaldehyde_TOGA_APEL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-42f96bfc-7550-42fc-8f79-05a675f4f315' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-42f96bfc-7550-42fc-8f79-05a675f4f315' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c58280e8-45ca-40c2-afb5-4e1717fcdfe7' class='xr-var-data-in' type='checkbox'><label for='data-c58280e8-45ca-40c2-afb5-4e1717fcdfe7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>arbppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>C2Cl4_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-0462960c-768b-4e04-a98a-7368fc3bc576' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0462960c-768b-4e04-a98a-7368fc3bc576' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7555919b-9ebb-4ad0-997b-9ced3c10cfd9' class='xr-var-data-in' type='checkbox'><label for='data-7555919b-9ebb-4ad0-997b-9ced3c10cfd9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CHCl3_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ea4e1b67-87e9-48c5-b748-accbb6bce9d0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ea4e1b67-87e9-48c5-b748-accbb6bce9d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8206ca8e-4d0d-4ab7-933d-d162a729d587' class='xr-var-data-in' type='checkbox'><label for='data-8206ca8e-4d0d-4ab7-933d-d162a729d587' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Ethane_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-fc8f85db-ca0d-4e64-8423-865f79a0b843' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fc8f85db-ca0d-4e64-8423-865f79a0b843' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-133fd01e-85d8-4af5-9583-1f15f809ded7' class='xr-var-data-in' type='checkbox'><label for='data-133fd01e-85d8-4af5-9583-1f15f809ded7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Propane_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-602e0375-269c-4a59-acba-646a611bfbe2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-602e0375-269c-4a59-acba-646a611bfbe2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-160c6b68-d5f9-415b-96a4-e16447b9c3a8' class='xr-var-data-in' type='checkbox'><label for='data-160c6b68-d5f9-415b-96a4-e16447b9c3a8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nButane_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-b83ae1cd-f81c-4389-bbed-3958bdfa52fe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b83ae1cd-f81c-4389-bbed-3958bdfa52fe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d8ac3add-e12f-4370-b98c-62cfcf49116e' class='xr-var-data-in' type='checkbox'><label for='data-d8ac3add-e12f-4370-b98c-62cfcf49116e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>iButane_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-02b303b8-e801-4a38-8ffa-44448a3f95c9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-02b303b8-e801-4a38-8ffa-44448a3f95c9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9108f775-5c03-4ecc-8371-b927b50bf3b5' class='xr-var-data-in' type='checkbox'><label for='data-9108f775-5c03-4ecc-8371-b927b50bf3b5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nPentane_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-4a5f3181-156f-450b-ac71-65792f7949ec' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4a5f3181-156f-450b-ac71-65792f7949ec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0633835b-4a6b-413c-a1ef-b5e107e8f0d6' class='xr-var-data-in' type='checkbox'><label for='data-0633835b-4a6b-413c-a1ef-b5e107e8f0d6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>iPentane_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-f57134de-60b6-468a-bd3d-99bfd1c2ff4b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f57134de-60b6-468a-bd3d-99bfd1c2ff4b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-781d5418-a91b-425a-925d-eae914a946a8' class='xr-var-data-in' type='checkbox'><label for='data-781d5418-a91b-425a-925d-eae914a946a8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nHexane_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-c6f571e3-450a-43eb-ae04-9474fd15a97b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c6f571e3-450a-43eb-ae04-9474fd15a97b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1da89a54-f548-4a40-8411-5eda149a596d' class='xr-var-data-in' type='checkbox'><label for='data-1da89a54-f548-4a40-8411-5eda149a596d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x2MePentane_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-6f60478d-6999-4f54-a27a-7ebd7b0aa3fc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6f60478d-6999-4f54-a27a-7ebd7b0aa3fc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b0563e6b-af68-47cf-a6cb-8d37f9474078' class='xr-var-data-in' type='checkbox'><label for='data-b0563e6b-af68-47cf-a6cb-8d37f9474078' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x3MePentane_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-c85206ce-50aa-4318-a9d7-bb622796d05a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c85206ce-50aa-4318-a9d7-bb622796d05a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5183dc24-f170-4882-b2b6-73bddc51b1b0' class='xr-var-data-in' type='checkbox'><label for='data-5183dc24-f170-4882-b2b6-73bddc51b1b0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x22DiMeButane_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-4dba1de3-b056-4b59-adc0-3df02589a4ef' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4dba1de3-b056-4b59-adc0-3df02589a4ef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eeb5402e-3ecc-48a1-8f41-b851c090b84e' class='xr-var-data-in' type='checkbox'><label for='data-eeb5402e-3ecc-48a1-8f41-b851c090b84e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x24DiMePentane_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-3e59633c-ca0d-4bbd-8f57-0faf31ca8cb9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3e59633c-ca0d-4bbd-8f57-0faf31ca8cb9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e53c2b18-6768-4890-8b4a-1776a6e0e0ea' class='xr-var-data-in' type='checkbox'><label for='data-e53c2b18-6768-4890-8b4a-1776a6e0e0ea' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nOctane_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-12cbab20-d946-40a0-b317-332940f551f8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-12cbab20-d946-40a0-b317-332940f551f8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b165c289-e0b6-40c6-a838-b0c09e62829e' class='xr-var-data-in' type='checkbox'><label for='data-b165c289-e0b6-40c6-a838-b0c09e62829e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x224TriMePentane_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-24741175-86ef-4daa-afdf-bab8d94fcc42' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-24741175-86ef-4daa-afdf-bab8d94fcc42' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e918e115-36ae-4a1b-aad6-861dd604bfd7' class='xr-var-data-in' type='checkbox'><label for='data-e918e115-36ae-4a1b-aad6-861dd604bfd7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nNonane_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-c210d28e-5814-49bf-b1db-39396bad0d76' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c210d28e-5814-49bf-b1db-39396bad0d76' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e429433b-fcbd-43c2-a675-82688835bfcc' class='xr-var-data-in' type='checkbox'><label for='data-e429433b-fcbd-43c2-a675-82688835bfcc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nDecane_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-26a77ff3-65ce-40c5-aa18-ed5aee221431' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-26a77ff3-65ce-40c5-aa18-ed5aee221431' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8b94736b-07ea-4e1f-bbe8-e8c2d362cd04' class='xr-var-data-in' type='checkbox'><label for='data-8b94736b-07ea-4e1f-bbe8-e8c2d362cd04' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MeCycPentane_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-43aa276b-1646-4258-8446-0531b0da0e9d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-43aa276b-1646-4258-8446-0531b0da0e9d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d69d7289-21a8-4b15-ae64-54f30ab74c00' class='xr-var-data-in' type='checkbox'><label for='data-d69d7289-21a8-4b15-ae64-54f30ab74c00' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CycHexane_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-c1fd042e-fcc8-49b0-92e0-b19bd315571c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c1fd042e-fcc8-49b0-92e0-b19bd315571c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0ed81aa0-6e60-44c1-ac84-9d4aff371d5e' class='xr-var-data-in' type='checkbox'><label for='data-0ed81aa0-6e60-44c1-ac84-9d4aff371d5e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MeCycHexane_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e2f0e955-a7cb-44a3-a744-e935f4db600f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e2f0e955-a7cb-44a3-a744-e935f4db600f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5a2ad5a2-fb56-4e98-a456-d8e74a7e12d7' class='xr-var-data-in' type='checkbox'><label for='data-5a2ad5a2-fb56-4e98-a456-d8e74a7e12d7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Ethyne_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-b7064fec-6081-45a7-b3cc-1801f87210bd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b7064fec-6081-45a7-b3cc-1801f87210bd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cde48f0d-d280-46b9-8150-65a6f86163a7' class='xr-var-data-in' type='checkbox'><label for='data-cde48f0d-d280-46b9-8150-65a6f86163a7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Ethene_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-a2c97ddf-6dc3-47fa-b3de-e6e6e1a4abf7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a2c97ddf-6dc3-47fa-b3de-e6e6e1a4abf7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c6c0321a-8760-49e3-b77d-f53deddec6b4' class='xr-var-data-in' type='checkbox'><label for='data-c6c0321a-8760-49e3-b77d-f53deddec6b4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Propene_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-fd2df700-2e01-4414-b13b-acefbf32d82e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fd2df700-2e01-4414-b13b-acefbf32d82e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1b36022f-dddb-4ba1-b8cd-0532d61aa718' class='xr-var-data-in' type='checkbox'><label for='data-1b36022f-dddb-4ba1-b8cd-0532d61aa718' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x1Butene_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e7c7a3b5-0462-47ae-9b7e-9e559185c260' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e7c7a3b5-0462-47ae-9b7e-9e559185c260' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7f5e6930-30b5-40ad-b0ef-025dc46743a2' class='xr-var-data-in' type='checkbox'><label for='data-7f5e6930-30b5-40ad-b0ef-025dc46743a2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>c2Butene_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-48862f43-37ce-4d6d-891e-24ee19c98183' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-48862f43-37ce-4d6d-891e-24ee19c98183' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b839a5e5-e5d6-4b3b-9d25-14027e76eedc' class='xr-var-data-in' type='checkbox'><label for='data-b839a5e5-e5d6-4b3b-9d25-14027e76eedc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>t2butene_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-bd6fee97-674b-46d1-9d68-8346b75a8a27' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bd6fee97-674b-46d1-9d68-8346b75a8a27' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-899d6f6c-cc31-4be7-838d-02d94bf9eba4' class='xr-var-data-in' type='checkbox'><label for='data-899d6f6c-cc31-4be7-838d-02d94bf9eba4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>iButene_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-19ee57fe-6103-4e4b-acb2-3639b0c399d5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-19ee57fe-6103-4e4b-acb2-3639b0c399d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-54889dec-2cd4-485a-a07f-d376fabbfdfb' class='xr-var-data-in' type='checkbox'><label for='data-54889dec-2cd4-485a-a07f-d376fabbfdfb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x1Pentene_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e0ae1a11-8465-4b04-8f89-512a97570918' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e0ae1a11-8465-4b04-8f89-512a97570918' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c3ead368-bb71-4523-86fa-45fedc71d1c0' class='xr-var-data-in' type='checkbox'><label for='data-c3ead368-bb71-4523-86fa-45fedc71d1c0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>c2Pentene_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-76da518b-2531-4b48-85f6-7521c673a62d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-76da518b-2531-4b48-85f6-7521c673a62d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ea1547e7-bccd-48c5-ab50-97f5275efb0d' class='xr-var-data-in' type='checkbox'><label for='data-ea1547e7-bccd-48c5-ab50-97f5275efb0d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>t2Pentene_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-673eb970-8f7e-4ff9-866f-c858089a3b22' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-673eb970-8f7e-4ff9-866f-c858089a3b22' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-22fb9eaa-4505-4754-b19e-31b2b7e16c7f' class='xr-var-data-in' type='checkbox'><label for='data-22fb9eaa-4505-4754-b19e-31b2b7e16c7f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x2Me1Butene_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-2b4a0983-5086-4058-86af-fb9ecb1c63ae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2b4a0983-5086-4058-86af-fb9ecb1c63ae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-432cf7cc-f85e-4764-a052-7882baacd268' class='xr-var-data-in' type='checkbox'><label for='data-432cf7cc-f85e-4764-a052-7882baacd268' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x3Me1Butene_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-1bd762c3-b6cb-41d2-95d0-b4f144af373d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1bd762c3-b6cb-41d2-95d0-b4f144af373d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3bed92b6-d495-4002-9237-11b7940827b7' class='xr-var-data-in' type='checkbox'><label for='data-3bed92b6-d495-4002-9237-11b7940827b7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>t13Pentadiene_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-909b203a-a074-4828-ad9a-3fff371da406' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-909b203a-a074-4828-ad9a-3fff371da406' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ae40feab-bc3f-4701-b502-c33cb4eb32ed' class='xr-var-data-in' type='checkbox'><label for='data-ae40feab-bc3f-4701-b502-c33cb4eb32ed' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Isoprene_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-6bf78c78-f387-46ea-b3fb-4cb8d211530a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6bf78c78-f387-46ea-b3fb-4cb8d211530a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3552bf6a-3f10-403c-8486-d39779a0deed' class='xr-var-data-in' type='checkbox'><label for='data-3552bf6a-3f10-403c-8486-d39779a0deed' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aPinene_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-b5616621-b925-4c78-91ed-c367db2f8c5a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b5616621-b925-4c78-91ed-c367db2f8c5a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-103b5109-4c16-4207-9d4c-466d81a9eb2b' class='xr-var-data-in' type='checkbox'><label for='data-103b5109-4c16-4207-9d4c-466d81a9eb2b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Benzene_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-318eb895-1cf9-4591-a25b-2c28d485c0b8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-318eb895-1cf9-4591-a25b-2c28d485c0b8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fc3fa81f-441f-4396-bb88-eb57cedc25ef' class='xr-var-data-in' type='checkbox'><label for='data-fc3fa81f-441f-4396-bb88-eb57cedc25ef' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Toluene_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e7f78f9f-4474-48f1-b61f-b0a217bb250c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e7f78f9f-4474-48f1-b61f-b0a217bb250c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-967d0cbf-4015-4f45-8bc5-fe882c48e9b5' class='xr-var-data-in' type='checkbox'><label for='data-967d0cbf-4015-4f45-8bc5-fe882c48e9b5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>EthBenzene_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-86bd8e58-7997-4c93-b29c-d924425ec89e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-86bd8e58-7997-4c93-b29c-d924425ec89e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e71b8192-c85a-4bce-b026-c3989740011c' class='xr-var-data-in' type='checkbox'><label for='data-e71b8192-c85a-4bce-b026-c3989740011c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>oXylene_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-b5c6d642-eb16-439a-9d7b-95bd13dbc283' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b5c6d642-eb16-439a-9d7b-95bd13dbc283' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2e4e0d29-0356-4961-b3e0-b35372ce10ae' class='xr-var-data-in' type='checkbox'><label for='data-2e4e0d29-0356-4961-b3e0-b35372ce10ae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mpXylene_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-da3b55d6-d576-4de1-ac78-9045185908c6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-da3b55d6-d576-4de1-ac78-9045185908c6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9a034822-4afc-4d0b-b8bc-3b9fae4aaf2a' class='xr-var-data-in' type='checkbox'><label for='data-9a034822-4afc-4d0b-b8bc-3b9fae4aaf2a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Acetone_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-060c9282-e170-461b-9636-90e76cfea95c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-060c9282-e170-461b-9636-90e76cfea95c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-79759cc7-238c-44cf-8ff2-de55c240ae9c' class='xr-var-data-in' type='checkbox'><label for='data-79759cc7-238c-44cf-8ff2-de55c240ae9c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MEK_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-836963aa-427c-4539-b149-845990169f26' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-836963aa-427c-4539-b149-845990169f26' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-53a2dfaf-1c8c-454e-b471-f2ce7e34a79d' class='xr-var-data-in' type='checkbox'><label for='data-53a2dfaf-1c8c-454e-b471-f2ce7e34a79d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MeFormate_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-5913928a-06d4-4654-a4ea-55f8d39fab0c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5913928a-06d4-4654-a4ea-55f8d39fab0c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-82d9922b-5533-413a-99eb-2c99f292103a' class='xr-var-data-in' type='checkbox'><label for='data-82d9922b-5533-413a-99eb-2c99f292103a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Furan_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-c2551e13-bb7c-4c97-90eb-55ccf976f942' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c2551e13-bb7c-4c97-90eb-55ccf976f942' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ecc0e98c-38ab-4d99-9892-7ca2fba64aaf' class='xr-var-data-in' type='checkbox'><label for='data-ecc0e98c-38ab-4d99-9892-7ca2fba64aaf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH3CN_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-2799217f-99c2-4adc-8c42-7e55c4b5a615' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2799217f-99c2-4adc-8c42-7e55c4b5a615' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c002f2b1-ba6d-414d-be19-ad674ca7e229' class='xr-var-data-in' type='checkbox'><label for='data-c002f2b1-ba6d-414d-be19-ad674ca7e229' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Acrylonitrile_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-4efd7251-25e6-41f6-8177-43ad4d4614f0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4efd7251-25e6-41f6-8177-43ad4d4614f0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a1430390-32f9-4c17-ac83-967c33928eb0' class='xr-var-data-in' type='checkbox'><label for='data-a1430390-32f9-4c17-ac83-967c33928eb0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HCN_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.507 ... nan nan nan</div><input id='attrs-4255e908-5e9b-46bc-aa19-b682b4f9f05f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4255e908-5e9b-46bc-aa19-b682b4f9f05f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5d759fb0-66ea-4631-a715-d48601744220' class='xr-var-data-in' type='checkbox'><label for='data-5d759fb0-66ea-4631-a715-d48601744220' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH2O_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-bb50eaa5-1e25-4a46-a7fc-36ab25b73809' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bb50eaa5-1e25-4a46-a7fc-36ab25b73809' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c01cc121-c466-4997-8817-3671d243562a' class='xr-var-data-in' type='checkbox'><label for='data-c01cc121-c466-4997-8817-3671d243562a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH3OH_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 6.159 ... nan nan nan</div><input id='attrs-fa90584b-ce85-4c1b-8bb4-8b31f14c7604' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fa90584b-ce85-4c1b-8bb4-8b31f14c7604' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bd92096f-1b87-4440-ad52-2c32df85cf6e' class='xr-var-data-in' type='checkbox'><label for='data-bd92096f-1b87-4440-ad52-2c32df85cf6e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH3CN_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.156 ... nan nan nan</div><input id='attrs-37c21678-4c0b-406d-b1c5-a756f4de3c91' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-37c21678-4c0b-406d-b1c5-a756f4de3c91' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-815c3272-07a6-40dc-be12-952e5e2a8a96' class='xr-var-data-in' type='checkbox'><label for='data-815c3272-07a6-40dc-be12-952e5e2a8a96' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HNCO_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.0918 ... nan nan nan</div><input id='attrs-34449b14-bb1e-4f8b-8a94-804c4b36ac0a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-34449b14-bb1e-4f8b-8a94-804c4b36ac0a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0a4d24de-775b-4aaf-ba9f-f1a6d6c62fab' class='xr-var-data-in' type='checkbox'><label for='data-0a4d24de-775b-4aaf-ba9f-f1a6d6c62fab' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH3CHO_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 1.113 ... nan nan nan</div><input id='attrs-b21ab083-bd98-4db8-ab23-b3b9f1ba044b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b21ab083-bd98-4db8-ab23-b3b9f1ba044b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-95640e8a-20c8-4058-929a-b9ed5247610d' class='xr-var-data-in' type='checkbox'><label for='data-95640e8a-20c8-4058-929a-b9ed5247610d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>C2H5OH_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.905 ... nan nan nan</div><input id='attrs-f524a5da-ea79-466f-a281-93ffd23e6889' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f524a5da-ea79-466f-a281-93ffd23e6889' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-055ca0fd-406a-493e-b0bf-a228503842e6' class='xr-var-data-in' type='checkbox'><label for='data-055ca0fd-406a-493e-b0bf-a228503842e6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HCOOH_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 3.341 ... nan nan nan</div><input id='attrs-f6009bea-7c69-4397-a223-cd5f775ae23f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f6009bea-7c69-4397-a223-cd5f775ae23f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d68240a1-aed4-4ab9-85da-14a240f86dda' class='xr-var-data-in' type='checkbox'><label for='data-d68240a1-aed4-4ab9-85da-14a240f86dda' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Acrylonitrile_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.001 ... nan nan nan</div><input id='attrs-3a9efd67-b59c-4bb6-aa12-5083ae7b2919' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3a9efd67-b59c-4bb6-aa12-5083ae7b2919' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e36f127-f4b5-4ebd-885d-7379592c1eea' class='xr-var-data-in' type='checkbox'><label for='data-5e36f127-f4b5-4ebd-885d-7379592c1eea' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Acrolein_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.119 ... nan nan nan</div><input id='attrs-50d5f42e-5fb6-4f31-946a-0b51191cd019' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-50d5f42e-5fb6-4f31-946a-0b51191cd019' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a79d9244-3b67-4ef5-bb1b-3a6d4fc3819f' class='xr-var-data-in' type='checkbox'><label for='data-a79d9244-3b67-4ef5-bb1b-3a6d4fc3819f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>AcetonePropanal_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 3.822 ... nan nan nan</div><input id='attrs-72eaba32-cfb6-42df-ab96-812e5b92c895' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-72eaba32-cfb6-42df-ab96-812e5b92c895' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b705e6a8-9a61-49ee-89e0-ef716d6e5c13' class='xr-var-data-in' type='checkbox'><label for='data-b705e6a8-9a61-49ee-89e0-ef716d6e5c13' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Glycolaldehyde_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.7238 ... nan nan nan</div><input id='attrs-ddd2f607-4a81-4b2d-9496-bd979e24000d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ddd2f607-4a81-4b2d-9496-bd979e24000d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2a9551ac-b4e4-4125-9d33-c2b3e9b78b60' class='xr-var-data-in' type='checkbox'><label for='data-2a9551ac-b4e4-4125-9d33-c2b3e9b78b60' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH3NO2_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.0222 ... nan nan nan</div><input id='attrs-8d473c0c-7405-4b70-a532-c377c69f3fc9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8d473c0c-7405-4b70-a532-c377c69f3fc9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-21330471-4d1c-46b1-8d0c-990534ac549c' class='xr-var-data-in' type='checkbox'><label for='data-21330471-4d1c-46b1-8d0c-990534ac549c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>DMS_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.0038 ... nan nan nan</div><input id='attrs-6c4e6894-2582-46fd-9798-ca6afc5c5ccb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6c4e6894-2582-46fd-9798-ca6afc5c5ccb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a48fb99f-ee79-4bbd-8897-402233367375' class='xr-var-data-in' type='checkbox'><label for='data-a48fb99f-ee79-4bbd-8897-402233367375' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>C4H5N_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.0014 ... nan nan nan</div><input id='attrs-82634e90-5127-4cd5-b0d5-8db8a9d5e876' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-82634e90-5127-4cd5-b0d5-8db8a9d5e876' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6a576a56-c273-48d7-8fee-31bf835537f4' class='xr-var-data-in' type='checkbox'><label for='data-6a576a56-c273-48d7-8fee-31bf835537f4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Isoprene_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.3092 ... nan nan nan</div><input id='attrs-d55158b0-3ee3-48ee-bb13-cb84d1f095be' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d55158b0-3ee3-48ee-bb13-cb84d1f095be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2c0515c5-5b72-4aa3-b1a5-286f0aa11cbe' class='xr-var-data-in' type='checkbox'><label for='data-2c0515c5-5b72-4aa3-b1a5-286f0aa11cbe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Furan_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan -0.0156 ... nan nan nan</div><input id='attrs-86b566ce-e41e-4606-924a-ee2a5744dcfb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-86b566ce-e41e-4606-924a-ee2a5744dcfb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7bbcbd8a-ab14-4b60-9098-54db55603851' class='xr-var-data-in' type='checkbox'><label for='data-7bbcbd8a-ab14-4b60-9098-54db55603851' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MVKMAC_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.346 ... nan nan nan</div><input id='attrs-d824339a-a227-42af-baca-a5d199e15b81' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d824339a-a227-42af-baca-a5d199e15b81' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5702073e-d703-4be3-b694-36741b120742' class='xr-var-data-in' type='checkbox'><label for='data-5702073e-d703-4be3-b694-36741b120742' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>C4Carbonyls_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.405 ... nan nan nan</div><input id='attrs-ac5587f0-b23b-4df6-b82d-769bb9eff316' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ac5587f0-b23b-4df6-b82d-769bb9eff316' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1ad9013f-dee7-43d1-afce-6e5a1aecbcb5' class='xr-var-data-in' type='checkbox'><label for='data-1ad9013f-dee7-43d1-afce-6e5a1aecbcb5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>C3H6O2_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.5092 ... nan nan nan</div><input id='attrs-45f8bb59-35ff-4c0c-87ee-32c8ba8eec86' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-45f8bb59-35ff-4c0c-87ee-32c8ba8eec86' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8319fef1-eb5b-4fd4-863c-2ba6abc600d2' class='xr-var-data-in' type='checkbox'><label for='data-8319fef1-eb5b-4fd4-863c-2ba6abc600d2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Benzene_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.0686 ... nan nan nan</div><input id='attrs-ffe7b02f-6bce-4187-93b9-609bcd8e61e8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ffe7b02f-6bce-4187-93b9-609bcd8e61e8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f2aa06e7-0491-4293-8fba-9db55e31db25' class='xr-var-data-in' type='checkbox'><label for='data-f2aa06e7-0491-4293-8fba-9db55e31db25' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x2MeFuranx3MeFuran_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.0562 ... nan nan nan</div><input id='attrs-ff7aaf92-7ed7-4e9e-8bb3-a93bc2074e54' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ff7aaf92-7ed7-4e9e-8bb3-a93bc2074e54' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e727fd2e-4311-49e9-a880-cb72c4c2368b' class='xr-var-data-in' type='checkbox'><label for='data-e727fd2e-4311-49e9-a880-cb72c4c2368b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x2Furanone_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan -0.0132 ... nan nan nan</div><input id='attrs-77fca200-4c06-41ad-a89f-1f93527bb6ea' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-77fca200-4c06-41ad-a89f-1f93527bb6ea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d753fced-70ce-4483-8510-ff149a87c7d5' class='xr-var-data-in' type='checkbox'><label for='data-d753fced-70ce-4483-8510-ff149a87c7d5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x23Butanedione_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.0684 ... nan nan nan</div><input id='attrs-f48d26d7-7e36-4ed7-a75b-8b0649651557' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f48d26d7-7e36-4ed7-a75b-8b0649651557' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-77db4a72-220d-42b2-8fd7-af610d3592f3' class='xr-var-data-in' type='checkbox'><label for='data-77db4a72-220d-42b2-8fd7-af610d3592f3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Toluene_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.0674 ... nan nan nan</div><input id='attrs-5e412a54-b9f0-452a-b590-3dec51dbbfb1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5e412a54-b9f0-452a-b590-3dec51dbbfb1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b9159226-d01f-4a39-ab84-210e62c66b1b' class='xr-var-data-in' type='checkbox'><label for='data-b9159226-d01f-4a39-ab84-210e62c66b1b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Phenol_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.0134 ... nan nan nan</div><input id='attrs-81899587-38db-4ecb-8ad3-5d64b8a52d9b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-81899587-38db-4ecb-8ad3-5d64b8a52d9b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-06d6adc2-7608-484a-8a1a-4a9cef63c8ed' class='xr-var-data-in' type='checkbox'><label for='data-06d6adc2-7608-484a-8a1a-4a9cef63c8ed' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Furfural_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.0038 ... nan nan nan</div><input id='attrs-abc32bd3-4221-4438-9db7-afde180ae05f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-abc32bd3-4221-4438-9db7-afde180ae05f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5f8990ba-3d0b-4525-803c-18aeca82605c' class='xr-var-data-in' type='checkbox'><label for='data-5f8990ba-3d0b-4525-803c-18aeca82605c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>DimeFurans_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.0338 ... nan nan nan</div><input id='attrs-ea04e7d2-3a0a-499c-beb3-2b4a4ea522a7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ea04e7d2-3a0a-499c-beb3-2b4a4ea522a7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c05de0dc-eca8-4f16-9d60-22bd0565c4c3' class='xr-var-data-in' type='checkbox'><label for='data-c05de0dc-eca8-4f16-9d60-22bd0565c4c3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MaleicAnhyd_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.0036 ... nan nan nan</div><input id='attrs-976af343-531a-4e07-9f52-72e001aed8a8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-976af343-531a-4e07-9f52-72e001aed8a8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4b702270-7d00-48fe-8cc1-750bf2104702' class='xr-var-data-in' type='checkbox'><label for='data-4b702270-7d00-48fe-8cc1-750bf2104702' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>BenzNitrile_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.0006 ... nan nan nan</div><input id='attrs-6a049ed6-5336-4518-abcb-b16243bd47e8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6a049ed6-5336-4518-abcb-b16243bd47e8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0a13c4d1-1917-4fe2-ad3a-980b1f9966b6' class='xr-var-data-in' type='checkbox'><label for='data-0a13c4d1-1917-4fe2-ad3a-980b1f9966b6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Styrene_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.0014 ... nan nan nan</div><input id='attrs-6c98cb70-101e-48a0-879d-6c672a1ab48b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6c98cb70-101e-48a0-879d-6c672a1ab48b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4ce6a9a3-0f99-4313-96d5-a4a90ecb1fc1' class='xr-var-data-in' type='checkbox'><label for='data-4ce6a9a3-0f99-4313-96d5-a4a90ecb1fc1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Benzaldehyde_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.0042 ... nan nan nan</div><input id='attrs-443f79ff-c0b3-4dce-90ec-469d79a1d33b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-443f79ff-c0b3-4dce-90ec-469d79a1d33b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-19d25bc4-921f-4a89-b364-cccfe4ba1aac' class='xr-var-data-in' type='checkbox'><label for='data-19d25bc4-921f-4a89-b364-cccfe4ba1aac' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>C8Aromatics_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.0244 ... nan nan nan</div><input id='attrs-9199c363-3b6f-49f4-b968-780d219e702a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9199c363-3b6f-49f4-b968-780d219e702a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7f599970-3a6b-4d8a-8937-5585458f51c1' class='xr-var-data-in' type='checkbox'><label for='data-7f599970-3a6b-4d8a-8937-5585458f51c1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>C7H8O_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.017 ... nan nan nan</div><input id='attrs-b17f5d29-85d9-4c3d-b357-5e9d2f4ac8fa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b17f5d29-85d9-4c3d-b357-5e9d2f4ac8fa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aeee799a-d122-4cf6-8e9f-c4724f040ff3' class='xr-var-data-in' type='checkbox'><label for='data-aeee799a-d122-4cf6-8e9f-c4724f040ff3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Catecholx5MeFurfural_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.0256 ... nan nan nan</div><input id='attrs-33297663-aa07-4075-81be-7de49764a463' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-33297663-aa07-4075-81be-7de49764a463' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b4bb3e4d-979f-4e5e-a862-14c82029baec' class='xr-var-data-in' type='checkbox'><label for='data-b4bb3e4d-979f-4e5e-a862-14c82029baec' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>BenzFuran_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan -0.0004 ... nan nan nan</div><input id='attrs-83b65685-6092-4a0c-b6ec-a94a91e4862a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-83b65685-6092-4a0c-b6ec-a94a91e4862a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9e9ea335-e136-4a2b-afd4-664c358f3f62' class='xr-var-data-in' type='checkbox'><label for='data-9e9ea335-e136-4a2b-afd4-664c358f3f62' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>C9Aromatics_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.008 ... nan nan nan</div><input id='attrs-27e5943a-f627-48c7-a63b-8bee71098601' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-27e5943a-f627-48c7-a63b-8bee71098601' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c27891e7-da0f-43ce-85a1-2fc4d5ff8f2c' class='xr-var-data-in' type='checkbox'><label for='data-c27891e7-da0f-43ce-85a1-2fc4d5ff8f2c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>C6H4O3_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan -0.0004 ... nan nan nan</div><input id='attrs-472a177b-9aa7-4e79-9c80-e9cf1b6ed4ef' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-472a177b-9aa7-4e79-9c80-e9cf1b6ed4ef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3665c3ad-dcd3-4e6b-82cf-d252887c76ae' class='xr-var-data-in' type='checkbox'><label for='data-3665c3ad-dcd3-4e6b-82cf-d252887c76ae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Guaiacol_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.0124 ... nan nan nan</div><input id='attrs-036fecc0-af8d-498d-965f-6f17ad298a36' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-036fecc0-af8d-498d-965f-6f17ad298a36' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-59a4c974-f7be-45ba-990c-f31cabf9a3df' class='xr-var-data-in' type='checkbox'><label for='data-59a4c974-f7be-45ba-990c-f31cabf9a3df' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Naphthalene_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan -0.0024 ... nan nan nan</div><input id='attrs-ab7d5922-0b48-455b-888c-7e0db04d5cd1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ab7d5922-0b48-455b-888c-7e0db04d5cd1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2a29807e-5a1e-4f65-aebc-ff948b83f663' class='xr-var-data-in' type='checkbox'><label for='data-2a29807e-5a1e-4f65-aebc-ff948b83f663' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Monoterpenes_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.0488 ... nan nan nan</div><input id='attrs-48e36579-a3f0-4dc0-9761-d5f99445f653' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-48e36579-a3f0-4dc0-9761-d5f99445f653' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0296e82b-0d7b-49b2-87ef-6a5fe989bfb3' class='xr-var-data-in' type='checkbox'><label for='data-0296e82b-0d7b-49b2-87ef-6a5fe989bfb3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Cresols_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.0088 ... nan nan nan</div><input id='attrs-79c40540-5c6a-4a46-926a-bfc80f8eaea1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-79c40540-5c6a-4a46-926a-bfc80f8eaea1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0c985186-ab77-412e-9efe-a095ed66cfb8' class='xr-var-data-in' type='checkbox'><label for='data-0c985186-ab77-412e-9efe-a095ed66cfb8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Syringol_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.0014 ... nan nan nan</div><input id='attrs-efb642d8-4bb5-4eff-b4c1-0b8dca5d22b5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-efb642d8-4bb5-4eff-b4c1-0b8dca5d22b5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d6fd08d1-b48a-4e8d-842e-f4021d591f37' class='xr-var-data-in' type='checkbox'><label for='data-d6fd08d1-b48a-4e8d-842e-f4021d591f37' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>BrCN_NOAACIMS_VERES</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.1316 ... nan nan nan</div><input id='attrs-0c0c1591-0744-4778-b581-a2e9748ac1fb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0c0c1591-0744-4778-b581-a2e9748ac1fb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8c83f95a-5c10-4070-946e-ca24c8e92ca2' class='xr-var-data-in' type='checkbox'><label for='data-8c83f95a-5c10-4070-946e-ca24c8e92ca2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>BrCl_NOAACIMS_VERES</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.353 ... nan nan nan</div><input id='attrs-cd082274-2b99-4bd4-a88d-a35639302028' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cd082274-2b99-4bd4-a88d-a35639302028' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8f52828b-3b50-4267-b0ca-c938674d0bab' class='xr-var-data-in' type='checkbox'><label for='data-8f52828b-3b50-4267-b0ca-c938674d0bab' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>BrO_NOAACIMS_VERES</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan -0.085 ... nan nan nan</div><input id='attrs-4ab84931-741d-4a6b-97ed-e55388f2df5d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4ab84931-741d-4a6b-97ed-e55388f2df5d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5afc96df-1585-4644-9ed7-713b8cf6698d' class='xr-var-data-in' type='checkbox'><label for='data-5afc96df-1585-4644-9ed7-713b8cf6698d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH3COOCl_NOAACIMS_VERES</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.8676 ... nan nan nan</div><input id='attrs-c5023d5a-a2db-428d-8413-5aaf4c515125' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c5023d5a-a2db-428d-8413-5aaf4c515125' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-86480285-508f-4958-a252-966154223a9d' class='xr-var-data-in' type='checkbox'><label for='data-86480285-508f-4958-a252-966154223a9d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Cl2_NOAACIMS_VERES</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.0058 ... nan nan nan</div><input id='attrs-2aadadbf-5ee1-47f0-b635-76622ed48185' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2aadadbf-5ee1-47f0-b635-76622ed48185' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-13ce6daf-b3c3-4715-830e-6f5fe0744a34' class='xr-var-data-in' type='checkbox'><label for='data-13ce6daf-b3c3-4715-830e-6f5fe0744a34' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ClNO2_NOAACIMS_VERES</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.2222 ... nan nan nan</div><input id='attrs-d519e9ec-e383-4406-bf86-44ac85f27be6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d519e9ec-e383-4406-bf86-44ac85f27be6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-df324a66-64a0-4f74-aae3-8035fc76db6b' class='xr-var-data-in' type='checkbox'><label for='data-df324a66-64a0-4f74-aae3-8035fc76db6b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HCN_NOAACIMS_VERES</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 94.82 ... nan nan nan</div><input id='attrs-01d5d23d-fb47-46bd-b336-5b6886c73667' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-01d5d23d-fb47-46bd-b336-5b6886c73667' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f3612fae-4aa6-4054-9719-97bcab045e76' class='xr-var-data-in' type='checkbox'><label for='data-f3612fae-4aa6-4054-9719-97bcab045e76' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HCOOH_NOAACIMS_VERES</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 887.0 ... nan nan nan</div><input id='attrs-4e6ccd85-60af-43d4-a2f0-c5da0339f369' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4e6ccd85-60af-43d4-a2f0-c5da0339f369' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ac0b9da0-c570-4361-abb7-b7f8c502117f' class='xr-var-data-in' type='checkbox'><label for='data-ac0b9da0-c570-4361-abb7-b7f8c502117f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HNCO_NOAACIMS_VERES</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 181.5 ... nan nan nan</div><input id='attrs-3b2b30a1-5419-4b92-ad15-5f38f6bbbed6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3b2b30a1-5419-4b92-ad15-5f38f6bbbed6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c07e365c-1c7b-4901-a58d-623752766bdb' class='xr-var-data-in' type='checkbox'><label for='data-c07e365c-1c7b-4901-a58d-623752766bdb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HPMTF_NOAACIMS_VERES</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-646a0a25-de29-4c6f-9a8d-6c71fc54532b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-646a0a25-de29-4c6f-9a8d-6c71fc54532b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0dd6d4f1-1b8f-4ab0-8dea-fd99854b5dd6' class='xr-var-data-in' type='checkbox'><label for='data-0dd6d4f1-1b8f-4ab0-8dea-fd99854b5dd6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppt</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>BUTENE-HN-1Hz_CIT_WENNBERG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.55 0.71 1.31 ... nan nan nan</div><input id='attrs-55bf002f-edea-435c-823d-8ecaee0e714d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-55bf002f-edea-435c-823d-8ecaee0e714d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-137c0136-4932-4600-9fd5-323e364ba71b' class='xr-var-data-in' type='checkbox'><label for='data-137c0136-4932-4600-9fd5-323e364ba71b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([-0.55,  0.71,  1.31, ...,   nan,   nan,   nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>BUTENE-HP-1Hz_CIT_WENNBERG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.1667 0.1 0.1 ... nan nan nan</div><input id='attrs-c6db4874-6d9c-4dd2-b3b0-8b2beef29874' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c6db4874-6d9c-4dd2-b3b0-8b2beef29874' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f6fbd7e0-b844-4085-ab4a-58ce6c418a61' class='xr-var-data-in' type='checkbox'><label for='data-f6fbd7e0-b844-4085-ab4a-58ce6c418a61' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([-0.16667,  0.1    ,  0.1    , ...,      nan,      nan,      nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ETHENE-HN-1Hz_CIT_WENNBERG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.1 0.53 1.0 1.03 ... nan nan nan</div><input id='attrs-8a6d2269-f62a-423b-9ada-3986a199e476' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8a6d2269-f62a-423b-9ada-3986a199e476' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4f989886-381b-4737-864c-482c51ac208f' class='xr-var-data-in' type='checkbox'><label for='data-4f989886-381b-4737-864c-482c51ac208f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([1.1 , 0.53, 1.  , ...,  nan,  nan,  nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ETHENE-HP-1Hz_CIT_WENNBERG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.35 2.66 1.51 2.66 ... nan nan nan</div><input id='attrs-4a295d74-81bf-4dcd-81d2-9dac06fcc1ce' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4a295d74-81bf-4dcd-81d2-9dac06fcc1ce' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-331befbe-2fbd-4ecb-b2da-986d88f92e6a' class='xr-var-data-in' type='checkbox'><label for='data-331befbe-2fbd-4ecb-b2da-986d88f92e6a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([0.35, 2.66, 1.51, ...,  nan,  nan,  nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PHENOL-1Hz_CIT_WENNBERG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.767 -1.92 -1.22 ... nan nan nan</div><input id='attrs-334a9cc2-937b-4e73-ae6b-5ba2216e3b7f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-334a9cc2-937b-4e73-ae6b-5ba2216e3b7f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fd64b118-cb59-449c-8a90-cbc526193bc4' class='xr-var-data-in' type='checkbox'><label for='data-fd64b118-cb59-449c-8a90-cbc526193bc4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([ 4.76667, -1.92   , -1.22   , ...,      nan,      nan,      nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>H2O2-1Hz_CIT_WENNBERG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.028e+03 752.8 645.1 ... nan nan</div><input id='attrs-3e7d6e89-9f9c-45cd-8737-32237e18cecc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3e7d6e89-9f9c-45cd-8737-32237e18cecc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bc91177b-a124-4c63-9716-79f25c4aa8f2' class='xr-var-data-in' type='checkbox'><label for='data-bc91177b-a124-4c63-9716-79f25c4aa8f2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([1027.62,  752.77,  645.12, ...,     nan,     nan,     nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ISOPN-1Hz_CIT_WENNBERG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.567 4.0 4.63 3.66 ... nan nan nan</div><input id='attrs-b4f8fdce-53b6-4c28-bc8f-4256bb9a5844' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b4f8fdce-53b6-4c28-bc8f-4256bb9a5844' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0592b702-3594-4fdc-b839-1fd172e77829' class='xr-var-data-in' type='checkbox'><label for='data-0592b702-3594-4fdc-b839-1fd172e77829' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([2.56667, 4.     , 4.63   , ...,     nan,     nan,     nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PROPENE-HN-1Hz_CIT_WENNBERG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.067 1.01 1.05 0.6 ... nan nan nan</div><input id='attrs-7f48b2f1-95fe-43f8-8ac2-14fc420e5d9a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7f48b2f1-95fe-43f8-8ac2-14fc420e5d9a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d7ab39de-6755-4b84-880e-d08d3a0bb161' class='xr-var-data-in' type='checkbox'><label for='data-d7ab39de-6755-4b84-880e-d08d3a0bb161' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([1.06667, 1.01   , 1.05   , ...,     nan,     nan,     nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PROPENE-HP-1Hz_CIT_WENNBERG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>15.33 13.63 13.72 ... nan nan nan</div><input id='attrs-7985438b-940c-455e-a968-f50aae529c4e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7985438b-940c-455e-a968-f50aae529c4e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-acf6c60f-90b4-4aab-87ff-b2525f3fa9d7' class='xr-var-data-in' type='checkbox'><label for='data-acf6c60f-90b4-4aab-87ff-b2525f3fa9d7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([15.3333, 13.63  , 13.72  , ...,     nan,     nan,     nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HCN-1Hz_CIT_WENNBERG</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>146.0 151.4 175.6 ... nan nan nan</div><input id='attrs-da2c57ea-d41e-45b1-b371-bbdcf2433ece' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-da2c57ea-d41e-45b1-b371-bbdcf2433ece' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9a45fa1f-92eb-4af0-8622-d1078d7d98b7' class='xr-var-data-in' type='checkbox'><label for='data-9a45fa1f-92eb-4af0-8622-d1078d7d98b7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([146.0167, 151.38  , 175.55  , ...,      nan,      nan,      nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SO2_LIF_ROLLINS</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-3044769f-0cff-4ad5-bc2a-6a311323999c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3044769f-0cff-4ad5-bc2a-6a311323999c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2efec585-b8f7-40e8-819b-82af450d00ad' class='xr-var-data-in' type='checkbox'><label for='data-2efec585-b8f7-40e8-819b-82af450d00ad' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pptv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH3COCHO_ACES_WOMACK</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 1.456 ... nan nan nan</div><input id='attrs-a72c915c-7dcb-4c62-b939-dc8a86db4777' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a72c915c-7dcb-4c62-b939-dc8a86db4777' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-358544dc-d53d-4dc7-97ea-74017ecf0fda' class='xr-var-data-in' type='checkbox'><label for='data-358544dc-d53d-4dc7-97ea-74017ecf0fda' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CHOCHO_ACES_WOMACK</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.016 ... nan nan nan</div><input id='attrs-96cc1f6e-31bc-4107-9f99-2baa6838626c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-96cc1f6e-31bc-4107-9f99-2baa6838626c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-524d6fdf-8938-4a84-94f0-c0e06fbef6c1' class='xr-var-data-in' type='checkbox'><label for='data-524d6fdf-8938-4a84-94f0-c0e06fbef6c1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ppbv</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CNgt3nm_stdPT_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-9d672070-413c-472b-80e3-97a24a427752' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9d672070-413c-472b-80e3-97a24a427752' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dba0ede6-a470-40e1-9ece-9f5a2ec371b3' class='xr-var-data-in' type='checkbox'><label for='data-dba0ede6-a470-40e1-9ece-9f5a2ec371b3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CNgt6nm_stdPT_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-13d30b42-ac88-4234-bb23-144b7859877a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-13d30b42-ac88-4234-bb23-144b7859877a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-09c16bb4-8c83-4b44-b09b-5d4e9fdefbf0' class='xr-var-data-in' type='checkbox'><label for='data-09c16bb4-8c83-4b44-b09b-5d4e9fdefbf0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CNgt20nm_stdPT_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-89bd2045-481f-4da8-be3b-12a76ff883b8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-89bd2045-481f-4da8-be3b-12a76ff883b8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4f03089b-a5f7-495f-a944-ba14543fe80f' class='xr-var-data-in' type='checkbox'><label for='data-4f03089b-a5f7-495f-a944-ba14543fe80f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CNgt20nm_nonvol_stdPT_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-de3c09c4-790b-4ca4-b8b9-d1b46487fd19' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-de3c09c4-790b-4ca4-b8b9-d1b46487fd19' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fba7f166-301e-455f-a40d-7f18ff150dbd' class='xr-var-data-in' type='checkbox'><label for='data-fba7f166-301e-455f-a40d-7f18ff150dbd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Ngt100nm_LAS_stdPT_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e614578f-db34-46b6-b3b6-da86359ae858' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e614578f-db34-46b6-b3b6-da86359ae858' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b532a774-c9da-4064-b70f-aa71833dd229' class='xr-var-data-in' type='checkbox'><label for='data-b532a774-c9da-4064-b70f-aa71833dd229' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Ngt100nm_LAS_nonvol_stdPT_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-2ee5eba3-604d-423c-bdfb-754425137432' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2ee5eba3-604d-423c-bdfb-754425137432' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-de35431f-480b-4095-85e1-be7743fe7278' class='xr-var-data-in' type='checkbox'><label for='data-de35431f-480b-4095-85e1-be7743fe7278' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CCN_034_stdPT_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-0bf63d7c-9e94-400c-a183-accfd1278b9d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0bf63d7c-9e94-400c-a183-accfd1278b9d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-32ef9277-daa0-4569-b173-d8b846f2d822' class='xr-var-data-in' type='checkbox'><label for='data-32ef9277-daa0-4569-b173-d8b846f2d822' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>N_800to50000nm_CPSPD_stdPT_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-7a2172b3-b8e5-4b55-8fd0-e1ad80ef0d1a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7a2172b3-b8e5-4b55-8fd0-e1ad80ef0d1a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e2c058ca-2d19-4770-9f73-add7cc546129' class='xr-var-data-in' type='checkbox'><label for='data-e2c058ca-2d19-4770-9f73-add7cc546129' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>V_800to50000nm_CPSPD_stdPT_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-182e7b1e-f257-4dcf-9732-db947c223591' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-182e7b1e-f257-4dcf-9732-db947c223591' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-93c48079-c561-4f77-ab51-c47ca78981f8' class='xr-var-data-in' type='checkbox'><label for='data-93c48079-c561-4f77-ab51-c47ca78981f8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>N_2000to50000nm_CDP_ambPT_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-2c44257e-175e-4901-8a1a-9eed6a6a721f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2c44257e-175e-4901-8a1a-9eed6a6a721f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b59e2ea6-b695-4570-8df2-a7b155fbb8db' class='xr-var-data-in' type='checkbox'><label for='data-b59e2ea6-b695-4570-8df2-a7b155fbb8db' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>V_2000to50000nm_CDP_ambPT_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-5e3636e5-9575-494a-b467-873abeebb3c8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5e3636e5-9575-494a-b467-873abeebb3c8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-672d71fa-e07c-4ac5-80d0-49db604f0ecb' class='xr-var-data-in' type='checkbox'><label for='data-672d71fa-e07c-4ac5-80d0-49db604f0ecb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nSMPS_stdPT_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-7a02d74c-4e1d-42f4-af8c-d81213a44830' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7a02d74c-4e1d-42f4-af8c-d81213a44830' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f06434d8-43e0-4f7d-b6fc-b62e8b7301d8' class='xr-var-data-in' type='checkbox'><label for='data-f06434d8-43e0-4f7d-b6fc-b62e8b7301d8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sSMPS_stdPT_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e05a55c5-0a30-42b7-9e78-5f3051d8d951' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e05a55c5-0a30-42b7-9e78-5f3051d8d951' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c9dd1875-0b89-45e2-93f2-edcd5b1e6faf' class='xr-var-data-in' type='checkbox'><label for='data-c9dd1875-0b89-45e2-93f2-edcd5b1e6faf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vSMPS_stdPT_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ee856fb2-04f7-4396-9e60-f79315b6b823' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ee856fb2-04f7-4396-9e60-f79315b6b823' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-24dd0352-ebb9-446c-86f0-4bde2dcae8ee' class='xr-var-data-in' type='checkbox'><label for='data-24dd0352-ebb9-446c-86f0-4bde2dcae8ee' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nLAScold_stdPT_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-831eaafc-4693-4278-ba7c-04896ea7f35f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-831eaafc-4693-4278-ba7c-04896ea7f35f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6952b32a-5cea-4353-8860-4cc8eb590c7d' class='xr-var-data-in' type='checkbox'><label for='data-6952b32a-5cea-4353-8860-4cc8eb590c7d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nLAShot_stdPT_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-90d334ba-6e0a-4fd6-a04c-a06005a71113' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-90d334ba-6e0a-4fd6-a04c-a06005a71113' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7274f3fb-5d3a-4ac2-9c7b-a477bc6097a5' class='xr-var-data-in' type='checkbox'><label for='data-7274f3fb-5d3a-4ac2-9c7b-a477bc6097a5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>totSC450_stdPT_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-58995af7-0950-4796-92f5-bbf281c36896' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-58995af7-0950-4796-92f5-bbf281c36896' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c266a9b9-2d6e-4f38-97f8-3d4d40adb672' class='xr-var-data-in' type='checkbox'><label for='data-c266a9b9-2d6e-4f38-97f8-3d4d40adb672' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>totSC550_stdPT_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-75b757b4-3a7d-4d4c-8bda-2c4b24095379' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-75b757b4-3a7d-4d4c-8bda-2c4b24095379' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b62d062c-1146-4cb8-957c-02b509d83868' class='xr-var-data-in' type='checkbox'><label for='data-b62d062c-1146-4cb8-957c-02b509d83868' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>totSC700_stdPT_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-96ae1346-9a0b-41e2-a478-d8aa1afe9701' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-96ae1346-9a0b-41e2-a478-d8aa1afe9701' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7ca818ef-a7ec-4158-8a5d-e6a43bd19772' class='xr-var-data-in' type='checkbox'><label for='data-7ca818ef-a7ec-4158-8a5d-e6a43bd19772' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Abs470_stdPT_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-8b8ed746-4501-43a2-80d2-003bb7ef7d11' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8b8ed746-4501-43a2-80d2-003bb7ef7d11' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0dc2a7bb-5603-4982-8586-286964b6dd99' class='xr-var-data-in' type='checkbox'><label for='data-0dc2a7bb-5603-4982-8586-286964b6dd99' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Abs532_stdPT_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-912ea924-d048-428e-9eb8-df554fc9c3e8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-912ea924-d048-428e-9eb8-df554fc9c3e8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4fde1808-2abb-4417-ac59-56739acdb612' class='xr-var-data-in' type='checkbox'><label for='data-4fde1808-2abb-4417-ac59-56739acdb612' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Abs660_stdPT_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-f948a82b-aaad-49a3-9b81-3d30833eb5ee' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f948a82b-aaad-49a3-9b81-3d30833eb5ee' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dcc77f1f-a840-4f83-8a27-5ae43887e0e3' class='xr-var-data-in' type='checkbox'><label for='data-dcc77f1f-a840-4f83-8a27-5ae43887e0e3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gamma450_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-13d1bde2-3272-4988-9805-bddd084ae286' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-13d1bde2-3272-4988-9805-bddd084ae286' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ef177558-3cda-4233-9d57-b5cc7f91b0fb' class='xr-var-data-in' type='checkbox'><label for='data-ef177558-3cda-4233-9d57-b5cc7f91b0fb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gamma550_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-b27c9a82-376b-4ad7-9ce7-4b501e568c92' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b27c9a82-376b-4ad7-9ce7-4b501e568c92' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-072c5229-a0c7-4424-85a7-a3196189f3a4' class='xr-var-data-in' type='checkbox'><label for='data-072c5229-a0c7-4424-85a7-a3196189f3a4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gamma700_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-3bceb418-f70d-403c-a31f-e0a364b956d2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3bceb418-f70d-403c-a31f-e0a364b956d2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c1585659-8d31-4b5e-bf0c-80c9512aee85' class='xr-var-data-in' type='checkbox'><label for='data-c1585659-8d31-4b5e-bf0c-80c9512aee85' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fRH450_RH20to85_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-8aa9ac29-427c-4e05-8c83-ff7ffb1c9284' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8aa9ac29-427c-4e05-8c83-ff7ffb1c9284' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e57add57-b2fa-48bf-a7dd-fd1b6a2d30e6' class='xr-var-data-in' type='checkbox'><label for='data-e57add57-b2fa-48bf-a7dd-fd1b6a2d30e6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fRH550_RH20to85_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-36e3c01c-8113-4623-b755-316383bdb2ba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-36e3c01c-8113-4623-b755-316383bdb2ba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a963a7f3-933d-4798-b619-896158a07a3c' class='xr-var-data-in' type='checkbox'><label for='data-a963a7f3-933d-4798-b619-896158a07a3c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fRH700_RH20to85_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-98256d85-8368-45e8-b3cb-69655a34bb7f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-98256d85-8368-45e8-b3cb-69655a34bb7f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7a971945-0654-4322-a91d-a43da47065ee' class='xr-var-data-in' type='checkbox'><label for='data-7a971945-0654-4322-a91d-a43da47065ee' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ambSC450_stdPT_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-93e65abb-6421-4696-8975-480c533a52a4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-93e65abb-6421-4696-8975-480c533a52a4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4bb1c483-0e13-41ce-bcd6-58b3871f2f28' class='xr-var-data-in' type='checkbox'><label for='data-4bb1c483-0e13-41ce-bcd6-58b3871f2f28' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ambSC550_stdPT_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-7de5a2dd-5baf-4efa-9094-084f51327a9f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7de5a2dd-5baf-4efa-9094-084f51327a9f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-511fd4f2-035f-4998-b183-7926513c0f0d' class='xr-var-data-in' type='checkbox'><label for='data-511fd4f2-035f-4998-b183-7926513c0f0d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ambSC700_stdPT_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-5e0c127d-3420-4875-b72f-e71a2a36d6fa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5e0c127d-3420-4875-b72f-e71a2a36d6fa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-126c7cd4-50c5-4db5-a2fe-9057c895421a' class='xr-var-data-in' type='checkbox'><label for='data-126c7cd4-50c5-4db5-a2fe-9057c895421a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dryAEscat_550to700_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-b274e20f-e112-437d-a6bc-d60257d34ce0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b274e20f-e112-437d-a6bc-d60257d34ce0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c1a73515-79aa-4165-bec2-f79f014506f2' class='xr-var-data-in' type='checkbox'><label for='data-c1a73515-79aa-4165-bec2-f79f014506f2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>drySSA_450_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-c6d05ed4-312b-4d54-a0b1-0086cc79b3a8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c6d05ed4-312b-4d54-a0b1-0086cc79b3a8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2802c435-4d5f-497b-8f8d-d91f33717d51' class='xr-var-data-in' type='checkbox'><label for='data-2802c435-4d5f-497b-8f8d-d91f33717d51' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>drySSA_550_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-3fc67178-be28-4265-8cc0-11edb320d737' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3fc67178-be28-4265-8cc0-11edb320d737' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5faca261-9ab1-41b4-9297-530c906a7ad8' class='xr-var-data-in' type='checkbox'><label for='data-5faca261-9ab1-41b4-9297-530c906a7ad8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>drySSA_700_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-edadad74-5f17-42e9-ba27-44b40fb20335' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-edadad74-5f17-42e9-ba27-44b40fb20335' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-32f12b27-a37f-42e2-b9e3-d758fa5e4cdc' class='xr-var-data-in' type='checkbox'><label for='data-32f12b27-a37f-42e2-b9e3-d758fa5e4cdc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ambSSA_450_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-f6347aae-dcd3-4389-ae32-323462286a80' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f6347aae-dcd3-4389-ae32-323462286a80' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ea7a1801-5e76-443e-b25b-1c94e6e9287f' class='xr-var-data-in' type='checkbox'><label for='data-ea7a1801-5e76-443e-b25b-1c94e6e9287f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ambSSA_550_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-411a18d5-b54d-4621-a1fa-8948076fd495' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-411a18d5-b54d-4621-a1fa-8948076fd495' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2f46db8c-d369-4d4f-9c42-387d81ce2369' class='xr-var-data-in' type='checkbox'><label for='data-2f46db8c-d369-4d4f-9c42-387d81ce2369' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ambSSA_700_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-3262cb7c-b7fd-4087-afef-b7db83dfbbfc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3262cb7c-b7fd-4087-afef-b7db83dfbbfc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-28012312-95c6-493e-803d-1b5027d2bcd0' class='xr-var-data-in' type='checkbox'><label for='data-28012312-95c6-493e-803d-1b5027d2bcd0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dryEXT_532_stdPT_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-7f8da852-7259-47b7-a92c-5ed260630fc4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7f8da852-7259-47b7-a92c-5ed260630fc4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9c769d62-8c4b-4db0-b7c6-0853ff6ad4fe' class='xr-var-data-in' type='checkbox'><label for='data-9c769d62-8c4b-4db0-b7c6-0853ff6ad4fe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ambEXT_532_stdPT_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-a553abb2-9e1d-461d-9aa3-1a4f09447be0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a553abb2-9e1d-461d-9aa3-1a4f09447be0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a6936643-2dbc-4f02-b789-f21749aa8d35' class='xr-var-data-in' type='checkbox'><label for='data-a6936643-2dbc-4f02-b789-f21749aa8d35' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ext_dry_664_WAGNER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.5756 -0.5923 ... 17.29 17.18</div><input id='attrs-95878135-b9b2-457b-a45e-7936382f8c03' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-95878135-b9b2-457b-a45e-7936382f8c03' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-00347333-b117-4101-8332-6300d0b2f2bc' class='xr-var-data-in' type='checkbox'><label for='data-00347333-b117-4101-8332-6300d0b2f2bc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([-0.57565, -0.59228, -0.65777, ..., 16.4262 , 17.2862 , 17.1846 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ext_dry_532_WAGNER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.08265 0.1334 ... 27.93 27.17</div><input id='attrs-46653912-8ebc-43ad-8a38-29e4af2def84' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-46653912-8ebc-43ad-8a38-29e4af2def84' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8c0f1bf1-d6e7-4d0b-a65d-999be81fa68d' class='xr-var-data-in' type='checkbox'><label for='data-8c0f1bf1-d6e7-4d0b-a65d-999be81fa68d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([ 0.08265,  0.13339,  0.11323, ..., 27.7803 , 27.9337 , 27.169  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ext_dry_405_WAGNER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.734 0.9544 1.156 ... 45.41 47.7</div><input id='attrs-8412b900-ddb7-4b70-b81c-9bb2ece6c027' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8412b900-ddb7-4b70-b81c-9bb2ece6c027' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8c667d68-378c-45bf-a301-1a6ece9e5600' class='xr-var-data-in' type='checkbox'><label for='data-8c667d68-378c-45bf-a301-1a6ece9e5600' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([ 0.73403,  0.95442,  1.156  , ..., 47.1043 , 45.4115 , 47.7003 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>abs_dry_664_WAGNER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-de013de1-8a74-45ea-91c2-162615c1fda3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-de013de1-8a74-45ea-91c2-162615c1fda3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-23bee4a2-54ce-4db0-98d8-cea040b67d42' class='xr-var-data-in' type='checkbox'><label for='data-23bee4a2-54ce-4db0-98d8-cea040b67d42' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>abs_dry_532_WAGNER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e392077d-6811-4631-ae6c-1350a793c503' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e392077d-6811-4631-ae6c-1350a793c503' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f2d9795a-8ac5-4035-9196-353c32298647' class='xr-var-data-in' type='checkbox'><label for='data-f2d9795a-8ac5-4035-9196-353c32298647' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>abs_dry_405_WAGNER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan ... 4.609 3.964 3.639</div><input id='attrs-6a70a0fb-242c-46c0-a103-9f4413a50082' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6a70a0fb-242c-46c0-a103-9f4413a50082' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-77563b21-9eaf-448b-833f-70bb46bf9041' class='xr-var-data-in' type='checkbox'><label for='data-77563b21-9eaf-448b-833f-70bb46bf9041' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([    nan,     nan,     nan, ..., 4.60915, 3.96378, 3.63945])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>AOP_RH_dry_WAGNER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>33.97 33.99 34.03 ... 31.98 31.92</div><input id='attrs-b9d035f5-8dcc-458b-9122-8ac7f93d135b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b9d035f5-8dcc-458b-9122-8ac7f93d135b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ac6bd982-f99b-437b-8cf0-53f2a9f9d721' class='xr-var-data-in' type='checkbox'><label for='data-ac6bd982-f99b-437b-8cf0-53f2a9f9d721' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pct</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([33.9694, 33.9896, 34.0255, ..., 32.0511, 31.9831, 31.9186])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ext_medRH_664_WAGNER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.132 0.0703 ... 27.71 27.08</div><input id='attrs-23cd5581-d5f4-4e9b-86e5-ae7b61f2584f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-23cd5581-d5f4-4e9b-86e5-ae7b61f2584f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d6504d2c-97d5-478d-9201-9907d1b3b653' class='xr-var-data-in' type='checkbox'><label for='data-d6504d2c-97d5-478d-9201-9907d1b3b653' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([ 1.31960e-01,  7.03000e-02, -2.66200e-02, ...,  2.65252e+01,\n",
+       "        2.77137e+01,  2.70757e+01])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>AOP_RH_med_WAGNER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>81.18 81.27 79.95 ... 78.17 78.46</div><input id='attrs-5fd882ea-9234-4b57-bfb4-9c4c4fd36c0a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5fd882ea-9234-4b57-bfb4-9c4c4fd36c0a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-942076a2-fe39-49e6-a6ff-e6f7be3783df' class='xr-var-data-in' type='checkbox'><label for='data-942076a2-fe39-49e6-a6ff-e6f7be3783df' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pct</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([81.1797, 81.2682, 79.9451, ..., 78.5303, 78.1746, 78.4558])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ext_highRH_664_WAGNER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.3878 -0.4691 ... 32.23 33.65</div><input id='attrs-2e03d7a2-ee96-437b-8240-eb72557e8d35' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2e03d7a2-ee96-437b-8240-eb72557e8d35' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8dbec80a-fe9d-46e5-be66-82db7918bd55' class='xr-var-data-in' type='checkbox'><label for='data-8dbec80a-fe9d-46e5-be66-82db7918bd55' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([-0.38784, -0.46913, -0.62592, ..., 29.4226 , 32.231  , 33.6454 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>AOP_RH_high_WAGNER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>84.94 85.27 85.72 ... 84.84 84.94</div><input id='attrs-71746d8c-a3bd-47f7-adee-0d3fb14984e0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-71746d8c-a3bd-47f7-adee-0d3fb14984e0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-11d099e2-3656-4ffc-abbc-904021e18baf' class='xr-var-data-in' type='checkbox'><label for='data-11d099e2-3656-4ffc-abbc-904021e18baf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pct</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([84.9387, 85.2683, 85.7231, ..., 84.8818, 84.8354, 84.9448])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ext_TD_664_WAGNER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.3379 0.2323 0.073 ... 5.859 9.141</div><input id='attrs-d9953c0f-3a83-4eed-9f86-a2a6bacde02e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d9953c0f-3a83-4eed-9f86-a2a6bacde02e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2c4e41af-dcea-488f-a8f8-87d8b4ca3096' class='xr-var-data-in' type='checkbox'><label for='data-2c4e41af-dcea-488f-a8f8-87d8b4ca3096' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([0.3379 , 0.23226, 0.073  , ..., 8.05547, 5.8587 , 9.14125])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ext_TD_405_WAGNER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.005 0.5646 ... 7.825 7.683</div><input id='attrs-50750fd3-56f1-4281-9ccc-764a91d95d0f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-50750fd3-56f1-4281-9ccc-764a91d95d0f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-425e9b27-0d5d-4090-a64f-acdd5b29a1b2' class='xr-var-data-in' type='checkbox'><label for='data-425e9b27-0d5d-4090-a64f-acdd5b29a1b2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([ 1.00523,  0.56456, -0.0581 , ..., 10.476  ,  7.82464,  7.68255])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>abs_TD_664_WAGNER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-bc457326-2da4-43df-8f04-635cb17f31f0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bc457326-2da4-43df-8f04-635cb17f31f0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-37ff4f1b-3817-4fef-ae9d-a4261bd66414' class='xr-var-data-in' type='checkbox'><label for='data-37ff4f1b-3817-4fef-ae9d-a4261bd66414' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>abs_TD_405_WAGNER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan ... 2.906 3.688 5.598</div><input id='attrs-4a3238cc-c8a1-441d-b94e-c16eaab994c1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4a3238cc-c8a1-441d-b94e-c16eaab994c1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-03d57636-3c07-4cb0-a415-119f1425a4eb' class='xr-var-data-in' type='checkbox'><label for='data-03d57636-3c07-4cb0-a415-119f1425a4eb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([    nan,     nan,     nan, ..., 2.90556, 3.6881 , 5.5978 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>AOP_TD_bypass_flag_WAGNER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-aaf44d38-bc53-4136-8002-149145786a55' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aaf44d38-bc53-4136-8002-149145786a55' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aef2659c-255a-4d60-8f82-f5aef0bca2f7' class='xr-var-data-in' type='checkbox'><label for='data-aef2659c-255a-4d60-8f82-f5aef0bca2f7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pct</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>AOP_filter_flag_WAGNER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 -6.667e+04 ... 0.0 0.0 0.0</div><input id='attrs-fed22307-9809-4554-b8a5-cdc376c1e425' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fed22307-9809-4554-b8a5-cdc376c1e425' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-20f29fc5-2946-4b58-ac35-02e7d8fff67e' class='xr-var-data-in' type='checkbox'><label for='data-20f29fc5-2946-4b58-ac35-02e7d8fff67e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>pct</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([     0.,      0., -66666., ...,      0.,      0.,      0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs300_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-838818e4-d068-46ce-be08-c6130ef561f2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-838818e4-d068-46ce-be08-c6130ef561f2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3605bcfe-d383-401a-b6d6-5fb487e8e99b' class='xr-var-data-in' type='checkbox'><label for='data-3605bcfe-d383-401a-b6d6-5fb487e8e99b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs320_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-3bfc86d0-8257-4393-8285-a0886d83b7f3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3bfc86d0-8257-4393-8285-a0886d83b7f3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-22a737b0-5696-4c1a-91f3-090542a55f41' class='xr-var-data-in' type='checkbox'><label for='data-22a737b0-5696-4c1a-91f3-090542a55f41' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs340_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-93558762-6ecf-4bd2-a3b6-9ae1760fbb00' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-93558762-6ecf-4bd2-a3b6-9ae1760fbb00' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d8e1f38b-ec2b-4b3e-b15d-9362f2832785' class='xr-var-data-in' type='checkbox'><label for='data-d8e1f38b-ec2b-4b3e-b15d-9362f2832785' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs360_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-f7a42abc-ff30-449f-8d22-21a81565c809' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f7a42abc-ff30-449f-8d22-21a81565c809' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-60a48b32-39dd-42fc-af5c-3313eccc62ee' class='xr-var-data-in' type='checkbox'><label for='data-60a48b32-39dd-42fc-af5c-3313eccc62ee' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs380_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-780057d5-06b9-453e-ba02-d0ad498a58a1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-780057d5-06b9-453e-ba02-d0ad498a58a1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c66a6194-3a78-4061-9276-0aeecaca4715' class='xr-var-data-in' type='checkbox'><label for='data-c66a6194-3a78-4061-9276-0aeecaca4715' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs400_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-c4ea5908-e080-4694-9757-f3b7494eb7c3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c4ea5908-e080-4694-9757-f3b7494eb7c3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-792c2402-1150-4d51-964c-9605a9ae9854' class='xr-var-data-in' type='checkbox'><label for='data-792c2402-1150-4d51-964c-9605a9ae9854' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs420_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-3ecac36c-a690-4237-8f7e-d7290c108396' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3ecac36c-a690-4237-8f7e-d7290c108396' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b6bdee8d-b387-40d7-a496-b64cfb5aad0a' class='xr-var-data-in' type='checkbox'><label for='data-b6bdee8d-b387-40d7-a496-b64cfb5aad0a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs440_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-07618896-410b-4844-b011-285fb7ec9c1c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-07618896-410b-4844-b011-285fb7ec9c1c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3b53fad7-e79b-4283-ac8c-5f84f5bd02e3' class='xr-var-data-in' type='checkbox'><label for='data-3b53fad7-e79b-4283-ac8c-5f84f5bd02e3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs460_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-3d376e84-59ae-47fe-ade9-f818dfae02e2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3d376e84-59ae-47fe-ade9-f818dfae02e2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1b1503e5-d604-43d8-9a4d-abd5c9dd55a6' class='xr-var-data-in' type='checkbox'><label for='data-1b1503e5-d604-43d8-9a4d-abd5c9dd55a6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs480_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-9f534b37-50a1-4fac-833a-c0d873f4f93d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9f534b37-50a1-4fac-833a-c0d873f4f93d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1ac21b48-5787-45a9-b66b-f0c296c5a7e6' class='xr-var-data-in' type='checkbox'><label for='data-1ac21b48-5787-45a9-b66b-f0c296c5a7e6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs500_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-aed2e174-64f4-4db4-b50b-67e6b7e10125' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aed2e174-64f4-4db4-b50b-67e6b7e10125' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d6d3a915-7789-499a-baae-75467e745fc1' class='xr-var-data-in' type='checkbox'><label for='data-d6d3a915-7789-499a-baae-75467e745fc1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs520_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-524dbc25-a65a-4341-83ba-868f8a25325f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-524dbc25-a65a-4341-83ba-868f8a25325f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a435ad19-a2e3-4208-96c4-2cc5c796ac63' class='xr-var-data-in' type='checkbox'><label for='data-a435ad19-a2e3-4208-96c4-2cc5c796ac63' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs540_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ef9469e3-8265-46e3-9d50-03bc335bef90' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ef9469e3-8265-46e3-9d50-03bc335bef90' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-81389f09-cc4b-40d6-b2cb-004a93cdce44' class='xr-var-data-in' type='checkbox'><label for='data-81389f09-cc4b-40d6-b2cb-004a93cdce44' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs560_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-3e08cf62-71b2-45ce-a472-1ce9c6a63aad' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3e08cf62-71b2-45ce-a472-1ce9c6a63aad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b62e1e6d-6822-47fc-97a5-0213cf8af161' class='xr-var-data-in' type='checkbox'><label for='data-b62e1e6d-6822-47fc-97a5-0213cf8af161' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs580_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-6d6d527d-a1d1-4455-8450-3319f9406cad' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6d6d527d-a1d1-4455-8450-3319f9406cad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3c202cd5-2495-40b6-a5ac-ca9c0ede828f' class='xr-var-data-in' type='checkbox'><label for='data-3c202cd5-2495-40b6-a5ac-ca9c0ede828f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs600_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-cce2e5f1-6485-4ce8-99f8-4e810f57ba48' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cce2e5f1-6485-4ce8-99f8-4e810f57ba48' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b9a8f8c3-825c-4f44-9693-e410b232b39d' class='xr-var-data-in' type='checkbox'><label for='data-b9a8f8c3-825c-4f44-9693-e410b232b39d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs620_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-65d38dd1-b126-4719-851f-2f242622caa0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-65d38dd1-b126-4719-851f-2f242622caa0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0b8ad14d-cd51-48c7-9347-fb17147902e3' class='xr-var-data-in' type='checkbox'><label for='data-0b8ad14d-cd51-48c7-9347-fb17147902e3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs640_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-d38d8ee2-2027-497c-b778-97fcc1fc9d5e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d38d8ee2-2027-497c-b778-97fcc1fc9d5e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4364a150-3685-4a1a-a918-e7171d102897' class='xr-var-data-in' type='checkbox'><label for='data-4364a150-3685-4a1a-a918-e7171d102897' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs660_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-9d072f93-f4e5-4347-b1ed-35b213104ac7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9d072f93-f4e5-4347-b1ed-35b213104ac7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ec45bc94-b604-48f8-ab54-bfceb06e9942' class='xr-var-data-in' type='checkbox'><label for='data-ec45bc94-b604-48f8-ab54-bfceb06e9942' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs680_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-f1ba7c3e-088c-4e66-9be8-19358738804e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f1ba7c3e-088c-4e66-9be8-19358738804e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-824d83fc-6dcd-4645-a5b7-afa2c03106b8' class='xr-var-data-in' type='checkbox'><label for='data-824d83fc-6dcd-4645-a5b7-afa2c03106b8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs700_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-d1abf5b2-59c3-4ef7-810b-3e8495676835' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d1abf5b2-59c3-4ef7-810b-3e8495676835' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0dc0d3cb-04bc-4e41-ad7d-5b6e791cd64a' class='xr-var-data-in' type='checkbox'><label for='data-0dc0d3cb-04bc-4e41-ad7d-5b6e791cd64a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs365_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-b40889d4-bf63-44f9-8b19-36e374f9ffc8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b40889d4-bf63-44f9-8b19-36e374f9ffc8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eb796777-4562-4150-92b1-f7eb816cd5bb' class='xr-var-data-in' type='checkbox'><label for='data-eb796777-4562-4150-92b1-f7eb816cd5bb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSOC_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-4a1c9d4c-7d9d-476e-9103-ce510c061444' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4a1c9d4c-7d9d-476e-9103-ce510c061444' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cd733fed-0273-4dba-b16e-6e3a8aba75d3' class='xr-var-data-in' type='checkbox'><label for='data-cd733fed-0273-4dba-b16e-6e3a8aba75d3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ug m-3</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs300_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-11a81ab3-f010-44bf-a842-6b9dcbf364b6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-11a81ab3-f010-44bf-a842-6b9dcbf364b6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d922eec5-e9f7-49ae-9724-4c2ba9eaac39' class='xr-var-data-in' type='checkbox'><label for='data-d922eec5-e9f7-49ae-9724-4c2ba9eaac39' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs320_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e0f5d024-ef7e-4be5-86c8-f46155a0f5fa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e0f5d024-ef7e-4be5-86c8-f46155a0f5fa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3512f518-f131-4747-9f1f-8875ad452c23' class='xr-var-data-in' type='checkbox'><label for='data-3512f518-f131-4747-9f1f-8875ad452c23' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs340_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-8b26d13e-b50b-473f-9274-c674c76cb32a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8b26d13e-b50b-473f-9274-c674c76cb32a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9aa9d9a7-5da3-489c-8c1b-5952d09c17af' class='xr-var-data-in' type='checkbox'><label for='data-9aa9d9a7-5da3-489c-8c1b-5952d09c17af' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs360_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-73866df5-9495-4a44-95fa-b90affc3f50f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-73866df5-9495-4a44-95fa-b90affc3f50f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8af87592-ec1b-4a7c-8113-d3686a401c04' class='xr-var-data-in' type='checkbox'><label for='data-8af87592-ec1b-4a7c-8113-d3686a401c04' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs380_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-f4afb8b8-d687-4d5b-ab2e-d464ca97e48c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f4afb8b8-d687-4d5b-ab2e-d464ca97e48c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-664e67eb-f051-4e5d-b1bc-94d4fab078e4' class='xr-var-data-in' type='checkbox'><label for='data-664e67eb-f051-4e5d-b1bc-94d4fab078e4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs400_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-4667504d-4716-4d5f-8206-03040636dfe0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4667504d-4716-4d5f-8206-03040636dfe0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dd35b25b-5aec-42ae-9dbb-3fb9f325523e' class='xr-var-data-in' type='checkbox'><label for='data-dd35b25b-5aec-42ae-9dbb-3fb9f325523e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs420_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-f265befd-1a2e-4c67-8c6b-884cdfae7282' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f265befd-1a2e-4c67-8c6b-884cdfae7282' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7388fc7f-2f41-4053-bbf3-0791e01792b2' class='xr-var-data-in' type='checkbox'><label for='data-7388fc7f-2f41-4053-bbf3-0791e01792b2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs440_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-6356dbd8-22f2-4616-b40f-d95f1969eb1b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6356dbd8-22f2-4616-b40f-d95f1969eb1b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b3bda39-6251-4843-9fdc-dadada9f70e5' class='xr-var-data-in' type='checkbox'><label for='data-9b3bda39-6251-4843-9fdc-dadada9f70e5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs460_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-0be52281-674d-4dd8-93e3-12874dfad206' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0be52281-674d-4dd8-93e3-12874dfad206' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5b68840e-7de9-4ca8-8125-898ac9587b0d' class='xr-var-data-in' type='checkbox'><label for='data-5b68840e-7de9-4ca8-8125-898ac9587b0d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs480_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-b75e200b-df92-437f-91f9-1f7a88996327' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b75e200b-df92-437f-91f9-1f7a88996327' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7ee971ea-69b0-48b4-9c93-afc8afc3590e' class='xr-var-data-in' type='checkbox'><label for='data-7ee971ea-69b0-48b4-9c93-afc8afc3590e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs500_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-d352076c-8713-42ff-be1a-cbe69fbcb472' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d352076c-8713-42ff-be1a-cbe69fbcb472' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4498692c-ca41-4465-a744-6d6b891f455f' class='xr-var-data-in' type='checkbox'><label for='data-4498692c-ca41-4465-a744-6d6b891f455f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs520_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-1b303209-f2f8-490f-9396-2ee8c9ab76ff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1b303209-f2f8-490f-9396-2ee8c9ab76ff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4a2bda27-8f05-4ef5-a8ae-dce37f271bf1' class='xr-var-data-in' type='checkbox'><label for='data-4a2bda27-8f05-4ef5-a8ae-dce37f271bf1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs540_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-b703995a-f1a7-45bd-bee5-276de8222c77' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b703995a-f1a7-45bd-bee5-276de8222c77' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3007c56e-8ec7-489b-b4f3-7ef89078a486' class='xr-var-data-in' type='checkbox'><label for='data-3007c56e-8ec7-489b-b4f3-7ef89078a486' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs560_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-21d90a39-4672-4da5-a190-d7d8a5c4ea36' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-21d90a39-4672-4da5-a190-d7d8a5c4ea36' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-58f73d32-f792-409f-9ddd-5082c09a08a6' class='xr-var-data-in' type='checkbox'><label for='data-58f73d32-f792-409f-9ddd-5082c09a08a6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs580_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-9893e9a7-b722-46b0-81f1-0187dcb306a2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9893e9a7-b722-46b0-81f1-0187dcb306a2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d2ad160c-3b16-4a2b-a068-77b710c35145' class='xr-var-data-in' type='checkbox'><label for='data-d2ad160c-3b16-4a2b-a068-77b710c35145' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs600_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-dba23303-2212-41fc-a74d-9d27ca613ef9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dba23303-2212-41fc-a74d-9d27ca613ef9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-36ff681e-9c86-4251-9709-06bd539612a3' class='xr-var-data-in' type='checkbox'><label for='data-36ff681e-9c86-4251-9709-06bd539612a3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs620_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-31398b90-b5b0-4967-9ea9-2655ecea856e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-31398b90-b5b0-4967-9ea9-2655ecea856e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6951d046-4ffa-445e-abb2-401fbe9ed435' class='xr-var-data-in' type='checkbox'><label for='data-6951d046-4ffa-445e-abb2-401fbe9ed435' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs640_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-945f0a60-7fec-48e1-9231-1a8dd906d25c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-945f0a60-7fec-48e1-9231-1a8dd906d25c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3b6f9045-f2ee-4c3c-b267-d1707d68d647' class='xr-var-data-in' type='checkbox'><label for='data-3b6f9045-f2ee-4c3c-b267-d1707d68d647' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs660_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-3e69c3aa-8cd3-44dc-a786-ac4725b2d22f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3e69c3aa-8cd3-44dc-a786-ac4725b2d22f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9603cc5e-b69e-496b-b9e5-104a34559750' class='xr-var-data-in' type='checkbox'><label for='data-9603cc5e-b69e-496b-b9e5-104a34559750' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs680_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-10bc6c13-78c4-4753-bfdc-4406d0bc083d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-10bc6c13-78c4-4753-bfdc-4406d0bc083d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b9da3820-9dbb-477d-ba3a-19376e62e404' class='xr-var-data-in' type='checkbox'><label for='data-b9da3820-9dbb-477d-ba3a-19376e62e404' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs700_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-4db88494-06a1-4268-98f6-c852f7f62ce9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4db88494-06a1-4268-98f6-c852f7f62ce9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a3016408-c59c-4f79-a2ef-71715095dfbb' class='xr-var-data-in' type='checkbox'><label for='data-a3016408-c59c-4f79-a2ef-71715095dfbb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs365_AERO_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-3f22bc6d-e364-4a62-9b44-de8f6a7926f9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3f22bc6d-e364-4a62-9b44-de8f6a7926f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0b60776c-9965-4c7b-9862-66e069e5e401' class='xr-var-data-in' type='checkbox'><label for='data-0b60776c-9965-4c7b-9862-66e069e5e401' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs300_MC_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 1.754 ... nan nan nan</div><input id='attrs-7fb038fe-84f6-4f81-98e6-75544b7592b1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7fb038fe-84f6-4f81-98e6-75544b7592b1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d286aeb2-b026-400e-97a9-73eb3ab3fc6c' class='xr-var-data-in' type='checkbox'><label for='data-d286aeb2-b026-400e-97a9-73eb3ab3fc6c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs320_MC_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 1.616 ... nan nan nan</div><input id='attrs-7b3939cb-e46b-4037-ac71-0e651396b56c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7b3939cb-e46b-4037-ac71-0e651396b56c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7b885faa-443f-44c0-8178-f22701b42634' class='xr-var-data-in' type='checkbox'><label for='data-7b885faa-443f-44c0-8178-f22701b42634' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs340_MC_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 1.236 ... nan nan nan</div><input id='attrs-655ffb01-a7cd-4125-9e93-2992401858f3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-655ffb01-a7cd-4125-9e93-2992401858f3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6616f913-fb27-42c8-87d1-23ee8028ad68' class='xr-var-data-in' type='checkbox'><label for='data-6616f913-fb27-42c8-87d1-23ee8028ad68' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs360_MC_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.9711 ... nan nan nan</div><input id='attrs-57e639b5-0b44-44f1-8684-2e632c4d040d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-57e639b5-0b44-44f1-8684-2e632c4d040d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-744eaf8a-8e42-4997-adff-b8b6e2439775' class='xr-var-data-in' type='checkbox'><label for='data-744eaf8a-8e42-4997-adff-b8b6e2439775' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs380_MC_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.831 ... nan nan nan</div><input id='attrs-9c77007f-767c-4622-b233-bb2de1b58e7d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9c77007f-767c-4622-b233-bb2de1b58e7d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cfd7d98a-5f37-4325-ac8f-346dacc9d408' class='xr-var-data-in' type='checkbox'><label for='data-cfd7d98a-5f37-4325-ac8f-346dacc9d408' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs400_MC_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.6922 ... nan nan nan</div><input id='attrs-e5ccb287-a7a4-45f0-8dfd-68d35616ffb9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e5ccb287-a7a4-45f0-8dfd-68d35616ffb9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d280171a-7db8-4795-b122-d338f375b07d' class='xr-var-data-in' type='checkbox'><label for='data-d280171a-7db8-4795-b122-d338f375b07d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs420_MC_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.6079 ... nan nan nan</div><input id='attrs-f528b634-014d-4a4b-921d-84ebb835b8dd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f528b634-014d-4a4b-921d-84ebb835b8dd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9dca5141-d4bb-4bb2-9918-566b4f60558f' class='xr-var-data-in' type='checkbox'><label for='data-9dca5141-d4bb-4bb2-9918-566b4f60558f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs440_MC_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.5151 ... nan nan nan</div><input id='attrs-9db7e98d-9c2f-4bb6-896e-9b281f93d75a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9db7e98d-9c2f-4bb6-896e-9b281f93d75a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-441fb05d-3aed-461a-a9da-c877503a520e' class='xr-var-data-in' type='checkbox'><label for='data-441fb05d-3aed-461a-a9da-c877503a520e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs460_MC_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.4528 ... nan nan nan</div><input id='attrs-099d5daa-24dd-46c7-81b1-0ebac7ad1fc0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-099d5daa-24dd-46c7-81b1-0ebac7ad1fc0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-116d2bde-bd2e-4f22-91f8-23d9b7a7cd68' class='xr-var-data-in' type='checkbox'><label for='data-116d2bde-bd2e-4f22-91f8-23d9b7a7cd68' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs480_MC_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.3803 ... nan nan nan</div><input id='attrs-44dd24c5-12a3-4305-94eb-de69bb0bb56f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-44dd24c5-12a3-4305-94eb-de69bb0bb56f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6ce397f3-a765-4326-9c39-40cb22b89182' class='xr-var-data-in' type='checkbox'><label for='data-6ce397f3-a765-4326-9c39-40cb22b89182' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs500_MC_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.3375 ... nan nan nan</div><input id='attrs-c934bb61-e837-4aac-a10e-e111ae5ec79d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c934bb61-e837-4aac-a10e-e111ae5ec79d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-11b0ef90-901e-47bc-a1cb-d28114ef2548' class='xr-var-data-in' type='checkbox'><label for='data-11b0ef90-901e-47bc-a1cb-d28114ef2548' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs520_MC_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.2838 ... nan nan nan</div><input id='attrs-2dada290-c986-431b-8e14-9fb1bafdd8ee' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2dada290-c986-431b-8e14-9fb1bafdd8ee' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d09bd1f2-f8d6-451a-96f9-a5dcdd6dd8ad' class='xr-var-data-in' type='checkbox'><label for='data-d09bd1f2-f8d6-451a-96f9-a5dcdd6dd8ad' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs540_MC_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.2785 ... nan nan nan</div><input id='attrs-ca49f817-7976-4114-ba39-bff972ab67f8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ca49f817-7976-4114-ba39-bff972ab67f8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-908b701e-12a9-40ce-a1eb-f3920a164d09' class='xr-var-data-in' type='checkbox'><label for='data-908b701e-12a9-40ce-a1eb-f3920a164d09' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs560_MC_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.2692 ... nan nan nan</div><input id='attrs-fd97dd64-29a2-44f9-abe7-b8890f22f52d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fd97dd64-29a2-44f9-abe7-b8890f22f52d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cade9ca6-7aff-44b1-98f5-814e816b5fbe' class='xr-var-data-in' type='checkbox'><label for='data-cade9ca6-7aff-44b1-98f5-814e816b5fbe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs580_MC_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.2077 ... nan nan nan</div><input id='attrs-9736abbe-0dcc-4fff-a052-7c94eba01772' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9736abbe-0dcc-4fff-a052-7c94eba01772' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-930d0adc-28fd-4e80-b071-6970d83e6987' class='xr-var-data-in' type='checkbox'><label for='data-930d0adc-28fd-4e80-b071-6970d83e6987' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs600_MC_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.1844 ... nan nan nan</div><input id='attrs-b358f573-809a-42f5-9676-87aa1bd14c23' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b358f573-809a-42f5-9676-87aa1bd14c23' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7aad35e8-ccdb-4f82-854a-1b6a6ce489b2' class='xr-var-data-in' type='checkbox'><label for='data-7aad35e8-ccdb-4f82-854a-1b6a6ce489b2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs620_MC_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.1732 ... nan nan nan</div><input id='attrs-8d40c66e-a5bb-4958-8eae-e322025f4df1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8d40c66e-a5bb-4958-8eae-e322025f4df1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bc1950c9-d4bd-4727-a4ed-6478d943d361' class='xr-var-data-in' type='checkbox'><label for='data-bc1950c9-d4bd-4727-a4ed-6478d943d361' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs640_MC_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.1301 ... nan nan nan</div><input id='attrs-3d17d340-d221-4936-98c1-a6d27cd0045e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3d17d340-d221-4936-98c1-a6d27cd0045e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8b994578-01fc-45f4-9cdc-2c9442362e0e' class='xr-var-data-in' type='checkbox'><label for='data-8b994578-01fc-45f4-9cdc-2c9442362e0e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs660_MC_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.1486 ... nan nan nan</div><input id='attrs-50fd9e0c-838e-48c9-8c6b-b676f0e9f3f4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-50fd9e0c-838e-48c9-8c6b-b676f0e9f3f4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0ccd72d1-5ea8-4407-99ab-a225f2fd9146' class='xr-var-data-in' type='checkbox'><label for='data-0ccd72d1-5ea8-4407-99ab-a225f2fd9146' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs680_MC_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.07588 ... nan nan nan</div><input id='attrs-21a6a714-d777-431b-9f98-3deba2e43d0a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-21a6a714-d777-431b-9f98-3deba2e43d0a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bb4b6cdf-a358-4676-87c2-3d694f3fd87a' class='xr-var-data-in' type='checkbox'><label for='data-bb4b6cdf-a358-4676-87c2-3d694f3fd87a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs700_MC_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan ... nan nan nan</div><input id='attrs-0bc2d293-7ca2-43a2-a4a9-aa77e68701c4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0bc2d293-7ca2-43a2-a4a9-aa77e68701c4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c61bcdd9-2f9b-40ad-abe5-ba4bf00b983a' class='xr-var-data-in' type='checkbox'><label for='data-c61bcdd9-2f9b-40ad-abe5-ba4bf00b983a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs365_MC_WEBER</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan 0.9267 ... nan nan nan</div><input id='attrs-a4a2d945-05eb-47fb-b92e-27a31ff426cf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a4a2d945-05eb-47fb-b92e-27a31ff426cf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-575815f1-e90c-4cd8-adc3-b38fcf410229' class='xr-var-data-in' type='checkbox'><label for='data-575815f1-e90c-4cd8-adc3-b38fcf410229' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Mm-1</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>BC_mass_90_550_nm_SCHWARZ</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.058 0.0 0.0 0.0 ... nan nan nan</div><input id='attrs-479915b1-3500-432d-837a-4105f2c5dc7e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-479915b1-3500-432d-837a-4105f2c5dc7e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-55bb9f70-c57c-42fb-ba90-af88be636e66' class='xr-var-data-in' type='checkbox'><label for='data-55bb9f70-c57c-42fb-ba90-af88be636e66' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ng std m-3</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([0.058, 0.   , 0.   , ...,   nan,   nan,   nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>BC_Dilution_Flag_SCHWARZ</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-74eb1bf7-56a7-48b4-b192-541187567c92' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-74eb1bf7-56a7-48b4-b192-541187567c92' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-07806fcc-782c-4d04-b85e-d376a27b6681' class='xr-var-data-in' type='checkbox'><label for='data-07806fcc-782c-4d04-b85e-d376a27b6681' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>unitless</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>OA_PM1_AMS_JIMENEZ</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-6f6773fc-94b5-4dc0-9e9a-6f7b0cc51238' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6f6773fc-94b5-4dc0-9e9a-6f7b0cc51238' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f16c01e3-9cd6-4e71-bbcf-880857c4d930' class='xr-var-data-in' type='checkbox'><label for='data-f16c01e3-9cd6-4e71-bbcf-880857c4d930' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ug sm-3</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Sulfate_PM1_AMS_JIMENEZ</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-121352e8-ffc8-47ab-b69c-cedcefd22b3d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-121352e8-ffc8-47ab-b69c-cedcefd22b3d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fae04c23-27cd-4b8c-9819-94a0a983c65d' class='xr-var-data-in' type='checkbox'><label for='data-fae04c23-27cd-4b8c-9819-94a0a983c65d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ug sm-3</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Nitrate_PM1_AMS_JIMENEZ</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-822f851c-e4ea-4804-a40b-e990f9db9641' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-822f851c-e4ea-4804-a40b-e990f9db9641' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ed547a93-19d8-4583-8fc5-158e4ed4aed9' class='xr-var-data-in' type='checkbox'><label for='data-ed547a93-19d8-4583-8fc5-158e4ed4aed9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ug sm-3</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Ammonium_PM1_AMS_JIMENEZ</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-b3207229-c6b6-4d48-8bfc-436ea94d3e99' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b3207229-c6b6-4d48-8bfc-436ea94d3e99' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-825c8d54-a482-4503-a51f-15e9ec868391' class='xr-var-data-in' type='checkbox'><label for='data-825c8d54-a482-4503-a51f-15e9ec868391' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ug sm-3</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NR_Chloride_PM1_AMS_JIMENEZ</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-7486abed-2185-44d0-8922-dfeb9f94e5d2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7486abed-2185-44d0-8922-dfeb9f94e5d2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f00ba759-ba37-4fbb-858f-f70e214c25c2' class='xr-var-data-in' type='checkbox'><label for='data-f00ba759-ba37-4fbb-858f-f70e214c25c2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ug sm-3</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Potassium_PM1_AMS_JIMENEZ</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-394ab1b2-c269-4086-a76e-bbc98274aeb4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-394ab1b2-c269-4086-a76e-bbc98274aeb4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-70e9575d-adec-496c-a505-55acf781b7fc' class='xr-var-data-in' type='checkbox'><label for='data-70e9575d-adec-496c-a505-55acf781b7fc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ug sm-3</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSA_PM1_AMS_JIMENEZ</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e0d8d778-61bd-409f-a402-358f665ba841' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e0d8d778-61bd-409f-a402-358f665ba841' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-769baf86-10e9-4937-8fc1-fdd11c509a22' class='xr-var-data-in' type='checkbox'><label for='data-769baf86-10e9-4937-8fc1-fdd11c509a22' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ug sm-3</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ClO4_PM1_AMS_JIMENEZ</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-bfe57634-a2ff-4a46-aab8-3515bc5417a2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bfe57634-a2ff-4a46-aab8-3515bc5417a2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6a2229d7-6ce0-4d0c-b7e4-5b213f0b1a3c' class='xr-var-data-in' type='checkbox'><label for='data-6a2229d7-6ce0-4d0c-b7e4-5b213f0b1a3c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ug sm-3</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Iodine_PM1_AMS_JIMENEZ</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-333ddeb4-d4ea-43d9-a705-2055aa7150ab' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-333ddeb4-d4ea-43d9-a705-2055aa7150ab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-28747999-95a2-4bba-806b-7d28820d15f2' class='xr-var-data-in' type='checkbox'><label for='data-28747999-95a2-4bba-806b-7d28820d15f2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ug sm-3</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Bromine_PM1_AMS_JIMENEZ</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-b55fe498-978d-417b-996d-b6c77d01bb81' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b55fe498-978d-417b-996d-b6c77d01bb81' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-de5cdb1c-6a95-441f-8115-145543e5ef19' class='xr-var-data-in' type='checkbox'><label for='data-de5cdb1c-6a95-441f-8115-145543e5ef19' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ug sm-3</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Seasalt_PM1_AMS_JIMENEZ</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-7ddd0aa7-e943-4e04-93d1-05434a0f74e8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7ddd0aa7-e943-4e04-93d1-05434a0f74e8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bf4a8c51-75f1-4919-8da6-ea376e185c9d' class='xr-var-data-in' type='checkbox'><label for='data-bf4a8c51-75f1-4919-8da6-ea376e185c9d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ug sm-3</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CloudFlag_AMS_JIMENEZ</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-dbbc11a5-fe0d-4189-b770-741baa490740' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dbbc11a5-fe0d-4189-b770-741baa490740' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-81a4bd3d-57ba-4c0f-ae7b-687bcd74a840' class='xr-var-data-in' type='checkbox'><label for='data-81a4bd3d-57ba-4c0f-ae7b-687bcd74a840' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>unitless</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>AmmBalance_PM1_AMS_JIMENEZ</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-5ce27ea5-6d44-471c-8327-0e80c46a1d07' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5ce27ea5-6d44-471c-8327-0e80c46a1d07' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e5656533-0111-4b27-bf38-334edd897308' class='xr-var-data-in' type='checkbox'><label for='data-e5656533-0111-4b27-bf38-334edd897308' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>unitless</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Density_PM1_AMS_JIMENEZ</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e83c9dda-b0e9-4c1c-8b32-d95e98436f77' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e83c9dda-b0e9-4c1c-8b32-d95e98436f77' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1e83602a-3d55-43db-89f5-257dbc365ef4' class='xr-var-data-in' type='checkbox'><label for='data-1e83602a-3d55-43db-89f5-257dbc365ef4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>g cm-3</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>OADensity_PM1_AMS_JIMENEZ</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e05d562a-c7c1-4767-8313-88752f60c521' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e05d562a-c7c1-4767-8313-88752f60c521' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9c4b3d93-a099-4de4-92c8-a29447f657bd' class='xr-var-data-in' type='checkbox'><label for='data-9c4b3d93-a099-4de4-92c8-a29447f657bd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>g cm-3</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>OSc_PM1_AMS_JIMENEZ</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-15ad7e6c-0025-4af3-973f-20b241de4604' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-15ad7e6c-0025-4af3-973f-20b241de4604' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f08f4920-5a65-4acd-b912-ce8cfe87f268' class='xr-var-data-in' type='checkbox'><label for='data-f08f4920-5a65-4acd-b912-ce8cfe87f268' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>unitless</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>C6H10O5_JIMENEZ</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-8ec6a82c-3f0f-4b74-b9ca-3868fca31411' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8ec6a82c-3f0f-4b74-b9ca-3868fca31411' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b40a6e6a-4800-45fe-8be8-373ada8e7d91' class='xr-var-data-in' type='checkbox'><label for='data-b40a6e6a-4800-45fe-8be8-373ada8e7d91' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>C6H5NO4_JIMENEZ</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-654b9098-df25-4b20-a759-0d2dd2d143ca' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-654b9098-df25-4b20-a759-0d2dd2d143ca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c6d5ca4f-cce2-4f68-a133-5b645517b144' class='xr-var-data-in' type='checkbox'><label for='data-c6d5ca4f-cce2-4f68-a133-5b645517b144' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Cl_ug/m3_DIBB</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ae911edb-c714-40a6-877c-f23742a94da0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ae911edb-c714-40a6-877c-f23742a94da0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-74757f2b-e651-4f05-af98-710fcf5ac457' class='xr-var-data-in' type='checkbox'><label for='data-74757f2b-e651-4f05-af98-710fcf5ac457' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ug/m3</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Br_ug/m3_DIBB</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-2a77711e-b031-4c6c-afd5-5891a34c0414' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2a77711e-b031-4c6c-afd5-5891a34c0414' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5f765916-7030-449d-a8ee-df363f8e77bf' class='xr-var-data-in' type='checkbox'><label for='data-5f765916-7030-449d-a8ee-df363f8e77bf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ug/m3</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NO3_ug/m3_DIBB</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-1b379339-b637-45fa-b8f3-ea0221c0f1d0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1b379339-b637-45fa-b8f3-ea0221c0f1d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4069fdbe-8965-4a50-bbb9-d99de4020f5f' class='xr-var-data-in' type='checkbox'><label for='data-4069fdbe-8965-4a50-bbb9-d99de4020f5f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ug/m3</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SO4_ug/m3_DIBB</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-f8fea583-57d0-4476-b512-bf832cd91c99' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f8fea583-57d0-4476-b512-bf832cd91c99' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1122d503-961c-4da3-9cbc-cb25f278af7a' class='xr-var-data-in' type='checkbox'><label for='data-1122d503-961c-4da3-9cbc-cb25f278af7a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ug/m3</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>C2O4_ug/m3_DIBB</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-700c05e0-bb28-431e-9b8b-83d099f329cb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-700c05e0-bb28-431e-9b8b-83d099f329cb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-954f1813-afaa-4a32-acb2-87a50ef0a565' class='xr-var-data-in' type='checkbox'><label for='data-954f1813-afaa-4a32-acb2-87a50ef0a565' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ug/m3</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Na_ug/m3_DIBB</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-bf45e087-cf64-4aee-b965-d705756db1bc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bf45e087-cf64-4aee-b965-d705756db1bc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3b3c0fa4-8d98-42a4-98b5-3191895a2aea' class='xr-var-data-in' type='checkbox'><label for='data-3b3c0fa4-8d98-42a4-98b5-3191895a2aea' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ug/m3</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NH4_ug/m3_DIBB</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-cc40b67b-6d70-4d52-b1f7-ee27b92c4494' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cc40b67b-6d70-4d52-b1f7-ee27b92c4494' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-668cbf2f-f67e-49b7-bd03-325b7854ced7' class='xr-var-data-in' type='checkbox'><label for='data-668cbf2f-f67e-49b7-bd03-325b7854ced7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ug/m3</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>K_ug/m3_DIBB</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e50f19a8-0fc1-4100-a3cc-24fa6dd68ff3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e50f19a8-0fc1-4100-a3cc-24fa6dd68ff3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-538ee335-808f-43f9-ab23-e62037416474' class='xr-var-data-in' type='checkbox'><label for='data-538ee335-808f-43f9-ab23-e62037416474' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ug/m3</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Mg_ug/m3_DIBB</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-1ffc1245-2730-4f8a-834d-0c4bd32c553a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1ffc1245-2730-4f8a-834d-0c4bd32c553a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2544f010-4d2f-42f2-9d4a-c8b862907a0a' class='xr-var-data-in' type='checkbox'><label for='data-2544f010-4d2f-42f2-9d4a-c8b862907a0a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ug/m3</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Ca_ug/m3_DIBB</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-502265b5-fb1d-45c6-bc51-01ee45d5ad5d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-502265b5-fb1d-45c6-bc51-01ee45d5ad5d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dbbc4d58-a692-4215-8972-865d45a4d781' class='xr-var-data-in' type='checkbox'><label for='data-dbbc4d58-a692-4215-8972-865d45a4d781' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ug/m3</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nCDP_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-7b56509b-1e4f-4273-a2de-36e776130071' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7b56509b-1e4f-4273-a2de-36e776130071' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-364edb67-95d1-42ac-93a6-02efb7d4050b' class='xr-var-data-in' type='checkbox'><label for='data-364edb67-95d1-42ac-93a6-02efb7d4050b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vCDP_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-0e506d47-e8e4-48ee-86de-76fbc62cf5b7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0e506d47-e8e4-48ee-86de-76fbc62cf5b7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-159598be-8fcc-437a-b8f4-9cae15d60fba' class='xr-var-data-in' type='checkbox'><label for='data-159598be-8fcc-437a-b8f4-9cae15d60fba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nCPSPD_stdPT_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-c17c2ba2-4399-482a-966a-a76016a68f45' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c17c2ba2-4399-482a-966a-a76016a68f45' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3d09927b-97d5-4da6-8fb4-f8fc1900784e' class='xr-var-data-in' type='checkbox'><label for='data-3d09927b-97d5-4da6-8fb4-f8fc1900784e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vCPSPD_stdPT_MOORE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-2d18a42c-0241-4859-91f7-f5bf45ae0387' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2d18a42c-0241-4859-91f7-f5bf45ae0387' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-22b51afb-27f7-4328-9fba-8e2ef1f6e4fb' class='xr-var-data-in' type='checkbox'><label for='data-22b51afb-27f7-4328-9fba-8e2ef1f6e4fb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>missing</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Nacc_CAPS_WEINZIERL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-aabd69a7-0711-4946-9fc6-06b58d46c270' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aabd69a7-0711-4946-9fc6-06b58d46c270' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-95455e5d-5170-48a8-9cb7-fe2b1e9dc04e' class='xr-var-data-in' type='checkbox'><label for='data-95455e5d-5170-48a8-9cb7-fe2b1e9dc04e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>#/cm^3 at 1013.25 hPa and 273.15 K</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Ncoa1_CAPS_WEINZIERL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-aa290c4a-5119-4092-917c-626928bbe41d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aa290c4a-5119-4092-917c-626928bbe41d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-45ec1b7a-450c-4207-8c6c-1c6c5f4c0424' class='xr-var-data-in' type='checkbox'><label for='data-45ec1b7a-450c-4207-8c6c-1c6c5f4c0424' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>#/cm^3 at 1013.25 hPa and 273.15 K</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Ncoa2_CAPS_WEINZIERL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-83604629-29dc-4f6f-baa1-0fbb67fff41e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-83604629-29dc-4f6f-baa1-0fbb67fff41e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5bbf3acc-651c-4d81-94d3-f74d2e7f3230' class='xr-var-data-in' type='checkbox'><label for='data-5bbf3acc-651c-4d81-94d3-f74d2e7f3230' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>#/cm^3 at 1013.25 hPa and 273.15 K</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Ncoa3_CAPS_WEINZIERL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-b178a02a-2177-4498-8ed6-4e94db18f19d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b178a02a-2177-4498-8ed6-4e94db18f19d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4fc211ce-2908-4f29-8b4b-bff07cfef057' class='xr-var-data-in' type='checkbox'><label for='data-4fc211ce-2908-4f29-8b4b-bff07cfef057' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>#/cm^3 at 1013.25 hPa and 273.15 K</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Ntot_CAPS_WEINZIERL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-0f5de46d-3447-4d6e-a9b7-ad1e402153a7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0f5de46d-3447-4d6e-a9b7-ad1e402153a7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8956ddc9-416c-4960-b049-9ab6b58f2f0d' class='xr-var-data-in' type='checkbox'><label for='data-8956ddc9-416c-4960-b049-9ab6b58f2f0d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>#/cm^3 at 1013.25 hPa and 273.15 K</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cloudindicator_CAPS_WEINZIERL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-f5852418-f201-4bf4-bc28-02f3be86e9e7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f5852418-f201-4bf4-bc28-02f3be86e9e7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-606afcfa-fd42-4e35-8631-54c7d8312aa9' class='xr-var-data-in' type='checkbox'><label for='data-606afcfa-fd42-4e35-8631-54c7d8312aa9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dimensionless</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jO3_O2_O1D_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.903e-05 2.881e-05 ... nan</div><input id='attrs-7429fbd7-412a-4f01-adb0-0354c2cf4078' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7429fbd7-412a-4f01-adb0-0354c2cf4078' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-25c9424f-0e0f-4afd-a37e-a403b2e37986' class='xr-var-data-in' type='checkbox'><label for='data-25c9424f-0e0f-4afd-a37e-a403b2e37986' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([2.903e-05, 2.881e-05, 2.904e-05, ..., 9.267e-06, 9.823e-06,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jNO2_NO_O3P_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.008803 0.008713 ... 0.005476 nan</div><input id='attrs-c05203f3-8d72-42ad-81ec-798ca978a584' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c05203f3-8d72-42ad-81ec-798ca978a584' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4a2ed288-bbd6-4ae3-bd7a-08ba9702e174' class='xr-var-data-in' type='checkbox'><label for='data-4a2ed288-bbd6-4ae3-bd7a-08ba9702e174' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([0.0088031, 0.0087127, 0.0087949, ..., 0.0048257, 0.0054755,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jH2O2_OH_OH_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.766e-06 6.712e-06 ... nan</div><input id='attrs-7be13236-e9ba-45bd-9053-d3bfafd593b9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7be13236-e9ba-45bd-9053-d3bfafd593b9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-220043ae-dd58-4407-b828-fea774045c55' class='xr-var-data-in' type='checkbox'><label for='data-220043ae-dd58-4407-b828-fea774045c55' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([6.766e-06, 6.712e-06, 6.763e-06, ..., 3.218e-06, 3.487e-06,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jNO3_NO_O2_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.02304 0.02231 ... 0.01676 nan</div><input id='attrs-f13bd390-f627-46d2-a4a3-0ff23901d9ef' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f13bd390-f627-46d2-a4a3-0ff23901d9ef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-45ab9230-c44c-4dd7-9197-17f5d942b919' class='xr-var-data-in' type='checkbox'><label for='data-45ab9230-c44c-4dd7-9197-17f5d942b919' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([0.023042, 0.022311, 0.022943, ..., 0.01251 , 0.016756,      nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jNO3_NO2_O3P_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.1923 0.187 0.1915 ... 0.1363 nan</div><input id='attrs-b7040af7-2c08-4371-8cd8-6524f5692de5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b7040af7-2c08-4371-8cd8-6524f5692de5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9368d193-3ac8-46b6-b4c6-3f68044896ea' class='xr-var-data-in' type='checkbox'><label for='data-9368d193-3ac8-46b6-b4c6-3f68044896ea' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([0.19225, 0.18695, 0.19152, ..., 0.10495, 0.13625,     nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jN2O5_NO3_NO2_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.016e-05 3.984e-05 ... nan</div><input id='attrs-a156f750-2b4d-4fa7-a2f6-8d8d3fae65e0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a156f750-2b4d-4fa7-a2f6-8d8d3fae65e0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-57d12481-0b6b-4bdc-9146-2a1abafdb15f' class='xr-var-data-in' type='checkbox'><label for='data-57d12481-0b6b-4bdc-9146-2a1abafdb15f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([4.016e-05, 3.984e-05, 4.012e-05, ..., 1.915e-05, 2.084e-05,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jHNO2_OH_NO_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.001372 0.001359 ... 0.0008325 nan</div><input id='attrs-123c485d-1070-4e9c-a8f6-7d12725607c1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-123c485d-1070-4e9c-a8f6-7d12725607c1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d40cf255-6431-4168-b246-3b99b7e472a5' class='xr-var-data-in' type='checkbox'><label for='data-d40cf255-6431-4168-b246-3b99b7e472a5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([0.0013718, 0.0013594, 0.0013703, ..., 0.0007451, 0.0008325,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jHNO3_OH_NO2_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.62e-07 5.576e-07 ... 2.37e-07 nan</div><input id='attrs-a65232cb-06b3-400c-86f0-a4bbbb9ff7b0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a65232cb-06b3-400c-86f0-a4bbbb9ff7b0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-96efa9f7-b7b7-4591-9b09-a774a24e3d2a' class='xr-var-data-in' type='checkbox'><label for='data-96efa9f7-b7b7-4591-9b09-a774a24e3d2a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([5.620e-07, 5.576e-07, 5.621e-07, ..., 2.222e-07, 2.370e-07,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jHNO4_HO2_NO2_UvVisOnly_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.73e-06 5.686e-06 ... nan</div><input id='attrs-63266964-674b-4496-9eb5-dc5081b54f56' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-63266964-674b-4496-9eb5-dc5081b54f56' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-44d53985-b925-4d07-998b-0bc951ad2b5f' class='xr-var-data-in' type='checkbox'><label for='data-44d53985-b925-4d07-998b-0bc951ad2b5f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([5.730e-06, 5.686e-06, 5.725e-06, ..., 2.462e-06, 2.641e-06,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jCH2O_H_HCO_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.818e-05 2.796e-05 ... nan</div><input id='attrs-27578bde-128a-44e1-8ca0-5a3f0f1aa039' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-27578bde-128a-44e1-8ca0-5a3f0f1aa039' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-23c5f4c1-4960-4a44-88fd-a2669d39cfcf' class='xr-var-data-in' type='checkbox'><label for='data-23c5f4c1-4960-4a44-88fd-a2669d39cfcf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([2.818e-05, 2.796e-05, 2.815e-05, ..., 1.256e-05, 1.345e-05,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jCH2O_H2_CO_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.512e-05 4.476e-05 ... nan</div><input id='attrs-304adc1c-4737-4eec-8b11-7fa4dce9ef20' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-304adc1c-4737-4eec-8b11-7fa4dce9ef20' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-597db13b-7d22-4447-9074-55a06e048196' class='xr-var-data-in' type='checkbox'><label for='data-597db13b-7d22-4447-9074-55a06e048196' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([4.512e-05, 4.476e-05, 4.509e-05, ..., 2.289e-05, 2.480e-05,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jCH3CHO_CH3_HCO_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.388e-06 4.355e-06 ... nan</div><input id='attrs-32e7da4f-c2bc-463d-abd7-fdbcb758cbc8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-32e7da4f-c2bc-463d-abd7-fdbcb758cbc8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-98f863f0-5287-4eb9-b70d-0887e8ac94cf' class='xr-var-data-in' type='checkbox'><label for='data-98f863f0-5287-4eb9-b70d-0887e8ac94cf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([4.388e-06, 4.355e-06, 4.386e-06, ..., 1.682e-06, 1.789e-06,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jPropanal_CH2CH3_HCO_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.506e-05 1.494e-05 ... nan</div><input id='attrs-96e93aeb-124c-495d-88c3-37f4024a72c6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-96e93aeb-124c-495d-88c3-37f4024a72c6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f4f2b7ce-ffc1-4a3f-964d-79813f5a5d9f' class='xr-var-data-in' type='checkbox'><label for='data-f4f2b7ce-ffc1-4a3f-964d-79813f5a5d9f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([1.506e-05, 1.494e-05, 1.505e-05, ..., 6.169e-06, 6.581e-06,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jCH3OOH_CH3O_OH_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.722e-06 4.685e-06 ... nan</div><input id='attrs-0f53b190-d45f-4d34-b35d-4bb4c199652f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0f53b190-d45f-4d34-b35d-4bb4c199652f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aaa1ecbc-5aa5-4c9f-ac5d-9e58ff150dc9' class='xr-var-data-in' type='checkbox'><label for='data-aaa1ecbc-5aa5-4c9f-ac5d-9e58ff150dc9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([4.722e-06, 4.685e-06, 4.718e-06, ..., 2.258e-06, 2.452e-06,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jMeONO2_CH3O_NO2_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.318e-07 8.252e-07 ... nan</div><input id='attrs-35af8d11-2f06-465f-9d5b-7925779ef698' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-35af8d11-2f06-465f-9d5b-7925779ef698' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-86de80bf-436f-4dae-af9e-f94e24c9e677' class='xr-var-data-in' type='checkbox'><label for='data-86de80bf-436f-4dae-af9e-f94e24c9e677' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([8.318e-07, 8.252e-07, 8.322e-07, ..., 3.291e-07, 3.507e-07,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jEthONO2_CH3CH2O_NO2_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.37e-06 1.359e-06 ... nan</div><input id='attrs-9b4db4db-3f14-4a95-8820-cb2477420b6e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9b4db4db-3f14-4a95-8820-cb2477420b6e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e18fcc78-70f6-4742-bff2-d91a879f14ba' class='xr-var-data-in' type='checkbox'><label for='data-e18fcc78-70f6-4742-bff2-d91a879f14ba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([1.370e-06, 1.359e-06, 1.371e-06, ..., 5.492e-07, 5.855e-07,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jPAN_CH3COO2_NO2_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.943e-07 4.902e-07 ... nan</div><input id='attrs-5b0fefce-0ffe-46f0-8c39-e6c2b6336af6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5b0fefce-0ffe-46f0-8c39-e6c2b6336af6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c9a95fda-1e71-4a9a-9cc0-89b8431a6ff0' class='xr-var-data-in' type='checkbox'><label for='data-c9a95fda-1e71-4a9a-9cc0-89b8431a6ff0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([4.943e-07, 4.902e-07, 4.947e-07, ..., 2.174e-07, 2.329e-07,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jPAN_CH3COO_NO3_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.118e-07 2.101e-07 ... nan</div><input id='attrs-4e5269ec-fbfa-4b31-a566-d5bb425b8f02' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4e5269ec-fbfa-4b31-a566-d5bb425b8f02' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d3ed7710-2107-470a-97a9-607002722c45' class='xr-var-data-in' type='checkbox'><label for='data-d3ed7710-2107-470a-97a9-607002722c45' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([2.118e-07, 2.101e-07, 2.120e-07, ..., 9.319e-08, 9.983e-08,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jMAC_NoProductsSpecified_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.488e-06 4.45e-06 ... nan</div><input id='attrs-7ec9cfab-d112-4496-92a6-0ec1ec47ba25' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7ec9cfab-d112-4496-92a6-0ec1ec47ba25' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-47c4d484-337e-48c9-9df3-ac8ed2e25ad5' class='xr-var-data-in' type='checkbox'><label for='data-47c4d484-337e-48c9-9df3-ac8ed2e25ad5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([4.488e-06, 4.450e-06, 4.483e-06, ..., 2.332e-06, 2.561e-06,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jMVK_NoProductsSpecified_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.872e-06 3.841e-06 ... nan</div><input id='attrs-0c1fd53f-cce9-4684-845d-d849504000d6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0c1fd53f-cce9-4684-845d-d849504000d6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ca026b33-e490-4d4f-83b9-e0f9289dcd4d' class='xr-var-data-in' type='checkbox'><label for='data-ca026b33-e490-4d4f-83b9-e0f9289dcd4d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([3.872e-06, 3.841e-06, 3.869e-06, ..., 1.930e-06, 2.087e-06,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jAcetone_CH3CO_CH3_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.323e-07 4.285e-07 ... nan</div><input id='attrs-39dd6dc0-2f2f-4dcb-96f8-50eeab24940b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-39dd6dc0-2f2f-4dcb-96f8-50eeab24940b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-749d2acd-b184-4d86-8295-aa05c78c28eb' class='xr-var-data-in' type='checkbox'><label for='data-749d2acd-b184-4d86-8295-aa05c78c28eb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([4.323e-07, 4.285e-07, 4.331e-07, ..., 1.425e-07, 1.506e-07,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jMEK_CH3CO_CH2CH3_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.166e-06 4.134e-06 ... nan</div><input id='attrs-953648e6-a13d-403e-a7db-f534b4a04857' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-953648e6-a13d-403e-a7db-f534b4a04857' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-175fcbd6-87c4-40d9-8c17-5b35846fd970' class='xr-var-data-in' type='checkbox'><label for='data-175fcbd6-87c4-40d9-8c17-5b35846fd970' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([4.166e-06, 4.134e-06, 4.163e-06, ..., 1.685e-06, 1.796e-06,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jHydroxyacetone_CH3CO_CH3O_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7.799e-07 7.74e-07 ... nan</div><input id='attrs-5cbbe825-334f-4925-92ec-e93511f56de5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5cbbe825-334f-4925-92ec-e93511f56de5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b600b078-ab64-4445-b011-c93e40398436' class='xr-var-data-in' type='checkbox'><label for='data-b600b078-ab64-4445-b011-c93e40398436' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([7.799e-07, 7.740e-07, 7.792e-07, ..., 3.178e-07, 3.396e-07,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jHydroxyacetone_CH3COO_CH3_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7.799e-07 7.74e-07 ... nan</div><input id='attrs-6426c326-47c2-4857-8478-fe7a3f07c712' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6426c326-47c2-4857-8478-fe7a3f07c712' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a78fd575-a6c3-48fa-a5ba-08002148079c' class='xr-var-data-in' type='checkbox'><label for='data-a78fd575-a6c3-48fa-a5ba-08002148079c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([7.799e-07, 7.740e-07, 7.792e-07, ..., 3.178e-07, 3.396e-07,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jCHOCHO_HCO_HCO_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.891e-05 6.819e-05 ... nan</div><input id='attrs-22e4d57e-e8e4-479f-8002-c477d88ade64' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-22e4d57e-e8e4-479f-8002-c477d88ade64' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2441f64e-d29a-4274-a8f0-3f53d831e68e' class='xr-var-data-in' type='checkbox'><label for='data-2441f64e-d29a-4274-a8f0-3f53d831e68e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([6.891e-05, 6.819e-05, 6.883e-05, ..., 3.677e-05, 4.166e-05,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jCHOCHO_H2_2CO_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.424e-05 1.413e-05 ... nan</div><input id='attrs-075ea4e1-1be5-4e9b-946c-e2f86159d557' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-075ea4e1-1be5-4e9b-946c-e2f86159d557' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bfa0999b-7a2a-4113-bdfc-4613dcbfef02' class='xr-var-data-in' type='checkbox'><label for='data-bfa0999b-7a2a-4113-bdfc-4613dcbfef02' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([1.424e-05, 1.413e-05, 1.423e-05, ..., 6.546e-06, 7.050e-06,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jCHOCHO_CH2O_CO_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.589e-05 2.569e-05 ... nan</div><input id='attrs-cfde9bc6-3c55-4ef8-b15e-804f350fcd2b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cfde9bc6-3c55-4ef8-b15e-804f350fcd2b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c2de72cb-a57a-461e-926d-6dcd682505e7' class='xr-var-data-in' type='checkbox'><label for='data-c2de72cb-a57a-461e-926d-6dcd682505e7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([2.589e-05, 2.569e-05, 2.587e-05, ..., 1.221e-05, 1.326e-05,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jCH3COCHO_CH3CO_HCO_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0001271 0.0001259 ... nan</div><input id='attrs-9ec7716d-c1c2-46ef-8c19-d6fbb7689513' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9ec7716d-c1c2-46ef-8c19-d6fbb7689513' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7a53f73b-d328-4ea3-ab2c-d76191eeb83c' class='xr-var-data-in' type='checkbox'><label for='data-7a53f73b-d328-4ea3-ab2c-d76191eeb83c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([1.271e-04, 1.259e-04, 1.270e-04, ..., 6.751e-05, 7.577e-05,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>j23Butanedione_NoProductsSpecified_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0002895 0.000285 ... 0.00019 nan</div><input id='attrs-ec9300b8-03ab-4bf5-a829-40636ff77150' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ec9300b8-03ab-4bf5-a829-40636ff77150' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-04f84b79-18ca-497e-b9a4-414877f430ce' class='xr-var-data-in' type='checkbox'><label for='data-04f84b79-18ca-497e-b9a4-414877f430ce' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([0.0002895, 0.000285 , 0.000289 , ..., 0.0001602, 0.00019  ,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jCl2_Cl_Cl_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.002092 0.002073 ... 0.001228 nan</div><input id='attrs-6fcf0dcf-0e24-493f-8455-f32dd5126d36' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6fcf0dcf-0e24-493f-8455-f32dd5126d36' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8cbeec09-ad0e-4971-9b7a-8bc7e009ab36' class='xr-var-data-in' type='checkbox'><label for='data-8cbeec09-ad0e-4971-9b7a-8bc7e009ab36' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([0.0020922, 0.0020725, 0.0020899, ..., 0.0011021, 0.0012277,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jClO_Cl_O3P_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.399e-05 4.363e-05 ... nan</div><input id='attrs-5215a4e8-ff59-4bf6-b913-374c30b305c2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5215a4e8-ff59-4bf6-b913-374c30b305c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-97d40b59-2c18-4f65-a8de-15a3e7f9d224' class='xr-var-data-in' type='checkbox'><label for='data-97d40b59-2c18-4f65-a8de-15a3e7f9d224' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([4.399e-05, 4.363e-05, 4.399e-05, ..., 1.452e-05, 1.538e-05,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jClNO2_Cl_NO2_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.000309 0.0003065 ... nan</div><input id='attrs-179482f8-4d6a-4a24-95ba-c63c9b0190b7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-179482f8-4d6a-4a24-95ba-c63c9b0190b7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a482afa2-88e7-49de-8047-298d441e39ae' class='xr-var-data-in' type='checkbox'><label for='data-a482afa2-88e7-49de-8047-298d441e39ae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([0.000309 , 0.0003065, 0.0003087, ..., 0.0001521, 0.0001661,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jClONO_Cl_NO2_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.003614 0.003585 ... 0.001969 nan</div><input id='attrs-ddf5cbbc-482a-45c5-b8d8-e609d89c3f6b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ddf5cbbc-482a-45c5-b8d8-e609d89c3f6b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1fa13650-42d7-49aa-9fdb-d6ff81a701e7' class='xr-var-data-in' type='checkbox'><label for='data-1fa13650-42d7-49aa-9fdb-d6ff81a701e7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([0.0036141, 0.0035848, 0.0036104, ..., 0.0018037, 0.0019692,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jClONO2_Cl_NO3_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.815e-05 3.779e-05 ... 2.2e-05 nan</div><input id='attrs-68bc983c-80e6-436e-aeb2-1966bf640e71' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-68bc983c-80e6-436e-aeb2-1966bf640e71' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-accf89df-ab45-420d-bb5a-7453bb4a1a43' class='xr-var-data-in' type='checkbox'><label for='data-accf89df-ab45-420d-bb5a-7453bb4a1a43' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([3.815e-05, 3.779e-05, 3.814e-05, ..., 1.974e-05, 2.200e-05,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jClONO2_ClO_NO2_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7.316e-06 7.258e-06 ... nan</div><input id='attrs-16727398-138a-4987-b4be-d1be183adecf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-16727398-138a-4987-b4be-d1be183adecf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c9434c05-fdf7-4f30-a300-101e9992bb3a' class='xr-var-data-in' type='checkbox'><label for='data-c9434c05-fdf7-4f30-a300-101e9992bb3a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([7.316e-06, 7.258e-06, 7.316e-06, ..., 3.289e-06, 3.535e-06,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jBr2_Br_Br_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.03349 0.03285 ... 0.02259 nan</div><input id='attrs-9c21d6f5-52f4-4a03-9ca1-6e08a137bddd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9c21d6f5-52f4-4a03-9ca1-6e08a137bddd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-324c5310-7e38-41e1-a3e3-3f6ad6a81ee8' class='xr-var-data-in' type='checkbox'><label for='data-324c5310-7e38-41e1-a3e3-3f6ad6a81ee8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([0.033486, 0.032854, 0.033412, ..., 0.018528, 0.022593,      nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jBrO_Br_O_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.03219 0.03193 ... 0.01804 nan</div><input id='attrs-5e77fa6b-684c-4d3d-946a-18997bdf9e16' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5e77fa6b-684c-4d3d-946a-18997bdf9e16' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-66739453-09d5-4c1f-b716-ed93c18321ae' class='xr-var-data-in' type='checkbox'><label for='data-66739453-09d5-4c1f-b716-ed93c18321ae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([0.03219 , 0.03193 , 0.032157, ..., 0.016535, 0.018043,      nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jHOBr_OH_Br_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.002092 0.002066 ... 0.001299 nan</div><input id='attrs-980eb6da-f44f-4094-93ba-dec8d3907010' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-980eb6da-f44f-4094-93ba-dec8d3907010' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b462261f-dbdf-4d8d-8e01-9e7b4b7bd05c' class='xr-var-data-in' type='checkbox'><label for='data-b462261f-dbdf-4d8d-8e01-9e7b4b7bd05c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([0.0020924, 0.0020663, 0.0020894, ..., 0.0011279, 0.0012993,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jBrNO_Br_NO_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0222 0.02174 ... 0.01505 nan</div><input id='attrs-bfe5eeb8-23ac-4252-ac63-c1c68f8c7b20' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bfe5eeb8-23ac-4252-ac63-c1c68f8c7b20' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a91148e8-85a9-47e4-a455-17388b560451' class='xr-var-data-in' type='checkbox'><label for='data-a91148e8-85a9-47e4-a455-17388b560451' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([0.022203, 0.02174 , 0.022145, ..., 0.01218 , 0.015051,      nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jBrONO_Br_NO2_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.009858 0.00978 ... 0.005401 nan</div><input id='attrs-b3b0df73-aaaf-4121-8997-7cb39f5816d6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b3b0df73-aaaf-4121-8997-7cb39f5816d6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1ed9a6d3-8c2e-448b-8075-1f7e70bf46b2' class='xr-var-data-in' type='checkbox'><label for='data-1ed9a6d3-8c2e-448b-8075-1f7e70bf46b2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([0.0098584, 0.0097797, 0.0098482, ..., 0.0049654, 0.005401 ,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jBrONO_BrO_NO_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.009858 0.00978 ... 0.005401 nan</div><input id='attrs-1f964a45-2f85-4aaa-b934-0f5b84433a3e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1f964a45-2f85-4aaa-b934-0f5b84433a3e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cb52ec07-5acf-42c6-83a3-571f02c7df94' class='xr-var-data-in' type='checkbox'><label for='data-cb52ec07-5acf-42c6-83a3-571f02c7df94' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([0.0098584, 0.0097797, 0.0098482, ..., 0.0049654, 0.005401 ,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jBrNO2_Br_NO2_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.00453 0.004474 ... 0.002863 nan</div><input id='attrs-e57bc5c5-798e-40aa-8627-9bc185a7f43f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e57bc5c5-798e-40aa-8627-9bc185a7f43f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6d9d7b85-1ad8-4f81-807a-4395076929ce' class='xr-var-data-in' type='checkbox'><label for='data-6d9d7b85-1ad8-4f81-807a-4395076929ce' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([0.0045303, 0.0044741, 0.0045244, ..., 0.0024796, 0.0028632,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jBrONO2_BrO_NO2_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0001949 0.0001926 ... nan</div><input id='attrs-ffb7e03e-6200-4110-be9f-bc0457538312' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ffb7e03e-6200-4110-be9f-bc0457538312' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f0aed5d3-5deb-4aa0-9a5b-7b162d73f61b' class='xr-var-data-in' type='checkbox'><label for='data-f0aed5d3-5deb-4aa0-9a5b-7b162d73f61b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([0.0001949, 0.0001926, 0.0001946, ..., 0.0001038, 0.0001186,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jBrONO2_Br_NO3_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.001104 0.001091 ... 0.000672 nan</div><input id='attrs-a15124fb-4940-45b3-86ff-2740da1dba7d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a15124fb-4940-45b3-86ff-2740da1dba7d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1860e42d-76aa-4937-ba72-a589dd392361' class='xr-var-data-in' type='checkbox'><label for='data-1860e42d-76aa-4937-ba72-a589dd392361' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([0.0011043, 0.0010914, 0.0011029, ..., 0.0005882, 0.000672 ,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jBrCl_Br_Cl_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.01058 0.01042 ... 0.006883 nan</div><input id='attrs-3fe92a18-79b9-47c4-9ccf-c9b8c6350255' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3fe92a18-79b9-47c4-9ccf-c9b8c6350255' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d31b9875-8f14-43e3-973e-749fab3dcc7e' class='xr-var-data-in' type='checkbox'><label for='data-d31b9875-8f14-43e3-973e-749fab3dcc7e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([0.010576 , 0.010421 , 0.010559 , ..., 0.0058421, 0.0068835,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jCHBr3_NoProductsSpecified_CAFS_HALL</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.135e-06 1.127e-06 ... nan</div><input id='attrs-90bbab21-d7d2-4b9e-8e7e-a8366b2bc894' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-90bbab21-d7d2-4b9e-8e7e-a8366b2bc894' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f5999200-3f9c-4157-9c60-5c0acaacf7b1' class='xr-var-data-in' type='checkbox'><label for='data-f5999200-3f9c-4157-9c60-5c0acaacf7b1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>/s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([1.135e-06, 1.127e-06, 1.134e-06, ..., 4.338e-07, 4.630e-07,\n",
+       "             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>smoke_age_HOLMES</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-22190512-76b2-4f36-b66f-c82b3456c37f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-22190512-76b2-4f36-b66f-c82b3456c37f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f0854aea-5e71-451e-894a-6a4c33811fab' class='xr-var-data-in' type='checkbox'><label for='data-f0854aea-5e71-451e-894a-6a4c33811fab' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>smoke_age_corr_HOLMES</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-6dd2ae55-334c-4142-99c3-08f5f487c801' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6dd2ae55-334c-4142-99c3-08f5f487c801' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-821c0047-d925-4705-b7c2-02ab5dc7bc78' class='xr-var-data-in' type='checkbox'><label for='data-821c0047-d925-4705-b7c2-02ab5dc7bc78' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>smoke_age_rise_HOLMES</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-da447177-d0c0-4cf5-b688-d689d1be0936' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-da447177-d0c0-4cf5-b688-d689d1be0936' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c869f25a-567d-44b6-8c8f-f622cac95213' class='xr-var-data-in' type='checkbox'><label for='data-c869f25a-567d-44b6-8c8f-f622cac95213' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>s</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>smoke_rise_HOLMES</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-be9aa317-f703-4370-9b6c-225269a56d19' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-be9aa317-f703-4370-9b6c-225269a56d19' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d176ed8-5b3b-4dee-bbe6-651e2f4033e2' class='xr-var-data-in' type='checkbox'><label for='data-1d176ed8-5b3b-4dee-bbe6-651e2f4033e2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fire_distance_HOLMES</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-4cd0f49c-253e-44d6-b926-02f2ea22d89b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4cd0f49c-253e-44d6-b926-02f2ea22d89b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ccd2bf4f-d0f3-4b3a-85f0-077f4aff2559' class='xr-var-data-in' type='checkbox'><label for='data-ccd2bf4f-d0f3-4b3a-85f0-077f4aff2559' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>smoke_agemethod_HOLMES</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ed1ce422-0a72-4318-bddc-ed2f8bbfc8f3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ed1ce422-0a72-4318-bddc-ed2f8bbfc8f3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f4e71f4e-b9ac-4cdd-adbd-72a5393566e3' class='xr-var-data-in' type='checkbox'><label for='data-f4e71f4e-b9ac-4cdd-adbd-72a5393566e3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>none</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a40fe47c-782a-4a25-bedc-016940590fee' class='xr-section-summary-in' type='checkbox'  ><label for='section-a40fe47c-782a-4a25-bedc-016940590fee' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-e5d20420-cf8b-4109-b77b-93d231563f5d' class='xr-index-data-in' type='checkbox'/><label for='index-e5d20420-cf8b-4109-b77b-93d231563f5d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2019-09-05 17:36:25&#x27;, &#x27;2019-09-05 17:36:35&#x27;,\n",
+       "               &#x27;2019-09-05 17:36:45&#x27;, &#x27;2019-09-05 17:36:55&#x27;,\n",
+       "               &#x27;2019-09-05 17:37:05&#x27;, &#x27;2019-09-05 17:37:15&#x27;,\n",
+       "               &#x27;2019-09-05 17:37:25&#x27;, &#x27;2019-09-05 17:37:35&#x27;,\n",
+       "               &#x27;2019-09-05 17:37:45&#x27;, &#x27;2019-09-05 17:37:55&#x27;,\n",
+       "               ...\n",
+       "               &#x27;2019-09-05 23:09:15&#x27;, &#x27;2019-09-05 23:09:25&#x27;,\n",
+       "               &#x27;2019-09-05 23:09:35&#x27;, &#x27;2019-09-05 23:09:45&#x27;,\n",
+       "               &#x27;2019-09-05 23:09:55&#x27;, &#x27;2019-09-05 23:10:05&#x27;,\n",
+       "               &#x27;2019-09-05 23:10:15&#x27;, &#x27;2019-09-05 23:10:25&#x27;,\n",
+       "               &#x27;2019-09-05 23:10:35&#x27;, &#x27;2019-09-05 23:10:45&#x27;],\n",
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=2007, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a56ef97e-b047-43b1-9085-486aa2002ff3' class='xr-section-summary-in' type='checkbox'  ><label for='section-a56ef97e-b047-43b1-9085-486aa2002ff3' class='xr-section-summary' >Attributes: <span>(23)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>source :</span></dt><dd>Merged Flight#20190905, on the DC8 platform. Data is merged to 10.000000 seconds. This merge was created on the Custom Data Merging tool.</dd><dt><span>Date Revised :</span></dt><dd>2022-02-11 00:00:00</dd><dt><span>mission :</span></dt><dd>FIREXAQ</dd><dt><span>organization :</span></dt><dd>NASA Langley Research Center</dd><dt><span>PI :</span></dt><dd>Suborbital Science Data for Atmospheric Composition</dd><dt><span>PI_CONTACT_INFO :</span></dt><dd>gao.chen@nasa.gov, michael.shook@nasa.gov, ali.a.aknan@nasa.gov</dd><dt><span>PLATFORM :</span></dt><dd>DC8_AIRCRAFT</dd><dt><span>LOCATION :</span></dt><dd>Included in data records</dd><dt><span>ASSOCIATED_DATA :</span></dt><dd>See following PI data</dd><dt><span>INSTRUMENT_INFO :</span></dt><dd>Please see PI data files for instrument information.</dd><dt><span>DATA_INFO :</span></dt><dd>Please see PI data files for</dd><dt><span>UNCERTAINTY :</span></dt><dd>Please see PI data files for uncertainty information.</dd><dt><span>ULOD_FLAG :</span></dt><dd>-777777</dd><dt><span>ULOD_VALUE :</span></dt><dd>N/A</dd><dt><span>LLOD_FLAG :</span></dt><dd>-888888</dd><dt><span>LLOD_VALUE :</span></dt><dd>N/A</dd><dt><span>DM_CONTACT_INFO :</span></dt><dd>gao.chen@nasa.gov, michael.shook@nasa.gov, ali.a.aknan@nasa.gov</dd><dt><span>PROJECT_INFO :</span></dt><dd>FIREXAQ</dd><dt><span>STIPULATIONS_ON_USE :</span></dt><dd>N/A</dd><dt><span>OTHER_COMMENTS :</span></dt><dd>This merge was created using the SSD-AC online merge tool. Data merge methods are described here</dd><dt><span>REVISION :</span></dt><dd>R1</dd><dt><span>R1 :</span></dt><dd>File generated from data submitted before 2022, 2, 11, adding data from firexaq-NOAAPTR-Urban-VOCs-1Hz, except for two variables for consistency with other flights</dd><dt><span>R0 :</span></dt><dd>File was generated using the online merge tool.</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset>\n",
+       "Dimensions:                                       (time: 2007)\n",
+       "Coordinates:\n",
+       "  * time                                          (time) datetime64[ns] 2019-...\n",
+       "Data variables: (12/642)\n",
+       "    Time_Stop                                     (time) float64 6.34e+04 ......\n",
+       "    Day_Of_Year_YANG                              (time) float64 248.0 ... 248.0\n",
+       "    latitude                                      (time) float64 38.81 ... 34.63\n",
+       "    longitude                                     (time) float64 -97.65 ... -...\n",
+       "    altitude                                      (time) float64 383.7 ... 771.0\n",
+       "    HAE_GPS_Altitude_YANG                         (time) float64 356.1 ... 737.3\n",
+       "    ...                                            ...\n",
+       "    smoke_age_HOLMES                              (time) float64 nan nan ... nan\n",
+       "    smoke_age_corr_HOLMES                         (time) float64 nan nan ... nan\n",
+       "    smoke_age_rise_HOLMES                         (time) float64 nan nan ... nan\n",
+       "    smoke_rise_HOLMES                             (time) float64 nan nan ... nan\n",
+       "    fire_distance_HOLMES                          (time) float64 nan nan ... nan\n",
+       "    smoke_agemethod_HOLMES                        (time) float64 nan nan ... nan\n",
+       "Attributes: (12/23)\n",
+       "    source:               Merged Flight#20190905, on the DC8 platform. Data i...\n",
+       "    Date Revised:         2022-02-11 00:00:00\n",
+       "    mission:              FIREXAQ\n",
+       "    organization:         NASA Langley Research Center\n",
+       "    PI:                   Suborbital Science Data for Atmospheric Composition\n",
+       "    PI_CONTACT_INFO:      gao.chen@nasa.gov, michael.shook@nasa.gov, ali.a.ak...\n",
+       "    ...                   ...\n",
+       "    PROJECT_INFO:         FIREXAQ\n",
+       "    STIPULATIONS_ON_USE:  N/A\n",
+       "    OTHER_COMMENTS:       This merge was created using the SSD-AC online merg...\n",
+       "    REVISION:             R1\n",
+       "    R1:                   File generated from data submitted before 2022, 2, ...\n",
+       "    R0:                   File was generated using the online merge tool."
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#All the info in the observation class can also be called.\n",
+    "an.obs['firexaq'].obj"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "ee5603ed",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "After pairing:        Time_Stop  Day_Of_Year_YANG   latitude                time   longitude  \\\n",
+      "0       63435.0             248.0  38.787221 2019-09-05 17:37:05  -97.645872   \n",
+      "1       63445.0             248.0  38.780171 2019-09-05 17:37:15  -97.645962   \n",
+      "2       63455.0             248.0  38.773174 2019-09-05 17:37:25  -97.645841   \n",
+      "3       63465.0             248.0  38.766109 2019-09-05 17:37:35  -97.645365   \n",
+      "4       63475.0             248.0  38.758565 2019-09-05 17:37:45  -97.644594   \n",
+      "...         ...               ...        ...                 ...         ...   \n",
+      "1896    83375.0             248.0  34.643454 2019-09-05 23:09:25 -118.050811   \n",
+      "1897    83385.0             248.0  34.639363 2019-09-05 23:09:35 -118.057049   \n",
+      "1898    83395.0             248.0  34.635485 2019-09-05 23:09:45 -118.063092   \n",
+      "1899    83405.0             248.0  34.632022 2019-09-05 23:09:55 -118.068432   \n",
+      "1900    83415.0             248.0  34.629492 2019-09-05 23:10:05 -118.072328   \n",
+      "\n",
+      "      altitude  HAE_GPS_Altitude_YANG  Pressure_Altitude_YANG  \\\n",
+      "0        433.7                 408.24                  1299.9   \n",
+      "1        542.5                 516.71                  1639.3   \n",
+      "2        633.3                 607.64                  1922.5   \n",
+      "3        709.5                 682.62                  2159.5   \n",
+      "4        737.9                 709.75                  2255.5   \n",
+      "...        ...                    ...                     ...   \n",
+      "1896     815.8                 781.35                  2587.4   \n",
+      "1897     787.9                 753.85                  2497.8   \n",
+      "1898     768.3                 734.61                  2402.5   \n",
+      "1899     767.0                 733.25                  2375.3   \n",
+      "1900     767.8                 734.33                  2373.9   \n",
+      "\n",
+      "      Radar_Altitude_YANG  Ground_Speed_YANG  ...  smoke_age_HOLMES  \\\n",
+      "0                     NaN             79.590  ...               NaN   \n",
+      "1                     NaN             77.700  ...               NaN   \n",
+      "2                     NaN             77.693  ...               NaN   \n",
+      "3                     NaN             80.382  ...               NaN   \n",
+      "4                     NaN             88.198  ...               NaN   \n",
+      "...                   ...                ...  ...               ...   \n",
+      "1896               183.55             73.445  ...               NaN   \n",
+      "1897                85.95             72.264  ...               NaN   \n",
+      "1898                11.60             67.295  ...               NaN   \n",
+      "1899                 3.70             55.265  ...               NaN   \n",
+      "1900                 3.70             36.045  ...               NaN   \n",
+      "\n",
+      "      smoke_age_corr_HOLMES  smoke_age_rise_HOLMES  smoke_rise_HOLMES  \\\n",
+      "0                       NaN                    NaN                NaN   \n",
+      "1                       NaN                    NaN                NaN   \n",
+      "2                       NaN                    NaN                NaN   \n",
+      "3                       NaN                    NaN                NaN   \n",
+      "4                       NaN                    NaN                NaN   \n",
+      "...                     ...                    ...                ...   \n",
+      "1896                    NaN                    NaN                NaN   \n",
+      "1897                    NaN                    NaN                NaN   \n",
+      "1898                    NaN                    NaN                NaN   \n",
+      "1899                    NaN                    NaN                NaN   \n",
+      "1900                    NaN                    NaN                NaN   \n",
+      "\n",
+      "      fire_distance_HOLMES  smoke_agemethod_HOLMES       no2        no  \\\n",
+      "0                      NaN                     NaN  0.581870  0.113245   \n",
+      "1                      NaN                     NaN  0.565219  0.112117   \n",
+      "2                      NaN                     NaN  0.549419  0.111447   \n",
+      "3                      NaN                     NaN  0.538119  0.111126   \n",
+      "4                      NaN                     NaN  0.534296  0.111007   \n",
+      "...                    ...                     ...       ...       ...   \n",
+      "1896                   NaN                     NaN  1.392371  0.166001   \n",
+      "1897                   NaN                     NaN  1.414110  0.166990   \n",
+      "1898                   NaN                     NaN  1.444719  0.169195   \n",
+      "1899                   NaN                     NaN  1.571442  0.167163   \n",
+      "1900                   NaN                     NaN  1.573416  0.167174   \n",
+      "\n",
+      "              o3  temp_model  \n",
+      "0      64.124157  305.718749  \n",
+      "1      64.521806  304.802475  \n",
+      "2      64.797092  303.837403  \n",
+      "3      64.961243  303.095742  \n",
+      "4      65.017264  302.847365  \n",
+      "...          ...         ...  \n",
+      "1896   97.036180  306.471604  \n",
+      "1897   97.001166  306.799350  \n",
+      "1898   96.930754  307.123718  \n",
+      "1899  105.220034  306.475217  \n",
+      "1900  105.277787  306.476382  \n",
+      "\n",
+      "[1901 rows x 647 columns]\n",
+      "After pairing:        Time_Stop  Day_Of_Year_YANG   latitude                time   longitude  \\\n",
+      "0       63435.0             248.0  38.787221 2019-09-05 17:37:05  -97.645872   \n",
+      "1       63445.0             248.0  38.780171 2019-09-05 17:37:15  -97.645962   \n",
+      "2       63455.0             248.0  38.773174 2019-09-05 17:37:25  -97.645841   \n",
+      "3       63465.0             248.0  38.766109 2019-09-05 17:37:35  -97.645365   \n",
+      "4       63475.0             248.0  38.758565 2019-09-05 17:37:45  -97.644594   \n",
+      "...         ...               ...        ...                 ...         ...   \n",
+      "1896    83375.0             248.0  34.643454 2019-09-05 23:09:25 -118.050811   \n",
+      "1897    83385.0             248.0  34.639363 2019-09-05 23:09:35 -118.057049   \n",
+      "1898    83395.0             248.0  34.635485 2019-09-05 23:09:45 -118.063092   \n",
+      "1899    83405.0             248.0  34.632022 2019-09-05 23:09:55 -118.068432   \n",
+      "1900    83415.0             248.0  34.629492 2019-09-05 23:10:05 -118.072328   \n",
+      "\n",
+      "      altitude  HAE_GPS_Altitude_YANG  Pressure_Altitude_YANG  \\\n",
+      "0        433.7                 408.24                  1299.9   \n",
+      "1        542.5                 516.71                  1639.3   \n",
+      "2        633.3                 607.64                  1922.5   \n",
+      "3        709.5                 682.62                  2159.5   \n",
+      "4        737.9                 709.75                  2255.5   \n",
+      "...        ...                    ...                     ...   \n",
+      "1896     815.8                 781.35                  2587.4   \n",
+      "1897     787.9                 753.85                  2497.8   \n",
+      "1898     768.3                 734.61                  2402.5   \n",
+      "1899     767.0                 733.25                  2375.3   \n",
+      "1900     767.8                 734.33                  2373.9   \n",
+      "\n",
+      "      Radar_Altitude_YANG  Ground_Speed_YANG  ...  smoke_age_HOLMES  \\\n",
+      "0                     NaN             79.590  ...               NaN   \n",
+      "1                     NaN             77.700  ...               NaN   \n",
+      "2                     NaN             77.693  ...               NaN   \n",
+      "3                     NaN             80.382  ...               NaN   \n",
+      "4                     NaN             88.198  ...               NaN   \n",
+      "...                   ...                ...  ...               ...   \n",
+      "1896               183.55             73.445  ...               NaN   \n",
+      "1897                85.95             72.264  ...               NaN   \n",
+      "1898                11.60             67.295  ...               NaN   \n",
+      "1899                 3.70             55.265  ...               NaN   \n",
+      "1900                 3.70             36.045  ...               NaN   \n",
+      "\n",
+      "      smoke_age_corr_HOLMES  smoke_age_rise_HOLMES  smoke_rise_HOLMES  \\\n",
+      "0                       NaN                    NaN                NaN   \n",
+      "1                       NaN                    NaN                NaN   \n",
+      "2                       NaN                    NaN                NaN   \n",
+      "3                       NaN                    NaN                NaN   \n",
+      "4                       NaN                    NaN                NaN   \n",
+      "...                     ...                    ...                ...   \n",
+      "1896                    NaN                    NaN                NaN   \n",
+      "1897                    NaN                    NaN                NaN   \n",
+      "1898                    NaN                    NaN                NaN   \n",
+      "1899                    NaN                    NaN                NaN   \n",
+      "1900                    NaN                    NaN                NaN   \n",
+      "\n",
+      "      fire_distance_HOLMES  smoke_agemethod_HOLMES       no2        no  \\\n",
+      "0                      NaN                     NaN  1.163741  0.226490   \n",
+      "1                      NaN                     NaN  1.130437  0.224235   \n",
+      "2                      NaN                     NaN  1.098838  0.222895   \n",
+      "3                      NaN                     NaN  1.076239  0.222252   \n",
+      "4                      NaN                     NaN  1.068592  0.222014   \n",
+      "...                    ...                     ...       ...       ...   \n",
+      "1896                   NaN                     NaN  2.784742  0.332001   \n",
+      "1897                   NaN                     NaN  2.828220  0.333980   \n",
+      "1898                   NaN                     NaN  2.889438  0.338391   \n",
+      "1899                   NaN                     NaN  3.142884  0.334325   \n",
+      "1900                   NaN                     NaN  3.146832  0.334348   \n",
+      "\n",
+      "              o3  temp_model  \n",
+      "0     128.248315  305.718749  \n",
+      "1     129.043612  304.802475  \n",
+      "2     129.594184  303.837403  \n",
+      "3     129.922486  303.095742  \n",
+      "4     130.034528  302.847365  \n",
+      "...          ...         ...  \n",
+      "1896  194.072360  306.471604  \n",
+      "1897  194.002332  306.799350  \n",
+      "1898  193.861507  307.123718  \n",
+      "1899  210.440068  306.475217  \n",
+      "1900  210.555573  306.476382  \n",
+      "\n",
+      "[1901 rows x 647 columns]\n"
+     ]
+    }
+   ],
+   "source": [
+    "#This just pairs the data\n",
+    "an.pair_data()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "57abb3af-c2e2-43d2-8822-d07c7e2ae555",
+   "metadata": {},
+   "outputs": [
+    {
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+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: '►';\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: '▼';\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
+       "Dimensions:                                       (time: 1901, x: 1)\n",
+       "Coordinates:\n",
+       "  * time                                          (time) datetime64[ns] 2019-...\n",
+       "Dimensions without coordinates: x\n",
+       "Data variables: (12/646)\n",
+       "    Time_Stop                                     (time, x) float64 6.344e+04...\n",
+       "    Day_Of_Year_YANG                              (time, x) float64 248.0 ......\n",
+       "    latitude                                      (time, x) float64 38.79 ......\n",
+       "    longitude                                     (time, x) float64 -97.65 .....\n",
+       "    altitude                                      (time, x) float64 433.7 ......\n",
+       "    HAE_GPS_Altitude_YANG                         (time, x) float64 408.2 ......\n",
+       "    ...                                            ...\n",
+       "    fire_distance_HOLMES                          (time, x) float64 nan ... nan\n",
+       "    smoke_agemethod_HOLMES                        (time, x) float64 nan ... nan\n",
+       "    no2                                           (time, x) float64 0.5819 .....\n",
+       "    no                                            (time, x) float64 0.1132 .....\n",
+       "    o3                                            (time, x) float64 64.12 ......\n",
+       "    temp_model                                    (time, x) float64 305.7 ......</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-f65d1eae-9ccb-4dc4-8204-d6a9cb2b0f36' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f65d1eae-9ccb-4dc4-8204-d6a9cb2b0f36' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1901</li><li><span>x</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-77c0045a-d072-4c51-982a-23dceb43f525' class='xr-section-summary-in' type='checkbox'  checked><label for='section-77c0045a-d072-4c51-982a-23dceb43f525' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-09-05T17:37:05 ... 2019-09-...</div><input id='attrs-8005cef3-002b-4102-83f3-86dc6a616be9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8005cef3-002b-4102-83f3-86dc6a616be9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-90310397-3178-4246-945f-be98ed180290' class='xr-var-data-in' type='checkbox'><label for='data-90310397-3178-4246-945f-be98ed180290' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-09-05T17:37:05.000000000&#x27;, &#x27;2019-09-05T17:37:15.000000000&#x27;,\n",
+       "       &#x27;2019-09-05T17:37:25.000000000&#x27;, ..., &#x27;2019-09-05T23:09:45.000000000&#x27;,\n",
+       "       &#x27;2019-09-05T23:09:55.000000000&#x27;, &#x27;2019-09-05T23:10:05.000000000&#x27;],\n",
+       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-844c9043-2449-4aba-8e90-8daedad036eb' class='xr-section-summary-in' type='checkbox'  ><label for='section-844c9043-2449-4aba-8e90-8daedad036eb' class='xr-section-summary' >Data variables: <span>(646)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>Time_Stop</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.344e+04 6.344e+04 ... 8.342e+04</div><input id='attrs-291154e9-296e-4c19-b845-07ead6c1c19c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-291154e9-296e-4c19-b845-07ead6c1c19c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-48fb1865-fe75-48b3-94b7-6698ea5092ad' class='xr-var-data-in' type='checkbox'><label for='data-48fb1865-fe75-48b3-94b7-6698ea5092ad' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[63435.],\n",
+       "       [63445.],\n",
+       "       [63455.],\n",
+       "       ...,\n",
+       "       [83395.],\n",
+       "       [83405.],\n",
+       "       [83415.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Day_Of_Year_YANG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>248.0 248.0 248.0 ... 248.0 248.0</div><input id='attrs-9889fa63-4d06-41da-b15e-7f88216c436d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9889fa63-4d06-41da-b15e-7f88216c436d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-beac7820-1680-45d9-8592-5f62b62f2446' class='xr-var-data-in' type='checkbox'><label for='data-beac7820-1680-45d9-8592-5f62b62f2446' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[248.],\n",
+       "       [248.],\n",
+       "       [248.],\n",
+       "       ...,\n",
+       "       [248.],\n",
+       "       [248.],\n",
+       "       [248.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>38.79 38.78 38.77 ... 34.63 34.63</div><input id='attrs-78424a7e-8483-45a4-8d5f-c5f754ac3914' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-78424a7e-8483-45a4-8d5f-c5f754ac3914' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c5e84db1-8bcb-472c-9453-3729d6811a60' class='xr-var-data-in' type='checkbox'><label for='data-c5e84db1-8bcb-472c-9453-3729d6811a60' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[38.787221],\n",
+       "       [38.780171],\n",
+       "       [38.773174],\n",
+       "       ...,\n",
+       "       [34.635485],\n",
+       "       [34.632022],\n",
+       "       [34.629492]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-97.65 -97.65 ... -118.1 -118.1</div><input id='attrs-f162b063-667a-4bd5-b288-50132bbd13b7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f162b063-667a-4bd5-b288-50132bbd13b7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f3a2faa5-2500-4e84-bf23-66258137c163' class='xr-var-data-in' type='checkbox'><label for='data-f3a2faa5-2500-4e84-bf23-66258137c163' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ -97.645872],\n",
+       "       [ -97.645962],\n",
+       "       [ -97.645841],\n",
+       "       ...,\n",
+       "       [-118.063092],\n",
+       "       [-118.068432],\n",
+       "       [-118.072328]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>altitude</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>433.7 542.5 633.3 ... 767.0 767.8</div><input id='attrs-5364c8d3-b61b-427e-9b82-925b3fb17bd4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5364c8d3-b61b-427e-9b82-925b3fb17bd4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5bc534b7-47cd-4f8a-9667-adeaff5e3298' class='xr-var-data-in' type='checkbox'><label for='data-5bc534b7-47cd-4f8a-9667-adeaff5e3298' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[433.7],\n",
+       "       [542.5],\n",
+       "       [633.3],\n",
+       "       ...,\n",
+       "       [768.3],\n",
+       "       [767. ],\n",
+       "       [767.8]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HAE_GPS_Altitude_YANG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>408.2 516.7 607.6 ... 733.2 734.3</div><input id='attrs-ea07d54a-d8e3-4d66-9f5e-b2c109f5df8f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ea07d54a-d8e3-4d66-9f5e-b2c109f5df8f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b55fe40-656c-4131-89aa-c5f39471a998' class='xr-var-data-in' type='checkbox'><label for='data-9b55fe40-656c-4131-89aa-c5f39471a998' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[408.24],\n",
+       "       [516.71],\n",
+       "       [607.64],\n",
+       "       ...,\n",
+       "       [734.61],\n",
+       "       [733.25],\n",
+       "       [734.33]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Pressure_Altitude_YANG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.3e+03 1.639e+03 ... 2.374e+03</div><input id='attrs-eea55cec-9ebd-4b43-822c-85e958af2a8c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-eea55cec-9ebd-4b43-822c-85e958af2a8c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-278a66bf-01c9-48d0-b1ec-3fba65f64f38' class='xr-var-data-in' type='checkbox'><label for='data-278a66bf-01c9-48d0-b1ec-3fba65f64f38' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[1299.9],\n",
+       "       [1639.3],\n",
+       "       [1922.5],\n",
+       "       ...,\n",
+       "       [2402.5],\n",
+       "       [2375.3],\n",
+       "       [2373.9]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Radar_Altitude_YANG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... 11.6 3.7 3.7</div><input id='attrs-84e8e614-7c42-4290-836b-44310e28ca02' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-84e8e614-7c42-4290-836b-44310e28ca02' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3188f13e-cf19-4f67-9621-6d3889c8bdc1' class='xr-var-data-in' type='checkbox'><label for='data-3188f13e-cf19-4f67-9621-6d3889c8bdc1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan],\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       ...,\n",
+       "       [11.6],\n",
+       "       [ 3.7],\n",
+       "       [ 3.7]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Ground_Speed_YANG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>79.59 77.7 77.69 ... 55.27 36.05</div><input id='attrs-743ac733-d26f-493f-a749-36e0a1ac7da4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-743ac733-d26f-493f-a749-36e0a1ac7da4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fc4ca652-a780-4311-8028-344836f59997' class='xr-var-data-in' type='checkbox'><label for='data-fc4ca652-a780-4311-8028-344836f59997' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[79.59 ],\n",
+       "       [77.7  ],\n",
+       "       [77.693],\n",
+       "       ...,\n",
+       "       [67.295],\n",
+       "       [55.265],\n",
+       "       [36.045]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>True_Air_Speed_YANG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>172.7 170.1 ... 118.5 -8.889e+05</div><input id='attrs-1f9b2ea1-68ca-4904-9d55-79c8dafc367d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1f9b2ea1-68ca-4904-9d55-79c8dafc367d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0763c6e1-ff93-419a-8c29-703c8ac3bdbf' class='xr-var-data-in' type='checkbox'><label for='data-0763c6e1-ff93-419a-8c29-703c8ac3bdbf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 1.726640e+02],\n",
+       "       [ 1.701140e+02],\n",
+       "       [ 1.712690e+02],\n",
+       "       ...,\n",
+       "       [ 1.410240e+02],\n",
+       "       [ 1.184688e+02],\n",
+       "       [-8.888880e+05]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Indicated_Air_Speed_YANG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>164.0 160.8 161.2 ... 104.7 69.57</div><input id='attrs-21586618-860d-4625-88be-42ecff7ce0c1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-21586618-860d-4625-88be-42ecff7ce0c1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-90db48ea-069d-4dea-98a8-e207bf1258d4' class='xr-var-data-in' type='checkbox'><label for='data-90db48ea-069d-4dea-98a8-e207bf1258d4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[163.994],\n",
+       "       [160.768],\n",
+       "       [161.206],\n",
+       "       ...,\n",
+       "       [129.944],\n",
+       "       [104.713],\n",
+       "       [ 69.569]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Mach_Number_YANG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.254 0.2506 ... 0.1674 0.114</div><input id='attrs-ab82c99f-d5fd-41fa-be8c-9ac838c065c6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ab82c99f-d5fd-41fa-be8c-9ac838c065c6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5d34190a-358b-4a4f-8dff-a4397a3c041f' class='xr-var-data-in' type='checkbox'><label for='data-5d34190a-358b-4a4f-8dff-a4397a3c041f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.254 ],\n",
+       "       [0.2506],\n",
+       "       [0.2526],\n",
+       "       ...,\n",
+       "       [0.2063],\n",
+       "       [0.1674],\n",
+       "       [0.114 ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Vertical_Speed_YANG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9.73 9.61 8.81 ... -0.8 0.11 0.1</div><input id='attrs-c563ddbf-1e4a-4c52-8abb-012f4689d80b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c563ddbf-1e4a-4c52-8abb-012f4689d80b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9ea8a61a-77b5-40fa-8bd1-4d778b4e6088' class='xr-var-data-in' type='checkbox'><label for='data-9ea8a61a-77b5-40fa-8bd1-4d778b4e6088' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 9.73],\n",
+       "       [ 9.61],\n",
+       "       [ 8.81],\n",
+       "       ...,\n",
+       "       [-0.8 ],\n",
+       "       [ 0.11],\n",
+       "       [ 0.1 ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>True_Heading_YANG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>183.6 182.8 182.4 ... 231.8 231.7</div><input id='attrs-2dc0fdae-db5c-47fc-830f-7052d4908a2d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2dc0fdae-db5c-47fc-830f-7052d4908a2d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f5ba8075-36ab-418e-b0b5-6527553ed885' class='xr-var-data-in' type='checkbox'><label for='data-f5ba8075-36ab-418e-b0b5-6527553ed885' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[183.573],\n",
+       "       [182.85 ],\n",
+       "       [182.42 ],\n",
+       "       ...,\n",
+       "       [230.594],\n",
+       "       [231.83 ],\n",
+       "       [231.708]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Track_Angle_YANG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>180.3 180.3 178.1 ... 231.9 231.8</div><input id='attrs-d2fd4e4f-a7a3-4d41-b545-7657504ab525' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d2fd4e4f-a7a3-4d41-b545-7657504ab525' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-deb04db6-29b1-47d4-b7a7-2d25719eedb4' class='xr-var-data-in' type='checkbox'><label for='data-deb04db6-29b1-47d4-b7a7-2d25719eedb4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[180.314],\n",
+       "       [180.299],\n",
+       "       [178.085],\n",
+       "       ...,\n",
+       "       [231.964],\n",
+       "       [231.904],\n",
+       "       [231.834]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Drift_Angle_YANG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-3.26 -2.57 -4.34 ... 0.08 0.13</div><input id='attrs-8806da34-3a5e-423a-bf19-608b795f05cb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8806da34-3a5e-423a-bf19-608b795f05cb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-008fbee9-b3cf-43da-9e10-543eedc016d9' class='xr-var-data-in' type='checkbox'><label for='data-008fbee9-b3cf-43da-9e10-543eedc016d9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-3.26],\n",
+       "       [-2.57],\n",
+       "       [-4.34],\n",
+       "       ...,\n",
+       "       [ 1.37],\n",
+       "       [ 0.08],\n",
+       "       [ 0.13]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Pitch_Angle_YANG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>12.43 11.45 11.39 ... 359.7 359.5</div><input id='attrs-62db4e4f-499e-43ca-8e9f-ed5d706e95af' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-62db4e4f-499e-43ca-8e9f-ed5d706e95af' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-719f7444-d9e1-4434-8ada-1be74083be81' class='xr-var-data-in' type='checkbox'><label for='data-719f7444-d9e1-4434-8ada-1be74083be81' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 12.4252],\n",
+       "       [ 11.447 ],\n",
+       "       [ 11.394 ],\n",
+       "       ...,\n",
+       "       [  1.048 ],\n",
+       "       [359.672 ],\n",
+       "       [359.506 ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Roll_Angle_YANG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.451 358.5 357.6 ... 0.231 0.296</div><input id='attrs-a2645d4c-49e9-47b7-b88b-f109504f42be' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a2645d4c-49e9-47b7-b88b-f109504f42be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-93ca6472-7a30-4de1-8d52-599d6c4535aa' class='xr-var-data-in' type='checkbox'><label for='data-93ca6472-7a30-4de1-8d52-599d6c4535aa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[4.51010e-01],\n",
+       "       [3.58541e+02],\n",
+       "       [3.57554e+02],\n",
+       "       ...,\n",
+       "       [3.59500e+02],\n",
+       "       [2.31000e-01],\n",
+       "       [2.96000e-01]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Static_Air_Temp_YANG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>31.21 30.14 29.39 ... 35.29 35.12</div><input id='attrs-2a34b758-5a20-47e5-aaf9-a5b5bd282291' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2a34b758-5a20-47e5-aaf9-a5b5bd282291' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-073c792a-37ee-4a06-903c-35315c0d38af' class='xr-var-data-in' type='checkbox'><label for='data-073c792a-37ee-4a06-903c-35315c0d38af' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[31.211],\n",
+       "       [30.143],\n",
+       "       [29.389],\n",
+       "       ...,\n",
+       "       [34.628],\n",
+       "       [35.294],\n",
+       "       [35.125]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Potential_Temp_YANG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>307.4 307.4 307.5 ... 315.0 314.8</div><input id='attrs-af8f4a6e-6cca-4ccb-b702-7cd0db6be0a6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-af8f4a6e-6cca-4ccb-b702-7cd0db6be0a6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-82f87549-f0a1-42aa-b299-43f2f00842e7' class='xr-var-data-in' type='checkbox'><label for='data-82f87549-f0a1-42aa-b299-43f2f00842e7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[307.35],\n",
+       "       [307.35],\n",
+       "       [307.5 ],\n",
+       "       ...,\n",
+       "       [314.4 ],\n",
+       "       [314.97],\n",
+       "       [314.79]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Dew_Point_YANG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>19.49 19.15 18.45 ... 12.8 12.8</div><input id='attrs-8f91038f-665a-4aa9-96ae-9a2a77474154' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8f91038f-665a-4aa9-96ae-9a2a77474154' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-167c6d8c-c974-4261-961e-a121dd73d281' class='xr-var-data-in' type='checkbox'><label for='data-167c6d8c-c974-4261-961e-a121dd73d281' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[19.49],\n",
+       "       [19.15],\n",
+       "       [18.45],\n",
+       "       ...,\n",
+       "       [12.83],\n",
+       "       [12.8 ],\n",
+       "       [12.8 ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Total_Air_Temp_YANG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>35.15 33.97 33.25 ... 37.05 35.89</div><input id='attrs-82f7c317-d8b7-41d3-bcf7-6068989038b7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-82f7c317-d8b7-41d3-bcf7-6068989038b7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3d130b23-d65d-40e9-aa05-fc10868c8842' class='xr-var-data-in' type='checkbox'><label for='data-3d130b23-d65d-40e9-aa05-fc10868c8842' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[35.15],\n",
+       "       [33.97],\n",
+       "       [33.25],\n",
+       "       ...,\n",
+       "       [37.27],\n",
+       "       [37.05],\n",
+       "       [35.89]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>IR_Surf_Temp_YANG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>37.87 45.49 42.8 ... 32.63 32.7</div><input id='attrs-85ffd969-df5f-4619-a4a1-c877affc3821' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-85ffd969-df5f-4619-a4a1-c877affc3821' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-57b6874e-abd2-4e1e-9838-a3073db24c41' class='xr-var-data-in' type='checkbox'><label for='data-57b6874e-abd2-4e1e-9838-a3073db24c41' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[37.87],\n",
+       "       [45.49],\n",
+       "       [42.8 ],\n",
+       "       ...,\n",
+       "       [32.52],\n",
+       "       [32.63],\n",
+       "       [32.7 ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Static_Pressure_YANG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>966.6 954.7 944.8 ... 929.2 929.3</div><input id='attrs-68103ca7-c0a1-4bb5-a122-7caedb4e8276' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-68103ca7-c0a1-4bb5-a122-7caedb4e8276' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bde7a677-5ca9-4cfd-aeaf-0c447267fadf' class='xr-var-data-in' type='checkbox'><label for='data-bde7a677-5ca9-4cfd-aeaf-0c447267fadf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[966.553],\n",
+       "       [954.651],\n",
+       "       [944.811],\n",
+       "       ...,\n",
+       "       [928.317],\n",
+       "       [929.245],\n",
+       "       [929.292]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Cabin_Pressure_YANG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>980.5 982.6 982.5 ... 937.5 936.6</div><input id='attrs-540e46b5-bc51-43ea-ae63-b8aa6989269a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-540e46b5-bc51-43ea-ae63-b8aa6989269a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2c265167-911f-4537-a6d5-7a4e0be07360' class='xr-var-data-in' type='checkbox'><label for='data-2c265167-911f-4537-a6d5-7a4e0be07360' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[980.53],\n",
+       "       [982.59],\n",
+       "       [982.48],\n",
+       "       ...,\n",
+       "       [939.86],\n",
+       "       [937.48],\n",
+       "       [936.56]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Wind_Speed_YANG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>10.4 10.48 12.2 ... 5.61 3.69 2.9</div><input id='attrs-f445cfe8-2ef7-42fa-9819-c8241ccc2a76' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f445cfe8-2ef7-42fa-9819-c8241ccc2a76' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5f0b1fc9-9f39-4a96-95c5-92832cd09b3c' class='xr-var-data-in' type='checkbox'><label for='data-5f0b1fc9-9f39-4a96-95c5-92832cd09b3c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[10.4 ],\n",
+       "       [10.48],\n",
+       "       [12.2 ],\n",
+       "       ...,\n",
+       "       [ 5.61],\n",
+       "       [ 3.69],\n",
+       "       [ 2.9 ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Wind_Direction_YANG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>209.4 202.1 211.3 ... 230.7 230.2</div><input id='attrs-9de1355d-9777-450d-a5f6-c9774cfe255a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9de1355d-9777-450d-a5f6-c9774cfe255a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-637975ec-0953-4eb2-bd91-6a0326e1236d' class='xr-var-data-in' type='checkbox'><label for='data-637975ec-0953-4eb2-bd91-6a0326e1236d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[209.4112],\n",
+       "       [202.1319],\n",
+       "       [211.3383],\n",
+       "       ...,\n",
+       "       [213.1879],\n",
+       "       [230.7186],\n",
+       "       [230.1525]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Solar_Zenith_Angle_YANG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>34.21 34.2 34.2 ... 53.33 53.4 53.4</div><input id='attrs-a2b032be-d5f5-4e7d-8026-9dca75963ea1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a2b032be-d5f5-4e7d-8026-9dca75963ea1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-65687909-63a7-4b38-805f-5933ea6d3043' class='xr-var-data-in' type='checkbox'><label for='data-65687909-63a7-4b38-805f-5933ea6d3043' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[34.21],\n",
+       "       [34.2 ],\n",
+       "       [34.2 ],\n",
+       "       ...,\n",
+       "       [53.33],\n",
+       "       [53.4 ],\n",
+       "       [53.4 ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Aircraft_Sun_Elevation_YANG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>44.27 45.8 46.13 ... 36.8 36.98</div><input id='attrs-33089749-fcb2-4b7c-a86a-2f091adb43dd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-33089749-fcb2-4b7c-a86a-2f091adb43dd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9bf2fffb-e523-403c-ba43-2f4081b12045' class='xr-var-data-in' type='checkbox'><label for='data-9bf2fffb-e523-403c-ba43-2f4081b12045' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[44.27],\n",
+       "       [45.8 ],\n",
+       "       [46.13],\n",
+       "       ...,\n",
+       "       [35.31],\n",
+       "       [36.8 ],\n",
+       "       [36.98]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Sun_Azimuth_YANG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>156.0 156.1 156.1 ... 250.2 250.3</div><input id='attrs-adfbd182-4756-4502-873d-a0f589585c3e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-adfbd182-4756-4502-873d-a0f589585c3e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e5f90e59-e071-49eb-aa3c-938e73ae4b1f' class='xr-var-data-in' type='checkbox'><label for='data-e5f90e59-e071-49eb-aa3c-938e73ae4b1f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[156.  ],\n",
+       "       [156.09],\n",
+       "       [156.14],\n",
+       "       ...,\n",
+       "       [250.2 ],\n",
+       "       [250.2 ],\n",
+       "       [250.26]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Aircraft_Sun_Azimuth_YANG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-21.44 -19.0 -17.4 ... 18.65 18.81</div><input id='attrs-9d2e7087-b517-4c87-a295-44feba2b5872' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9d2e7087-b517-4c87-a295-44feba2b5872' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3b087073-887d-43ab-935d-aca846efe1cb' class='xr-var-data-in' type='checkbox'><label for='data-3b087073-887d-43ab-935d-aca846efe1cb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-21.44],\n",
+       "       [-19.  ],\n",
+       "       [-17.4 ],\n",
+       "       ...,\n",
+       "       [ 20.04],\n",
+       "       [ 18.65],\n",
+       "       [ 18.81]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Mixing_Ratio_YANG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>15.08 14.95 14.45 ... 10.15 10.17</div><input id='attrs-8d6077ef-2ce1-4fcc-ae4f-3d6d4e278cd9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8d6077ef-2ce1-4fcc-ae4f-3d6d4e278cd9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0cec56a4-6de2-4153-bd09-1a4408b2b29e' class='xr-var-data-in' type='checkbox'><label for='data-0cec56a4-6de2-4153-bd09-1a4408b2b29e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[15.082],\n",
+       "       [14.947],\n",
+       "       [14.446],\n",
+       "       ...,\n",
+       "       [10.18 ],\n",
+       "       [10.146],\n",
+       "       [10.174]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Part_Press_Water_Vapor_YANG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>22.88 22.4 21.45 ... 14.92 14.96</div><input id='attrs-cb345620-4296-4571-aed3-adfdf0f3807b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cb345620-4296-4571-aed3-adfdf0f3807b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5d5944f2-988c-44e5-bbc4-389e31277fab' class='xr-var-data-in' type='checkbox'><label for='data-5d5944f2-988c-44e5-bbc4-389e31277fab' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[22.884],\n",
+       "       [22.401],\n",
+       "       [21.448],\n",
+       "       ...,\n",
+       "       [14.951],\n",
+       "       [14.918],\n",
+       "       [14.959]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Sat_Vapor_Press_H2O_YANG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>45.91 43.2 41.36 ... 57.7 57.18</div><input id='attrs-662b3b7b-62c3-49ed-b42e-e9217f8cf984' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-662b3b7b-62c3-49ed-b42e-e9217f8cf984' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ff7f6119-cf80-4547-a958-47737838cb95' class='xr-var-data-in' type='checkbox'><label for='data-ff7f6119-cf80-4547-a958-47737838cb95' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[45.912],\n",
+       "       [43.196],\n",
+       "       [41.36 ],\n",
+       "       ...,\n",
+       "       [55.614],\n",
+       "       [57.704],\n",
+       "       [57.177]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Sat_Vapor_Press_Ice_YANG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>61.91 57.66 54.82 ... 80.83 79.97</div><input id='attrs-2418a91f-dcbe-404a-9491-d18511ae9708' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2418a91f-dcbe-404a-9491-d18511ae9708' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-93a644f3-e986-425a-bcbf-ee1e69ca6f01' class='xr-var-data-in' type='checkbox'><label for='data-93a644f3-e986-425a-bcbf-ee1e69ca6f01' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[61.907],\n",
+       "       [57.664],\n",
+       "       [54.819],\n",
+       "       ...,\n",
+       "       [77.414],\n",
+       "       [80.828],\n",
+       "       [79.973]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Relative_Humidity_YANG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>49.85 51.86 51.85 ... 25.86 26.19</div><input id='attrs-19f018ff-756f-4252-8d23-aa834ef42cc6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-19f018ff-756f-4252-8d23-aa834ef42cc6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b0c20ca-d3c1-48a8-969a-ca4c2c149d84' class='xr-var-data-in' type='checkbox'><label for='data-9b0c20ca-d3c1-48a8-969a-ca4c2c149d84' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[49.851],\n",
+       "       [51.863],\n",
+       "       [51.852],\n",
+       "       ...,\n",
+       "       [26.888],\n",
+       "       [25.859],\n",
+       "       [26.188]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure_obs</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9.628e+04 9.54e+04 ... 9.296e+04</div><input id='attrs-45a90235-c0d5-411a-979a-853cafd722ee' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-45a90235-c0d5-411a-979a-853cafd722ee' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-30b6aa18-dd20-4995-ba61-224e7b697ed8' class='xr-var-data-in' type='checkbox'><label for='data-30b6aa18-dd20-4995-ba61-224e7b697ed8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[96276.56],\n",
+       "       [95398.09],\n",
+       "       [94417.4 ],\n",
+       "       ...,\n",
+       "       [92849.38],\n",
+       "       [92937.47],\n",
+       "       [92960.81]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>T_BUI</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>304.2 303.4 302.6 ... 308.6 308.7</div><input id='attrs-98066337-ec1c-4ff5-8422-6c705273f147' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-98066337-ec1c-4ff5-8422-6c705273f147' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1ea800a5-dd10-4698-912d-90371b8c3916' class='xr-var-data-in' type='checkbox'><label for='data-1ea800a5-dd10-4698-912d-90371b8c3916' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[304.1801],\n",
+       "       [303.3595],\n",
+       "       [302.6208],\n",
+       "       ...,\n",
+       "       [308.0099],\n",
+       "       [308.6421],\n",
+       "       [308.6696]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TAS_BUI</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>86.74 86.75 87.21 ... 57.34 40.55</div><input id='attrs-6194b48e-9f3e-4563-933a-44255c240479' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6194b48e-9f3e-4563-933a-44255c240479' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-22739379-b226-4ceb-9e00-f938a446be61' class='xr-var-data-in' type='checkbox'><label for='data-22739379-b226-4ceb-9e00-f938a446be61' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[86.743 ],\n",
+       "       [86.7483],\n",
+       "       [87.2067],\n",
+       "       ...,\n",
+       "       [71.5693],\n",
+       "       [57.3404],\n",
+       "       [40.5547]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>U_BUI</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.765 4.102 6.401 ... 1.274 0.4046</div><input id='attrs-7b25a5a2-be30-4c5b-a994-18a66950059a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7b25a5a2-be30-4c5b-a994-18a66950059a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f659fca6-ad66-4bb5-a2a3-2a1cdcd379a5' class='xr-var-data-in' type='checkbox'><label for='data-f659fca6-ad66-4bb5-a2a3-2a1cdcd379a5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[3.76513],\n",
+       "       [4.10215],\n",
+       "       [6.40135],\n",
+       "       ...,\n",
+       "       [1.56561],\n",
+       "       [1.27363],\n",
+       "       [0.40457]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>V_BUI</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7.427 8.468 ... 0.9356 -0.4536</div><input id='attrs-820def3e-862d-44a8-b34d-d7dad29ad10b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-820def3e-862d-44a8-b34d-d7dad29ad10b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4f183ffb-12fc-4a09-8ee1-ad22447bb517' class='xr-var-data-in' type='checkbox'><label for='data-4f183ffb-12fc-4a09-8ee1-ad22447bb517' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 7.42719],\n",
+       "       [ 8.46792],\n",
+       "       [ 9.05804],\n",
+       "       ...,\n",
+       "       [ 4.0826 ],\n",
+       "       [ 0.9356 ],\n",
+       "       [-0.45356]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>W_BUI</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.171 0.6296 0.82 ... 1.329 1.201</div><input id='attrs-b8e9b5b0-1f60-475d-9945-7a20d75407a6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b8e9b5b0-1f60-475d-9945-7a20d75407a6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8a32d678-ba09-4bc9-b146-3a4660de881b' class='xr-var-data-in' type='checkbox'><label for='data-8a32d678-ba09-4bc9-b146-3a4660de881b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[1.1715 ],\n",
+       "       [0.62961],\n",
+       "       [0.81996],\n",
+       "       ...,\n",
+       "       [1.25906],\n",
+       "       [1.3286 ],\n",
+       "       [1.20067]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TEDR_BUI</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-5.107 -6.045 ... -6.411 -6.121</div><input id='attrs-9ab5a593-90fa-4a71-973a-9ef9415bbe15' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9ab5a593-90fa-4a71-973a-9ef9415bbe15' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-913ae41b-17e0-46bd-9f6e-3a91ce2b598c' class='xr-var-data-in' type='checkbox'><label for='data-913ae41b-17e0-46bd-9f6e-3a91ce2b598c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-5.10672],\n",
+       "       [-6.04538],\n",
+       "       [-6.25195],\n",
+       "       ...,\n",
+       "       [-5.77378],\n",
+       "       [-6.41113],\n",
+       "       [-6.12108]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>REYN_BUI</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.698 5.733 5.809 ... 4.989 4.882</div><input id='attrs-7ea49696-3f2a-412d-8a5d-43387ec4a98c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7ea49696-3f2a-412d-8a5d-43387ec4a98c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-31079e01-480c-4a2d-9921-c223e1df5b26' class='xr-var-data-in' type='checkbox'><label for='data-31079e01-480c-4a2d-9921-c223e1df5b26' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[5.69776],\n",
+       "       [5.73257],\n",
+       "       [5.80907],\n",
+       "       ...,\n",
+       "       [5.37709],\n",
+       "       [4.9891 ],\n",
+       "       [4.88193]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>POT_BUI</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>307.5 307.5 307.6 ... 315.2 315.2</div><input id='attrs-6d6dc186-a29e-4390-9b6c-9fa6d693d60a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6d6dc186-a29e-4390-9b6c-9fa6d693d60a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-673542ca-f9b7-46d1-8697-e16e44dcaa79' class='xr-var-data-in' type='checkbox'><label for='data-673542ca-f9b7-46d1-8697-e16e44dcaa79' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[307.4951],\n",
+       "       [307.4717],\n",
+       "       [307.6294],\n",
+       "       ...,\n",
+       "       [314.6069],\n",
+       "       [315.1712],\n",
+       "       [315.1736]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ROLL_BUI</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.342 -0.8434 ... 0.3189 0.2941</div><input id='attrs-779693ce-d18c-44b2-b4d3-d30c7e1e5995' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-779693ce-d18c-44b2-b4d3-d30c7e1e5995' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-14f4318f-e275-471f-b9cd-0ebb3a7c3a81' class='xr-var-data-in' type='checkbox'><label for='data-14f4318f-e275-471f-b9cd-0ebb3a7c3a81' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 1.34175],\n",
+       "       [-0.84342],\n",
+       "       [-1.8231 ],\n",
+       "       ...,\n",
+       "       [-0.34101],\n",
+       "       [ 0.31894],\n",
+       "       [ 0.29414]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HDG_BUI</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>186.4 185.4 185.0 ... 234.3 234.0</div><input id='attrs-814bf94c-8882-4a46-8ed2-6be33c9d7f69' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-814bf94c-8882-4a46-8ed2-6be33c9d7f69' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9e2d723a-f3f2-4537-a55e-880c54a4c24f' class='xr-var-data-in' type='checkbox'><label for='data-9e2d723a-f3f2-4537-a55e-880c54a4c24f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[186.3995],\n",
+       "       [185.4014],\n",
+       "       [184.9756],\n",
+       "       ...,\n",
+       "       [233.0298],\n",
+       "       [234.2601],\n",
+       "       [234.0139]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PITCH_BUI</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>14.5 11.99 ... 0.1641 -0.02793</div><input id='attrs-6ccdaf6a-dfb4-409b-9e34-7830e33484b3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6ccdaf6a-dfb4-409b-9e34-7830e33484b3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-af463715-ea5e-40ba-945a-e7c3cccdf572' class='xr-var-data-in' type='checkbox'><label for='data-af463715-ea5e-40ba-945a-e7c3cccdf572' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[14.4996  ],\n",
+       "       [11.9857  ],\n",
+       "       [11.9777  ],\n",
+       "       ...,\n",
+       "       [ 1.56006 ],\n",
+       "       [ 0.16406 ],\n",
+       "       [-0.027929]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>YAW_BUI</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-2.938 -2.507 ... -1.088 0.2778</div><input id='attrs-aaccabd7-8d81-4fe1-aa69-ab8542eed21c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-aaccabd7-8d81-4fe1-aa69-ab8542eed21c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-750f52a0-c2b2-45b4-9ff0-dc9657660f5a' class='xr-var-data-in' type='checkbox'><label for='data-750f52a0-c2b2-45b4-9ff0-dc9657660f5a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-2.93768],\n",
+       "       [-2.50658],\n",
+       "       [-2.75549],\n",
+       "       ...,\n",
+       "       [-1.88989],\n",
+       "       [-1.08775],\n",
+       "       [ 0.27783]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>AOA_BUI</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.846 6.116 6.575 ... 2.052 2.903</div><input id='attrs-d760942f-6ec5-4e3c-b364-53e03eb4bd1f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d760942f-6ec5-4e3c-b364-53e03eb4bd1f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-521a6d70-dd1e-4a00-8952-41469b2c0084' class='xr-var-data-in' type='checkbox'><label for='data-521a6d70-dd1e-4a00-8952-41469b2c0084' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[6.84602],\n",
+       "       [6.1164 ],\n",
+       "       [6.57529],\n",
+       "       ...,\n",
+       "       [3.31335],\n",
+       "       [2.052  ],\n",
+       "       [2.90343]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Smoke_flag_SCHWARZ</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-14110182-20aa-4689-b89f-26f0e0c711b9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-14110182-20aa-4689-b89f-26f0e0c711b9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3a8f6c71-ca70-4a1a-82f6-ce3d6e3d1e25' class='xr-var-data-in' type='checkbox'><label for='data-3a8f6c71-ca70-4a1a-82f6-ce3d6e3d1e25' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transect_type_SCHWARZ</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-450729f4-4691-4fc9-ba04-ecdc64875841' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-450729f4-4691-4fc9-ba04-ecdc64875841' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1b16efc9-4173-425e-bdae-d3f15f5ee304' class='xr-var-data-in' type='checkbox'><label for='data-1b16efc9-4173-425e-bdae-d3f15f5ee304' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fire_id_SCHWARZ</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-9a2fc048-36cd-4ee6-9350-cefe2e565c54' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9a2fc048-36cd-4ee6-9350-cefe2e565c54' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6ee68e44-d806-4464-9fe6-877b332be5e8' class='xr-var-data-in' type='checkbox'><label for='data-6ee68e44-d806-4464-9fe6-877b332be5e8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Background_flag_SCHWARZ</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-8c96e132-11e5-4b84-8cf6-550fe3206caf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8c96e132-11e5-4b84-8cf6-550fe3206caf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-866b7bf5-c0c5-4a92-97df-657d63a7cf79' class='xr-var-data-in' type='checkbox'><label for='data-866b7bf5-c0c5-4a92-97df-657d63a7cf79' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transect_smoke_age_SCHWARZ</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-a2cde9bf-c1fb-4e59-874a-f26ba8fed59a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a2cde9bf-c1fb-4e59-874a-f26ba8fed59a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f70ffa1c-4e2b-4234-a5ac-aafad30e4ff7' class='xr-var-data-in' type='checkbox'><label for='data-f70ffa1c-4e2b-4234-a5ac-aafad30e4ff7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transect_smoke_MCE_SCHWARZ</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-d358484e-56ae-4f91-9bb1-b22be32c4328' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d358484e-56ae-4f91-9bb1-b22be32c4328' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-77cbea7b-6d2b-488e-90ac-643a7c894a4a' class='xr-var-data-in' type='checkbox'><label for='data-77cbea7b-6d2b-488e-90ac-643a7c894a4a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transect_number_SCHWARZ</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e35e4635-4b6b-4130-914e-69573de10369' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e35e4635-4b6b-4130-914e-69573de10369' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9e8ca147-0a84-4af5-8f30-c15b587459e3' class='xr-var-data-in' type='checkbox'><label for='data-9e8ca147-0a84-4af5-8f30-c15b587459e3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transect_plume_number_SCHWARZ</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-f7673db6-947b-488b-b357-a5a47cab3362' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f7673db6-947b-488b-b357-a5a47cab3362' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-746734aa-dd6c-4ec6-8b74-7d81fbadba25' class='xr-var-data-in' type='checkbox'><label for='data-746734aa-dd6c-4ec6-8b74-7d81fbadba25' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transect_mce_ODR_SCHWARZ</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-61e996ad-fa3f-4da9-b94f-8d96fd3af5bd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-61e996ad-fa3f-4da9-b94f-8d96fd3af5bd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b0bd19aa-f11b-4000-b64f-a74bfb344ed8' class='xr-var-data-in' type='checkbox'><label for='data-b0bd19aa-f11b-4000-b64f-a74bfb344ed8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transect_mce_odr_chisq_SCHWARZ</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-dfcc310c-18da-44a7-9583-150dc6554a76' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-dfcc310c-18da-44a7-9583-150dc6554a76' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-996f7ae2-cfed-4952-88cc-1fbe1f9c3fa5' class='xr-var-data-in' type='checkbox'><label for='data-996f7ae2-cfed-4952-88cc-1fbe1f9c3fa5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fire_distance_estimate_SCHWARZ</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-78eb33fa-1158-4471-ad06-758f9be761a2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-78eb33fa-1158-4471-ad06-758f9be761a2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-11d401e7-a03c-424c-8566-84173b281896' class='xr-var-data-in' type='checkbox'><label for='data-11d401e7-a03c-424c-8566-84173b281896' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>H2O_DLH_DISKIN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.004e+04 1.959e+04 ... nan nan</div><input id='attrs-061a5582-041a-44f4-b8e3-e837346f6f63' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-061a5582-041a-44f4-b8e3-e837346f6f63' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-92e366a0-79ac-44f3-8c62-0ddef81d642c' class='xr-var-data-in' type='checkbox'><label for='data-92e366a0-79ac-44f3-8c62-0ddef81d642c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[20040. ],\n",
+       "       [19593.3],\n",
+       "       [18589.7],\n",
+       "       ...,\n",
+       "       [13531.9],\n",
+       "       [    nan],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>RHi_DLH_DISKIN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-01b8fa64-a415-4b5d-acbc-81a235826aa5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-01b8fa64-a415-4b5d-acbc-81a235826aa5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b2b1611-324f-4593-aaf4-82f230d275ee' class='xr-var-data-in' type='checkbox'><label for='data-9b2b1611-324f-4593-aaf4-82f230d275ee' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>RHw_DLH_DISKIN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>41.86 43.37 42.48 ... 22.5 nan nan</div><input id='attrs-3298598f-37c2-4a26-b77a-351bb45436fc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3298598f-37c2-4a26-b77a-351bb45436fc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-62beb4e9-cb2f-4ea7-a0c5-2cbd0071329b' class='xr-var-data-in' type='checkbox'><label for='data-62beb4e9-cb2f-4ea7-a0c5-2cbd0071329b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[41.864 ],\n",
+       "       [43.37  ],\n",
+       "       [42.478 ],\n",
+       "       ...,\n",
+       "       [22.5043],\n",
+       "       [    nan],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>H2O_LGR_ppmv_PEISCHL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.172e+04 2.116e+04 ... nan nan</div><input id='attrs-e49f666a-82f6-4e0d-b2a3-a7cdcd792071' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e49f666a-82f6-4e0d-b2a3-a7cdcd792071' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-efcca3ea-8e75-4ad8-98e7-c9b6cfa7aa65' class='xr-var-data-in' type='checkbox'><label for='data-efcca3ea-8e75-4ad8-98e7-c9b6cfa7aa65' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[21718.3],\n",
+       "       [21164.2],\n",
+       "       [20294.4],\n",
+       "       ...,\n",
+       "       [14459.7],\n",
+       "       [    nan],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>O3_CL_RYERSON</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 48.22 ... 98.02 nan nan</div><input id='attrs-2710cb4c-5900-4ac9-b067-b0995d79caab' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2710cb4c-5900-4ac9-b067-b0995d79caab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ea8fd3cc-29cc-4b7a-96e3-232eb71a53a3' class='xr-var-data-in' type='checkbox'><label for='data-ea8fd3cc-29cc-4b7a-96e3-232eb71a53a3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[    nan],\n",
+       "       [    nan],\n",
+       "       [48.223 ],\n",
+       "       ...,\n",
+       "       [98.0217],\n",
+       "       [    nan],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NO_CL_RYERSON</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan 0.1586 0.1413 ... nan nan</div><input id='attrs-0949880e-6ce6-41b9-8187-6807e86dc043' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0949880e-6ce6-41b9-8187-6807e86dc043' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-08ca2c60-bf46-45d6-a7d1-0f7220515c08' class='xr-var-data-in' type='checkbox'><label for='data-08ca2c60-bf46-45d6-a7d1-0f7220515c08' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[    nan],\n",
+       "       [0.15863],\n",
+       "       [0.14129],\n",
+       "       ...,\n",
+       "       [0.13264],\n",
+       "       [    nan],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NO2_CL_RYERSON</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-c5557cd0-c36e-422f-bd61-381b1664bb9b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c5557cd0-c36e-422f-bd61-381b1664bb9b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-69b955b3-e377-4c70-b314-6e280a4d4f88' class='xr-var-data-in' type='checkbox'><label for='data-69b955b3-e377-4c70-b314-6e280a4d4f88' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NOy_CL_RYERSON</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan 1.74 1.679 ... 7.188 nan nan</div><input id='attrs-bfa280e7-b1c1-4359-a7cf-85fba133ca6e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bfa280e7-b1c1-4359-a7cf-85fba133ca6e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d6944b31-9bb8-4c70-91c0-58d1edca868f' class='xr-var-data-in' type='checkbox'><label for='data-d6944b31-9bb8-4c70-91c0-58d1edca868f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[    nan],\n",
+       "       [1.73959],\n",
+       "       [1.67937],\n",
+       "       ...,\n",
+       "       [7.18761],\n",
+       "       [    nan],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>O3_ROZE_HANISCO</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>53.52 54.13 54.83 ... nan nan nan</div><input id='attrs-d649bc42-a428-4ba7-ad31-e179cd844145' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d649bc42-a428-4ba7-ad31-e179cd844145' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-66d5127d-7f89-4f0b-92c3-0ced86e6a15f' class='xr-var-data-in' type='checkbox'><label for='data-66d5127d-7f89-4f0b-92c3-0ced86e6a15f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[53.525],\n",
+       "       [54.13 ],\n",
+       "       [54.83 ],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NO_LIF_ROLLINS</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... 136.3 nan nan</div><input id='attrs-766a6934-8c29-4d21-ae98-8591d97910b0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-766a6934-8c29-4d21-ae98-8591d97910b0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-09906382-aa8f-44ac-9b7b-fa177db8c541' class='xr-var-data-in' type='checkbox'><label for='data-09906382-aa8f-44ac-9b7b-fa177db8c541' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[     nan],\n",
+       "       [     nan],\n",
+       "       [     nan],\n",
+       "       ...,\n",
+       "       [136.3474],\n",
+       "       [     nan],\n",
+       "       [     nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NO2_ACES_WOMACK</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.286 0.292 0.26 ... 1.456 nan nan</div><input id='attrs-933be923-f752-4b18-9037-44c07ab238fe' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-933be923-f752-4b18-9037-44c07ab238fe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-709f3bbf-46a9-42bc-8ca2-0460f9462302' class='xr-var-data-in' type='checkbox'><label for='data-709f3bbf-46a9-42bc-8ca2-0460f9462302' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.286  ],\n",
+       "       [0.292  ],\n",
+       "       [0.26   ],\n",
+       "       ...,\n",
+       "       [1.45571],\n",
+       "       [    nan],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NO2_CANOE_STCLAIR</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-d422deae-5535-44f8-9d21-a35760ac4011' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d422deae-5535-44f8-9d21-a35760ac4011' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b526e419-bd84-4180-8bd4-76f703f289e9' class='xr-var-data-in' type='checkbox'><label for='data-b526e419-bd84-4180-8bd4-76f703f289e9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HNO2_NOAACIMS_VERES</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-7476ad4a-2006-44bb-b963-d9766e7fb352' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7476ad4a-2006-44bb-b963-d9766e7fb352' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4e391a3c-6085-4670-9de7-97b3bd737616' class='xr-var-data-in' type='checkbox'><label for='data-4e391a3c-6085-4670-9de7-97b3bd737616' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HNO2_ACES_WOMACK</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.294 0.293 0.191 ... nan nan</div><input id='attrs-7bbb56ac-3a60-438c-8184-e18861a90297' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7bbb56ac-3a60-438c-8184-e18861a90297' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bbd142bf-328b-4f9c-9669-679267271f18' class='xr-var-data-in' type='checkbox'><label for='data-bbd142bf-328b-4f9c-9669-679267271f18' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.294  ],\n",
+       "       [0.293  ],\n",
+       "       [0.191  ],\n",
+       "       ...,\n",
+       "       [0.40571],\n",
+       "       [    nan],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HONO_SAGA_DIBB</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>48.0 48.0 48.0 48.0 ... nan nan nan</div><input id='attrs-c8e11930-2979-4337-84fe-768b6f8fdc86' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c8e11930-2979-4337-84fe-768b6f8fdc86' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b7ec4f0d-a32c-4427-95b7-7b01fea48da8' class='xr-var-data-in' type='checkbox'><label for='data-b7ec4f0d-a32c-4427-95b7-7b01fea48da8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[48.],\n",
+       "       [48.],\n",
+       "       [48.],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HNO3+submicron-NO3_SAGA_DIBB</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>552.0 552.0 552.0 ... nan nan nan</div><input id='attrs-53412ebb-0e93-4d46-af65-05128f89cebd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-53412ebb-0e93-4d46-af65-05128f89cebd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-62060283-4d8b-44f2-ab31-52dfa568fb79' class='xr-var-data-in' type='checkbox'><label for='data-62060283-4d8b-44f2-ab31-52dfa568fb79' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[552.],\n",
+       "       [552.],\n",
+       "       [552.],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Sulfate_lt_1um_SAGA_DIBB</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.752 0.752 0.752 ... nan nan nan</div><input id='attrs-d7cc6446-3e4f-4016-90b9-132005621099' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d7cc6446-3e4f-4016-90b9-132005621099' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-94fae75c-f36a-497d-aab8-a8df90bc10e7' class='xr-var-data-in' type='checkbox'><label for='data-94fae75c-f36a-497d-aab8-a8df90bc10e7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.752],\n",
+       "       [0.752],\n",
+       "       [0.752],\n",
+       "       ...,\n",
+       "       [  nan],\n",
+       "       [  nan],\n",
+       "       [  nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HNO3-1Hz_CIT_WENNBERG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>175.6 188.5 195.4 ... nan nan nan</div><input id='attrs-3153ec9d-8410-485f-b8dc-091ecd9e7bb4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3153ec9d-8410-485f-b8dc-091ecd9e7bb4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ef0d015d-5681-4a2c-a7bd-dc3d89d1e21b' class='xr-var-data-in' type='checkbox'><label for='data-ef0d015d-5681-4a2c-a7bd-dc3d89d1e21b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[175.61],\n",
+       "       [188.52],\n",
+       "       [195.38],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PAN_GTCIMS_HUEY</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan ... 1.221e+03 nan nan</div><input id='attrs-e1174cf5-c579-45a0-88d1-fa54f6d1fc06' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e1174cf5-c579-45a0-88d1-fa54f6d1fc06' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c13f745-7bac-454b-835a-b35d79e2a18b' class='xr-var-data-in' type='checkbox'><label for='data-4c13f745-7bac-454b-835a-b35d79e2a18b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[    nan],\n",
+       "       [    nan],\n",
+       "       [    nan],\n",
+       "       ...,\n",
+       "       [1221.07],\n",
+       "       [    nan],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PPN_GTCIMS_HUEY</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... 91.68 nan nan</div><input id='attrs-f6db1b60-43e3-4e09-9197-a85ac4492c96' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f6db1b60-43e3-4e09-9197-a85ac4492c96' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b94521b6-d9b3-471f-9d33-b0b38a3a70d3' class='xr-var-data-in' type='checkbox'><label for='data-b94521b6-d9b3-471f-9d33-b0b38a3a70d3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[    nan],\n",
+       "       [    nan],\n",
+       "       [    nan],\n",
+       "       ...,\n",
+       "       [91.6839],\n",
+       "       [    nan],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>APAN_GTCIMS_HUEY</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... 12.43 nan nan</div><input id='attrs-366e240a-75f6-407e-99c8-cafa8882e6f3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-366e240a-75f6-407e-99c8-cafa8882e6f3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7c26542a-8be7-488e-acad-d4a23ff57226' class='xr-var-data-in' type='checkbox'><label for='data-7c26542a-8be7-488e-acad-d4a23ff57226' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[    nan],\n",
+       "       [    nan],\n",
+       "       [    nan],\n",
+       "       ...,\n",
+       "       [12.4295],\n",
+       "       [    nan],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PBN_GTCIMS_HUEY</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... 28.77 nan nan</div><input id='attrs-1e063500-4ba5-49f2-ac13-82555543368c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1e063500-4ba5-49f2-ac13-82555543368c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b0433b4-3663-47d5-b9b3-9d6aae54f84b' class='xr-var-data-in' type='checkbox'><label for='data-9b0433b4-3663-47d5-b9b3-9d6aae54f84b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[    nan],\n",
+       "       [    nan],\n",
+       "       [    nan],\n",
+       "       ...,\n",
+       "       [28.7747],\n",
+       "       [    nan],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NH3_UIOPTR_ppbV_WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-b6d87cd5-9e36-4277-a745-b4fc47008ae6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b6d87cd5-9e36-4277-a745-b4fc47008ae6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-35604949-3ab0-473e-9637-86ccbe8ea2c8' class='xr-var-data-in' type='checkbox'><label for='data-35604949-3ab0-473e-9637-86ccbe8ea2c8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>N2O5_NOAACIMS_VERES</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.2822 0.2383 0.1979 ... nan nan</div><input id='attrs-95439513-294e-4f57-9090-6a101dc3b00a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-95439513-294e-4f57-9090-6a101dc3b00a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d8d6c605-522d-45fb-8f80-9323c08c2401' class='xr-var-data-in' type='checkbox'><label for='data-d8d6c605-522d-45fb-8f80-9323c08c2401' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.2822],\n",
+       "       [0.2383],\n",
+       "       [0.1979],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>N2O_LGR_ppb_PEISCHL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>330.9 331.1 331.1 ... 334.0 nan nan</div><input id='attrs-131b0081-c86b-4c6b-9b04-017b5d4e55fb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-131b0081-c86b-4c6b-9b04-017b5d4e55fb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b6d56eba-29de-47ea-8b91-6c67f3dbd2ec' class='xr-var-data-in' type='checkbox'><label for='data-b6d56eba-29de-47ea-8b91-6c67f3dbd2ec' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[330.915 ],\n",
+       "       [331.0755],\n",
+       "       [331.0775],\n",
+       "       ...,\n",
+       "       [334.0006],\n",
+       "       [     nan],\n",
+       "       [     nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CO_DACOM_DISKIN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>142.0 140.6 140.0 ... 206.5 nan nan</div><input id='attrs-55f6ed40-fd51-45e2-ab97-d351cadf9c9c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-55f6ed40-fd51-45e2-ab97-d351cadf9c9c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8d5e14d5-2f37-45c2-92d0-7ed67080aed2' class='xr-var-data-in' type='checkbox'><label for='data-8d5e14d5-2f37-45c2-92d0-7ed67080aed2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[141.952 ],\n",
+       "       [140.626 ],\n",
+       "       [139.988 ],\n",
+       "       ...,\n",
+       "       [206.5129],\n",
+       "       [     nan],\n",
+       "       [     nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH4_DACOM_DISKIN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.037e+03 2.031e+03 ... nan nan</div><input id='attrs-ba7e37d5-46da-40d1-98c8-9e82a34d5ab4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ba7e37d5-46da-40d1-98c8-9e82a34d5ab4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cb6ce4bc-815c-4e13-a52b-ac29da00201f' class='xr-var-data-in' type='checkbox'><label for='data-cb6ce4bc-815c-4e13-a52b-ac29da00201f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[2037.21],\n",
+       "       [2030.52],\n",
+       "       [2026.98],\n",
+       "       ...,\n",
+       "       [1980.31],\n",
+       "       [    nan],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CO_LGR_ppb_PEISCHL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>138.4 137.8 139.8 ... 205.7 nan nan</div><input id='attrs-e326784f-9072-4967-b5ff-f394a23a53e1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e326784f-9072-4967-b5ff-f394a23a53e1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-02f5106d-7d5e-43b9-829b-441bfbbf4c16' class='xr-var-data-in' type='checkbox'><label for='data-02f5106d-7d5e-43b9-829b-441bfbbf4c16' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[138.37  ],\n",
+       "       [137.85  ],\n",
+       "       [139.75  ],\n",
+       "       ...,\n",
+       "       [205.7176],\n",
+       "       [     nan],\n",
+       "       [     nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CO2_7000_ppm_DISKIN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>406.2 406.7 407.6 ... 422.6 nan nan</div><input id='attrs-3b21a5e4-14b0-4d48-8953-9b174a584b91' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3b21a5e4-14b0-4d48-8953-9b174a584b91' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9af28609-bd4b-45e2-94dc-d878c95aff9f' class='xr-var-data-in' type='checkbox'><label for='data-9af28609-bd4b-45e2-94dc-d878c95aff9f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[406.207 ],\n",
+       "       [406.696 ],\n",
+       "       [407.604 ],\n",
+       "       ...,\n",
+       "       [422.6417],\n",
+       "       [     nan],\n",
+       "       [     nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>C2H6_CAMS_pptv_FRIED</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-beddac59-d367-4378-87c7-f42c52258e15' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-beddac59-d367-4378-87c7-f42c52258e15' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0d01d842-7a15-448c-89dd-82a0538b0f72' class='xr-var-data-in' type='checkbox'><label for='data-0d01d842-7a15-448c-89dd-82a0538b0f72' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH2O_CAMS_pptv_FRIED</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-f881cfcf-edf7-4670-994e-688061c99f79' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f881cfcf-edf7-4670-994e-688061c99f79' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-de972e3f-d8c2-4dc7-b7e1-86bb2478acba' class='xr-var-data-in' type='checkbox'><label for='data-de972e3f-d8c2-4dc7-b7e1-86bb2478acba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH2O_ISAF_HANISCO</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan ... 4.189e+03 nan nan</div><input id='attrs-c2d9a6ac-c254-4c88-b342-c6f331a2483e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c2d9a6ac-c254-4c88-b342-c6f331a2483e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c855b9b3-134d-4d22-a9ff-80386a464fa0' class='xr-var-data-in' type='checkbox'><label for='data-c855b9b3-134d-4d22-a9ff-80386a464fa0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[    nan],\n",
+       "       [    nan],\n",
+       "       [    nan],\n",
+       "       ...,\n",
+       "       [4188.67],\n",
+       "       [    nan],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH2O_UIOPTR_ppbV_WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-25ff81d3-ab99-4168-ac69-c9a672b07c0e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-25ff81d3-ab99-4168-ac69-c9a672b07c0e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-adfc404c-ea4e-454c-9f99-2017997cd74e' class='xr-var-data-in' type='checkbox'><label for='data-adfc404c-ea4e-454c-9f99-2017997cd74e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>OCS_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-0aa7ab14-065f-4d2e-ba2e-d7ca9addaa17' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0aa7ab14-065f-4d2e-ba2e-d7ca9addaa17' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7fc6d1ee-3151-4add-ab02-80d6be92293d' class='xr-var-data-in' type='checkbox'><label for='data-7fc6d1ee-3151-4add-ab02-80d6be92293d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>DMS_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-55eb2498-d845-4288-aa80-2be31a3ea8c3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-55eb2498-d845-4288-aa80-2be31a3ea8c3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-240545bf-50ac-4f3b-8306-8a6a7df1384b' class='xr-var-data-in' type='checkbox'><label for='data-240545bf-50ac-4f3b-8306-8a6a7df1384b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CFC12_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e18d6a7a-2011-4643-93d0-43684434a9fa' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e18d6a7a-2011-4643-93d0-43684434a9fa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-26a44bfd-386a-40a9-8bc2-9ddfd225508c' class='xr-var-data-in' type='checkbox'><label for='data-26a44bfd-386a-40a9-8bc2-9ddfd225508c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CFC11_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-54f2657d-1cb7-4270-88f5-1f1e5378e2a7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-54f2657d-1cb7-4270-88f5-1f1e5378e2a7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bd5eed4f-86c6-4458-b060-895e97ca8c82' class='xr-var-data-in' type='checkbox'><label for='data-bd5eed4f-86c6-4458-b060-895e97ca8c82' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CFC113_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-94b664fc-c9b1-4e34-942e-b93ae3a4bc44' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-94b664fc-c9b1-4e34-942e-b93ae3a4bc44' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9aecd152-8a6c-4019-8ff5-8de7b6b991f6' class='xr-var-data-in' type='checkbox'><label for='data-9aecd152-8a6c-4019-8ff5-8de7b6b991f6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CFC114_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-1b59ec94-c61b-4dec-95ac-5bfb1ebd4deb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1b59ec94-c61b-4dec-95ac-5bfb1ebd4deb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d36333e1-a3cb-4ab1-98c9-7edec3a39276' class='xr-var-data-in' type='checkbox'><label for='data-d36333e1-a3cb-4ab1-98c9-7edec3a39276' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HFC152a_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-358f571c-48b5-4f5b-9dca-6e9d0565bb8f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-358f571c-48b5-4f5b-9dca-6e9d0565bb8f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9a06a529-9107-4375-9d52-47b1dcfd24dc' class='xr-var-data-in' type='checkbox'><label for='data-9a06a529-9107-4375-9d52-47b1dcfd24dc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HFC134a_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-15ff1266-5b3f-47cf-8794-f8db6b94e446' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-15ff1266-5b3f-47cf-8794-f8db6b94e446' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d430ac04-3f42-4b4b-a469-f0405b870ec3' class='xr-var-data-in' type='checkbox'><label for='data-d430ac04-3f42-4b4b-a469-f0405b870ec3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HFC365mfc_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-2a2c1ee1-d43f-482e-8f81-1ea8fc7451e9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2a2c1ee1-d43f-482e-8f81-1ea8fc7451e9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a818d71d-684c-4b87-8a75-c46da2d8831f' class='xr-var-data-in' type='checkbox'><label for='data-a818d71d-684c-4b87-8a75-c46da2d8831f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HCFC22_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-3e72b1ab-be5f-495c-bca8-5b64526d37fc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3e72b1ab-be5f-495c-bca8-5b64526d37fc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-764d5398-ff05-43a4-b2a8-1fdff8855ab1' class='xr-var-data-in' type='checkbox'><label for='data-764d5398-ff05-43a4-b2a8-1fdff8855ab1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HCFC142b_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-68ca3ebf-16f4-4aff-96c5-e7ff58ae1843' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-68ca3ebf-16f4-4aff-96c5-e7ff58ae1843' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ed509bcb-fc93-463d-b4f1-7afbbf7a0d45' class='xr-var-data-in' type='checkbox'><label for='data-ed509bcb-fc93-463d-b4f1-7afbbf7a0d45' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HCFC141b_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-4d7a823e-7cf8-4117-8495-238aeff75fa3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4d7a823e-7cf8-4117-8495-238aeff75fa3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d45a31c1-c913-4750-8eae-84ee0ad68faf' class='xr-var-data-in' type='checkbox'><label for='data-d45a31c1-c913-4750-8eae-84ee0ad68faf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>H1301_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-48e19327-8d2e-40ed-8a5c-fe234e579138' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-48e19327-8d2e-40ed-8a5c-fe234e579138' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cbdc1fee-2f0e-43c7-944d-e4b23b2f6bae' class='xr-var-data-in' type='checkbox'><label for='data-cbdc1fee-2f0e-43c7-944d-e4b23b2f6bae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>H2402_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-4b42c7a3-1081-4c47-bb0f-f1507a7cc572' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4b42c7a3-1081-4c47-bb0f-f1507a7cc572' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0da5d411-8607-4bed-a580-ae47c2ce61db' class='xr-var-data-in' type='checkbox'><label for='data-0da5d411-8607-4bed-a580-ae47c2ce61db' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>H1211_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-641afc2f-13f2-4906-9eb2-0299d5cc4f9d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-641afc2f-13f2-4906-9eb2-0299d5cc4f9d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4364c087-86fc-461d-a125-9875be5180ec' class='xr-var-data-in' type='checkbox'><label for='data-4364c087-86fc-461d-a125-9875be5180ec' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH3CCl3_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-cccaab45-ad54-4d8e-bf67-1f4e70cb577c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cccaab45-ad54-4d8e-bf67-1f4e70cb577c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9e0dcadb-7e1a-44d3-9322-f83d4abed473' class='xr-var-data-in' type='checkbox'><label for='data-9e0dcadb-7e1a-44d3-9322-f83d4abed473' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CCl4_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-8817506b-f560-40fe-b178-e0ff7d8810c6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8817506b-f560-40fe-b178-e0ff7d8810c6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a0e1b5fe-8152-4e70-96f1-021831ba0b0a' class='xr-var-data-in' type='checkbox'><label for='data-a0e1b5fe-8152-4e70-96f1-021831ba0b0a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CHCl3_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-5cc5b7d0-254e-4fed-b98e-f0957aeb5797' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5cc5b7d0-254e-4fed-b98e-f0957aeb5797' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a7d13992-be4c-4091-9b06-4fadc418e49d' class='xr-var-data-in' type='checkbox'><label for='data-a7d13992-be4c-4091-9b06-4fadc418e49d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH2Cl2_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ed27b030-4fdf-40af-bf0b-6dd812135a80' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ed27b030-4fdf-40af-bf0b-6dd812135a80' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a680e883-884e-4fad-b41f-cf94cdfc616b' class='xr-var-data-in' type='checkbox'><label for='data-a680e883-884e-4fad-b41f-cf94cdfc616b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>C2HCl3_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-a5c518e5-33c2-4e68-867e-704b37483e81' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a5c518e5-33c2-4e68-867e-704b37483e81' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bedd3806-30f9-4dd4-8d8e-16f0a920cac7' class='xr-var-data-in' type='checkbox'><label for='data-bedd3806-30f9-4dd4-8d8e-16f0a920cac7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>C2Cl4_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-6566553a-a1ad-4472-bda9-7db47ca996b5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6566553a-a1ad-4472-bda9-7db47ca996b5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cd8acc14-5d1c-4e1a-ab3f-826794b9f29c' class='xr-var-data-in' type='checkbox'><label for='data-cd8acc14-5d1c-4e1a-ab3f-826794b9f29c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH3Cl_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-5bbe763e-2121-4fd4-82c6-7c8efbe642b1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5bbe763e-2121-4fd4-82c6-7c8efbe642b1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7c1a6323-4e6c-41da-b41b-65c676c4eed8' class='xr-var-data-in' type='checkbox'><label for='data-7c1a6323-4e6c-41da-b41b-65c676c4eed8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH3Br_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-0dd7e53a-ba78-4676-b619-a2389af33513' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0dd7e53a-ba78-4676-b619-a2389af33513' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4e83da35-9a99-4e9a-89f4-5db60880f228' class='xr-var-data-in' type='checkbox'><label for='data-4e83da35-9a99-4e9a-89f4-5db60880f228' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH3I_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-b323a223-ab80-4545-bdef-f5bbece5c5c0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b323a223-ab80-4545-bdef-f5bbece5c5c0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c2b661a2-1fe4-4b41-a801-596ba778278f' class='xr-var-data-in' type='checkbox'><label for='data-c2b661a2-1fe4-4b41-a801-596ba778278f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH2Br2_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-3b8fd32b-67df-40eb-81d4-ca0d614cdade' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3b8fd32b-67df-40eb-81d4-ca0d614cdade' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d3c0a786-f17b-414d-b3e5-2f223be4f75e' class='xr-var-data-in' type='checkbox'><label for='data-d3c0a786-f17b-414d-b3e5-2f223be4f75e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CHBrCl2_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ade2dcc8-e72d-46c8-852a-631bdfbb0018' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ade2dcc8-e72d-46c8-852a-631bdfbb0018' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-26d65f40-cb25-448d-8a29-4f841488cc06' class='xr-var-data-in' type='checkbox'><label for='data-26d65f40-cb25-448d-8a29-4f841488cc06' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CHBr2Cl_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-772a475d-bbf6-4333-a5ef-028444e290a8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-772a475d-bbf6-4333-a5ef-028444e290a8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-331c8246-8c8e-448e-84fe-d163dc094d7a' class='xr-var-data-in' type='checkbox'><label for='data-331c8246-8c8e-448e-84fe-d163dc094d7a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CHBr3_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e8473c9c-ff9f-40a4-8301-1efa52b54c64' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e8473c9c-ff9f-40a4-8301-1efa52b54c64' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-309a9cca-210d-42f6-8cbe-5a2582a03be5' class='xr-var-data-in' type='checkbox'><label for='data-309a9cca-210d-42f6-8cbe-5a2582a03be5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH2ClCH2Cl_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-514683fd-9391-4608-9ac4-e138c22ff08e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-514683fd-9391-4608-9ac4-e138c22ff08e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a720380-b860-4853-a865-76eb63a2104d' class='xr-var-data-in' type='checkbox'><label for='data-1a720380-b860-4853-a865-76eb63a2104d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>C2H5Cl_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-58187d3d-30fb-4f87-b859-a9ea2394c7fe' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-58187d3d-30fb-4f87-b859-a9ea2394c7fe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-840c3ece-777c-44c5-969c-0657b064e550' class='xr-var-data-in' type='checkbox'><label for='data-840c3ece-777c-44c5-969c-0657b064e550' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MeONO2_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-0a1c1f08-ef5b-4435-816d-2a8f7d064850' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0a1c1f08-ef5b-4435-816d-2a8f7d064850' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8097b67d-1557-4d0c-839c-dc573584d4b1' class='xr-var-data-in' type='checkbox'><label for='data-8097b67d-1557-4d0c-839c-dc573584d4b1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>EthONO2_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e8633dfa-e44c-4e21-8f23-c00eff6dc0ab' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e8633dfa-e44c-4e21-8f23-c00eff6dc0ab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-62e6742f-6644-4785-95c3-e01a75734739' class='xr-var-data-in' type='checkbox'><label for='data-62e6742f-6644-4785-95c3-e01a75734739' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>iPropONO2_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-724c47ae-8222-4fb4-a578-c7adc5dedb34' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-724c47ae-8222-4fb4-a578-c7adc5dedb34' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a42d13ec-7174-48ab-9914-408904eda291' class='xr-var-data-in' type='checkbox'><label for='data-a42d13ec-7174-48ab-9914-408904eda291' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nPropONO2_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-cf02de05-207c-47a1-a1a0-4da1cb781e47' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cf02de05-207c-47a1-a1a0-4da1cb781e47' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-688033cd-e695-4192-a3c9-de1c5fc8dafd' class='xr-var-data-in' type='checkbox'><label for='data-688033cd-e695-4192-a3c9-de1c5fc8dafd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x2ButONO2_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-a9894576-75fa-40ae-a882-37ca4209184f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a9894576-75fa-40ae-a882-37ca4209184f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bf64cdb5-e1c2-413b-a3cf-ecf7c3cea746' class='xr-var-data-in' type='checkbox'><label for='data-bf64cdb5-e1c2-413b-a3cf-ecf7c3cea746' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x3PentONO2_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-86984d77-6fb2-498a-a130-c9b72611a48d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-86984d77-6fb2-498a-a130-c9b72611a48d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2c67b088-bdf3-4c12-ba2a-5d97dd222400' class='xr-var-data-in' type='checkbox'><label for='data-2c67b088-bdf3-4c12-ba2a-5d97dd222400' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x2PentONO2_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-7e5b826a-9432-4c30-a15c-8cfcc8504406' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7e5b826a-9432-4c30-a15c-8cfcc8504406' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-51775925-bae7-4e2f-8ee1-4e19ed850b65' class='xr-var-data-in' type='checkbox'><label for='data-51775925-bae7-4e2f-8ee1-4e19ed850b65' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x3Me2ButONO2_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-99fe6bb4-a859-4a0f-a463-d87aa1c725db' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-99fe6bb4-a859-4a0f-a463-d87aa1c725db' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-794f13cd-71d9-4a7b-bbcb-07090b4e8b28' class='xr-var-data-in' type='checkbox'><label for='data-794f13cd-71d9-4a7b-bbcb-07090b4e8b28' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Ethane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ded7cb86-5bbf-4a7f-bd56-d7e7a9099d66' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ded7cb86-5bbf-4a7f-bd56-d7e7a9099d66' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b45cfbc6-8068-468a-a889-95e304f648da' class='xr-var-data-in' type='checkbox'><label for='data-b45cfbc6-8068-468a-a889-95e304f648da' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Ethene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-598410d9-c230-4c28-9654-fd22f3637b97' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-598410d9-c230-4c28-9654-fd22f3637b97' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7da63e55-20c3-4978-8ef8-b9ec4c2d9b42' class='xr-var-data-in' type='checkbox'><label for='data-7da63e55-20c3-4978-8ef8-b9ec4c2d9b42' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Ethyne_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-62ae625f-6289-4ca6-a0f9-2da9349b6797' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-62ae625f-6289-4ca6-a0f9-2da9349b6797' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aac5c117-99a5-442e-85a7-2c3af20754be' class='xr-var-data-in' type='checkbox'><label for='data-aac5c117-99a5-442e-85a7-2c3af20754be' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Propene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e8fd45b8-cd3c-4a6f-8f05-44617071adaa' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e8fd45b8-cd3c-4a6f-8f05-44617071adaa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7885ff2a-1c0d-48b0-8035-e95ea772f48b' class='xr-var-data-in' type='checkbox'><label for='data-7885ff2a-1c0d-48b0-8035-e95ea772f48b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Propane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-5645f57d-5362-417b-9bce-636397a7c204' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5645f57d-5362-417b-9bce-636397a7c204' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-91a409de-2128-48d8-9bd5-6aae33638512' class='xr-var-data-in' type='checkbox'><label for='data-91a409de-2128-48d8-9bd5-6aae33638512' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Propadiene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-47850a2d-b1bd-4946-89ce-acf601f0e1a1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-47850a2d-b1bd-4946-89ce-acf601f0e1a1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-11025051-48e6-48c9-b460-df41acd7c44a' class='xr-var-data-in' type='checkbox'><label for='data-11025051-48e6-48c9-b460-df41acd7c44a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Propyne_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-f5e76540-dccf-4e56-b459-29c1eba37422' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f5e76540-dccf-4e56-b459-29c1eba37422' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6286c8c4-f38e-4bc8-9bd8-fbf11606e989' class='xr-var-data-in' type='checkbox'><label for='data-6286c8c4-f38e-4bc8-9bd8-fbf11606e989' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>iButane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ec93f2a1-0116-4573-b2e1-cffc608021d3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ec93f2a1-0116-4573-b2e1-cffc608021d3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d6f94a61-e68c-4d9e-bb48-43230af7009e' class='xr-var-data-in' type='checkbox'><label for='data-d6f94a61-e68c-4d9e-bb48-43230af7009e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nButane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-0426014c-4213-45d5-9182-e226789af7a4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0426014c-4213-45d5-9182-e226789af7a4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a032f49b-351c-42e7-9bdb-f8d565044afa' class='xr-var-data-in' type='checkbox'><label for='data-a032f49b-351c-42e7-9bdb-f8d565044afa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x1Butene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-95525cbb-4b42-4a64-ad33-7f44e5b1534f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-95525cbb-4b42-4a64-ad33-7f44e5b1534f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bf78388b-40e2-42e0-b6c1-09024c20d2de' class='xr-var-data-in' type='checkbox'><label for='data-bf78388b-40e2-42e0-b6c1-09024c20d2de' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>iButene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-80a1b0aa-2c37-42ae-b871-f229a300ec19' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-80a1b0aa-2c37-42ae-b871-f229a300ec19' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-36356ad6-e365-4138-912c-06b16b9769ad' class='xr-var-data-in' type='checkbox'><label for='data-36356ad6-e365-4138-912c-06b16b9769ad' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>t2Butene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-838d5dde-1193-4473-a93c-ffb89afeda68' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-838d5dde-1193-4473-a93c-ffb89afeda68' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a246460e-bc30-4bcd-a17b-d8216bf1e29e' class='xr-var-data-in' type='checkbox'><label for='data-a246460e-bc30-4bcd-a17b-d8216bf1e29e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>c2Butene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-6e7e159f-ce76-4243-9c51-796957f6acf0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6e7e159f-ce76-4243-9c51-796957f6acf0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f5b46fce-8e58-4057-816a-49de6cb10dc3' class='xr-var-data-in' type='checkbox'><label for='data-f5b46fce-8e58-4057-816a-49de6cb10dc3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x13Butadiene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-6a2ec58f-ca88-4132-a9a7-211aa35b012c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6a2ec58f-ca88-4132-a9a7-211aa35b012c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-477bb714-8dc8-4af1-8d57-d254236b226f' class='xr-var-data-in' type='checkbox'><label for='data-477bb714-8dc8-4af1-8d57-d254236b226f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x12Butadiene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e729a7c3-f73a-499f-839b-caf266b493d0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e729a7c3-f73a-499f-839b-caf266b493d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e17a8b77-6677-4b69-80dd-9fa7ff4ee517' class='xr-var-data-in' type='checkbox'><label for='data-e17a8b77-6677-4b69-80dd-9fa7ff4ee517' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x1Buten3yne_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-95eb047c-4414-4a0c-897f-0a1efd1e228b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-95eb047c-4414-4a0c-897f-0a1efd1e228b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ced14adc-e61a-4d65-aea4-de83bfbd7914' class='xr-var-data-in' type='checkbox'><label for='data-ced14adc-e61a-4d65-aea4-de83bfbd7914' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x13Butadyine_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-3624edca-9f0c-4cbd-8797-955041c216b5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3624edca-9f0c-4cbd-8797-955041c216b5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5712ad69-a6e8-496f-9f59-601592cb2112' class='xr-var-data-in' type='checkbox'><label for='data-5712ad69-a6e8-496f-9f59-601592cb2112' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x1Butyne_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-70f12a47-872f-40af-8e5b-05e7283fedc7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-70f12a47-872f-40af-8e5b-05e7283fedc7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ee9600cd-919f-4379-839e-d3b4863ba0cc' class='xr-var-data-in' type='checkbox'><label for='data-ee9600cd-919f-4379-839e-d3b4863ba0cc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x2Butyne_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-7f25b4e6-2ed2-42d7-8107-7d34dabb872d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7f25b4e6-2ed2-42d7-8107-7d34dabb872d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-48e70a61-688c-40c1-8e6d-f4f6b0885d35' class='xr-var-data-in' type='checkbox'><label for='data-48e70a61-688c-40c1-8e6d-f4f6b0885d35' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>iPentane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-2b19a819-6dca-4fb5-bc66-4cbef346bea4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2b19a819-6dca-4fb5-bc66-4cbef346bea4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7a6f9b5a-e59e-4180-baa6-35ce8c8c0312' class='xr-var-data-in' type='checkbox'><label for='data-7a6f9b5a-e59e-4180-baa6-35ce8c8c0312' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nPentane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-f1555c0e-0afc-4e56-8195-798af943a3d5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f1555c0e-0afc-4e56-8195-798af943a3d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c6aaf16d-7702-4046-a4e7-18e94a1155cb' class='xr-var-data-in' type='checkbox'><label for='data-c6aaf16d-7702-4046-a4e7-18e94a1155cb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Isoprene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-cbe004a9-842e-4ce0-bbc8-65e50b51e472' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cbe004a9-842e-4ce0-bbc8-65e50b51e472' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d5ae6363-e106-4a49-8717-659c7defe47e' class='xr-var-data-in' type='checkbox'><label for='data-d5ae6363-e106-4a49-8717-659c7defe47e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x1Pentene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-d7da7281-6703-4d12-92e7-60ab36508f5f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d7da7281-6703-4d12-92e7-60ab36508f5f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6fbeb3d1-fca6-4c4d-b2f1-0e04652a7eec' class='xr-var-data-in' type='checkbox'><label for='data-6fbeb3d1-fca6-4c4d-b2f1-0e04652a7eec' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>t2Pentene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-44acf1a4-196e-4e81-84c6-bb37f10ad5ae' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-44acf1a4-196e-4e81-84c6-bb37f10ad5ae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e08951a3-8166-472e-92d2-73d5c7d8e35b' class='xr-var-data-in' type='checkbox'><label for='data-e08951a3-8166-472e-92d2-73d5c7d8e35b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>c2Pentene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-6c3e7c96-0eeb-419c-9af3-900eeb7a4b62' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6c3e7c96-0eeb-419c-9af3-900eeb7a4b62' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-afc0e3fa-5be0-43ea-8cd0-b1726df9a77b' class='xr-var-data-in' type='checkbox'><label for='data-afc0e3fa-5be0-43ea-8cd0-b1726df9a77b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>3Me1Butene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-61db5422-201e-4419-96ac-d83978398455' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-61db5422-201e-4419-96ac-d83978398455' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-23c9a32f-933a-4850-ab0c-052effdf8329' class='xr-var-data-in' type='checkbox'><label for='data-23c9a32f-933a-4850-ab0c-052effdf8329' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>2Me1Butene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-44f3b5a5-df20-43ff-8abb-b0d7d2bef546' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-44f3b5a5-df20-43ff-8abb-b0d7d2bef546' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dfdc1d2c-8132-45c0-977e-45d7d98d3daf' class='xr-var-data-in' type='checkbox'><label for='data-dfdc1d2c-8132-45c0-977e-45d7d98d3daf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>2Me2Butene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-3c17cc6a-8c1e-425c-a9ce-b0be9b7172e5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3c17cc6a-8c1e-425c-a9ce-b0be9b7172e5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ceb9b24-3520-4996-9f01-7c17316e47e0' class='xr-var-data-in' type='checkbox'><label for='data-5ceb9b24-3520-4996-9f01-7c17316e47e0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x13Pentadienes_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-177e6c5c-587b-414a-8354-b45f11f15cb3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-177e6c5c-587b-414a-8354-b45f11f15cb3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-27282422-a13a-4bda-b54e-e3fef029d2f9' class='xr-var-data-in' type='checkbox'><label for='data-27282422-a13a-4bda-b54e-e3fef029d2f9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x3Me1PenteneAnd4Me1Pentene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-96f8dc50-b058-450b-af78-08752e54a53b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-96f8dc50-b058-450b-af78-08752e54a53b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d501728c-43ff-49ff-9e4e-3517c3445059' class='xr-var-data-in' type='checkbox'><label for='data-d501728c-43ff-49ff-9e4e-3517c3445059' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x1Hexene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-8a40811e-304d-4922-87d9-03d6c0135fcb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8a40811e-304d-4922-87d9-03d6c0135fcb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4ff6e48d-7f9a-4c25-9b4c-ae4495600a93' class='xr-var-data-in' type='checkbox'><label for='data-4ff6e48d-7f9a-4c25-9b4c-ae4495600a93' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x1Heptene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-1d85d791-acb2-4be2-b524-fe51d1c8699d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1d85d791-acb2-4be2-b524-fe51d1c8699d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e88d939b-52e6-46fc-b061-6c48d9c604b1' class='xr-var-data-in' type='checkbox'><label for='data-e88d939b-52e6-46fc-b061-6c48d9c604b1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x1Octene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-95156122-ba0e-4e4f-95d1-57dc0e43db8a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-95156122-ba0e-4e4f-95d1-57dc0e43db8a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8d5d576a-0be7-48f7-b746-21d8926a7e55' class='xr-var-data-in' type='checkbox'><label for='data-8d5d576a-0be7-48f7-b746-21d8926a7e55' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x1Nonene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-82caa2af-5697-4bad-bd0c-f1c4bfc895fb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-82caa2af-5697-4bad-bd0c-f1c4bfc895fb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-21f8f72b-bbb9-4860-a9cc-686734dee8ba' class='xr-var-data-in' type='checkbox'><label for='data-21f8f72b-bbb9-4860-a9cc-686734dee8ba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x1Decene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-9fc62a2a-2c9f-46a6-aede-8c695a796990' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9fc62a2a-2c9f-46a6-aede-8c695a796990' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-201ebbdb-d8f6-4865-9678-1c7f3a3ede67' class='xr-var-data-in' type='checkbox'><label for='data-201ebbdb-d8f6-4865-9678-1c7f3a3ede67' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nHexane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-50839e87-182d-41fa-8118-69154e2e80e9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-50839e87-182d-41fa-8118-69154e2e80e9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9836331d-39ee-4f57-860a-1caf843d50cb' class='xr-var-data-in' type='checkbox'><label for='data-9836331d-39ee-4f57-860a-1caf843d50cb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nHeptane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-4f4fec03-b63b-43fb-90e3-7ed8be1ce5d5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4f4fec03-b63b-43fb-90e3-7ed8be1ce5d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6eb94208-8765-46dd-840e-5e3c009c8d7b' class='xr-var-data-in' type='checkbox'><label for='data-6eb94208-8765-46dd-840e-5e3c009c8d7b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nOctane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-5ce735c9-d014-4df4-8a78-e75323ca34a5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5ce735c9-d014-4df4-8a78-e75323ca34a5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-093206a0-bedd-4fd6-b9f6-d9e33ddc5d38' class='xr-var-data-in' type='checkbox'><label for='data-093206a0-bedd-4fd6-b9f6-d9e33ddc5d38' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nNonane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-25625de4-6ec1-4d5d-84f1-1231ea4cc100' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-25625de4-6ec1-4d5d-84f1-1231ea4cc100' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f54e299c-d629-4732-abb2-7530ff176c47' class='xr-var-data-in' type='checkbox'><label for='data-f54e299c-d629-4732-abb2-7530ff176c47' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nDecane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-93221a79-7256-40f1-ad2f-d4acf55d0fb2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-93221a79-7256-40f1-ad2f-d4acf55d0fb2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a45c3158-5747-4a22-b680-32142836be59' class='xr-var-data-in' type='checkbox'><label for='data-a45c3158-5747-4a22-b680-32142836be59' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nUndecane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ebe04bfd-ce8f-4bbf-a778-83dad33f7200' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ebe04bfd-ce8f-4bbf-a778-83dad33f7200' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ca82c222-d172-4dd7-8619-3125dc62a2bc' class='xr-var-data-in' type='checkbox'><label for='data-ca82c222-d172-4dd7-8619-3125dc62a2bc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x22Dimebutane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-de606f87-6385-4581-9842-6bb2540b542c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-de606f87-6385-4581-9842-6bb2540b542c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d7dd5af2-932d-4586-895d-e953239d8150' class='xr-var-data-in' type='checkbox'><label for='data-d7dd5af2-932d-4586-895d-e953239d8150' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x23Dimebutane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-b004a67b-168d-4e2b-b842-a617f11b9f3c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b004a67b-168d-4e2b-b842-a617f11b9f3c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3546304b-72ee-4c21-9e71-c8f86259893b' class='xr-var-data-in' type='checkbox'><label for='data-3546304b-72ee-4c21-9e71-c8f86259893b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x2MePentane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-01cdd983-7f2b-4557-8ac3-4c764e706fd9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-01cdd983-7f2b-4557-8ac3-4c764e706fd9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c1a64024-a6b7-4b30-84f1-d18092ac8e8c' class='xr-var-data-in' type='checkbox'><label for='data-c1a64024-a6b7-4b30-84f1-d18092ac8e8c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x3MePentane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-5b986b1e-b701-4632-8fcb-5368b9def818' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5b986b1e-b701-4632-8fcb-5368b9def818' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b755e901-b315-4867-b37b-e41b935741d0' class='xr-var-data-in' type='checkbox'><label for='data-b755e901-b315-4867-b37b-e41b935741d0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x2MeHexane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-264e35c0-b025-432f-be9f-88e9c75b275c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-264e35c0-b025-432f-be9f-88e9c75b275c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-17e13c3e-7f81-46dc-b835-fdcec0f043c7' class='xr-var-data-in' type='checkbox'><label for='data-17e13c3e-7f81-46dc-b835-fdcec0f043c7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x3MeHexane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-14a99951-8f54-4c47-903c-628d5f197f7c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-14a99951-8f54-4c47-903c-628d5f197f7c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bfa82442-2723-406c-95e5-dd5b2b82eedd' class='xr-var-data-in' type='checkbox'><label for='data-bfa82442-2723-406c-95e5-dd5b2b82eedd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x23DimePentane_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-d8b4f76c-cba0-400f-9952-67792bd5474e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d8b4f76c-cba0-400f-9952-67792bd5474e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e04cdfc8-a99f-4539-83f8-ccdd27f38e88' class='xr-var-data-in' type='checkbox'><label for='data-e04cdfc8-a99f-4539-83f8-ccdd27f38e88' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x224TrimePentane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-01548c99-112b-4209-bb27-ac7af2c1a8af' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-01548c99-112b-4209-bb27-ac7af2c1a8af' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c1495940-d526-4f3a-a10b-fc8c62c4033f' class='xr-var-data-in' type='checkbox'><label for='data-c1495940-d526-4f3a-a10b-fc8c62c4033f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x234TrimePentane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-2ffaaee0-3991-43d6-b67f-7b24c27c0495' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2ffaaee0-3991-43d6-b67f-7b24c27c0495' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2af7d026-9df4-4e67-af2c-d6fbe3541578' class='xr-var-data-in' type='checkbox'><label for='data-2af7d026-9df4-4e67-af2c-d6fbe3541578' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CycPentane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-0a6fc612-c10d-4e15-8223-7c96fdfd5270' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0a6fc612-c10d-4e15-8223-7c96fdfd5270' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c47f22ba-b64e-48b8-9ed9-bbb544698ceb' class='xr-var-data-in' type='checkbox'><label for='data-c47f22ba-b64e-48b8-9ed9-bbb544698ceb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MeCycPentane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-aad7b7be-c539-4971-bcd1-863028e5df93' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-aad7b7be-c539-4971-bcd1-863028e5df93' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-23eefa57-7c8a-4f95-97fc-01d5983d39c3' class='xr-var-data-in' type='checkbox'><label for='data-23eefa57-7c8a-4f95-97fc-01d5983d39c3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CycHexane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-17bfebe8-0d68-4824-b7cb-00f431ee08bd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-17bfebe8-0d68-4824-b7cb-00f431ee08bd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e493aca9-e38f-4f28-b95a-6911e81059e6' class='xr-var-data-in' type='checkbox'><label for='data-e493aca9-e38f-4f28-b95a-6911e81059e6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MeCycHexane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-93fcd3ed-abc4-4c94-9feb-c6bc9b4712ba' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-93fcd3ed-abc4-4c94-9feb-c6bc9b4712ba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-89f69b56-5a01-42c3-8810-e35013a31753' class='xr-var-data-in' type='checkbox'><label for='data-89f69b56-5a01-42c3-8810-e35013a31753' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CycPentene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-9960214c-b719-46e8-a9cd-83ee2e0136be' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9960214c-b719-46e8-a9cd-83ee2e0136be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d65ec729-c3ce-4546-982a-bc1bebdfbcf6' class='xr-var-data-in' type='checkbox'><label for='data-d65ec729-c3ce-4546-982a-bc1bebdfbcf6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Benzene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-afa7fa06-1c9d-4c9b-bf49-a3e8f22b0fde' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-afa7fa06-1c9d-4c9b-bf49-a3e8f22b0fde' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b094b913-6e20-4d05-85ac-a6e093a168af' class='xr-var-data-in' type='checkbox'><label for='data-b094b913-6e20-4d05-85ac-a6e093a168af' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Toluene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-99d554e4-7b27-4d7c-ac11-366db327a556' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-99d554e4-7b27-4d7c-ac11-366db327a556' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-20231d62-9425-4afa-8007-c1dc521829fb' class='xr-var-data-in' type='checkbox'><label for='data-20231d62-9425-4afa-8007-c1dc521829fb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>EthBenzene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-926303d7-5913-4ac1-9e70-55c174affbd9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-926303d7-5913-4ac1-9e70-55c174affbd9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d2b763bf-7d4e-4b58-a542-9a4dcfefc97f' class='xr-var-data-in' type='checkbox'><label for='data-d2b763bf-7d4e-4b58-a542-9a4dcfefc97f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mpXylene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-3424d1b8-b85d-4120-ba6b-444d8f4c945b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3424d1b8-b85d-4120-ba6b-444d8f4c945b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-541e9579-d61f-417c-a45e-c47247657210' class='xr-var-data-in' type='checkbox'><label for='data-541e9579-d61f-417c-a45e-c47247657210' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>oXylene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-423d322e-d5a2-4e9b-be28-191113f871f8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-423d322e-d5a2-4e9b-be28-191113f871f8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-42d9d3ad-9cca-4800-bf2d-31ca044249be' class='xr-var-data-in' type='checkbox'><label for='data-42d9d3ad-9cca-4800-bf2d-31ca044249be' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Styrene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-6698c679-86ca-4600-b383-26fa76ddaaf2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6698c679-86ca-4600-b383-26fa76ddaaf2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2b33e9db-5b62-4231-8203-697b85aba1fe' class='xr-var-data-in' type='checkbox'><label for='data-2b33e9db-5b62-4231-8203-697b85aba1fe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>EthynylBenzene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-f1d6d901-47b5-4cc1-b587-51fcac6f29a5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f1d6d901-47b5-4cc1-b587-51fcac6f29a5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b4f65e2-be88-41a2-a2d5-7675c04f974a' class='xr-var-data-in' type='checkbox'><label for='data-9b4f65e2-be88-41a2-a2d5-7675c04f974a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>iPropBenzene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-cd9a4984-8c69-43bf-a1eb-26f834322fbc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cd9a4984-8c69-43bf-a1eb-26f834322fbc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-97b4a9bd-c360-4f20-8928-ca275b391438' class='xr-var-data-in' type='checkbox'><label for='data-97b4a9bd-c360-4f20-8928-ca275b391438' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nPropBenzene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-a173d3ca-d8a8-4784-b7b7-c1eab526bd5c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a173d3ca-d8a8-4784-b7b7-c1eab526bd5c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fa058b72-1574-4cd0-b009-b5320b6dcc70' class='xr-var-data-in' type='checkbox'><label for='data-fa058b72-1574-4cd0-b009-b5320b6dcc70' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x3EthToluene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-902d8142-a704-4bd4-9371-68911948c91a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-902d8142-a704-4bd4-9371-68911948c91a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3e018d37-9285-4728-8667-7700556b6d9a' class='xr-var-data-in' type='checkbox'><label for='data-3e018d37-9285-4728-8667-7700556b6d9a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x4EthToluene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ea273cad-d030-49f0-ad4b-db475b9bdb2d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ea273cad-d030-49f0-ad4b-db475b9bdb2d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c308c6c7-efff-4b2f-acba-46551afcfbe3' class='xr-var-data-in' type='checkbox'><label for='data-c308c6c7-efff-4b2f-acba-46551afcfbe3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x2EthToluene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-6366db8f-605a-411b-9879-8ff6d90440aa' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6366db8f-605a-411b-9879-8ff6d90440aa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-41f9cde8-ee32-4c80-8929-356f04eb49bd' class='xr-var-data-in' type='checkbox'><label for='data-41f9cde8-ee32-4c80-8929-356f04eb49bd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x135rimeBenzene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-54cc539b-dd1d-4682-8262-1d6d9d2de06d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-54cc539b-dd1d-4682-8262-1d6d9d2de06d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3872f5c1-b7f8-4bce-ada4-b0daf751188e' class='xr-var-data-in' type='checkbox'><label for='data-3872f5c1-b7f8-4bce-ada4-b0daf751188e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x124rimeBenzene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-044706d3-e4db-4551-954d-fc8c33379ab0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-044706d3-e4db-4551-954d-fc8c33379ab0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b65fa130-4e25-4ec6-98ee-8e8f7fdede6d' class='xr-var-data-in' type='checkbox'><label for='data-b65fa130-4e25-4ec6-98ee-8e8f7fdede6d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ClBenzene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-77b3f062-2838-4e10-bd02-d43ee6558d39' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-77b3f062-2838-4e10-bd02-d43ee6558d39' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4e844892-66d9-460a-849d-36a8f749248a' class='xr-var-data-in' type='checkbox'><label for='data-4e844892-66d9-460a-849d-36a8f749248a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aPinene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-2b00fee2-f87f-4c2e-83e8-35e263f5428b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2b00fee2-f87f-4c2e-83e8-35e263f5428b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-be03bf44-db46-40ad-9530-65a14fed302a' class='xr-var-data-in' type='checkbox'><label for='data-be03bf44-db46-40ad-9530-65a14fed302a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>bPinene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e6d2344d-bef2-4b02-91a6-e09ca421bf68' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e6d2344d-bef2-4b02-91a6-e09ca421bf68' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f545e149-02b4-4afd-9ba6-24cd3238e50d' class='xr-var-data-in' type='checkbox'><label for='data-f545e149-02b4-4afd-9ba6-24cd3238e50d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Tricyclene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-a203fed9-ee30-4dc1-828b-25b0b9d110f4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a203fed9-ee30-4dc1-828b-25b0b9d110f4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ae760bc9-0354-4cca-b7b7-0ef12bf68e51' class='xr-var-data-in' type='checkbox'><label for='data-ae760bc9-0354-4cca-b7b7-0ef12bf68e51' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Camphene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-259b2a39-9b25-41f5-94e8-df1dfd82bd6c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-259b2a39-9b25-41f5-94e8-df1dfd82bd6c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d4f9b3cf-cdac-4faa-81d9-39fef7a83cb4' class='xr-var-data-in' type='checkbox'><label for='data-d4f9b3cf-cdac-4faa-81d9-39fef7a83cb4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Myrcene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-dfb3cf2c-8f1f-4516-8b3a-1a0209bace26' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-dfb3cf2c-8f1f-4516-8b3a-1a0209bace26' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cc3c517b-3118-42d4-974e-8966da739718' class='xr-var-data-in' type='checkbox'><label for='data-cc3c517b-3118-42d4-974e-8966da739718' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Limonene_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-46a0cdfc-fa4c-4d4b-b4a3-c9796f06af89' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-46a0cdfc-fa4c-4d4b-b4a3-c9796f06af89' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9082711b-c349-485a-b229-b962af73996f' class='xr-var-data-in' type='checkbox'><label for='data-9082711b-c349-485a-b229-b962af73996f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Furan_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-c3b3b9c6-317b-4512-bc15-892974b5357a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c3b3b9c6-317b-4512-bc15-892974b5357a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6eeba6ae-c628-4735-93ed-3fe34cd266c1' class='xr-var-data-in' type='checkbox'><label for='data-6eeba6ae-c628-4735-93ed-3fe34cd266c1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x2MeFuran_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-7dedef89-b1f5-4d54-941c-9f4eac126405' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7dedef89-b1f5-4d54-941c-9f4eac126405' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2d5f42a8-5496-49c4-91da-851f57b1517d' class='xr-var-data-in' type='checkbox'><label for='data-2d5f42a8-5496-49c4-91da-851f57b1517d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x3MeFuran_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-a1b70e00-59fc-4595-a5df-58c1f6ec376f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a1b70e00-59fc-4595-a5df-58c1f6ec376f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-efb31138-6056-4f1d-828d-b7952d08d3c4' class='xr-var-data-in' type='checkbox'><label for='data-efb31138-6056-4f1d-828d-b7952d08d3c4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>BenzFuran_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-79f77cb0-5018-4085-b3fc-fad2bab24e90' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-79f77cb0-5018-4085-b3fc-fad2bab24e90' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-01ad90aa-3a6f-4313-88de-1a92082d6ac3' class='xr-var-data-in' type='checkbox'><label for='data-01ad90aa-3a6f-4313-88de-1a92082d6ac3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>iButanal_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ed5d6ec3-e2a6-49ea-86bd-4e9cf33a205e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ed5d6ec3-e2a6-49ea-86bd-4e9cf33a205e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-84a4e10f-fdf0-4582-94c4-119cb1981c6c' class='xr-var-data-in' type='checkbox'><label for='data-84a4e10f-fdf0-4582-94c4-119cb1981c6c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Butanal_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-79cb9498-24ac-490d-b095-bfb5ca48dc23' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-79cb9498-24ac-490d-b095-bfb5ca48dc23' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-44ddf449-ddeb-4911-aa63-9041c1f23cc8' class='xr-var-data-in' type='checkbox'><label for='data-44ddf449-ddeb-4911-aa63-9041c1f23cc8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>AcetonePropanal_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-50340eec-3c16-49db-9e27-82ea4b1cd0f6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-50340eec-3c16-49db-9e27-82ea4b1cd0f6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-104bb026-846c-49cf-b77f-06331947c39d' class='xr-var-data-in' type='checkbox'><label for='data-104bb026-846c-49cf-b77f-06331947c39d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MEK_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-4971c329-80e7-4fba-a083-42eb7e50d733' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4971c329-80e7-4fba-a083-42eb7e50d733' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b65c5b24-c454-4349-92b5-1ab85fe7c541' class='xr-var-data-in' type='checkbox'><label for='data-b65c5b24-c454-4349-92b5-1ab85fe7c541' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MAC_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-a7f400be-bb20-43cc-9cce-fc6cbadc3994' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a7f400be-bb20-43cc-9cce-fc6cbadc3994' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8b399f4e-63ab-45c0-9abc-75a5c9c7acc4' class='xr-var-data-in' type='checkbox'><label for='data-8b399f4e-63ab-45c0-9abc-75a5c9c7acc4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MVK_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-9471278d-0257-4cf2-9261-5bbeaf0d91bd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9471278d-0257-4cf2-9261-5bbeaf0d91bd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-38beddc0-31be-49e2-b66a-192d897301f0' class='xr-var-data-in' type='checkbox'><label for='data-38beddc0-31be-49e2-b66a-192d897301f0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Acrolein_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-b27a957c-79e9-4e86-b54a-c0c2990300d3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b27a957c-79e9-4e86-b54a-c0c2990300d3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-249b29d7-412e-47be-9924-0258d66908c2' class='xr-var-data-in' type='checkbox'><label for='data-249b29d7-412e-47be-9924-0258d66908c2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>iPropanol_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-69bb053c-384d-44bc-80f6-1be1a3d01a54' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-69bb053c-384d-44bc-80f6-1be1a3d01a54' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e27b6d02-dc93-4882-a446-6cec4e4ddf77' class='xr-var-data-in' type='checkbox'><label for='data-e27b6d02-dc93-4882-a446-6cec4e4ddf77' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Nitromethane_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-213583ef-e9e0-4c72-bea0-5547194c488f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-213583ef-e9e0-4c72-bea0-5547194c488f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-973b2384-ed51-42c8-831d-73d3b1057b0e' class='xr-var-data-in' type='checkbox'><label for='data-973b2384-ed51-42c8-831d-73d3b1057b0e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Acrylonitrile_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-5a968797-dff8-4b47-961e-29bb14aabd50' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5a968797-dff8-4b47-961e-29bb14aabd50' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b110bc16-c3ec-4661-a7e7-b44f26442275' class='xr-var-data-in' type='checkbox'><label for='data-b110bc16-c3ec-4661-a7e7-b44f26442275' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PropNitrile_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-1b5d48e0-5811-4e17-a0e8-78ba1aef0df3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1b5d48e0-5811-4e17-a0e8-78ba1aef0df3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c2b3129d-0287-4650-9f23-ba44dbc91877' class='xr-var-data-in' type='checkbox'><label for='data-c2b3129d-0287-4650-9f23-ba44dbc91877' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MeAcetate_WAS_BLAKE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-578dc265-b5b4-46b8-bd7d-9eb3b763cc49' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-578dc265-b5b4-46b8-bd7d-9eb3b763cc49' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4740da25-7e1b-47eb-b03d-bb4bf45fe8d0' class='xr-var-data-in' type='checkbox'><label for='data-4740da25-7e1b-47eb-b03d-bb4bf45fe8d0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HFC134a_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 322.8 322.8 ... nan nan nan</div><input id='attrs-3c9eaaab-2395-4785-bed5-453da5a597f1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3c9eaaab-2395-4785-bed5-453da5a597f1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8fb79229-c2c3-43c9-94d6-2bc625eb8289' class='xr-var-data-in' type='checkbox'><label for='data-8fb79229-c2c3-43c9-94d6-2bc625eb8289' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan],\n",
+       "       [  nan],\n",
+       "       [322.8],\n",
+       "       ...,\n",
+       "       [  nan],\n",
+       "       [  nan],\n",
+       "       [  nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HCFC141b_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 50.4 50.4 ... nan nan nan</div><input id='attrs-9bd72f52-285a-426d-bf5b-a9ec7b608dbe' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9bd72f52-285a-426d-bf5b-a9ec7b608dbe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c296124a-1ddb-4f4a-85a0-3b03c1f2c90f' class='xr-var-data-in' type='checkbox'><label for='data-c296124a-1ddb-4f4a-85a0-3b03c1f2c90f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan],\n",
+       "       [ nan],\n",
+       "       [50.4],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HCFC142b_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 22.0 22.0 ... nan nan nan</div><input id='attrs-bd42070f-a9db-4dd9-9589-7c20c45dc169' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bd42070f-a9db-4dd9-9589-7c20c45dc169' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c00f8f98-ab2d-4e52-9968-cb4e77b9c263' class='xr-var-data-in' type='checkbox'><label for='data-c00f8f98-ab2d-4e52-9968-cb4e77b9c263' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [22.],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HCFC22_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 262.0 262.0 ... nan nan nan</div><input id='attrs-a5e5ed3b-110f-4df9-9af4-ead5845ec3dd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a5e5ed3b-110f-4df9-9af4-ead5845ec3dd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1ea818ff-35b6-4920-b1b6-b1144185d5b1' class='xr-var-data-in' type='checkbox'><label for='data-1ea818ff-35b6-4920-b1b6-b1144185d5b1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan],\n",
+       "       [ nan],\n",
+       "       [262.],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH2Cl2_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 57.1 57.1 ... nan nan nan</div><input id='attrs-b47654df-b035-4003-9356-6999cdf2c4fc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b47654df-b035-4003-9356-6999cdf2c4fc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-604d1bc6-284d-4a24-81ab-6309bfc1f6d6' class='xr-var-data-in' type='checkbox'><label for='data-604d1bc6-284d-4a24-81ab-6309bfc1f6d6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan],\n",
+       "       [ nan],\n",
+       "       [57.1],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CHCl3_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 14.29 14.29 ... nan nan nan</div><input id='attrs-79fa30ce-4c94-4773-b64c-f86a2a14d83b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-79fa30ce-4c94-4773-b64c-f86a2a14d83b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b6679fb6-45a4-4f5b-90f3-59ff79f46fd8' class='xr-var-data-in' type='checkbox'><label for='data-b6679fb6-45a4-4f5b-90f3-59ff79f46fd8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan],\n",
+       "       [  nan],\n",
+       "       [14.29],\n",
+       "       ...,\n",
+       "       [  nan],\n",
+       "       [  nan],\n",
+       "       [  nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH2ClCH2Cl_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 12.33 12.33 ... nan nan nan</div><input id='attrs-ab506e8d-7cde-405b-ac67-4edf2438d98f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ab506e8d-7cde-405b-ac67-4edf2438d98f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-df3525ff-08a8-4253-b208-954ba65c5253' class='xr-var-data-in' type='checkbox'><label for='data-df3525ff-08a8-4253-b208-954ba65c5253' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan],\n",
+       "       [  nan],\n",
+       "       [12.33],\n",
+       "       ...,\n",
+       "       [  nan],\n",
+       "       [  nan],\n",
+       "       [  nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH3CCl3_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 1.82 1.82 ... nan nan nan</div><input id='attrs-9758631f-1823-4425-9209-ebd81a9e36ae' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9758631f-1823-4425-9209-ebd81a9e36ae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fcb4dc18-d2b4-469d-a50c-b1520703bacc' class='xr-var-data-in' type='checkbox'><label for='data-fcb4dc18-d2b4-469d-a50c-b1520703bacc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan],\n",
+       "       [ nan],\n",
+       "       [1.82],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>C2Cl4_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 3.23 3.23 ... nan nan nan</div><input id='attrs-a07c5f39-c032-4ff7-9d61-5ba416478121' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a07c5f39-c032-4ff7-9d61-5ba416478121' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bd7d1164-5acf-448c-b434-5cffea3a69d7' class='xr-var-data-in' type='checkbox'><label for='data-bd7d1164-5acf-448c-b434-5cffea3a69d7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan],\n",
+       "       [ nan],\n",
+       "       [3.23],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ClBenzene_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 0.69 0.69 ... nan nan nan</div><input id='attrs-09ebb7b7-d5ef-49b3-920e-c323f7a732a6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-09ebb7b7-d5ef-49b3-920e-c323f7a732a6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-20711195-b1ba-4f0f-abe1-fc4931b927f8' class='xr-var-data-in' type='checkbox'><label for='data-20711195-b1ba-4f0f-abe1-fc4931b927f8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan],\n",
+       "       [ nan],\n",
+       "       [0.69],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CHBrCl2_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 0.42 0.42 ... nan nan nan</div><input id='attrs-a9f4ebfc-4130-4304-b6dd-b1b5c3122ffa' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a9f4ebfc-4130-4304-b6dd-b1b5c3122ffa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6d343154-64e5-4871-bdfb-2ae19f8e12ef' class='xr-var-data-in' type='checkbox'><label for='data-6d343154-64e5-4871-bdfb-2ae19f8e12ef' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan],\n",
+       "       [ nan],\n",
+       "       [0.42],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CHBr2Cl_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-7afffa6e-c52c-4039-8e62-d482047bc130' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7afffa6e-c52c-4039-8e62-d482047bc130' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-13cae8e1-ad10-4291-9bc5-3931b17ef8d7' class='xr-var-data-in' type='checkbox'><label for='data-13cae8e1-ad10-4291-9bc5-3931b17ef8d7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH3Br_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 6.66 6.66 ... nan nan nan</div><input id='attrs-6c7a1599-a486-4a9f-85aa-17d40644b7db' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6c7a1599-a486-4a9f-85aa-17d40644b7db' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e37e9bcd-9155-4fdd-adf4-189da41291f2' class='xr-var-data-in' type='checkbox'><label for='data-e37e9bcd-9155-4fdd-adf4-189da41291f2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan],\n",
+       "       [ nan],\n",
+       "       [6.66],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH2Br2_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 0.67 0.67 ... nan nan nan</div><input id='attrs-b28cfa4c-9948-4781-b799-7b72fd41a82c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b28cfa4c-9948-4781-b799-7b72fd41a82c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c41ee71-5f89-4e41-821f-89f98e9121de' class='xr-var-data-in' type='checkbox'><label for='data-4c41ee71-5f89-4e41-821f-89f98e9121de' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan],\n",
+       "       [ nan],\n",
+       "       [0.67],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CHBr3_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 0.42 0.42 ... nan nan nan</div><input id='attrs-814f5984-a82a-4ec9-8bbf-9231711e56d0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-814f5984-a82a-4ec9-8bbf-9231711e56d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9fd11863-03d3-457d-90c1-3184ce86fcf0' class='xr-var-data-in' type='checkbox'><label for='data-9fd11863-03d3-457d-90c1-3184ce86fcf0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan],\n",
+       "       [ nan],\n",
+       "       [0.42],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH2ClI_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-10987984-a8b6-4549-ba4a-a9d2e065a3ea' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-10987984-a8b6-4549-ba4a-a9d2e065a3ea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c27b34d2-b125-466b-a05c-4683f6828a6e' class='xr-var-data-in' type='checkbox'><label for='data-c27b34d2-b125-466b-a05c-4683f6828a6e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH3I_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 1.333 1.333 ... nan nan nan</div><input id='attrs-77791962-5de0-45dc-8b82-63c96caa0e2a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-77791962-5de0-45dc-8b82-63c96caa0e2a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-69be3f65-f012-40af-a1ab-b1af757794c9' class='xr-var-data-in' type='checkbox'><label for='data-69be3f65-f012-40af-a1ab-b1af757794c9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan],\n",
+       "       [  nan],\n",
+       "       [1.333],\n",
+       "       ...,\n",
+       "       [  nan],\n",
+       "       [  nan],\n",
+       "       [  nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CS2_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 7.1 7.1 ... nan nan nan nan</div><input id='attrs-f8655c45-1090-40c2-b5a4-154b69c9999c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f8655c45-1090-40c2-b5a4-154b69c9999c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-670dc427-3f23-413f-a9fd-d5e91fda2825' class='xr-var-data-in' type='checkbox'><label for='data-670dc427-3f23-413f-a9fd-d5e91fda2825' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [7.1],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH3SH_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 3.9 3.9 ... nan nan nan nan</div><input id='attrs-8e5fe08e-5e9b-4bf5-9e43-78e41d6434fd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8e5fe08e-5e9b-4bf5-9e43-78e41d6434fd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c8776af8-f32f-41bd-b04b-04e1dabf370d' class='xr-var-data-in' type='checkbox'><label for='data-c8776af8-f32f-41bd-b04b-04e1dabf370d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [3.9],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>DMS_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan -8.889e+05 ... nan nan nan</div><input id='attrs-8d2cd8af-fa36-4611-bd2f-63a88cf5d59b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8d2cd8af-fa36-4611-bd2f-63a88cf5d59b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-face6213-a4a3-405c-bdf4-9921eb8c4f5c' class='xr-var-data-in' type='checkbox'><label for='data-face6213-a4a3-405c-bdf4-9921eb8c4f5c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[     nan],\n",
+       "       [     nan],\n",
+       "       [-888888.],\n",
+       "       ...,\n",
+       "       [     nan],\n",
+       "       [     nan],\n",
+       "       [     nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Propane_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-0915f0a3-57fd-4f72-b7dd-04bba313c17a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0915f0a3-57fd-4f72-b7dd-04bba313c17a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-595279dc-ab15-4556-83d8-b2f1b973fa85' class='xr-var-data-in' type='checkbox'><label for='data-595279dc-ab15-4556-83d8-b2f1b973fa85' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>iButane_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 332.4 332.4 ... nan nan nan</div><input id='attrs-e07dc8cd-5e2d-420c-b22d-f04785f9dba3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e07dc8cd-5e2d-420c-b22d-f04785f9dba3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c5f6776-00ad-44d9-98ad-dbd8c5cd071d' class='xr-var-data-in' type='checkbox'><label for='data-4c5f6776-00ad-44d9-98ad-dbd8c5cd071d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan],\n",
+       "       [  nan],\n",
+       "       [332.4],\n",
+       "       ...,\n",
+       "       [  nan],\n",
+       "       [  nan],\n",
+       "       [  nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nButane_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 1.21e+03 ... nan nan nan</div><input id='attrs-e259173b-03c2-4790-8178-9d12fc07d2ec' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e259173b-03c2-4790-8178-9d12fc07d2ec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bcdd9b0c-1d14-46af-ad60-34d3c903ee58' class='xr-var-data-in' type='checkbox'><label for='data-bcdd9b0c-1d14-46af-ad60-34d3c903ee58' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[   nan],\n",
+       "       [   nan],\n",
+       "       [1209.8],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>iPentane_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 451.3 451.3 ... nan nan nan</div><input id='attrs-4298eaec-9b3e-4819-94f4-688c169d85a5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4298eaec-9b3e-4819-94f4-688c169d85a5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-085d61df-2357-4a94-84f9-81effb13e721' class='xr-var-data-in' type='checkbox'><label for='data-085d61df-2357-4a94-84f9-81effb13e721' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan],\n",
+       "       [  nan],\n",
+       "       [451.3],\n",
+       "       ...,\n",
+       "       [  nan],\n",
+       "       [  nan],\n",
+       "       [  nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nPentane_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 455.7 455.7 ... nan nan nan</div><input id='attrs-d4cf2656-8fd6-4c29-b100-41ff1eb83fe0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d4cf2656-8fd6-4c29-b100-41ff1eb83fe0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dbb2ad70-092d-475c-bc95-6e74542d5db6' class='xr-var-data-in' type='checkbox'><label for='data-dbb2ad70-092d-475c-bc95-6e74542d5db6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan],\n",
+       "       [  nan],\n",
+       "       [455.7],\n",
+       "       ...,\n",
+       "       [  nan],\n",
+       "       [  nan],\n",
+       "       [  nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x2MePentane_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 130.6 130.6 ... nan nan nan</div><input id='attrs-22cf4684-cd44-4e1e-a152-5701732413a1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-22cf4684-cd44-4e1e-a152-5701732413a1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-442ef984-20cc-4cee-b42e-ecf2c5f5d97c' class='xr-var-data-in' type='checkbox'><label for='data-442ef984-20cc-4cee-b42e-ecf2c5f5d97c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan],\n",
+       "       [  nan],\n",
+       "       [130.6],\n",
+       "       ...,\n",
+       "       [  nan],\n",
+       "       [  nan],\n",
+       "       [  nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x3MePentane_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 58.6 58.6 ... nan nan nan</div><input id='attrs-a47ccbcb-9b37-4313-89a0-c77411a5c7f7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a47ccbcb-9b37-4313-89a0-c77411a5c7f7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-06d93578-4768-4a6d-bbf0-3a1b0477e519' class='xr-var-data-in' type='checkbox'><label for='data-06d93578-4768-4a6d-bbf0-3a1b0477e519' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan],\n",
+       "       [ nan],\n",
+       "       [58.6],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nHexane_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 150.3 150.3 ... nan nan nan</div><input id='attrs-e4b4ff99-3e51-4f5f-830b-a6b96e8bccaf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e4b4ff99-3e51-4f5f-830b-a6b96e8bccaf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7d309371-18f7-410d-b09c-eddbfa5ffe72' class='xr-var-data-in' type='checkbox'><label for='data-7d309371-18f7-410d-b09c-eddbfa5ffe72' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan],\n",
+       "       [  nan],\n",
+       "       [150.3],\n",
+       "       ...,\n",
+       "       [  nan],\n",
+       "       [  nan],\n",
+       "       [  nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x224TrimePentane_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 51.7 51.7 ... nan nan nan</div><input id='attrs-1606565f-d54f-4f25-80dc-f0dd884fd7cd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1606565f-d54f-4f25-80dc-f0dd884fd7cd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-86173c17-857a-47ca-9b0b-f025a9da80a6' class='xr-var-data-in' type='checkbox'><label for='data-86173c17-857a-47ca-9b0b-f025a9da80a6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan],\n",
+       "       [ nan],\n",
+       "       [51.7],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nHeptane_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 45.8 45.8 ... nan nan nan</div><input id='attrs-6e96a1d4-897f-4fcb-82e2-33c782745a8e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6e96a1d4-897f-4fcb-82e2-33c782745a8e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b1a7071-e99a-429c-bfe0-f4592faf9e3e' class='xr-var-data-in' type='checkbox'><label for='data-9b1a7071-e99a-429c-bfe0-f4592faf9e3e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan],\n",
+       "       [ nan],\n",
+       "       [45.8],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nOctane_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 22.4 22.4 ... nan nan nan</div><input id='attrs-d34a0ffc-5dc4-4df4-b35b-388a72dcd9cc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d34a0ffc-5dc4-4df4-b35b-388a72dcd9cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3e4eff56-9809-4f87-aa99-81b6ed6ad506' class='xr-var-data-in' type='checkbox'><label for='data-3e4eff56-9809-4f87-aa99-81b6ed6ad506' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan],\n",
+       "       [ nan],\n",
+       "       [22.4],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Propene_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-861a8622-a7cf-4906-b405-8ca2ae89b578' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-861a8622-a7cf-4906-b405-8ca2ae89b578' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bcccd1cb-9930-445a-8016-ed3e650f3822' class='xr-var-data-in' type='checkbox'><label for='data-bcccd1cb-9930-445a-8016-ed3e650f3822' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>iButene1Butene_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 52.0 52.0 ... nan nan nan</div><input id='attrs-36fb4074-f182-42ba-a456-884709324aca' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-36fb4074-f182-42ba-a456-884709324aca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-332c5518-31ce-449c-a324-a718d94a3449' class='xr-var-data-in' type='checkbox'><label for='data-332c5518-31ce-449c-a324-a718d94a3449' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [52.],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Isoprene_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 58.5 58.5 ... nan nan nan</div><input id='attrs-96332910-b065-44e7-b387-6bf69e9bd855' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-96332910-b065-44e7-b387-6bf69e9bd855' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-83a89704-3481-4e1f-aad1-d704959a6b4d' class='xr-var-data-in' type='checkbox'><label for='data-83a89704-3481-4e1f-aad1-d704959a6b4d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan],\n",
+       "       [ nan],\n",
+       "       [58.5],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Tricyclene_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 3.29 3.29 ... nan nan nan</div><input id='attrs-59d43484-2773-4415-97a8-ecd60df126ca' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-59d43484-2773-4415-97a8-ecd60df126ca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-44f3f319-0183-49e3-ad0e-1b91751bdb18' class='xr-var-data-in' type='checkbox'><label for='data-44f3f319-0183-49e3-ad0e-1b91751bdb18' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan],\n",
+       "       [ nan],\n",
+       "       [3.29],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aPinene_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 4.3 4.3 ... nan nan nan nan</div><input id='attrs-4889664c-568d-48fc-ac61-fb88d8c95411' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4889664c-568d-48fc-ac61-fb88d8c95411' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a8bc8882-1ce7-4d91-a7ed-48369ebbe7e7' class='xr-var-data-in' type='checkbox'><label for='data-a8bc8882-1ce7-4d91-a7ed-48369ebbe7e7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [4.3],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Camphene_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan -8.889e+05 ... nan nan nan</div><input id='attrs-93994851-ae94-4939-a2eb-0492731db6e9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-93994851-ae94-4939-a2eb-0492731db6e9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7b6924c0-fbd8-4cba-bec0-18d2c9c9e3f2' class='xr-var-data-in' type='checkbox'><label for='data-7b6924c0-fbd8-4cba-bec0-18d2c9c9e3f2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[     nan],\n",
+       "       [     nan],\n",
+       "       [-888888.],\n",
+       "       ...,\n",
+       "       [     nan],\n",
+       "       [     nan],\n",
+       "       [     nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>bPineneMyrcene_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan -8.889e+05 ... nan nan nan</div><input id='attrs-d73e4e7a-d78a-4ee3-8528-ff05d682892b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d73e4e7a-d78a-4ee3-8528-ff05d682892b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b808c4d4-92d2-4111-b083-c9c65f87855b' class='xr-var-data-in' type='checkbox'><label for='data-b808c4d4-92d2-4111-b083-c9c65f87855b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[     nan],\n",
+       "       [     nan],\n",
+       "       [-888888.],\n",
+       "       ...,\n",
+       "       [     nan],\n",
+       "       [     nan],\n",
+       "       [     nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>LimoneneD3Carene_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan -8.889e+05 ... nan nan nan</div><input id='attrs-71952e46-33ff-47dd-b9a1-e1efd0cd63b4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-71952e46-33ff-47dd-b9a1-e1efd0cd63b4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-67f1587f-8283-4182-b259-0d03096b4a8a' class='xr-var-data-in' type='checkbox'><label for='data-67f1587f-8283-4182-b259-0d03096b4a8a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[     nan],\n",
+       "       [     nan],\n",
+       "       [-888888.],\n",
+       "       ...,\n",
+       "       [     nan],\n",
+       "       [     nan],\n",
+       "       [     nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Benzene_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 70.24 70.24 ... nan nan nan</div><input id='attrs-f401a54a-7e6c-414f-84fb-fdd7dcc89071' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f401a54a-7e6c-414f-84fb-fdd7dcc89071' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-91d8ad96-e0a6-404c-9a12-402295c02123' class='xr-var-data-in' type='checkbox'><label for='data-91d8ad96-e0a6-404c-9a12-402295c02123' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan],\n",
+       "       [  nan],\n",
+       "       [70.24],\n",
+       "       ...,\n",
+       "       [  nan],\n",
+       "       [  nan],\n",
+       "       [  nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Toluene_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 85.47 85.47 ... nan nan nan</div><input id='attrs-22fe23be-1be2-4fd8-af08-e353b37e8e4f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-22fe23be-1be2-4fd8-af08-e353b37e8e4f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-da6be90f-d14a-46cd-8678-31b458fdae1d' class='xr-var-data-in' type='checkbox'><label for='data-da6be90f-d14a-46cd-8678-31b458fdae1d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan],\n",
+       "       [  nan],\n",
+       "       [85.47],\n",
+       "       ...,\n",
+       "       [  nan],\n",
+       "       [  nan],\n",
+       "       [  nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>EthBenzene_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 8.7 8.7 ... nan nan nan nan</div><input id='attrs-3055a992-9105-430b-9e97-5885301d5d07' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3055a992-9105-430b-9e97-5885301d5d07' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-34ad6251-6b87-42b3-878a-6aef2238f32f' class='xr-var-data-in' type='checkbox'><label for='data-34ad6251-6b87-42b3-878a-6aef2238f32f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [8.7],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mpXylene_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 16.25 16.25 ... nan nan nan</div><input id='attrs-fbf7d83d-0b29-45a2-8bf6-97276a14670e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fbf7d83d-0b29-45a2-8bf6-97276a14670e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-af69ecc3-9e0b-4a82-be06-a3993797aa22' class='xr-var-data-in' type='checkbox'><label for='data-af69ecc3-9e0b-4a82-be06-a3993797aa22' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan],\n",
+       "       [  nan],\n",
+       "       [16.25],\n",
+       "       ...,\n",
+       "       [  nan],\n",
+       "       [  nan],\n",
+       "       [  nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>oXylene_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 7.08 7.08 ... nan nan nan</div><input id='attrs-4ce81c29-a317-44eb-af10-09b35e851b7c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4ce81c29-a317-44eb-af10-09b35e851b7c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8c5b56d1-199a-41f1-9ee2-96f2abf3409c' class='xr-var-data-in' type='checkbox'><label for='data-8c5b56d1-199a-41f1-9ee2-96f2abf3409c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan],\n",
+       "       [ nan],\n",
+       "       [7.08],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Styrene_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 2.49 2.49 ... nan nan nan</div><input id='attrs-767f0e4a-87bb-4ca4-a5a5-b304bfebc9ca' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-767f0e4a-87bb-4ca4-a5a5-b304bfebc9ca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5f6a66a4-4689-4806-9c0d-3b1723e17554' class='xr-var-data-in' type='checkbox'><label for='data-5f6a66a4-4689-4806-9c0d-3b1723e17554' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan],\n",
+       "       [ nan],\n",
+       "       [2.49],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>EthynylBenzene_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan -8.889e+05 ... nan nan nan</div><input id='attrs-ea16c02d-dd95-430f-8a98-b6d15dba1915' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ea16c02d-dd95-430f-8a98-b6d15dba1915' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9d1c3f40-1970-4a22-84d6-48e16984af12' class='xr-var-data-in' type='checkbox'><label for='data-9d1c3f40-1970-4a22-84d6-48e16984af12' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[     nan],\n",
+       "       [     nan],\n",
+       "       [-888888.],\n",
+       "       ...,\n",
+       "       [     nan],\n",
+       "       [     nan],\n",
+       "       [     nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH2O_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 3.839e+03 ... nan nan nan</div><input id='attrs-ddb73256-ea66-4f5e-8a2c-1df6a88a4354' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ddb73256-ea66-4f5e-8a2c-1df6a88a4354' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8bacd7e5-f8c7-40b4-81f9-40577fdd7309' class='xr-var-data-in' type='checkbox'><label for='data-8bacd7e5-f8c7-40b4-81f9-40577fdd7309' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan],\n",
+       "       [  nan],\n",
+       "       [3839.],\n",
+       "       ...,\n",
+       "       [  nan],\n",
+       "       [  nan],\n",
+       "       [  nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH3CHO_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 1.69e+03 ... nan nan nan</div><input id='attrs-e682e572-3fe4-49b7-8966-39aff56d7d88' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e682e572-3fe4-49b7-8966-39aff56d7d88' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2858f8f8-a5a5-4337-9052-fa050817365f' class='xr-var-data-in' type='checkbox'><label for='data-2858f8f8-a5a5-4337-9052-fa050817365f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[   nan],\n",
+       "       [   nan],\n",
+       "       [1690.3],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Propanal_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 230.0 230.0 ... nan nan nan</div><input id='attrs-6044b8cf-69e5-490b-90cc-bf07f8d5bf6e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6044b8cf-69e5-490b-90cc-bf07f8d5bf6e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3cbdf975-2ea0-47b9-a543-90458e892bce' class='xr-var-data-in' type='checkbox'><label for='data-3cbdf975-2ea0-47b9-a543-90458e892bce' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan],\n",
+       "       [ nan],\n",
+       "       [230.],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Butanal_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 87.0 87.0 ... nan nan nan</div><input id='attrs-75345718-9d2a-44d0-a64c-ab3c2791ec85' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-75345718-9d2a-44d0-a64c-ab3c2791ec85' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-33011c05-46de-4a77-8682-cd0a83c4d1d0' class='xr-var-data-in' type='checkbox'><label for='data-33011c05-46de-4a77-8682-cd0a83c4d1d0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [87.],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>iButanal_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 52.3 52.3 ... nan nan nan</div><input id='attrs-729457d4-3902-410e-9a67-b82e7d29b0c0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-729457d4-3902-410e-9a67-b82e7d29b0c0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ddb6b793-85f9-49c9-978f-8db47a0223cc' class='xr-var-data-in' type='checkbox'><label for='data-ddb6b793-85f9-49c9-978f-8db47a0223cc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan],\n",
+       "       [ nan],\n",
+       "       [52.3],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Acrolein_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 98.0 98.0 ... nan nan nan</div><input id='attrs-4d8dcbb4-0874-412e-8303-adc0e7c990ef' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4d8dcbb4-0874-412e-8303-adc0e7c990ef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cae305fe-c646-481b-bd36-effd218b0c9b' class='xr-var-data-in' type='checkbox'><label for='data-cae305fe-c646-481b-bd36-effd218b0c9b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [98.],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x2Butenals_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 37.0 37.0 ... nan nan nan</div><input id='attrs-2e3da92e-cf03-443a-90b9-2c8514d706a6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2e3da92e-cf03-443a-90b9-2c8514d706a6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4cf34e54-7151-4d39-a016-03ec8b6f4480' class='xr-var-data-in' type='checkbox'><label for='data-4cf34e54-7151-4d39-a016-03ec8b6f4480' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [37.],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Acetone_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 4.217e+03 ... nan nan nan</div><input id='attrs-4c373516-a3ae-48c4-9b59-00b0d0f59d1f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4c373516-a3ae-48c4-9b59-00b0d0f59d1f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cfa38818-231d-48f8-8f3f-05e5244336b3' class='xr-var-data-in' type='checkbox'><label for='data-cfa38818-231d-48f8-8f3f-05e5244336b3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[   nan],\n",
+       "       [   nan],\n",
+       "       [4216.9],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MEK_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 405.4 405.4 ... nan nan nan</div><input id='attrs-9e4e0c1b-a3a9-44b5-9558-f5b26bcffe94' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9e4e0c1b-a3a9-44b5-9558-f5b26bcffe94' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7d9b6f01-1664-4157-8bf2-bec2468aca01' class='xr-var-data-in' type='checkbox'><label for='data-7d9b6f01-1664-4157-8bf2-bec2468aca01' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan],\n",
+       "       [  nan],\n",
+       "       [405.4],\n",
+       "       ...,\n",
+       "       [  nan],\n",
+       "       [  nan],\n",
+       "       [  nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH3OH_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 1.248e+04 ... nan nan nan</div><input id='attrs-e4b2cc8d-5b40-427b-8327-267e016caa33' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e4b2cc8d-5b40-427b-8327-267e016caa33' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d0015afe-1cce-4416-a941-49922533036d' class='xr-var-data-in' type='checkbox'><label for='data-d0015afe-1cce-4416-a941-49922533036d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[   nan],\n",
+       "       [   nan],\n",
+       "       [12485.],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>C2H5OH_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 636.4 636.4 ... nan nan nan</div><input id='attrs-e5134af2-84c4-4048-9e3b-ec392e5d8794' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e5134af2-84c4-4048-9e3b-ec392e5d8794' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bab4648f-8da5-4f2d-9257-00d7620e4868' class='xr-var-data-in' type='checkbox'><label for='data-bab4648f-8da5-4f2d-9257-00d7620e4868' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan],\n",
+       "       [  nan],\n",
+       "       [636.4],\n",
+       "       ...,\n",
+       "       [  nan],\n",
+       "       [  nan],\n",
+       "       [  nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>iPropanol_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 86.6 86.6 ... nan nan nan</div><input id='attrs-05517ae2-5dec-4e53-8fe3-40bb7852febe' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-05517ae2-5dec-4e53-8fe3-40bb7852febe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3cf27d46-0bc5-4953-bd39-41b123d3e6e2' class='xr-var-data-in' type='checkbox'><label for='data-3cf27d46-0bc5-4953-bd39-41b123d3e6e2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan],\n",
+       "       [ nan],\n",
+       "       [86.6],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MBO_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan -8.889e+05 ... nan nan nan</div><input id='attrs-1868aae1-c043-4b31-95b2-4f415ae08563' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1868aae1-c043-4b31-95b2-4f415ae08563' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6d7f8c07-94e0-4b44-a7c3-d59ea4ad0a27' class='xr-var-data-in' type='checkbox'><label for='data-6d7f8c07-94e0-4b44-a7c3-d59ea4ad0a27' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[     nan],\n",
+       "       [     nan],\n",
+       "       [-888888.],\n",
+       "       ...,\n",
+       "       [     nan],\n",
+       "       [     nan],\n",
+       "       [     nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MAC_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 58.8 58.8 ... nan nan nan</div><input id='attrs-bfc3fce3-055b-4fd4-837f-b51f2537b298' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bfc3fce3-055b-4fd4-837f-b51f2537b298' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-99b32e8d-add4-4b4c-86c3-d5d1e5f631b9' class='xr-var-data-in' type='checkbox'><label for='data-99b32e8d-add4-4b4c-86c3-d5d1e5f631b9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan],\n",
+       "       [ nan],\n",
+       "       [58.8],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MVK_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 161.6 161.6 ... nan nan nan</div><input id='attrs-4596743e-ae4e-441f-a21d-260d62a613e1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4596743e-ae4e-441f-a21d-260d62a613e1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-883bdcf2-b783-449d-8f8a-c9dbfa4795e1' class='xr-var-data-in' type='checkbox'><label for='data-883bdcf2-b783-449d-8f8a-c9dbfa4795e1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan],\n",
+       "       [  nan],\n",
+       "       [161.6],\n",
+       "       ...,\n",
+       "       [  nan],\n",
+       "       [  nan],\n",
+       "       [  nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MeFormate_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 77.9 77.9 ... nan nan nan</div><input id='attrs-52be4885-3602-4a5d-8e5d-0ba6f4ce838e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-52be4885-3602-4a5d-8e5d-0ba6f4ce838e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-177dc2e9-ca18-4642-9aac-c620e7c5a287' class='xr-var-data-in' type='checkbox'><label for='data-177dc2e9-ca18-4642-9aac-c620e7c5a287' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan],\n",
+       "       [ nan],\n",
+       "       [77.9],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MeAcetate_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 88.5 88.5 ... nan nan nan</div><input id='attrs-d5cdcec1-6697-496e-8672-04fd26ca79cb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d5cdcec1-6697-496e-8672-04fd26ca79cb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-986c5f2b-e7d7-4e41-9234-da0d4b879899' class='xr-var-data-in' type='checkbox'><label for='data-986c5f2b-e7d7-4e41-9234-da0d4b879899' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan],\n",
+       "       [ nan],\n",
+       "       [88.5],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Furan_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 5.3 5.3 ... nan nan nan nan</div><input id='attrs-85f34532-0ec6-401c-b7c9-d1eab9eb84d0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-85f34532-0ec6-401c-b7c9-d1eab9eb84d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aefc575c-6683-4c8a-b10c-891ce4f8d2b5' class='xr-var-data-in' type='checkbox'><label for='data-aefc575c-6683-4c8a-b10c-891ce4f8d2b5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [5.3],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x2MeFuran_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 2.6 2.6 ... nan nan nan nan</div><input id='attrs-4d1aa535-16f1-4e75-b70c-7bd54e805ddb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4d1aa535-16f1-4e75-b70c-7bd54e805ddb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dc9e0aa7-c94b-4739-8360-45084c75c5e7' class='xr-var-data-in' type='checkbox'><label for='data-dc9e0aa7-c94b-4739-8360-45084c75c5e7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [2.6],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x3MeFuran_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 16.9 16.9 ... nan nan nan</div><input id='attrs-cb6388bd-1227-4977-8a4f-07dd0d6f2f12' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cb6388bd-1227-4977-8a4f-07dd0d6f2f12' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-29fa0f6e-e7f9-485d-8a10-34ff3f7d6902' class='xr-var-data-in' type='checkbox'><label for='data-29fa0f6e-e7f9-485d-8a10-34ff3f7d6902' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan],\n",
+       "       [ nan],\n",
+       "       [16.9],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Furfural_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan -8.889e+05 ... nan nan nan</div><input id='attrs-5bf5bd46-9050-4752-a082-0c8168980ce0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5bf5bd46-9050-4752-a082-0c8168980ce0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7a6d0c27-331e-4fbd-9a97-b59fd834ee7e' class='xr-var-data-in' type='checkbox'><label for='data-7a6d0c27-331e-4fbd-9a97-b59fd834ee7e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[     nan],\n",
+       "       [     nan],\n",
+       "       [-888888.],\n",
+       "       ...,\n",
+       "       [     nan],\n",
+       "       [     nan],\n",
+       "       [     nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HCN_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 255.0 255.0 ... nan nan nan</div><input id='attrs-89a9972f-9b89-4725-9876-ed7fa583aa66' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-89a9972f-9b89-4725-9876-ed7fa583aa66' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7683ca56-af13-46ae-824c-b16b6e9b9cd7' class='xr-var-data-in' type='checkbox'><label for='data-7683ca56-af13-46ae-824c-b16b6e9b9cd7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan],\n",
+       "       [ nan],\n",
+       "       [255.],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH3CN_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 219.4 219.4 ... nan nan nan</div><input id='attrs-1cdfbbb8-ed06-447a-a636-3267088fdd37' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1cdfbbb8-ed06-447a-a636-3267088fdd37' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-59417868-8b44-472b-986d-7ff4e9ea596c' class='xr-var-data-in' type='checkbox'><label for='data-59417868-8b44-472b-986d-7ff4e9ea596c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan],\n",
+       "       [  nan],\n",
+       "       [219.4],\n",
+       "       ...,\n",
+       "       [  nan],\n",
+       "       [  nan],\n",
+       "       [  nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PropNitrile_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 8.3 8.3 ... nan nan nan nan</div><input id='attrs-4ca7f3d4-bc69-4098-a03a-ab05b27a7a58' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4ca7f3d4-bc69-4098-a03a-ab05b27a7a58' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-857ac4e9-b0a4-4dea-b1b2-ffd95131d9e8' class='xr-var-data-in' type='checkbox'><label for='data-857ac4e9-b0a4-4dea-b1b2-ffd95131d9e8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [8.3],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Acrylonitrile_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 6.3 6.3 ... nan nan nan nan</div><input id='attrs-49d27ebd-975e-4e8e-9742-b5df718ce676' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-49d27ebd-975e-4e8e-9742-b5df718ce676' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8d08846d-a6bc-4cca-bd3c-aeb16dc124ea' class='xr-var-data-in' type='checkbox'><label for='data-8d08846d-a6bc-4cca-bd3c-aeb16dc124ea' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [6.3],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MeAcrylonitrile_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan -8.889e+05 ... nan nan nan</div><input id='attrs-803b2212-d173-4b34-b315-d3a4be0d8d7f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-803b2212-d173-4b34-b315-d3a4be0d8d7f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9e6b6681-03d1-42a8-96b9-68a8fa9f4364' class='xr-var-data-in' type='checkbox'><label for='data-9e6b6681-03d1-42a8-96b9-68a8fa9f4364' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[     nan],\n",
+       "       [     nan],\n",
+       "       [-888888.],\n",
+       "       ...,\n",
+       "       [     nan],\n",
+       "       [     nan],\n",
+       "       [     nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Pyrrole_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan -8.889e+05 ... nan nan nan</div><input id='attrs-557a8c5a-c0c9-45c6-a542-f8af4eeafdab' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-557a8c5a-c0c9-45c6-a542-f8af4eeafdab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-13427523-5c78-4fea-8dcc-20454ee147ab' class='xr-var-data-in' type='checkbox'><label for='data-13427523-5c78-4fea-8dcc-20454ee147ab' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[     nan],\n",
+       "       [     nan],\n",
+       "       [-888888.],\n",
+       "       ...,\n",
+       "       [     nan],\n",
+       "       [     nan],\n",
+       "       [     nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Nitromethane_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 36.8 36.8 ... nan nan nan</div><input id='attrs-cdf1abf0-7cd2-4382-b58a-7d1e3352d921' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cdf1abf0-7cd2-4382-b58a-7d1e3352d921' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7a5c986a-9a9f-458e-acce-74c621d28047' class='xr-var-data-in' type='checkbox'><label for='data-7a5c986a-9a9f-458e-acce-74c621d28047' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan],\n",
+       "       [ nan],\n",
+       "       [36.8],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MeONO2_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 6.85 6.85 ... nan nan nan</div><input id='attrs-fe7a5660-fd6c-4545-9367-6b2812351a84' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fe7a5660-fd6c-4545-9367-6b2812351a84' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5961490a-923f-45c9-8e50-65e96c98affa' class='xr-var-data-in' type='checkbox'><label for='data-5961490a-923f-45c9-8e50-65e96c98affa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan],\n",
+       "       [ nan],\n",
+       "       [6.85],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>EthONO2_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 4.18 4.18 ... nan nan nan</div><input id='attrs-bda7bae8-e623-455a-ab2c-ab20c8230ef5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bda7bae8-e623-455a-ab2c-ab20c8230ef5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f8cd2a2c-443c-4c8f-bafb-7afe865f5b06' class='xr-var-data-in' type='checkbox'><label for='data-f8cd2a2c-443c-4c8f-bafb-7afe865f5b06' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan],\n",
+       "       [ nan],\n",
+       "       [4.18],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>iPropONO2_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 22.68 22.68 ... nan nan nan</div><input id='attrs-de5dda0d-7cb8-4d2b-8d2e-f6d0c6dd5077' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-de5dda0d-7cb8-4d2b-8d2e-f6d0c6dd5077' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d61c7f0-2f81-49ee-9b26-3236e48f1258' class='xr-var-data-in' type='checkbox'><label for='data-1d61c7f0-2f81-49ee-9b26-3236e48f1258' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan],\n",
+       "       [  nan],\n",
+       "       [22.68],\n",
+       "       ...,\n",
+       "       [  nan],\n",
+       "       [  nan],\n",
+       "       [  nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x2ButONO2iButONO2_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 28.72 28.72 ... nan nan nan</div><input id='attrs-5ecba7e6-e961-492a-a23b-a0c94dfbee93' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5ecba7e6-e961-492a-a23b-a0c94dfbee93' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-705d5a25-3658-40d0-8e03-d057bc9e24f1' class='xr-var-data-in' type='checkbox'><label for='data-705d5a25-3658-40d0-8e03-d057bc9e24f1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan],\n",
+       "       [  nan],\n",
+       "       [28.72],\n",
+       "       ...,\n",
+       "       [  nan],\n",
+       "       [  nan],\n",
+       "       [  nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>UnknownC2H4O_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 61.04 61.04 ... nan nan nan</div><input id='attrs-301110da-df0f-401b-aa52-bd14fab16c28' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-301110da-df0f-401b-aa52-bd14fab16c28' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-333eedc4-a8bb-4c55-a8de-2f9f2eb0f056' class='xr-var-data-in' type='checkbox'><label for='data-333eedc4-a8bb-4c55-a8de-2f9f2eb0f056' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan],\n",
+       "       [  nan],\n",
+       "       [61.04],\n",
+       "       ...,\n",
+       "       [  nan],\n",
+       "       [  nan],\n",
+       "       [  nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>C3O2_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 8.46 8.46 ... nan nan nan</div><input id='attrs-172a53ba-1b95-464b-baf8-a3a7a492fe05' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-172a53ba-1b95-464b-baf8-a3a7a492fe05' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-56a302cf-caa5-4d2b-8c52-368d55454cc7' class='xr-var-data-in' type='checkbox'><label for='data-56a302cf-caa5-4d2b-8c52-368d55454cc7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan],\n",
+       "       [ nan],\n",
+       "       [8.46],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>THF_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 2.17 2.17 ... nan nan nan</div><input id='attrs-0eb90f87-aa1f-442b-9c3b-f882d7818b8d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0eb90f87-aa1f-442b-9c3b-f882d7818b8d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ade4050f-6b02-4c2b-81c1-7ba7a4bfd0a7' class='xr-var-data-in' type='checkbox'><label for='data-ade4050f-6b02-4c2b-81c1-7ba7a4bfd0a7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan],\n",
+       "       [ nan],\n",
+       "       [2.17],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x23Butanedione_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 24.91 24.91 ... nan nan nan</div><input id='attrs-8ea9550c-bbe6-4800-9b68-e0e91579e31d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8ea9550c-bbe6-4800-9b68-e0e91579e31d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-37db02e7-41e2-4dc7-9dea-20dc4f0eac6a' class='xr-var-data-in' type='checkbox'><label for='data-37db02e7-41e2-4dc7-9dea-20dc4f0eac6a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan],\n",
+       "       [  nan],\n",
+       "       [24.91],\n",
+       "       ...,\n",
+       "       [  nan],\n",
+       "       [  nan],\n",
+       "       [  nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>EthAcetate_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 2.66 2.66 ... nan nan nan</div><input id='attrs-38a5ac7b-9b97-4da1-864c-4f592b85fd1f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-38a5ac7b-9b97-4da1-864c-4f592b85fd1f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-56d2191c-9a62-41db-87df-865b21033a1e' class='xr-var-data-in' type='checkbox'><label for='data-56d2191c-9a62-41db-87df-865b21033a1e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan],\n",
+       "       [ nan],\n",
+       "       [2.66],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MePropionate_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 1.05 1.05 ... nan nan nan</div><input id='attrs-724effb0-94d3-4e0e-a41e-602baf0c82c4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-724effb0-94d3-4e0e-a41e-602baf0c82c4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-62603aaa-0d9a-4efd-9488-6818c1bb6039' class='xr-var-data-in' type='checkbox'><label for='data-62603aaa-0d9a-4efd-9488-6818c1bb6039' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan],\n",
+       "       [ nan],\n",
+       "       [1.05],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x2EthFuran_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan -8.889e+05 ... nan nan nan</div><input id='attrs-cb568153-5a00-460e-84d1-a1cd5c1765e4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cb568153-5a00-460e-84d1-a1cd5c1765e4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-31a6c12a-f674-411c-aaf7-69fdabecd3ee' class='xr-var-data-in' type='checkbox'><label for='data-31a6c12a-f674-411c-aaf7-69fdabecd3ee' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[     nan],\n",
+       "       [     nan],\n",
+       "       [-888888.],\n",
+       "       ...,\n",
+       "       [     nan],\n",
+       "       [     nan],\n",
+       "       [     nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>DimeFurans_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan -8.889e+05 ... nan nan nan</div><input id='attrs-939a0381-8e6c-47c6-becc-4b30dc6f3646' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-939a0381-8e6c-47c6-becc-4b30dc6f3646' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f717c166-57e9-460a-a2dc-1e306a183e81' class='xr-var-data-in' type='checkbox'><label for='data-f717c166-57e9-460a-a2dc-1e306a183e81' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[     nan],\n",
+       "       [     nan],\n",
+       "       [-888888.],\n",
+       "       ...,\n",
+       "       [     nan],\n",
+       "       [     nan],\n",
+       "       [     nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>UnknownC6H8O_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan -8.889e+05 ... nan nan nan</div><input id='attrs-2366fa5e-a342-424f-bd08-32394db35b24' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2366fa5e-a342-424f-bd08-32394db35b24' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-20ef08ce-4249-483c-885a-b1f2e38fd5ae' class='xr-var-data-in' type='checkbox'><label for='data-20ef08ce-4249-483c-885a-b1f2e38fd5ae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[     nan],\n",
+       "       [     nan],\n",
+       "       [-888888.],\n",
+       "       ...,\n",
+       "       [     nan],\n",
+       "       [     nan],\n",
+       "       [     nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>VinylFuranA_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan -8.889e+05 ... nan nan nan</div><input id='attrs-8a628856-52fe-4b31-8de9-71aea051e8c2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8a628856-52fe-4b31-8de9-71aea051e8c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d4d0975d-7e13-44dd-a9a0-f5b9d92841d9' class='xr-var-data-in' type='checkbox'><label for='data-d4d0975d-7e13-44dd-a9a0-f5b9d92841d9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[     nan],\n",
+       "       [     nan],\n",
+       "       [-888888.],\n",
+       "       ...,\n",
+       "       [     nan],\n",
+       "       [     nan],\n",
+       "       [     nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>VinylFuranB_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan -8.889e+05 ... nan nan nan</div><input id='attrs-89bc31ca-dc68-4bf5-b20f-f6f73b918a52' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-89bc31ca-dc68-4bf5-b20f-f6f73b918a52' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-22689530-8466-444b-9825-69cc8ee982bd' class='xr-var-data-in' type='checkbox'><label for='data-22689530-8466-444b-9825-69cc8ee982bd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[     nan],\n",
+       "       [     nan],\n",
+       "       [-888888.],\n",
+       "       ...,\n",
+       "       [     nan],\n",
+       "       [     nan],\n",
+       "       [     nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x3Furaldehyde_TOGA_APEL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan -8.889e+05 ... nan nan nan</div><input id='attrs-a6fec31a-16d6-4123-b3b6-630c6b4a9233' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a6fec31a-16d6-4123-b3b6-630c6b4a9233' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3818d2df-368f-41c8-b649-6c2fa21c7722' class='xr-var-data-in' type='checkbox'><label for='data-3818d2df-368f-41c8-b649-6c2fa21c7722' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[     nan],\n",
+       "       [     nan],\n",
+       "       [-888888.],\n",
+       "       ...,\n",
+       "       [     nan],\n",
+       "       [     nan],\n",
+       "       [     nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>C2Cl4_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-b07663ba-08cd-450d-af6b-51df0cc3d5a5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b07663ba-08cd-450d-af6b-51df0cc3d5a5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-29e1875b-1d14-468c-bf8b-d69ed742d210' class='xr-var-data-in' type='checkbox'><label for='data-29e1875b-1d14-468c-bf8b-d69ed742d210' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CHCl3_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-331d50a6-1c06-4145-9622-17e9d4a117fb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-331d50a6-1c06-4145-9622-17e9d4a117fb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e62558d5-e449-43ae-925d-d65eb693b784' class='xr-var-data-in' type='checkbox'><label for='data-e62558d5-e449-43ae-925d-d65eb693b784' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Ethane_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-230cf95b-a599-4afa-b834-45285df7d183' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-230cf95b-a599-4afa-b834-45285df7d183' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2152107c-c1fe-4edf-b67e-07697a73e51f' class='xr-var-data-in' type='checkbox'><label for='data-2152107c-c1fe-4edf-b67e-07697a73e51f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Propane_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-b6446904-c73d-44f2-b7b1-e151fad4e9a0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b6446904-c73d-44f2-b7b1-e151fad4e9a0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bd756e11-99c6-40b5-b861-69ef67fbb7db' class='xr-var-data-in' type='checkbox'><label for='data-bd756e11-99c6-40b5-b861-69ef67fbb7db' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nButane_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-9dcd7a66-b470-43c6-9c56-7183cf600a55' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9dcd7a66-b470-43c6-9c56-7183cf600a55' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fbfe2806-8f25-4a43-9878-48c1c19fbc40' class='xr-var-data-in' type='checkbox'><label for='data-fbfe2806-8f25-4a43-9878-48c1c19fbc40' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>iButane_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-6f714a8b-6110-4247-a3b8-4445effdf256' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6f714a8b-6110-4247-a3b8-4445effdf256' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-de9dbf41-04e2-45e2-8486-76d78844ea7d' class='xr-var-data-in' type='checkbox'><label for='data-de9dbf41-04e2-45e2-8486-76d78844ea7d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nPentane_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-02d1913c-a51b-4d61-a4b2-cdeeb35483ec' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-02d1913c-a51b-4d61-a4b2-cdeeb35483ec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a4d2a691-c2fe-446f-a6e5-0c3d5b04bc48' class='xr-var-data-in' type='checkbox'><label for='data-a4d2a691-c2fe-446f-a6e5-0c3d5b04bc48' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>iPentane_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-a34154be-29b9-4e10-8736-2c22b3511c9d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a34154be-29b9-4e10-8736-2c22b3511c9d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c9a9bd15-f1da-42f7-8714-b2b3b85bb2dc' class='xr-var-data-in' type='checkbox'><label for='data-c9a9bd15-f1da-42f7-8714-b2b3b85bb2dc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nHexane_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-a2a61a8b-a3bd-4b1d-8a81-8b42a33cc515' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a2a61a8b-a3bd-4b1d-8a81-8b42a33cc515' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-28580759-dc5b-48e7-aafb-432f2bd9c73b' class='xr-var-data-in' type='checkbox'><label for='data-28580759-dc5b-48e7-aafb-432f2bd9c73b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x2MePentane_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-3497b2a8-de90-4915-87aa-5a00f4533d28' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3497b2a8-de90-4915-87aa-5a00f4533d28' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3f7331c4-b949-4b93-bab5-d9561b03f89c' class='xr-var-data-in' type='checkbox'><label for='data-3f7331c4-b949-4b93-bab5-d9561b03f89c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x3MePentane_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-856567d0-793f-4fd9-a98e-15232b6a56a1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-856567d0-793f-4fd9-a98e-15232b6a56a1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4853b170-c672-49f5-99c1-50ad0dd9f8a2' class='xr-var-data-in' type='checkbox'><label for='data-4853b170-c672-49f5-99c1-50ad0dd9f8a2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x22DiMeButane_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-2c920541-d0aa-4de3-9854-2ea07d5956a4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2c920541-d0aa-4de3-9854-2ea07d5956a4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d6b06a28-f35f-4daa-8b8f-f6702346accb' class='xr-var-data-in' type='checkbox'><label for='data-d6b06a28-f35f-4daa-8b8f-f6702346accb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x24DiMePentane_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-12709edb-b2f2-45fc-a714-5688dd8c64da' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-12709edb-b2f2-45fc-a714-5688dd8c64da' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4f2bd3ff-3426-4a12-b32c-8ae7e88be9f0' class='xr-var-data-in' type='checkbox'><label for='data-4f2bd3ff-3426-4a12-b32c-8ae7e88be9f0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nOctane_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-89dd212f-57a8-4164-a00c-3fe3f2bde383' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-89dd212f-57a8-4164-a00c-3fe3f2bde383' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-74ed63d9-eddd-4cae-85b3-fdaed2da817c' class='xr-var-data-in' type='checkbox'><label for='data-74ed63d9-eddd-4cae-85b3-fdaed2da817c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x224TriMePentane_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-f6bcfc71-91c1-4ad4-98a1-a9f8d15807a2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f6bcfc71-91c1-4ad4-98a1-a9f8d15807a2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f1d1e36f-52d7-4c14-8895-de90768577d8' class='xr-var-data-in' type='checkbox'><label for='data-f1d1e36f-52d7-4c14-8895-de90768577d8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nNonane_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-bf909b53-0609-4fea-b2c9-a297c18c07e3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bf909b53-0609-4fea-b2c9-a297c18c07e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-43393270-07cf-49e1-a3c2-7db87ada8acd' class='xr-var-data-in' type='checkbox'><label for='data-43393270-07cf-49e1-a3c2-7db87ada8acd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nDecane_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-013aa47e-c62c-47a8-8f41-02ff69f5049a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-013aa47e-c62c-47a8-8f41-02ff69f5049a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bd6acc73-2cda-4c5b-bf63-1523922cee2c' class='xr-var-data-in' type='checkbox'><label for='data-bd6acc73-2cda-4c5b-bf63-1523922cee2c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MeCycPentane_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-f8d83635-50d2-4a26-8722-f42125983645' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f8d83635-50d2-4a26-8722-f42125983645' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d475b520-9431-4b1a-9e1b-ef2e36793318' class='xr-var-data-in' type='checkbox'><label for='data-d475b520-9431-4b1a-9e1b-ef2e36793318' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CycHexane_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-9336e4d6-ddbf-40fb-b9a1-a667a1eddf26' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9336e4d6-ddbf-40fb-b9a1-a667a1eddf26' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e0043159-f70d-40e2-85ad-42d139dd4755' class='xr-var-data-in' type='checkbox'><label for='data-e0043159-f70d-40e2-85ad-42d139dd4755' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MeCycHexane_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ee0d6703-9dd5-4b1a-b63e-50ca359c1827' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ee0d6703-9dd5-4b1a-b63e-50ca359c1827' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ea1361e1-348a-40f2-8b44-a29b93bf1d9a' class='xr-var-data-in' type='checkbox'><label for='data-ea1361e1-348a-40f2-8b44-a29b93bf1d9a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Ethyne_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-1d3630a6-389a-40e3-8c38-d0d74696c65d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1d3630a6-389a-40e3-8c38-d0d74696c65d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f4d9a767-50f4-4992-8f5e-1c6d86e76fb8' class='xr-var-data-in' type='checkbox'><label for='data-f4d9a767-50f4-4992-8f5e-1c6d86e76fb8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Ethene_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-6276ef08-7c83-402f-addd-22a5f8e3b831' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6276ef08-7c83-402f-addd-22a5f8e3b831' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eaea5a66-33d0-4e94-887e-9b6ce21c6b53' class='xr-var-data-in' type='checkbox'><label for='data-eaea5a66-33d0-4e94-887e-9b6ce21c6b53' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Propene_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-f5ed1316-bdcc-46e6-bfaa-d253dbbfa51e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f5ed1316-bdcc-46e6-bfaa-d253dbbfa51e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4269a3a8-917f-45dd-beac-687e0c804fe5' class='xr-var-data-in' type='checkbox'><label for='data-4269a3a8-917f-45dd-beac-687e0c804fe5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x1Butene_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-51da00ac-e588-4004-a6dc-c3915511574c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-51da00ac-e588-4004-a6dc-c3915511574c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-217e86e9-060f-4b2e-b622-25391fdf6f7a' class='xr-var-data-in' type='checkbox'><label for='data-217e86e9-060f-4b2e-b622-25391fdf6f7a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>c2Butene_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e95af34b-994e-43c6-9cd6-f60a4102ce6d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e95af34b-994e-43c6-9cd6-f60a4102ce6d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5a304930-cf20-476f-b54a-750028eff3ba' class='xr-var-data-in' type='checkbox'><label for='data-5a304930-cf20-476f-b54a-750028eff3ba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>t2butene_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-216b1d1d-4a6e-4c04-8018-daf21084aacf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-216b1d1d-4a6e-4c04-8018-daf21084aacf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d4711c60-ca1d-4a34-8faf-6ea23e7aff3b' class='xr-var-data-in' type='checkbox'><label for='data-d4711c60-ca1d-4a34-8faf-6ea23e7aff3b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>iButene_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-a54e8f98-8844-400e-b0be-03a4def0cdce' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a54e8f98-8844-400e-b0be-03a4def0cdce' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eb971b76-d792-4b01-9a8a-5c1f0d811289' class='xr-var-data-in' type='checkbox'><label for='data-eb971b76-d792-4b01-9a8a-5c1f0d811289' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x1Pentene_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e7b4d015-ba5d-4d97-8bef-52ff64f93695' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e7b4d015-ba5d-4d97-8bef-52ff64f93695' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9d63c6ed-c394-434b-8e7b-6f794d14eae7' class='xr-var-data-in' type='checkbox'><label for='data-9d63c6ed-c394-434b-8e7b-6f794d14eae7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>c2Pentene_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-1877d204-e383-41d2-a1fd-15fe7e04ce86' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1877d204-e383-41d2-a1fd-15fe7e04ce86' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ac58fb36-1d7f-4c9b-982b-059ffda9f7d9' class='xr-var-data-in' type='checkbox'><label for='data-ac58fb36-1d7f-4c9b-982b-059ffda9f7d9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>t2Pentene_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-d256ae6c-caf7-4734-a2ce-34ee33d9c378' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d256ae6c-caf7-4734-a2ce-34ee33d9c378' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-67421289-7f3c-4951-9ad6-76cbc6bcee0a' class='xr-var-data-in' type='checkbox'><label for='data-67421289-7f3c-4951-9ad6-76cbc6bcee0a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x2Me1Butene_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ff6b1ac2-77f3-4664-a02a-c71808ff10f1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ff6b1ac2-77f3-4664-a02a-c71808ff10f1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fe8bc7ce-220f-46e1-a5f2-3aa5fb5c3b1c' class='xr-var-data-in' type='checkbox'><label for='data-fe8bc7ce-220f-46e1-a5f2-3aa5fb5c3b1c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x3Me1Butene_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-dc149095-e9d8-4a49-bf7d-c69a5ab4251e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-dc149095-e9d8-4a49-bf7d-c69a5ab4251e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4889c893-77b5-4f3c-b43d-89eb877a56e7' class='xr-var-data-in' type='checkbox'><label for='data-4889c893-77b5-4f3c-b43d-89eb877a56e7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>t13Pentadiene_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-dcc0a3ef-ed07-4d5e-9c11-52d951369472' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-dcc0a3ef-ed07-4d5e-9c11-52d951369472' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8edeb199-ba40-49d0-b0dc-e867a8f5b76a' class='xr-var-data-in' type='checkbox'><label for='data-8edeb199-ba40-49d0-b0dc-e867a8f5b76a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Isoprene_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ae639d6e-0e67-43f8-919c-d31b5a1122a1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ae639d6e-0e67-43f8-919c-d31b5a1122a1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1844aca8-a7b2-4c40-a549-757328505df1' class='xr-var-data-in' type='checkbox'><label for='data-1844aca8-a7b2-4c40-a549-757328505df1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aPinene_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-bb4b7728-09ee-42a0-b119-9fe53de93535' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bb4b7728-09ee-42a0-b119-9fe53de93535' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-075d051f-21ae-48d9-a9e7-05aca2ab3879' class='xr-var-data-in' type='checkbox'><label for='data-075d051f-21ae-48d9-a9e7-05aca2ab3879' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Benzene_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-7671de2b-63f2-4946-be3c-07c40227e710' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7671de2b-63f2-4946-be3c-07c40227e710' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d7ad4aee-d14f-4552-a38a-ebd0e5cbf7d8' class='xr-var-data-in' type='checkbox'><label for='data-d7ad4aee-d14f-4552-a38a-ebd0e5cbf7d8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Toluene_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ecd2c39f-23ef-4f3d-bbd0-b9974c69c297' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ecd2c39f-23ef-4f3d-bbd0-b9974c69c297' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-52d9c0d5-7f0e-4141-9542-7dad51b03eae' class='xr-var-data-in' type='checkbox'><label for='data-52d9c0d5-7f0e-4141-9542-7dad51b03eae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>EthBenzene_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-5944b55a-d146-40f3-a6f4-244db2ed0a54' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5944b55a-d146-40f3-a6f4-244db2ed0a54' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9addbfdd-3475-40fb-b86c-672f273cacc8' class='xr-var-data-in' type='checkbox'><label for='data-9addbfdd-3475-40fb-b86c-672f273cacc8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>oXylene_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-663fbf61-4cc3-4503-aaea-3692680661a5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-663fbf61-4cc3-4503-aaea-3692680661a5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0147b10a-76ee-40d6-9cc9-3ac724d239cc' class='xr-var-data-in' type='checkbox'><label for='data-0147b10a-76ee-40d6-9cc9-3ac724d239cc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mpXylene_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-6a92b093-f89c-4b90-a939-91e2dc13ac9e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6a92b093-f89c-4b90-a939-91e2dc13ac9e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a3b5b62c-6cd3-4b05-8a10-1fe30a2823cd' class='xr-var-data-in' type='checkbox'><label for='data-a3b5b62c-6cd3-4b05-8a10-1fe30a2823cd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Acetone_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-64e8fe69-9a18-4a79-869b-00d5ea425721' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-64e8fe69-9a18-4a79-869b-00d5ea425721' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-618d359f-4d23-4ec8-8fa4-11fe274b78ac' class='xr-var-data-in' type='checkbox'><label for='data-618d359f-4d23-4ec8-8fa4-11fe274b78ac' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MEK_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-a1f51581-9d8f-4215-95b0-1ad8cec97649' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a1f51581-9d8f-4215-95b0-1ad8cec97649' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1f8251ff-e6cd-4199-8f3b-cbf70ab83a8d' class='xr-var-data-in' type='checkbox'><label for='data-1f8251ff-e6cd-4199-8f3b-cbf70ab83a8d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MeFormate_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-91358d81-58e6-4736-b83b-b04886209b1a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-91358d81-58e6-4736-b83b-b04886209b1a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-75b14e2d-db39-471f-9c11-6fccddfafd13' class='xr-var-data-in' type='checkbox'><label for='data-75b14e2d-db39-471f-9c11-6fccddfafd13' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Furan_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ea34dbfa-0a86-49c3-b9ef-2ab4c1de0f33' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ea34dbfa-0a86-49c3-b9ef-2ab4c1de0f33' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-88daa7ef-bf95-48db-90a3-03e94e722a1b' class='xr-var-data-in' type='checkbox'><label for='data-88daa7ef-bf95-48db-90a3-03e94e722a1b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH3CN_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-99940c1b-4ae8-431f-8be1-d15cfd4464bb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-99940c1b-4ae8-431f-8be1-d15cfd4464bb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-514bea7e-9e09-4fbc-b6d0-c93e910e2468' class='xr-var-data-in' type='checkbox'><label for='data-514bea7e-9e09-4fbc-b6d0-c93e910e2468' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Acrylonitrile_NOAAiWAS_GILMAN</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-2ec7fa70-0dca-4411-b76b-a005f0dbea2f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2ec7fa70-0dca-4411-b76b-a005f0dbea2f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3a2f7714-1a98-4abb-b375-62c8561b02a8' class='xr-var-data-in' type='checkbox'><label for='data-3a2f7714-1a98-4abb-b375-62c8561b02a8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HCN_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.3738 0.3895 0.4295 ... nan nan</div><input id='attrs-31972a75-702e-4cab-acc5-d3ec6c26f081' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-31972a75-702e-4cab-acc5-d3ec6c26f081' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8a5a3fab-8b53-4d7f-ab0c-c6fc19d90a3f' class='xr-var-data-in' type='checkbox'><label for='data-8a5a3fab-8b53-4d7f-ab0c-c6fc19d90a3f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.3738],\n",
+       "       [0.3895],\n",
+       "       [0.4295],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH2O_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-5c64e11b-f81a-4e07-afb0-93784a50f9a3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5c64e11b-f81a-4e07-afb0-93784a50f9a3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bd48a6f6-a76d-4412-84f6-e1afa7c6112c' class='xr-var-data-in' type='checkbox'><label for='data-bd48a6f6-a76d-4412-84f6-e1afa7c6112c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH3OH_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.844 5.678 5.472 ... nan nan nan</div><input id='attrs-a0474b35-cabe-4944-a353-a58ea8b1f101' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a0474b35-cabe-4944-a353-a58ea8b1f101' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d0a9538b-427a-4f3c-86f9-da15bf502763' class='xr-var-data-in' type='checkbox'><label for='data-d0a9538b-427a-4f3c-86f9-da15bf502763' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[5.844 ],\n",
+       "       [5.6777],\n",
+       "       [5.4719],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH3CN_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.1522 0.1612 0.1442 ... nan nan</div><input id='attrs-7b92ef0e-4da6-454a-b5b0-7c8789d0f162' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7b92ef0e-4da6-454a-b5b0-7c8789d0f162' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9728174a-7388-490e-85ef-4ba0974f7b8c' class='xr-var-data-in' type='checkbox'><label for='data-9728174a-7388-490e-85ef-4ba0974f7b8c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.1522],\n",
+       "       [0.1612],\n",
+       "       [0.1442],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HNCO_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.0272 0.0461 -0.0084 ... nan nan</div><input id='attrs-052b7ff0-4859-4b76-a0df-d7476bb5c7f6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-052b7ff0-4859-4b76-a0df-d7476bb5c7f6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ead5204f-c891-4088-a851-8d39d6dcee9f' class='xr-var-data-in' type='checkbox'><label for='data-ead5204f-c891-4088-a851-8d39d6dcee9f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-0.0272],\n",
+       "       [ 0.0461],\n",
+       "       [-0.0084],\n",
+       "       ...,\n",
+       "       [    nan],\n",
+       "       [    nan],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH3CHO_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.075 1.099 0.9414 ... nan nan nan</div><input id='attrs-26ec694d-6a68-4dab-a0ce-ee637e987205' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-26ec694d-6a68-4dab-a0ce-ee637e987205' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e8ddf1f7-01fb-4d66-9398-6381b8dfbca8' class='xr-var-data-in' type='checkbox'><label for='data-e8ddf1f7-01fb-4d66-9398-6381b8dfbca8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[1.0747],\n",
+       "       [1.0985],\n",
+       "       [0.9414],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>C2H5OH_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.15 1.03 0.8292 ... nan nan nan</div><input id='attrs-e4ed8e76-71d0-4b08-9e5d-6b7e03506c34' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e4ed8e76-71d0-4b08-9e5d-6b7e03506c34' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ebb690ae-d506-4c37-928e-90aab7426889' class='xr-var-data-in' type='checkbox'><label for='data-ebb690ae-d506-4c37-928e-90aab7426889' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[1.1499],\n",
+       "       [1.0299],\n",
+       "       [0.8292],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HCOOH_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.837 2.962 3.084 ... nan nan nan</div><input id='attrs-3ea8e62f-51a1-4d62-8a7d-4a08ffe8a650' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3ea8e62f-51a1-4d62-8a7d-4a08ffe8a650' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b1aae89f-57cc-4c30-972b-804776c9683c' class='xr-var-data-in' type='checkbox'><label for='data-b1aae89f-57cc-4c30-972b-804776c9683c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[2.8371],\n",
+       "       [2.962 ],\n",
+       "       [3.084 ],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Acrylonitrile_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0006 0.0 0.0 ... nan nan nan</div><input id='attrs-4211437a-e361-48c0-8b8e-145869d92615' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4211437a-e361-48c0-8b8e-145869d92615' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a8e22c05-7ede-4360-9f3b-262076311f30' class='xr-var-data-in' type='checkbox'><label for='data-a8e22c05-7ede-4360-9f3b-262076311f30' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.0006],\n",
+       "       [0.    ],\n",
+       "       [0.    ],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Acrolein_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.137 0.1097 0.1142 ... nan nan nan</div><input id='attrs-90fe743d-cb7b-493e-be9d-f49016e77e4c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-90fe743d-cb7b-493e-be9d-f49016e77e4c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c788d7b6-9232-41fa-be2d-b045171dcc2d' class='xr-var-data-in' type='checkbox'><label for='data-c788d7b6-9232-41fa-be2d-b045171dcc2d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.137 ],\n",
+       "       [0.1097],\n",
+       "       [0.1142],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>AcetonePropanal_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.844 3.86 3.754 ... nan nan nan</div><input id='attrs-e99f24be-5ee9-4648-9d91-5710a9bb8504' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e99f24be-5ee9-4648-9d91-5710a9bb8504' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5d6d9d34-3adf-4c47-bc05-a4524e4a8a6b' class='xr-var-data-in' type='checkbox'><label for='data-5d6d9d34-3adf-4c47-bc05-a4524e4a8a6b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[3.8442],\n",
+       "       [3.8602],\n",
+       "       [3.7541],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Glycolaldehyde_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.7678 0.8025 0.8136 ... nan nan</div><input id='attrs-a4008a10-22ad-47c1-a5f8-e4a086b84af7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a4008a10-22ad-47c1-a5f8-e4a086b84af7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9c4cd0e1-6976-4525-a2df-f1f7c0b025fc' class='xr-var-data-in' type='checkbox'><label for='data-9c4cd0e1-6976-4525-a2df-f1f7c0b025fc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.7678],\n",
+       "       [0.8025],\n",
+       "       [0.8136],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH3NO2_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0139 0.0154 0.0135 ... nan nan</div><input id='attrs-bcc23631-132a-44a6-ae1d-c3005440f0e3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bcc23631-132a-44a6-ae1d-c3005440f0e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-65889a04-a8f1-4ec0-9732-7ae34e7ec83c' class='xr-var-data-in' type='checkbox'><label for='data-65889a04-a8f1-4ec0-9732-7ae34e7ec83c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.0139],\n",
+       "       [0.0154],\n",
+       "       [0.0135],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>DMS_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0036 0.0075 0.0006 ... nan nan</div><input id='attrs-d9856a35-63d5-4eef-bfd9-2fb7b5d8d2c9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d9856a35-63d5-4eef-bfd9-2fb7b5d8d2c9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9cd2adf8-acf0-4a63-8984-4f66aa6455e5' class='xr-var-data-in' type='checkbox'><label for='data-9cd2adf8-acf0-4a63-8984-4f66aa6455e5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.0036],\n",
+       "       [0.0075],\n",
+       "       [0.0006],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>C4H5N_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.0006 0.0003 -0.0001 ... nan nan</div><input id='attrs-8d8595e5-af0b-4b18-80fb-bd80f0f2a05a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8d8595e5-af0b-4b18-80fb-bd80f0f2a05a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-10e88e3f-8ffe-4889-8695-95a45837b7e6' class='xr-var-data-in' type='checkbox'><label for='data-10e88e3f-8ffe-4889-8695-95a45837b7e6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-0.0006],\n",
+       "       [ 0.0003],\n",
+       "       [-0.0001],\n",
+       "       ...,\n",
+       "       [    nan],\n",
+       "       [    nan],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Isoprene_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.2988 0.2588 0.2286 ... nan nan</div><input id='attrs-218de168-2267-405e-8c03-9d7664a0328f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-218de168-2267-405e-8c03-9d7664a0328f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-70243131-86ce-4a26-9207-609c6412277c' class='xr-var-data-in' type='checkbox'><label for='data-70243131-86ce-4a26-9207-609c6412277c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.2988],\n",
+       "       [0.2588],\n",
+       "       [0.2286],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Furan_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.0166 -0.0154 -0.0263 ... nan nan</div><input id='attrs-f441d38c-f099-43a9-b13f-c90275689400' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f441d38c-f099-43a9-b13f-c90275689400' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6c8e6e17-1947-4e34-a590-392a536876de' class='xr-var-data-in' type='checkbox'><label for='data-6c8e6e17-1947-4e34-a590-392a536876de' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-0.0166],\n",
+       "       [-0.0154],\n",
+       "       [-0.0263],\n",
+       "       ...,\n",
+       "       [    nan],\n",
+       "       [    nan],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MVKMAC_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.3416 0.3288 0.2951 ... nan nan</div><input id='attrs-a7ff0617-7902-4604-9104-37206e5d0b5d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a7ff0617-7902-4604-9104-37206e5d0b5d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4802b0c9-51ba-494b-a3fd-851689b16252' class='xr-var-data-in' type='checkbox'><label for='data-4802b0c9-51ba-494b-a3fd-851689b16252' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.3416],\n",
+       "       [0.3288],\n",
+       "       [0.2951],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>C4Carbonyls_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.4069 0.4009 0.3925 ... nan nan</div><input id='attrs-70e70411-86d1-404f-a4c2-07791d66e59b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-70e70411-86d1-404f-a4c2-07791d66e59b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6ca882f4-3ecb-4f5d-8894-a1bddf35fadd' class='xr-var-data-in' type='checkbox'><label for='data-6ca882f4-3ecb-4f5d-8894-a1bddf35fadd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.4069],\n",
+       "       [0.4009],\n",
+       "       [0.3925],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>C3H6O2_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.4549 0.4702 0.4619 ... nan nan</div><input id='attrs-bbbc8421-27e6-4e73-aada-8e599e6ed126' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bbbc8421-27e6-4e73-aada-8e599e6ed126' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2242fb0b-5376-4ec4-a15a-e98d9fb848b8' class='xr-var-data-in' type='checkbox'><label for='data-2242fb0b-5376-4ec4-a15a-e98d9fb848b8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.4549],\n",
+       "       [0.4702],\n",
+       "       [0.4619],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Benzene_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.057 0.0533 0.0562 ... nan nan nan</div><input id='attrs-09ca698c-a216-4d19-b7ea-67d9bf2b5e41' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-09ca698c-a216-4d19-b7ea-67d9bf2b5e41' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3d31b85e-b546-43f9-8e7b-21fcab932cad' class='xr-var-data-in' type='checkbox'><label for='data-3d31b85e-b546-43f9-8e7b-21fcab932cad' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.057 ],\n",
+       "       [0.0533],\n",
+       "       [0.0562],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x2MeFuranx3MeFuran_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0662 0.0689 0.0502 ... nan nan</div><input id='attrs-d5939a3b-5551-4b32-91a8-f29bd1147ed0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d5939a3b-5551-4b32-91a8-f29bd1147ed0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a62f7a68-965b-4b98-99de-ca7404358420' class='xr-var-data-in' type='checkbox'><label for='data-a62f7a68-965b-4b98-99de-ca7404358420' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.0662],\n",
+       "       [0.0689],\n",
+       "       [0.0502],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x2Furanone_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.0091 -0.0092 -0.0175 ... nan nan</div><input id='attrs-d0cf497e-072e-437b-abb3-c2bb1e68883c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d0cf497e-072e-437b-abb3-c2bb1e68883c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e81f5ed0-40a8-4c7d-b3c4-b8686837d533' class='xr-var-data-in' type='checkbox'><label for='data-e81f5ed0-40a8-4c7d-b3c4-b8686837d533' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-0.0091],\n",
+       "       [-0.0092],\n",
+       "       [-0.0175],\n",
+       "       ...,\n",
+       "       [    nan],\n",
+       "       [    nan],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x23Butanedione_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0622 0.068 0.0665 ... nan nan nan</div><input id='attrs-e19ed19a-2779-4ebc-9e5e-c4d1233f0b1a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e19ed19a-2779-4ebc-9e5e-c4d1233f0b1a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-90abe933-feed-4ee0-93ea-cfe6df49fb78' class='xr-var-data-in' type='checkbox'><label for='data-90abe933-feed-4ee0-93ea-cfe6df49fb78' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.0622],\n",
+       "       [0.068 ],\n",
+       "       [0.0665],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Toluene_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.068 0.0527 0.0388 ... nan nan nan</div><input id='attrs-1f723074-4df2-4079-9f59-4713af0ab25a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1f723074-4df2-4079-9f59-4713af0ab25a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1fb1b8a4-ef01-4668-824f-02e4806b6f4a' class='xr-var-data-in' type='checkbox'><label for='data-1fb1b8a4-ef01-4668-824f-02e4806b6f4a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.068 ],\n",
+       "       [0.0527],\n",
+       "       [0.0388],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Phenol_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0137 0.0082 0.0093 ... nan nan</div><input id='attrs-bbbe37f1-3667-4608-8988-7578121026e8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bbbe37f1-3667-4608-8988-7578121026e8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8e8bc1b5-eece-4ac5-bcee-75fc221ac8dd' class='xr-var-data-in' type='checkbox'><label for='data-8e8bc1b5-eece-4ac5-bcee-75fc221ac8dd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.0137],\n",
+       "       [0.0082],\n",
+       "       [0.0093],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Furfural_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0004 0.0058 0.0051 ... nan nan</div><input id='attrs-5697555b-bcd4-4ff3-95c3-92f72ee166ae' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5697555b-bcd4-4ff3-95c3-92f72ee166ae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6eedd94f-2795-4d0e-8b35-e216d0db32eb' class='xr-var-data-in' type='checkbox'><label for='data-6eedd94f-2795-4d0e-8b35-e216d0db32eb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.0004],\n",
+       "       [0.0058],\n",
+       "       [0.0051],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>DimeFurans_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0289 0.0252 0.0179 ... nan nan</div><input id='attrs-2c932330-5d4e-4dc9-ae6e-6309edb9fe73' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2c932330-5d4e-4dc9-ae6e-6309edb9fe73' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6db204d9-4459-4242-9616-889f8d0b8960' class='xr-var-data-in' type='checkbox'><label for='data-6db204d9-4459-4242-9616-889f8d0b8960' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.0289],\n",
+       "       [0.0252],\n",
+       "       [0.0179],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MaleicAnhyd_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0045 0.0042 0.0049 ... nan nan</div><input id='attrs-2dac6eaf-ae07-43aa-8dbd-6ac7b290456c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2dac6eaf-ae07-43aa-8dbd-6ac7b290456c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c6ed99c4-6086-4d56-852a-7d6d323d3365' class='xr-var-data-in' type='checkbox'><label for='data-c6ed99c4-6086-4d56-852a-7d6d323d3365' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.0045],\n",
+       "       [0.0042],\n",
+       "       [0.0049],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>BenzNitrile_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0041 0.0024 0.0016 ... nan nan</div><input id='attrs-4a4d2575-d139-488b-823f-b1e7462564dc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4a4d2575-d139-488b-823f-b1e7462564dc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3adc78d8-0b49-4412-ba9a-3b666a1da40e' class='xr-var-data-in' type='checkbox'><label for='data-3adc78d8-0b49-4412-ba9a-3b666a1da40e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.0041],\n",
+       "       [0.0024],\n",
+       "       [0.0016],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Styrene_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.0001 0.0044 0.0011 ... nan nan</div><input id='attrs-55fd0ca8-4c12-41ff-a0b0-2883b3d10f70' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-55fd0ca8-4c12-41ff-a0b0-2883b3d10f70' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-be7715a6-d4d8-425f-b8f5-8628dd540def' class='xr-var-data-in' type='checkbox'><label for='data-be7715a6-d4d8-425f-b8f5-8628dd540def' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-0.0001],\n",
+       "       [ 0.0044],\n",
+       "       [ 0.0011],\n",
+       "       ...,\n",
+       "       [    nan],\n",
+       "       [    nan],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Benzaldehyde_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0115 0.0053 0.0093 ... nan nan</div><input id='attrs-c579fff5-6e89-47ff-970d-9d307da17327' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c579fff5-6e89-47ff-970d-9d307da17327' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d216cc5-7fbc-4914-800b-cddc6cb7e1e5' class='xr-var-data-in' type='checkbox'><label for='data-1d216cc5-7fbc-4914-800b-cddc6cb7e1e5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.0115],\n",
+       "       [0.0053],\n",
+       "       [0.0093],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>C8Aromatics_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0174 0.0151 0.0109 ... nan nan</div><input id='attrs-ba78e730-43d5-4e45-b81d-21cc13ab43a8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ba78e730-43d5-4e45-b81d-21cc13ab43a8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-edf74729-6388-43e3-b77c-3e807547af10' class='xr-var-data-in' type='checkbox'><label for='data-edf74729-6388-43e3-b77c-3e807547af10' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.0174],\n",
+       "       [0.0151],\n",
+       "       [0.0109],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>C7H8O_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0036 0.0092 0.0059 ... nan nan</div><input id='attrs-a59ca048-d16b-4bd4-a866-c53b04214b4d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a59ca048-d16b-4bd4-a866-c53b04214b4d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c6c81b4-ce5c-4259-885a-90455f8e5dc5' class='xr-var-data-in' type='checkbox'><label for='data-4c6c81b4-ce5c-4259-885a-90455f8e5dc5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.0036],\n",
+       "       [0.0092],\n",
+       "       [0.0059],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Catecholx5MeFurfural_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0112 0.0131 0.0109 ... nan nan</div><input id='attrs-739be000-b6fa-4f0c-89d1-0d8ce984b050' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-739be000-b6fa-4f0c-89d1-0d8ce984b050' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-908de09f-fcd4-44b2-b6d7-31dc60953839' class='xr-var-data-in' type='checkbox'><label for='data-908de09f-fcd4-44b2-b6d7-31dc60953839' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.0112],\n",
+       "       [0.0131],\n",
+       "       [0.0109],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>BenzFuran_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0049 -0.0004 -0.002 ... nan nan</div><input id='attrs-cc3b5d61-dc6d-4f87-a0b5-7a7d47a3a47b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cc3b5d61-dc6d-4f87-a0b5-7a7d47a3a47b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a417ccbf-b193-45b4-a156-f91a5b3e7f8f' class='xr-var-data-in' type='checkbox'><label for='data-a417ccbf-b193-45b4-a156-f91a5b3e7f8f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 0.0049],\n",
+       "       [-0.0004],\n",
+       "       [-0.002 ],\n",
+       "       ...,\n",
+       "       [    nan],\n",
+       "       [    nan],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>C9Aromatics_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0047 0.0054 0.0024 ... nan nan</div><input id='attrs-4ddf0612-f5d0-4b8a-950a-8e4073458a8c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4ddf0612-f5d0-4b8a-950a-8e4073458a8c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-42a0b596-ab56-4a72-a6a3-484a23bb7074' class='xr-var-data-in' type='checkbox'><label for='data-42a0b596-ab56-4a72-a6a3-484a23bb7074' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.0047],\n",
+       "       [0.0054],\n",
+       "       [0.0024],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>C6H4O3_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.0007 0.0018 -0.0009 ... nan nan</div><input id='attrs-0ea836f7-faea-4956-b023-68935eb20b38' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0ea836f7-faea-4956-b023-68935eb20b38' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a2f1520-a24c-4b76-870b-104cf1cb3c3f' class='xr-var-data-in' type='checkbox'><label for='data-1a2f1520-a24c-4b76-870b-104cf1cb3c3f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-0.0007],\n",
+       "       [ 0.0018],\n",
+       "       [-0.0009],\n",
+       "       ...,\n",
+       "       [    nan],\n",
+       "       [    nan],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Guaiacol_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0081 0.0086 0.0084 ... nan nan</div><input id='attrs-accbb74f-765c-4158-bab4-959121508152' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-accbb74f-765c-4158-bab4-959121508152' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b416bd66-907e-4d84-b8fe-6ccb90ca72cf' class='xr-var-data-in' type='checkbox'><label for='data-b416bd66-907e-4d84-b8fe-6ccb90ca72cf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.0081],\n",
+       "       [0.0086],\n",
+       "       [0.0084],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Naphthalene_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0035 0.002 0.0034 ... nan nan nan</div><input id='attrs-8ff21944-e8b2-4542-b8b1-a6e0f07b2332' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8ff21944-e8b2-4542-b8b1-a6e0f07b2332' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a9d7c3a6-315a-4ad1-ae6b-cc7d6187665c' class='xr-var-data-in' type='checkbox'><label for='data-a9d7c3a6-315a-4ad1-ae6b-cc7d6187665c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.0035],\n",
+       "       [0.002 ],\n",
+       "       [0.0034],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Monoterpenes_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0362 0.0198 0.0174 ... nan nan</div><input id='attrs-2a0cab13-9120-4d96-9364-aeb4eb863e96' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2a0cab13-9120-4d96-9364-aeb4eb863e96' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-03b76a56-1857-46ab-88a4-247239c30e23' class='xr-var-data-in' type='checkbox'><label for='data-03b76a56-1857-46ab-88a4-247239c30e23' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.0362],\n",
+       "       [0.0198],\n",
+       "       [0.0174],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Cresols_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0061 0.0017 0.0088 ... nan nan</div><input id='attrs-4928b393-7ae2-4e18-8638-095117997788' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4928b393-7ae2-4e18-8638-095117997788' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d1f3cd63-d6b3-4b39-aade-eed99383b658' class='xr-var-data-in' type='checkbox'><label for='data-d1f3cd63-d6b3-4b39-aade-eed99383b658' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.0061],\n",
+       "       [0.0017],\n",
+       "       [0.0088],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Syringol_PTR_WARNEKE&amp;WISTHALER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0051 0.0035 0.0055 ... nan nan</div><input id='attrs-a0d8705e-5e95-4c2b-a6de-76ded2bd05cd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a0d8705e-5e95-4c2b-a6de-76ded2bd05cd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-14ae3cef-2f91-4b02-a6c9-d9f56dac092e' class='xr-var-data-in' type='checkbox'><label for='data-14ae3cef-2f91-4b02-a6c9-d9f56dac092e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.0051],\n",
+       "       [0.0035],\n",
+       "       [0.0055],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>BrCN_NOAACIMS_VERES</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.4485 0.2663 0.0433 ... nan nan</div><input id='attrs-3fec0899-e430-4012-b405-b90eb9130e08' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3fec0899-e430-4012-b405-b90eb9130e08' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-81d8e986-2807-4bd8-bd23-91ee358b6dcc' class='xr-var-data-in' type='checkbox'><label for='data-81d8e986-2807-4bd8-bd23-91ee358b6dcc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.4485],\n",
+       "       [0.2663],\n",
+       "       [0.0433],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>BrCl_NOAACIMS_VERES</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.2919 0.407 0.2058 ... nan nan nan</div><input id='attrs-a1bcd89b-7895-44c5-8159-4f4c77cd4494' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a1bcd89b-7895-44c5-8159-4f4c77cd4494' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-344185af-32f1-404a-aaf2-eb5021949ff0' class='xr-var-data-in' type='checkbox'><label for='data-344185af-32f1-404a-aaf2-eb5021949ff0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.2919],\n",
+       "       [0.407 ],\n",
+       "       [0.2058],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>BrO_NOAACIMS_VERES</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.206 0.0433 0.1046 ... nan nan nan</div><input id='attrs-db45f3b1-aa3c-43c7-b52d-35451c199f45' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-db45f3b1-aa3c-43c7-b52d-35451c199f45' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3aa8f2b8-0999-4718-a131-57d3a163f5be' class='xr-var-data-in' type='checkbox'><label for='data-3aa8f2b8-0999-4718-a131-57d3a163f5be' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.206 ],\n",
+       "       [0.0433],\n",
+       "       [0.1046],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH3COOCl_NOAACIMS_VERES</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.9702 0.6399 0.7261 ... nan nan</div><input id='attrs-801837a7-d1ef-4262-bddb-6c1e728b9ebd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-801837a7-d1ef-4262-bddb-6c1e728b9ebd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e9420195-f9d5-4868-b75b-e63722636797' class='xr-var-data-in' type='checkbox'><label for='data-e9420195-f9d5-4868-b75b-e63722636797' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.9702],\n",
+       "       [0.6399],\n",
+       "       [0.7261],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Cl2_NOAACIMS_VERES</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.1714 0.0765 0.1252 ... nan nan</div><input id='attrs-617d5f2c-246a-4729-a869-9033d495c0df' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-617d5f2c-246a-4729-a869-9033d495c0df' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b1d68f2-cb45-4d05-ae4c-9db47c8b1a3a' class='xr-var-data-in' type='checkbox'><label for='data-9b1d68f2-cb45-4d05-ae4c-9db47c8b1a3a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.1714],\n",
+       "       [0.0765],\n",
+       "       [0.1252],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ClNO2_NOAACIMS_VERES</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.1803 0.1531 0.0838 ... nan nan</div><input id='attrs-db04d3ec-6077-48e7-aff1-fcc11fcbb419' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-db04d3ec-6077-48e7-aff1-fcc11fcbb419' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7a69f774-69c5-4be0-a45c-9d10dba2b8e4' class='xr-var-data-in' type='checkbox'><label for='data-7a69f774-69c5-4be0-a45c-9d10dba2b8e4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.1803],\n",
+       "       [0.1531],\n",
+       "       [0.0838],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HCN_NOAACIMS_VERES</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>64.66 108.0 115.0 ... nan nan nan</div><input id='attrs-faee030b-ce96-422f-81b2-27849b99f34e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-faee030b-ce96-422f-81b2-27849b99f34e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7f0a9f1c-2fb4-4ba6-b78d-9d1c311b64c3' class='xr-var-data-in' type='checkbox'><label for='data-7f0a9f1c-2fb4-4ba6-b78d-9d1c311b64c3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 64.66],\n",
+       "       [108.04],\n",
+       "       [114.96],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HCOOH_NOAACIMS_VERES</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>856.5 820.6 814.2 ... nan nan nan</div><input id='attrs-638a2b73-d607-47d4-9b67-b01dd5280284' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-638a2b73-d607-47d4-9b67-b01dd5280284' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f2f557ce-aa81-4aa1-b4db-de973584e6c6' class='xr-var-data-in' type='checkbox'><label for='data-f2f557ce-aa81-4aa1-b4db-de973584e6c6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[856.54],\n",
+       "       [820.6 ],\n",
+       "       [814.25],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HNCO_NOAACIMS_VERES</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>221.7 148.7 174.4 ... nan nan nan</div><input id='attrs-09afec80-6712-4d0b-b0e8-48ae69198e5d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-09afec80-6712-4d0b-b0e8-48ae69198e5d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ade4478f-3b77-4160-a0ac-793d64f8775b' class='xr-var-data-in' type='checkbox'><label for='data-ade4478f-3b77-4160-a0ac-793d64f8775b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[221.6561],\n",
+       "       [148.6502],\n",
+       "       [174.4033],\n",
+       "       ...,\n",
+       "       [     nan],\n",
+       "       [     nan],\n",
+       "       [     nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HPMTF_NOAACIMS_VERES</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-c8cec0fe-ba02-4b8b-af08-d26c661c295c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c8cec0fe-ba02-4b8b-af08-d26c661c295c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-19b8ec03-f03b-4799-a3eb-29a77db9aaab' class='xr-var-data-in' type='checkbox'><label for='data-19b8ec03-f03b-4799-a3eb-29a77db9aaab' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>BUTENE-HN-1Hz_CIT_WENNBERG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.53 1.56 2.11 1.18 ... nan nan nan</div><input id='attrs-4de0a0f9-9e62-476b-b572-1c64d9d3111f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4de0a0f9-9e62-476b-b572-1c64d9d3111f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7356a9ae-612e-4fbf-92c2-9e34fb529084' class='xr-var-data-in' type='checkbox'><label for='data-7356a9ae-612e-4fbf-92c2-9e34fb529084' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.53],\n",
+       "       [1.56],\n",
+       "       [2.11],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>BUTENE-HP-1Hz_CIT_WENNBERG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.95 1.45 2.88 0.5 ... nan nan nan</div><input id='attrs-37df83cc-f648-4c85-99b7-8c84052e4ae3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-37df83cc-f648-4c85-99b7-8c84052e4ae3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a80e92db-31bb-4710-a264-7e061121717c' class='xr-var-data-in' type='checkbox'><label for='data-a80e92db-31bb-4710-a264-7e061121717c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.95],\n",
+       "       [1.45],\n",
+       "       [2.88],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ETHENE-HN-1Hz_CIT_WENNBERG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.21 0.66 1.25 0.36 ... nan nan nan</div><input id='attrs-a3feb029-fe9c-481f-90e7-9231520a6300' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a3feb029-fe9c-481f-90e7-9231520a6300' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-db4cab33-7168-4722-85d1-d1f9832ce90e' class='xr-var-data-in' type='checkbox'><label for='data-db4cab33-7168-4722-85d1-d1f9832ce90e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[1.21],\n",
+       "       [0.66],\n",
+       "       [1.25],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ETHENE-HP-1Hz_CIT_WENNBERG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.17 1.99 1.67 3.32 ... nan nan nan</div><input id='attrs-a2e3dd3e-52e1-4bd2-aa4f-d209b2a8a91a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a2e3dd3e-52e1-4bd2-aa4f-d209b2a8a91a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6b5d226a-2781-4157-90d0-ae5b80b91e4e' class='xr-var-data-in' type='checkbox'><label for='data-6b5d226a-2781-4157-90d0-ae5b80b91e4e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[2.17],\n",
+       "       [1.99],\n",
+       "       [1.67],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PHENOL-1Hz_CIT_WENNBERG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-4.11 -0.71 -3.51 ... nan nan nan</div><input id='attrs-a181ebea-57d9-42db-94fe-04fc5b5a361a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a181ebea-57d9-42db-94fe-04fc5b5a361a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f00c55c9-a8f5-438b-a3f9-25ca475cb984' class='xr-var-data-in' type='checkbox'><label for='data-f00c55c9-a8f5-438b-a3f9-25ca475cb984' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-4.11],\n",
+       "       [-0.71],\n",
+       "       [-3.51],\n",
+       "       ...,\n",
+       "       [  nan],\n",
+       "       [  nan],\n",
+       "       [  nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>H2O2-1Hz_CIT_WENNBERG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>633.2 653.2 715.0 ... nan nan nan</div><input id='attrs-6a2d7276-21cc-4c3e-9fc7-b9042c5b0c37' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6a2d7276-21cc-4c3e-9fc7-b9042c5b0c37' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-568665ac-15fa-4499-83e7-4b873b21719c' class='xr-var-data-in' type='checkbox'><label for='data-568665ac-15fa-4499-83e7-4b873b21719c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[633.19],\n",
+       "       [653.25],\n",
+       "       [714.99],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ISOPN-1Hz_CIT_WENNBERG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.96 3.4 3.73 2.86 ... nan nan nan</div><input id='attrs-28215eeb-593a-4133-95cf-3a3f433d146f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-28215eeb-593a-4133-95cf-3a3f433d146f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-176243d9-d4f6-4182-b7a7-13efbc4d0325' class='xr-var-data-in' type='checkbox'><label for='data-176243d9-d4f6-4182-b7a7-13efbc4d0325' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[3.96],\n",
+       "       [3.4 ],\n",
+       "       [3.73],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PROPENE-HN-1Hz_CIT_WENNBERG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.86 0.94 0.55 0.53 ... nan nan nan</div><input id='attrs-834aac05-6062-4af5-a56f-27e353f18bf8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-834aac05-6062-4af5-a56f-27e353f18bf8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6c498d2a-3738-4b02-b8dc-d3cda1c8668d' class='xr-var-data-in' type='checkbox'><label for='data-6c498d2a-3738-4b02-b8dc-d3cda1c8668d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.86],\n",
+       "       [0.94],\n",
+       "       [0.55],\n",
+       "       ...,\n",
+       "       [ nan],\n",
+       "       [ nan],\n",
+       "       [ nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PROPENE-HP-1Hz_CIT_WENNBERG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>11.89 10.18 6.45 ... nan nan nan</div><input id='attrs-4c4ff780-5072-4857-8f90-c65bc9d0aec2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4c4ff780-5072-4857-8f90-c65bc9d0aec2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-822392b6-ae69-4067-9201-b45032b69713' class='xr-var-data-in' type='checkbox'><label for='data-822392b6-ae69-4067-9201-b45032b69713' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[11.89],\n",
+       "       [10.18],\n",
+       "       [ 6.45],\n",
+       "       ...,\n",
+       "       [  nan],\n",
+       "       [  nan],\n",
+       "       [  nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HCN-1Hz_CIT_WENNBERG</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>156.1 133.8 146.2 ... nan nan nan</div><input id='attrs-9c61c05e-0742-4267-84f6-1c28d2457045' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9c61c05e-0742-4267-84f6-1c28d2457045' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0da3cb93-e1db-4bcb-b43f-6575a9f780f5' class='xr-var-data-in' type='checkbox'><label for='data-0da3cb93-e1db-4bcb-b43f-6575a9f780f5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[156.06],\n",
+       "       [133.84],\n",
+       "       [146.15],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SO2_LIF_ROLLINS</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... 197.2 nan nan</div><input id='attrs-b34cba3b-a807-4209-849a-52044539a7eb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b34cba3b-a807-4209-849a-52044539a7eb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6fafafaf-2800-4a54-baad-17be5329d870' class='xr-var-data-in' type='checkbox'><label for='data-6fafafaf-2800-4a54-baad-17be5329d870' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[     nan],\n",
+       "       [     nan],\n",
+       "       [     nan],\n",
+       "       ...,\n",
+       "       [197.1635],\n",
+       "       [     nan],\n",
+       "       [     nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CH3COCHO_ACES_WOMACK</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.568 1.703 1.772 ... nan nan</div><input id='attrs-02ff4f81-cb8f-4d3b-8008-f8d563272dbd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-02ff4f81-cb8f-4d3b-8008-f8d563272dbd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-25118e9c-111b-401e-8f74-4ca464e5418a' class='xr-var-data-in' type='checkbox'><label for='data-25118e9c-111b-401e-8f74-4ca464e5418a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 1.568  ],\n",
+       "       [ 1.703  ],\n",
+       "       [ 1.772  ],\n",
+       "       ...,\n",
+       "       [-0.32714],\n",
+       "       [     nan],\n",
+       "       [     nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CHOCHO_ACES_WOMACK</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.027 -0.021 -0.086 ... nan nan</div><input id='attrs-cd274c41-fc24-4564-821f-dd1195f9ec79' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cd274c41-fc24-4564-821f-dd1195f9ec79' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-281c64b1-207d-4c9c-acd5-0881cea0fec5' class='xr-var-data-in' type='checkbox'><label for='data-281c64b1-207d-4c9c-acd5-0881cea0fec5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 0.027   ],\n",
+       "       [-0.021   ],\n",
+       "       [-0.086   ],\n",
+       "       ...,\n",
+       "       [ 0.052857],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CNgt3nm_stdPT_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-514991f3-0874-4cfd-aa09-9dc55189649e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-514991f3-0874-4cfd-aa09-9dc55189649e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-efc8daec-93bf-4935-9985-f5faf8225859' class='xr-var-data-in' type='checkbox'><label for='data-efc8daec-93bf-4935-9985-f5faf8225859' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CNgt6nm_stdPT_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-08b05a5d-0c16-406f-8318-f003648c0af5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-08b05a5d-0c16-406f-8318-f003648c0af5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2c31447b-3478-417f-b6d8-8e506cda2318' class='xr-var-data-in' type='checkbox'><label for='data-2c31447b-3478-417f-b6d8-8e506cda2318' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CNgt20nm_stdPT_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-826a11b7-1821-4cf3-ad41-ad742aaea243' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-826a11b7-1821-4cf3-ad41-ad742aaea243' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-126e0514-8af1-4c68-84c5-86b46c5287db' class='xr-var-data-in' type='checkbox'><label for='data-126e0514-8af1-4c68-84c5-86b46c5287db' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CNgt20nm_nonvol_stdPT_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-d3e5e46e-42cb-41b3-b1c1-764c7a4d80f8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d3e5e46e-42cb-41b3-b1c1-764c7a4d80f8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bed76505-1111-43ac-97d9-d2767b99cc33' class='xr-var-data-in' type='checkbox'><label for='data-bed76505-1111-43ac-97d9-d2767b99cc33' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Ngt100nm_LAS_stdPT_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-38fbad02-2cd2-45a9-90ab-3b507b031030' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-38fbad02-2cd2-45a9-90ab-3b507b031030' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c75425da-ba5c-4bbc-9874-08ffd68b9787' class='xr-var-data-in' type='checkbox'><label for='data-c75425da-ba5c-4bbc-9874-08ffd68b9787' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Ngt100nm_LAS_nonvol_stdPT_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-f22a3662-616d-4607-87e8-3a419a0f05a1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f22a3662-616d-4607-87e8-3a419a0f05a1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-896c7958-eb9c-4f7a-aafe-12a00d9acd69' class='xr-var-data-in' type='checkbox'><label for='data-896c7958-eb9c-4f7a-aafe-12a00d9acd69' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CCN_034_stdPT_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-d5ab5914-10ab-4a88-9841-e4e4d5b18a31' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d5ab5914-10ab-4a88-9841-e4e4d5b18a31' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-88710eb6-e2ac-4c8e-b74a-5f0d8a5353bd' class='xr-var-data-in' type='checkbox'><label for='data-88710eb6-e2ac-4c8e-b74a-5f0d8a5353bd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>N_800to50000nm_CPSPD_stdPT_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-c8810ba9-0f45-41c2-9578-fed8bd7e0ff1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c8810ba9-0f45-41c2-9578-fed8bd7e0ff1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8d6f226f-83a6-463d-9b4b-9e2f6a7085bd' class='xr-var-data-in' type='checkbox'><label for='data-8d6f226f-83a6-463d-9b4b-9e2f6a7085bd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>V_800to50000nm_CPSPD_stdPT_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-0a762e8b-c1e7-440c-8735-9fd50f0e966d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0a762e8b-c1e7-440c-8735-9fd50f0e966d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-28ea7103-e954-4cd1-b708-6afed0735591' class='xr-var-data-in' type='checkbox'><label for='data-28ea7103-e954-4cd1-b708-6afed0735591' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>N_2000to50000nm_CDP_ambPT_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-0f44d305-0eb5-44f6-ae62-e340370372b7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0f44d305-0eb5-44f6-ae62-e340370372b7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1c388dc6-2566-445c-bb41-2afe02b952ca' class='xr-var-data-in' type='checkbox'><label for='data-1c388dc6-2566-445c-bb41-2afe02b952ca' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>V_2000to50000nm_CDP_ambPT_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-5302e9f0-d1ec-4670-a21a-1c093fe81865' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5302e9f0-d1ec-4670-a21a-1c093fe81865' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f894007b-e54d-4ddd-87de-f4d32ae22e65' class='xr-var-data-in' type='checkbox'><label for='data-f894007b-e54d-4ddd-87de-f4d32ae22e65' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nSMPS_stdPT_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ca953165-a87a-4a33-a7e1-95aeef14fc3b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ca953165-a87a-4a33-a7e1-95aeef14fc3b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a97385f-83cb-4f07-8c84-719e6db155f5' class='xr-var-data-in' type='checkbox'><label for='data-1a97385f-83cb-4f07-8c84-719e6db155f5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sSMPS_stdPT_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-5e494ecd-d4ce-4121-b764-706c0e67a9af' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5e494ecd-d4ce-4121-b764-706c0e67a9af' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-764a83b1-7043-4483-9714-b8057b7a3f51' class='xr-var-data-in' type='checkbox'><label for='data-764a83b1-7043-4483-9714-b8057b7a3f51' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vSMPS_stdPT_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-fd755200-b0dd-4059-84d4-acf4ef7eb63d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fd755200-b0dd-4059-84d4-acf4ef7eb63d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1f47b462-4b28-4381-b087-255625440dfc' class='xr-var-data-in' type='checkbox'><label for='data-1f47b462-4b28-4381-b087-255625440dfc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nLAScold_stdPT_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-2ebc5bf0-25cc-4fdd-9a5c-4c0bb616faed' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2ebc5bf0-25cc-4fdd-9a5c-4c0bb616faed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-63db4742-3996-459b-aa74-4d6271acb844' class='xr-var-data-in' type='checkbox'><label for='data-63db4742-3996-459b-aa74-4d6271acb844' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nLAShot_stdPT_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-0f5532d5-e2d3-49ae-9b1a-2cdb17c0e286' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0f5532d5-e2d3-49ae-9b1a-2cdb17c0e286' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ba95e8f-8a07-4a9e-92be-bc9a1f6725e4' class='xr-var-data-in' type='checkbox'><label for='data-5ba95e8f-8a07-4a9e-92be-bc9a1f6725e4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>totSC450_stdPT_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-327d700f-2b0f-414d-88a8-24af78d5ebec' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-327d700f-2b0f-414d-88a8-24af78d5ebec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6385613c-cd8e-4d43-8310-1e768caab97b' class='xr-var-data-in' type='checkbox'><label for='data-6385613c-cd8e-4d43-8310-1e768caab97b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>totSC550_stdPT_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-f3372aab-4af6-4ba3-939a-8bfcabb1a028' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f3372aab-4af6-4ba3-939a-8bfcabb1a028' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d8ff21c5-3ba0-4539-87df-b884bae86e63' class='xr-var-data-in' type='checkbox'><label for='data-d8ff21c5-3ba0-4539-87df-b884bae86e63' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>totSC700_stdPT_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-9d2edc2e-5f4f-4e64-a8bb-3d7044f59732' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9d2edc2e-5f4f-4e64-a8bb-3d7044f59732' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1079ffae-b11b-414f-8ad0-0cee6b318ee4' class='xr-var-data-in' type='checkbox'><label for='data-1079ffae-b11b-414f-8ad0-0cee6b318ee4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Abs470_stdPT_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-3804e60f-6b5e-42a4-b1af-fa0605cc7a6a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3804e60f-6b5e-42a4-b1af-fa0605cc7a6a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d842a4a9-b2b8-48f5-8c07-3fc3bf9ef5e8' class='xr-var-data-in' type='checkbox'><label for='data-d842a4a9-b2b8-48f5-8c07-3fc3bf9ef5e8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Abs532_stdPT_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-f9cf7b8e-03c0-48a8-9259-a4bc7db049c5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f9cf7b8e-03c0-48a8-9259-a4bc7db049c5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-77edbcb1-f819-44b9-9aec-9ab73171f378' class='xr-var-data-in' type='checkbox'><label for='data-77edbcb1-f819-44b9-9aec-9ab73171f378' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Abs660_stdPT_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-8506a615-833e-4873-8dea-e5bd8f0b0638' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8506a615-833e-4873-8dea-e5bd8f0b0638' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4feade8c-12a6-4615-8ca3-0757f1e20da4' class='xr-var-data-in' type='checkbox'><label for='data-4feade8c-12a6-4615-8ca3-0757f1e20da4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gamma450_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-4746e22f-fbd7-4e96-81af-f67724a84a13' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4746e22f-fbd7-4e96-81af-f67724a84a13' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a61eb3c-80b4-45d7-b2b9-7bfc53585d6c' class='xr-var-data-in' type='checkbox'><label for='data-1a61eb3c-80b4-45d7-b2b9-7bfc53585d6c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gamma550_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-eb6e7a33-6029-4ef8-bf07-34703e88c1d8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-eb6e7a33-6029-4ef8-bf07-34703e88c1d8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-422885b7-27a8-4d09-8221-ac3f0d716b58' class='xr-var-data-in' type='checkbox'><label for='data-422885b7-27a8-4d09-8221-ac3f0d716b58' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gamma700_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-4f524ae6-7caf-4202-928e-f5a95c29a413' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4f524ae6-7caf-4202-928e-f5a95c29a413' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bca9075e-966d-4ed7-98c0-8488ae42731a' class='xr-var-data-in' type='checkbox'><label for='data-bca9075e-966d-4ed7-98c0-8488ae42731a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fRH450_RH20to85_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-4b34c7d1-9428-45cf-b806-060aac399988' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4b34c7d1-9428-45cf-b806-060aac399988' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1e87df58-b428-4f72-bfb0-d8eb159eb1ab' class='xr-var-data-in' type='checkbox'><label for='data-1e87df58-b428-4f72-bfb0-d8eb159eb1ab' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fRH550_RH20to85_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-43cc3940-c246-4134-858a-61a5707d69c8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-43cc3940-c246-4134-858a-61a5707d69c8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c03da1cf-ff1c-4117-8213-33e45dec4c46' class='xr-var-data-in' type='checkbox'><label for='data-c03da1cf-ff1c-4117-8213-33e45dec4c46' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fRH700_RH20to85_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-8c63d200-872b-4ec9-bcdd-9bec0239307e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8c63d200-872b-4ec9-bcdd-9bec0239307e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-359976ff-aa45-48fb-a547-e6da3a812589' class='xr-var-data-in' type='checkbox'><label for='data-359976ff-aa45-48fb-a547-e6da3a812589' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ambSC450_stdPT_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-182ea344-5d96-4691-aaf3-59d2e3f3acf4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-182ea344-5d96-4691-aaf3-59d2e3f3acf4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a93185d3-0fa3-47f1-8a29-2b611d2bf1e5' class='xr-var-data-in' type='checkbox'><label for='data-a93185d3-0fa3-47f1-8a29-2b611d2bf1e5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ambSC550_stdPT_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-a03a2093-77af-4f6b-ac3d-5aecaf5ee7a0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a03a2093-77af-4f6b-ac3d-5aecaf5ee7a0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7b66d95a-b19c-47bb-b717-a754c2f70732' class='xr-var-data-in' type='checkbox'><label for='data-7b66d95a-b19c-47bb-b717-a754c2f70732' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ambSC700_stdPT_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-a05f006a-6f7b-40f5-9a23-05cddb923284' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a05f006a-6f7b-40f5-9a23-05cddb923284' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-01d2eaf4-c252-465d-a711-4c897c107cba' class='xr-var-data-in' type='checkbox'><label for='data-01d2eaf4-c252-465d-a711-4c897c107cba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dryAEscat_550to700_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-df09c837-8a53-4d7e-9377-2c7736d89d03' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-df09c837-8a53-4d7e-9377-2c7736d89d03' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c07bf5b5-993c-4777-8779-e621cf42fdf6' class='xr-var-data-in' type='checkbox'><label for='data-c07bf5b5-993c-4777-8779-e621cf42fdf6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>drySSA_450_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-06e31338-5928-457d-ab7d-40fd44419201' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-06e31338-5928-457d-ab7d-40fd44419201' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c393b489-fd2a-4051-9f2b-bd92ab96b3fe' class='xr-var-data-in' type='checkbox'><label for='data-c393b489-fd2a-4051-9f2b-bd92ab96b3fe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>drySSA_550_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-6b4c39a2-438c-4c51-a14c-75894b02f44b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6b4c39a2-438c-4c51-a14c-75894b02f44b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0f0df46d-a558-4c9e-8fc2-49dc6ac24b8b' class='xr-var-data-in' type='checkbox'><label for='data-0f0df46d-a558-4c9e-8fc2-49dc6ac24b8b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>drySSA_700_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-41c22ba9-4edf-490c-b5ca-ab83412d5bdc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-41c22ba9-4edf-490c-b5ca-ab83412d5bdc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-014c9ba7-1d8f-4da5-a6fa-ee504f8a532a' class='xr-var-data-in' type='checkbox'><label for='data-014c9ba7-1d8f-4da5-a6fa-ee504f8a532a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ambSSA_450_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-aee89a06-7e2b-49eb-bcaf-d5feca9e80c7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-aee89a06-7e2b-49eb-bcaf-d5feca9e80c7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3fd042d5-9fd9-4409-8000-1f35f2479047' class='xr-var-data-in' type='checkbox'><label for='data-3fd042d5-9fd9-4409-8000-1f35f2479047' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ambSSA_550_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-63befec6-9592-4e9b-8e93-39700d0daea4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-63befec6-9592-4e9b-8e93-39700d0daea4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3c60d5db-5c3f-4a86-9f2b-49c4e8fdf302' class='xr-var-data-in' type='checkbox'><label for='data-3c60d5db-5c3f-4a86-9f2b-49c4e8fdf302' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ambSSA_700_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-1d3d130e-78c5-462e-9648-be33c85bf0f3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1d3d130e-78c5-462e-9648-be33c85bf0f3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d526e27-9ffe-4fb9-ab74-a6a705907c48' class='xr-var-data-in' type='checkbox'><label for='data-1d526e27-9ffe-4fb9-ab74-a6a705907c48' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dryEXT_532_stdPT_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-52928da8-badb-41ee-9193-889e17e26484' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-52928da8-badb-41ee-9193-889e17e26484' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ae81225a-d230-4011-a3fd-b8da56e244fd' class='xr-var-data-in' type='checkbox'><label for='data-ae81225a-d230-4011-a3fd-b8da56e244fd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ambEXT_532_stdPT_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ba6e3376-ff62-4274-80d9-b742d2545ba5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ba6e3376-ff62-4274-80d9-b742d2545ba5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9140d9e4-01e1-41c1-905a-047e077e6655' class='xr-var-data-in' type='checkbox'><label for='data-9140d9e4-01e1-41c1-905a-047e077e6655' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ext_dry_664_WAGNER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... 18.19 17.12 nan</div><input id='attrs-2314e433-0a8c-44f0-8d64-68ddaab79e4b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2314e433-0a8c-44f0-8d64-68ddaab79e4b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b594c619-8b89-4f49-b671-e276f8f6fd8a' class='xr-var-data-in' type='checkbox'><label for='data-b594c619-8b89-4f49-b671-e276f8f6fd8a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[    nan],\n",
+       "       [    nan],\n",
+       "       [    nan],\n",
+       "       ...,\n",
+       "       [18.1893],\n",
+       "       [17.1234],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ext_dry_532_WAGNER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... 29.13 25.87 nan</div><input id='attrs-417cfb74-41a0-4b98-9a52-40b98195ded2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-417cfb74-41a0-4b98-9a52-40b98195ded2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8b45e5b9-d182-49ee-8a0a-f1f85fa178fa' class='xr-var-data-in' type='checkbox'><label for='data-8b45e5b9-d182-49ee-8a0a-f1f85fa178fa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[    nan],\n",
+       "       [    nan],\n",
+       "       [    nan],\n",
+       "       ...,\n",
+       "       [29.1258],\n",
+       "       [25.867 ],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ext_dry_405_WAGNER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... 45.27 44.35 nan</div><input id='attrs-f38352ab-90d5-499d-bb32-37047259e05a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f38352ab-90d5-499d-bb32-37047259e05a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7b4ae6d6-e007-4bc9-bfff-4e833b15e218' class='xr-var-data-in' type='checkbox'><label for='data-7b4ae6d6-e007-4bc9-bfff-4e833b15e218' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[    nan],\n",
+       "       [    nan],\n",
+       "       [    nan],\n",
+       "       ...,\n",
+       "       [45.2742],\n",
+       "       [44.3451],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>abs_dry_664_WAGNER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e41c7579-31b6-4e5c-99a1-a0fe1021d304' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e41c7579-31b6-4e5c-99a1-a0fe1021d304' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-55c6c430-abaa-405a-aafc-4d7c499d8208' class='xr-var-data-in' type='checkbox'><label for='data-55c6c430-abaa-405a-aafc-4d7c499d8208' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>abs_dry_532_WAGNER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-3bfc19f2-8a4c-46c3-b014-d27679289a20' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3bfc19f2-8a4c-46c3-b014-d27679289a20' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4e3dc1cb-9357-4381-bb44-ff08821ef07d' class='xr-var-data-in' type='checkbox'><label for='data-4e3dc1cb-9357-4381-bb44-ff08821ef07d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>abs_dry_405_WAGNER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-bb2c7ca7-e348-446e-90d6-49d603ad5012' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bb2c7ca7-e348-446e-90d6-49d603ad5012' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4516ac8d-ab4d-43ec-aaf9-55351a8107d7' class='xr-var-data-in' type='checkbox'><label for='data-4516ac8d-ab4d-43ec-aaf9-55351a8107d7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>AOP_RH_dry_WAGNER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>34.07 34.07 34.04 ... 32.23 32.17</div><input id='attrs-35743e20-6c97-4422-bf24-c08bf30e227a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-35743e20-6c97-4422-bf24-c08bf30e227a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-50fc2f05-5bab-42e1-803e-4fbb4e528851' class='xr-var-data-in' type='checkbox'><label for='data-50fc2f05-5bab-42e1-803e-4fbb4e528851' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[34.0728],\n",
+       "       [34.0678],\n",
+       "       [34.0448],\n",
+       "       ...,\n",
+       "       [32.2655],\n",
+       "       [32.2279],\n",
+       "       [32.1668]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ext_medRH_664_WAGNER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... 29.42 24.5 nan</div><input id='attrs-fb82d337-7d00-4cb0-a644-30f932e60dfc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fb82d337-7d00-4cb0-a644-30f932e60dfc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-36c5e261-0819-416a-aa69-00cd46471839' class='xr-var-data-in' type='checkbox'><label for='data-36c5e261-0819-416a-aa69-00cd46471839' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[    nan],\n",
+       "       [    nan],\n",
+       "       [    nan],\n",
+       "       ...,\n",
+       "       [29.4163],\n",
+       "       [24.4985],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>AOP_RH_med_WAGNER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>78.38 78.85 79.8 ... 80.66 80.44</div><input id='attrs-7cae60b7-14c5-4a6e-9aa8-7c78118d60ec' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7cae60b7-14c5-4a6e-9aa8-7c78118d60ec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fc854152-b2e7-4670-91df-a10278658dfe' class='xr-var-data-in' type='checkbox'><label for='data-fc854152-b2e7-4670-91df-a10278658dfe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[78.3762],\n",
+       "       [78.8469],\n",
+       "       [79.803 ],\n",
+       "       ...,\n",
+       "       [79.6992],\n",
+       "       [80.6617],\n",
+       "       [80.44  ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ext_highRH_664_WAGNER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... 29.1 28.78 nan</div><input id='attrs-6e216367-09cc-4e88-bf26-c9f349cee169' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6e216367-09cc-4e88-bf26-c9f349cee169' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d3643cb5-2e21-4914-b972-8f26544c5b90' class='xr-var-data-in' type='checkbox'><label for='data-d3643cb5-2e21-4914-b972-8f26544c5b90' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[    nan],\n",
+       "       [    nan],\n",
+       "       [    nan],\n",
+       "       ...,\n",
+       "       [29.0982],\n",
+       "       [28.7837],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>AOP_RH_high_WAGNER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>84.99 84.72 84.2 ... 85.04 84.59</div><input id='attrs-60af8421-c3f4-42f1-bd71-e912be998126' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-60af8421-c3f4-42f1-bd71-e912be998126' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-43de7aa9-e444-4713-ad0f-90907a271c01' class='xr-var-data-in' type='checkbox'><label for='data-43de7aa9-e444-4713-ad0f-90907a271c01' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[84.9851],\n",
+       "       [84.7158],\n",
+       "       [84.1962],\n",
+       "       ...,\n",
+       "       [85.5692],\n",
+       "       [85.0406],\n",
+       "       [84.5869]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ext_TD_664_WAGNER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... 8.49 4.61 nan</div><input id='attrs-1e0ffce3-1f61-4f82-90d9-5678ff5cc33c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1e0ffce3-1f61-4f82-90d9-5678ff5cc33c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c61eb89f-cbd9-4843-aa91-1d5fc8067157' class='xr-var-data-in' type='checkbox'><label for='data-c61eb89f-cbd9-4843-aa91-1d5fc8067157' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[    nan],\n",
+       "       [    nan],\n",
+       "       [    nan],\n",
+       "       ...,\n",
+       "       [8.49026],\n",
+       "       [4.61039],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ext_TD_405_WAGNER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... 6.684 6.114 nan</div><input id='attrs-4c99b1b3-6d62-45fd-b070-a79c6a9f427e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4c99b1b3-6d62-45fd-b070-a79c6a9f427e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-11f01a84-8102-45cf-b678-5764976abcfc' class='xr-var-data-in' type='checkbox'><label for='data-11f01a84-8102-45cf-b678-5764976abcfc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[    nan],\n",
+       "       [    nan],\n",
+       "       [    nan],\n",
+       "       ...,\n",
+       "       [6.68408],\n",
+       "       [6.11433],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>abs_TD_664_WAGNER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-b01770d3-771c-496c-8ac4-756a8f1759c3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b01770d3-771c-496c-8ac4-756a8f1759c3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-315d0d2b-b8af-41e2-a2ea-2081693eb13c' class='xr-var-data-in' type='checkbox'><label for='data-315d0d2b-b8af-41e2-a2ea-2081693eb13c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>abs_TD_405_WAGNER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-d6477f0e-bc49-4953-be38-2c087e996af5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d6477f0e-bc49-4953-be38-2c087e996af5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2adf28a5-e4ef-4fe7-94d5-37157e206e24' class='xr-var-data-in' type='checkbox'><label for='data-2adf28a5-e4ef-4fe7-94d5-37157e206e24' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>AOP_TD_bypass_flag_WAGNER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-2007742d-631c-449b-a60b-b7868fc9ba3f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2007742d-631c-449b-a60b-b7868fc9ba3f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-57bf5a6c-e82d-40ea-9b4e-ad13fd4e0dbf' class='xr-var-data-in' type='checkbox'><label for='data-57bf5a6c-e82d-40ea-9b4e-ad13fd4e0dbf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.],\n",
+       "       [0.],\n",
+       "       [0.],\n",
+       "       ...,\n",
+       "       [0.],\n",
+       "       [0.],\n",
+       "       [0.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>AOP_filter_flag_WAGNER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 1.0 1.0 ... 0.0 0.0 0.0</div><input id='attrs-be2ff6b3-7bce-4f1f-84f4-cd204f70a1c2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-be2ff6b3-7bce-4f1f-84f4-cd204f70a1c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-77296a56-89e3-4855-b740-81a7124a44a8' class='xr-var-data-in' type='checkbox'><label for='data-77296a56-89e3-4855-b740-81a7124a44a8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[1.],\n",
+       "       [1.],\n",
+       "       [1.],\n",
+       "       ...,\n",
+       "       [0.],\n",
+       "       [0.],\n",
+       "       [0.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs300_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-d99e2262-7ad7-425a-ac04-2020fe8f40b3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d99e2262-7ad7-425a-ac04-2020fe8f40b3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6b029d78-4929-4ec2-ba48-36946346e96d' class='xr-var-data-in' type='checkbox'><label for='data-6b029d78-4929-4ec2-ba48-36946346e96d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs320_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-57a83f4f-2acd-4d07-9730-fc0d19ece14a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-57a83f4f-2acd-4d07-9730-fc0d19ece14a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-53726720-4c51-4e03-947e-a28bc5fb7190' class='xr-var-data-in' type='checkbox'><label for='data-53726720-4c51-4e03-947e-a28bc5fb7190' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs340_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-c9756667-50cc-4e67-9ab1-139dbd4e3448' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c9756667-50cc-4e67-9ab1-139dbd4e3448' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8119809b-c96c-44aa-85e9-878f9004f682' class='xr-var-data-in' type='checkbox'><label for='data-8119809b-c96c-44aa-85e9-878f9004f682' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs360_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ed7629ba-bbfc-4b6b-b697-96498f20e204' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ed7629ba-bbfc-4b6b-b697-96498f20e204' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-616e48f7-5927-43f7-bea4-234ee7877d32' class='xr-var-data-in' type='checkbox'><label for='data-616e48f7-5927-43f7-bea4-234ee7877d32' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs380_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-b580dbee-fc69-4962-bd87-08027a5ad9ef' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b580dbee-fc69-4962-bd87-08027a5ad9ef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c59875dc-3085-45a8-a57f-2946fd8df7d9' class='xr-var-data-in' type='checkbox'><label for='data-c59875dc-3085-45a8-a57f-2946fd8df7d9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs400_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-25277ebe-3f53-4dc3-9c7d-77fef974e074' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-25277ebe-3f53-4dc3-9c7d-77fef974e074' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bb5c35d7-ff3d-46ed-9b07-9e41a2472683' class='xr-var-data-in' type='checkbox'><label for='data-bb5c35d7-ff3d-46ed-9b07-9e41a2472683' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs420_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-952be604-0a28-438d-946d-b910d7f5834a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-952be604-0a28-438d-946d-b910d7f5834a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3d6a26f1-530a-4826-8570-283a973bd41d' class='xr-var-data-in' type='checkbox'><label for='data-3d6a26f1-530a-4826-8570-283a973bd41d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs440_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-524360ec-b01d-4413-a9ac-4dd82bad04fa' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-524360ec-b01d-4413-a9ac-4dd82bad04fa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f5ee2fa7-d9fa-4f02-9e8f-162fe8d6a106' class='xr-var-data-in' type='checkbox'><label for='data-f5ee2fa7-d9fa-4f02-9e8f-162fe8d6a106' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs460_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-1b8b7d9b-a410-4d6a-b117-df3ced1a8b37' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1b8b7d9b-a410-4d6a-b117-df3ced1a8b37' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bcc40df3-1727-4b90-8580-c7e8a51bc2c5' class='xr-var-data-in' type='checkbox'><label for='data-bcc40df3-1727-4b90-8580-c7e8a51bc2c5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs480_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-c02aae5f-969f-4f39-8187-a376ab8cf964' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c02aae5f-969f-4f39-8187-a376ab8cf964' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c8df2fe1-6de4-4076-834c-07a24e48d495' class='xr-var-data-in' type='checkbox'><label for='data-c8df2fe1-6de4-4076-834c-07a24e48d495' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs500_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e53d6b79-0550-448e-b237-2d18d9b8098a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e53d6b79-0550-448e-b237-2d18d9b8098a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ebeca37a-adbe-4f4a-b223-b04049dd3eda' class='xr-var-data-in' type='checkbox'><label for='data-ebeca37a-adbe-4f4a-b223-b04049dd3eda' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs520_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-40df204b-56cf-43fc-ba35-bb066567e1db' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-40df204b-56cf-43fc-ba35-bb066567e1db' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c8953ebf-a2b5-4afd-a3e3-f2da69fd7cf6' class='xr-var-data-in' type='checkbox'><label for='data-c8953ebf-a2b5-4afd-a3e3-f2da69fd7cf6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs540_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-5e153b23-af1a-46df-85cd-7913fc17a4f4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5e153b23-af1a-46df-85cd-7913fc17a4f4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c6184e42-42d4-4da4-8254-de5b11630348' class='xr-var-data-in' type='checkbox'><label for='data-c6184e42-42d4-4da4-8254-de5b11630348' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs560_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e8063ea2-e1bf-4b0a-8f23-bc4fb7ec0e0f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e8063ea2-e1bf-4b0a-8f23-bc4fb7ec0e0f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-13a8e104-16ee-497e-9f90-29af9480a538' class='xr-var-data-in' type='checkbox'><label for='data-13a8e104-16ee-497e-9f90-29af9480a538' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs580_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-0e3c9bf1-9b2b-4892-a1f0-de784b35f7df' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0e3c9bf1-9b2b-4892-a1f0-de784b35f7df' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-631c9ef6-d8a2-4d56-98fc-86fab0ab80c9' class='xr-var-data-in' type='checkbox'><label for='data-631c9ef6-d8a2-4d56-98fc-86fab0ab80c9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs600_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-48d41991-09f5-4626-8571-58b296081658' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-48d41991-09f5-4626-8571-58b296081658' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f284cae9-02c7-42ee-ae82-00040f737fd3' class='xr-var-data-in' type='checkbox'><label for='data-f284cae9-02c7-42ee-ae82-00040f737fd3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs620_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-9cabe587-c701-454f-b3bc-96720d968162' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9cabe587-c701-454f-b3bc-96720d968162' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9a9018b2-1fc6-4c66-92e4-fc5232dcb406' class='xr-var-data-in' type='checkbox'><label for='data-9a9018b2-1fc6-4c66-92e4-fc5232dcb406' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs640_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-1e592ecd-7069-4499-af4b-101abd7b59b3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1e592ecd-7069-4499-af4b-101abd7b59b3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9fe86e1b-cef3-480c-a0ad-27f9378ede7e' class='xr-var-data-in' type='checkbox'><label for='data-9fe86e1b-cef3-480c-a0ad-27f9378ede7e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs660_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-343b8ceb-504c-4fab-b785-6df5cb8e05c6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-343b8ceb-504c-4fab-b785-6df5cb8e05c6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-db22c0c7-f381-4bb5-91b2-765a62e55e14' class='xr-var-data-in' type='checkbox'><label for='data-db22c0c7-f381-4bb5-91b2-765a62e55e14' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs680_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e533ba91-d64c-480c-911a-a7d7518436e2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e533ba91-d64c-480c-911a-a7d7518436e2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-69d0f9b0-a766-4eac-adb4-740651f81444' class='xr-var-data-in' type='checkbox'><label for='data-69d0f9b0-a766-4eac-adb4-740651f81444' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs700_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-aabefb52-ce97-4d0e-952c-8af5e649eace' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-aabefb52-ce97-4d0e-952c-8af5e649eace' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9a7ad774-0dc7-460b-9c16-5b43cb7fcebf' class='xr-var-data-in' type='checkbox'><label for='data-9a7ad774-0dc7-460b-9c16-5b43cb7fcebf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs365_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-53c82510-690b-4dfe-b20a-62e27a8f3088' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-53c82510-690b-4dfe-b20a-62e27a8f3088' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b2151d29-6005-4c2c-a6ca-e0b80452da6b' class='xr-var-data-in' type='checkbox'><label for='data-b2151d29-6005-4c2c-a6ca-e0b80452da6b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSOC_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-03b3017e-8481-4109-886b-3b891b595905' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-03b3017e-8481-4109-886b-3b891b595905' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-861d35b6-b8b7-4f62-81f7-16f79fdcc9ab' class='xr-var-data-in' type='checkbox'><label for='data-861d35b6-b8b7-4f62-81f7-16f79fdcc9ab' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs300_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-7fa34479-1e1a-4c19-9efc-28b27656ff5c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7fa34479-1e1a-4c19-9efc-28b27656ff5c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8a16f39c-6219-4ef3-913b-6dc1d596e249' class='xr-var-data-in' type='checkbox'><label for='data-8a16f39c-6219-4ef3-913b-6dc1d596e249' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs320_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e063a941-945c-4640-a614-b8a8266f22ad' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e063a941-945c-4640-a614-b8a8266f22ad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ecb4ac90-806f-471d-8065-96aad3629735' class='xr-var-data-in' type='checkbox'><label for='data-ecb4ac90-806f-471d-8065-96aad3629735' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs340_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-0d463c1e-b071-45a7-86f6-01b98b8c0844' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0d463c1e-b071-45a7-86f6-01b98b8c0844' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-327b7466-8e3d-41dc-adf3-987f305dbcb3' class='xr-var-data-in' type='checkbox'><label for='data-327b7466-8e3d-41dc-adf3-987f305dbcb3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs360_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-3702f10d-994e-470e-85e4-776cbeba8781' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3702f10d-994e-470e-85e4-776cbeba8781' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d7583608-d189-4f78-85f2-03b7d40d2195' class='xr-var-data-in' type='checkbox'><label for='data-d7583608-d189-4f78-85f2-03b7d40d2195' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs380_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-6c99f211-1495-4d53-bf55-f162231ba9c4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6c99f211-1495-4d53-bf55-f162231ba9c4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b3345920-383f-4108-be8b-7dc44144aec8' class='xr-var-data-in' type='checkbox'><label for='data-b3345920-383f-4108-be8b-7dc44144aec8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs400_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-58b02e40-3861-4792-b931-df3b0cbba4a1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-58b02e40-3861-4792-b931-df3b0cbba4a1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-768b5903-1024-4645-9c2c-e82e0c81bb03' class='xr-var-data-in' type='checkbox'><label for='data-768b5903-1024-4645-9c2c-e82e0c81bb03' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs420_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-99c6ec55-9fac-476c-841f-034f643d3768' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-99c6ec55-9fac-476c-841f-034f643d3768' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9af32663-8a93-485c-8e18-4d7c69e9dc42' class='xr-var-data-in' type='checkbox'><label for='data-9af32663-8a93-485c-8e18-4d7c69e9dc42' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs440_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-3b4b8d7d-36d1-40e3-9a5a-f48628944163' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3b4b8d7d-36d1-40e3-9a5a-f48628944163' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4bffa66f-e6a0-452b-bc9f-ca94c92b5509' class='xr-var-data-in' type='checkbox'><label for='data-4bffa66f-e6a0-452b-bc9f-ca94c92b5509' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs460_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ca015a75-4bed-4d16-be1d-3e639142f582' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ca015a75-4bed-4d16-be1d-3e639142f582' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a5720d47-9de6-4955-a3df-b899aaf3be9b' class='xr-var-data-in' type='checkbox'><label for='data-a5720d47-9de6-4955-a3df-b899aaf3be9b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs480_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-1671b2b9-5c86-46b6-aa0f-4589482f4a97' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1671b2b9-5c86-46b6-aa0f-4589482f4a97' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7a7db27d-b0e2-4a9f-8c88-17d191546430' class='xr-var-data-in' type='checkbox'><label for='data-7a7db27d-b0e2-4a9f-8c88-17d191546430' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs500_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-c36141b4-9144-48a0-b50d-0ee77735a5cb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c36141b4-9144-48a0-b50d-0ee77735a5cb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6da76472-d2a5-43ee-9929-055b80c532b6' class='xr-var-data-in' type='checkbox'><label for='data-6da76472-d2a5-43ee-9929-055b80c532b6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs520_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-177b2b5c-3b56-4f85-95bb-e2f1e78d40e1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-177b2b5c-3b56-4f85-95bb-e2f1e78d40e1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-344912f2-d30a-4ced-8a43-f018a68b3abc' class='xr-var-data-in' type='checkbox'><label for='data-344912f2-d30a-4ced-8a43-f018a68b3abc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs540_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-9117ecef-5f74-4e22-bb5f-15e69182bf07' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9117ecef-5f74-4e22-bb5f-15e69182bf07' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e891010-a958-47cd-86c0-c61040dbebb5' class='xr-var-data-in' type='checkbox'><label for='data-5e891010-a958-47cd-86c0-c61040dbebb5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs560_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-33bb9db0-b827-4c33-9222-9c317ac1a077' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-33bb9db0-b827-4c33-9222-9c317ac1a077' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dab5c351-dd02-4ba4-bfd5-19088faa2f1f' class='xr-var-data-in' type='checkbox'><label for='data-dab5c351-dd02-4ba4-bfd5-19088faa2f1f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs580_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-abf28e99-1f92-47a7-8d01-1cbe52fc1f58' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-abf28e99-1f92-47a7-8d01-1cbe52fc1f58' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d189cb5a-0c98-4771-b347-dec80a8a64f7' class='xr-var-data-in' type='checkbox'><label for='data-d189cb5a-0c98-4771-b347-dec80a8a64f7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs600_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-07ffedcc-9e31-4fce-b35b-7b3232573147' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-07ffedcc-9e31-4fce-b35b-7b3232573147' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8154f2c6-93af-4658-8819-188a49549afc' class='xr-var-data-in' type='checkbox'><label for='data-8154f2c6-93af-4658-8819-188a49549afc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs620_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-06761365-7fdf-4ec1-afd3-5aa65feda857' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-06761365-7fdf-4ec1-afd3-5aa65feda857' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3330c69d-2a36-4f7b-b701-b26f4236bd83' class='xr-var-data-in' type='checkbox'><label for='data-3330c69d-2a36-4f7b-b701-b26f4236bd83' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs640_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-42939f26-587f-41aa-aafd-99a53ad55dca' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-42939f26-587f-41aa-aafd-99a53ad55dca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8608424d-df0a-4151-9160-e460a3a84c26' class='xr-var-data-in' type='checkbox'><label for='data-8608424d-df0a-4151-9160-e460a3a84c26' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs660_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-98951318-08b5-44cc-8b14-2a02371ae6b8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-98951318-08b5-44cc-8b14-2a02371ae6b8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-106cb440-8d4d-40dc-a3e8-c011389a617f' class='xr-var-data-in' type='checkbox'><label for='data-106cb440-8d4d-40dc-a3e8-c011389a617f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs680_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-5b4b3ed3-4188-4768-8e3e-dd7d21d2e06e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5b4b3ed3-4188-4768-8e3e-dd7d21d2e06e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4accf907-3c92-403d-a5f8-75d1f31a52ac' class='xr-var-data-in' type='checkbox'><label for='data-4accf907-3c92-403d-a5f8-75d1f31a52ac' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs700_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-7ed35df3-fad4-41ab-9dd1-fe350ad9737e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7ed35df3-fad4-41ab-9dd1-fe350ad9737e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eb680aeb-c762-4e3b-af78-0653b1ac11a4' class='xr-var-data-in' type='checkbox'><label for='data-eb680aeb-c762-4e3b-af78-0653b1ac11a4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSAbs365_AERO_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ae5c4a79-9522-4cfa-b883-432bc6540429' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ae5c4a79-9522-4cfa-b883-432bc6540429' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6a7c7abf-60b4-4642-88e9-8f732686707f' class='xr-var-data-in' type='checkbox'><label for='data-6a7c7abf-60b4-4642-88e9-8f732686707f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs300_MC_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.754 1.754 1.754 ... nan nan nan</div><input id='attrs-803b8349-fbb9-4fbc-af84-96fc93987a85' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-803b8349-fbb9-4fbc-af84-96fc93987a85' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6f6b30f7-d4ab-41f9-afef-c8aab0b7572e' class='xr-var-data-in' type='checkbox'><label for='data-6f6b30f7-d4ab-41f9-afef-c8aab0b7572e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[1.7537],\n",
+       "       [1.7537],\n",
+       "       [1.7537],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs320_MC_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.616 1.616 1.616 ... nan nan nan</div><input id='attrs-6d74299d-9d78-42cc-8001-7b32ae312918' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6d74299d-9d78-42cc-8001-7b32ae312918' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fe0b5b3f-8abe-408e-9cd4-e5674bb80fbc' class='xr-var-data-in' type='checkbox'><label for='data-fe0b5b3f-8abe-408e-9cd4-e5674bb80fbc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[1.61601],\n",
+       "       [1.61601],\n",
+       "       [1.61601],\n",
+       "       ...,\n",
+       "       [    nan],\n",
+       "       [    nan],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs340_MC_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.236 1.236 1.236 ... nan nan nan</div><input id='attrs-c7db0bad-8b53-4ad7-9a2f-41ecdc3e8d8a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c7db0bad-8b53-4ad7-9a2f-41ecdc3e8d8a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-21a863ac-516a-49f4-b6fd-efa51fc7ec70' class='xr-var-data-in' type='checkbox'><label for='data-21a863ac-516a-49f4-b6fd-efa51fc7ec70' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[1.23578],\n",
+       "       [1.23578],\n",
+       "       [1.23578],\n",
+       "       ...,\n",
+       "       [    nan],\n",
+       "       [    nan],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs360_MC_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.9711 0.9711 0.9711 ... nan nan</div><input id='attrs-2b0ca63e-b56d-4e35-99a3-8870fc4fc4dc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2b0ca63e-b56d-4e35-99a3-8870fc4fc4dc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f6c99127-9f99-4a6a-8716-0c2821d43c73' class='xr-var-data-in' type='checkbox'><label for='data-f6c99127-9f99-4a6a-8716-0c2821d43c73' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.97112],\n",
+       "       [0.97112],\n",
+       "       [0.97112],\n",
+       "       ...,\n",
+       "       [    nan],\n",
+       "       [    nan],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs380_MC_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.831 0.831 0.831 ... nan nan nan</div><input id='attrs-61d0d284-6877-4d05-99db-51dcde6b3f4c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-61d0d284-6877-4d05-99db-51dcde6b3f4c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c16b932-f62b-47ad-884f-d26c6fd23c16' class='xr-var-data-in' type='checkbox'><label for='data-4c16b932-f62b-47ad-884f-d26c6fd23c16' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.83105],\n",
+       "       [0.83105],\n",
+       "       [0.83105],\n",
+       "       ...,\n",
+       "       [    nan],\n",
+       "       [    nan],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs400_MC_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.6922 0.6922 0.6922 ... nan nan</div><input id='attrs-539b95d5-fd38-4d5a-a25c-17d5f10829ad' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-539b95d5-fd38-4d5a-a25c-17d5f10829ad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5adf4070-cc59-43fb-b1c4-57d28daa17a1' class='xr-var-data-in' type='checkbox'><label for='data-5adf4070-cc59-43fb-b1c4-57d28daa17a1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.69224],\n",
+       "       [0.69224],\n",
+       "       [0.69224],\n",
+       "       ...,\n",
+       "       [    nan],\n",
+       "       [    nan],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs420_MC_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.6079 0.6079 0.6079 ... nan nan</div><input id='attrs-3fd09cbb-7376-4a2d-982e-8f1d8d0f641b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3fd09cbb-7376-4a2d-982e-8f1d8d0f641b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a544dc7d-686c-4425-90d7-4f11a9870e0f' class='xr-var-data-in' type='checkbox'><label for='data-a544dc7d-686c-4425-90d7-4f11a9870e0f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.60793],\n",
+       "       [0.60793],\n",
+       "       [0.60793],\n",
+       "       ...,\n",
+       "       [    nan],\n",
+       "       [    nan],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs440_MC_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.5151 0.5151 0.5151 ... nan nan</div><input id='attrs-800466e1-133c-40d6-9fe3-d42b04bacd13' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-800466e1-133c-40d6-9fe3-d42b04bacd13' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d1db1707-07bc-4e16-a633-13147ec25728' class='xr-var-data-in' type='checkbox'><label for='data-d1db1707-07bc-4e16-a633-13147ec25728' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.51514],\n",
+       "       [0.51514],\n",
+       "       [0.51514],\n",
+       "       ...,\n",
+       "       [    nan],\n",
+       "       [    nan],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs460_MC_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.4528 0.4528 0.4528 ... nan nan</div><input id='attrs-c17221ae-c55c-4203-8f44-7930414c8000' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c17221ae-c55c-4203-8f44-7930414c8000' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5f259497-1166-498f-9a13-58dfb9c57468' class='xr-var-data-in' type='checkbox'><label for='data-5f259497-1166-498f-9a13-58dfb9c57468' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.45279],\n",
+       "       [0.45279],\n",
+       "       [0.45279],\n",
+       "       ...,\n",
+       "       [    nan],\n",
+       "       [    nan],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs480_MC_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.3803 0.3803 0.3803 ... nan nan</div><input id='attrs-8bfa88f4-2e06-4819-b531-e64903fe2e61' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8bfa88f4-2e06-4819-b531-e64903fe2e61' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-222352c8-a76d-4050-82a5-7d767062af6f' class='xr-var-data-in' type='checkbox'><label for='data-222352c8-a76d-4050-82a5-7d767062af6f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.38028],\n",
+       "       [0.38028],\n",
+       "       [0.38028],\n",
+       "       ...,\n",
+       "       [    nan],\n",
+       "       [    nan],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs500_MC_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.3375 0.3375 0.3375 ... nan nan</div><input id='attrs-8ab614cb-d7f5-4c1b-80f3-28c4ab6007e3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8ab614cb-d7f5-4c1b-80f3-28c4ab6007e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a4f66630-16ec-4763-b548-509f3303ae8d' class='xr-var-data-in' type='checkbox'><label for='data-a4f66630-16ec-4763-b548-509f3303ae8d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.33745],\n",
+       "       [0.33745],\n",
+       "       [0.33745],\n",
+       "       ...,\n",
+       "       [    nan],\n",
+       "       [    nan],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs520_MC_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.2838 0.2838 0.2838 ... nan nan</div><input id='attrs-4b20df55-7d4e-4ff1-a2ff-a1d5b23c1e7d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4b20df55-7d4e-4ff1-a2ff-a1d5b23c1e7d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-26268367-f8d7-4b2a-9369-03b7027383a0' class='xr-var-data-in' type='checkbox'><label for='data-26268367-f8d7-4b2a-9369-03b7027383a0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.28382],\n",
+       "       [0.28382],\n",
+       "       [0.28382],\n",
+       "       ...,\n",
+       "       [    nan],\n",
+       "       [    nan],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs540_MC_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.2785 0.2785 0.2785 ... nan nan</div><input id='attrs-fd1b2af8-cf90-4063-9fc8-04b544c51392' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fd1b2af8-cf90-4063-9fc8-04b544c51392' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-08d2fce1-9baa-41e7-b62a-a27a5942c031' class='xr-var-data-in' type='checkbox'><label for='data-08d2fce1-9baa-41e7-b62a-a27a5942c031' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.27853],\n",
+       "       [0.27853],\n",
+       "       [0.27853],\n",
+       "       ...,\n",
+       "       [    nan],\n",
+       "       [    nan],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs560_MC_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.2692 0.2692 0.2692 ... nan nan</div><input id='attrs-59d87014-a5ca-45ef-a259-5c6d1a695554' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-59d87014-a5ca-45ef-a259-5c6d1a695554' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f629cc41-a11e-40f5-863b-54468ca4781a' class='xr-var-data-in' type='checkbox'><label for='data-f629cc41-a11e-40f5-863b-54468ca4781a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.2692],\n",
+       "       [0.2692],\n",
+       "       [0.2692],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs580_MC_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.2077 0.2077 0.2077 ... nan nan</div><input id='attrs-b0aa0b9b-bc8e-4d4f-bed2-7a65e77f910b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b0aa0b9b-bc8e-4d4f-bed2-7a65e77f910b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7438cfc7-cca3-4947-8941-101c009bc3fb' class='xr-var-data-in' type='checkbox'><label for='data-7438cfc7-cca3-4947-8941-101c009bc3fb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.20768],\n",
+       "       [0.20768],\n",
+       "       [0.20768],\n",
+       "       ...,\n",
+       "       [    nan],\n",
+       "       [    nan],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs600_MC_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.1844 0.1844 0.1844 ... nan nan</div><input id='attrs-9a2eb977-ad08-4651-8087-c0ee31287767' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9a2eb977-ad08-4651-8087-c0ee31287767' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-612564ea-20eb-4ffc-a59a-71b1cb870f3b' class='xr-var-data-in' type='checkbox'><label for='data-612564ea-20eb-4ffc-a59a-71b1cb870f3b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.18443],\n",
+       "       [0.18443],\n",
+       "       [0.18443],\n",
+       "       ...,\n",
+       "       [    nan],\n",
+       "       [    nan],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs620_MC_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.1732 0.1732 0.1732 ... nan nan</div><input id='attrs-b7644b84-86af-4f72-8deb-176640f054f9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b7644b84-86af-4f72-8deb-176640f054f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d774b6b8-7263-43d3-b772-e0532e4ddf01' class='xr-var-data-in' type='checkbox'><label for='data-d774b6b8-7263-43d3-b772-e0532e4ddf01' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.17322],\n",
+       "       [0.17322],\n",
+       "       [0.17322],\n",
+       "       ...,\n",
+       "       [    nan],\n",
+       "       [    nan],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs640_MC_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.1301 0.1301 0.1301 ... nan nan</div><input id='attrs-ee066847-b1b7-44b6-aea4-bc0bc0e2a8bc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ee066847-b1b7-44b6-aea4-bc0bc0e2a8bc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5d61dad0-9a76-4563-815a-1cc7c601c533' class='xr-var-data-in' type='checkbox'><label for='data-5d61dad0-9a76-4563-815a-1cc7c601c533' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.13007],\n",
+       "       [0.13007],\n",
+       "       [0.13007],\n",
+       "       ...,\n",
+       "       [    nan],\n",
+       "       [    nan],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs660_MC_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.1486 0.1486 0.1486 ... nan nan</div><input id='attrs-4125889e-a930-4f11-bf91-46042a873335' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4125889e-a930-4f11-bf91-46042a873335' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f47c4e68-42d2-4611-9df8-b185450f4b2c' class='xr-var-data-in' type='checkbox'><label for='data-f47c4e68-42d2-4611-9df8-b185450f4b2c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.1486],\n",
+       "       [0.1486],\n",
+       "       [0.1486],\n",
+       "       ...,\n",
+       "       [   nan],\n",
+       "       [   nan],\n",
+       "       [   nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs680_MC_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.07588 0.07588 0.07588 ... nan nan</div><input id='attrs-5ce280fe-6423-4bde-b172-f860479c3604' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5ce280fe-6423-4bde-b172-f860479c3604' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e9998d1f-4ca2-4fe7-b7ec-f0b27798a306' class='xr-var-data-in' type='checkbox'><label for='data-e9998d1f-4ca2-4fe7-b7ec-f0b27798a306' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.075883],\n",
+       "       [0.075883],\n",
+       "       [0.075883],\n",
+       "       ...,\n",
+       "       [     nan],\n",
+       "       [     nan],\n",
+       "       [     nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs700_MC_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.04348 -0.04348 ... nan nan</div><input id='attrs-fdb4f758-d5c5-4c47-b36e-2503b0554616' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fdb4f758-d5c5-4c47-b36e-2503b0554616' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-15ec1b53-8639-46ac-941b-c41246abeb56' class='xr-var-data-in' type='checkbox'><label for='data-15ec1b53-8639-46ac-941b-c41246abeb56' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-0.04348],\n",
+       "       [-0.04348],\n",
+       "       [-0.04348],\n",
+       "       ...,\n",
+       "       [     nan],\n",
+       "       [     nan],\n",
+       "       [     nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WSAbs365_MC_WEBER</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.9267 0.9267 0.9267 ... nan nan</div><input id='attrs-2dcff053-1d13-44c9-85b9-09a56cd2c0ab' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2dcff053-1d13-44c9-85b9-09a56cd2c0ab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6f6e13b3-676f-4155-af35-dd587b73dde5' class='xr-var-data-in' type='checkbox'><label for='data-6f6e13b3-676f-4155-af35-dd587b73dde5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.92666],\n",
+       "       [0.92666],\n",
+       "       [0.92666],\n",
+       "       ...,\n",
+       "       [    nan],\n",
+       "       [    nan],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>BC_mass_90_550_nm_SCHWARZ</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.068 0.0 0.0 ... 228.9 230.3 359.4</div><input id='attrs-3ad9ece3-7887-4525-b790-2ea94b0019a0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3ad9ece3-7887-4525-b790-2ea94b0019a0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b1608640-3e6a-4813-bb8a-037393949d9b' class='xr-var-data-in' type='checkbox'><label for='data-b1608640-3e6a-4813-bb8a-037393949d9b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[6.80000e-02],\n",
+       "       [0.00000e+00],\n",
+       "       [0.00000e+00],\n",
+       "       ...,\n",
+       "       [2.28934e+02],\n",
+       "       [2.30260e+02],\n",
+       "       [3.59429e+02]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>BC_Dilution_Flag_SCHWARZ</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-c836cc6f-a245-41f8-b8ad-a79828a6f14e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c836cc6f-a245-41f8-b8ad-a79828a6f14e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ceb79bd7-9762-4f55-aea8-a42f3cccb48d' class='xr-var-data-in' type='checkbox'><label for='data-ceb79bd7-9762-4f55-aea8-a42f3cccb48d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>OA_PM1_AMS_JIMENEZ</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-4b25853e-21a1-47f4-804a-6a809c46bb27' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4b25853e-21a1-47f4-804a-6a809c46bb27' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a6c845c1-7f49-4382-9ca5-b2df47a56843' class='xr-var-data-in' type='checkbox'><label for='data-a6c845c1-7f49-4382-9ca5-b2df47a56843' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Sulfate_PM1_AMS_JIMENEZ</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-d3ca5e50-a2b1-4dee-8ad3-afd9e90226f4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d3ca5e50-a2b1-4dee-8ad3-afd9e90226f4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-646872d7-dfc9-43b3-a110-b15d1cef542f' class='xr-var-data-in' type='checkbox'><label for='data-646872d7-dfc9-43b3-a110-b15d1cef542f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Nitrate_PM1_AMS_JIMENEZ</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ba89a492-6fb5-45af-a66e-726da716b005' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ba89a492-6fb5-45af-a66e-726da716b005' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2cdf6729-995f-4810-8554-a92c5e9df8fd' class='xr-var-data-in' type='checkbox'><label for='data-2cdf6729-995f-4810-8554-a92c5e9df8fd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Ammonium_PM1_AMS_JIMENEZ</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-f304c78b-460e-4d14-a354-eb897d78d939' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f304c78b-460e-4d14-a354-eb897d78d939' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b404a96b-8ac4-468c-abb0-33e0fb0300a3' class='xr-var-data-in' type='checkbox'><label for='data-b404a96b-8ac4-468c-abb0-33e0fb0300a3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NR_Chloride_PM1_AMS_JIMENEZ</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-fc11a951-de9a-4bb4-914d-05089c3d34e1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fc11a951-de9a-4bb4-914d-05089c3d34e1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5240e232-1521-44e6-9267-1e69369aa82c' class='xr-var-data-in' type='checkbox'><label for='data-5240e232-1521-44e6-9267-1e69369aa82c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Potassium_PM1_AMS_JIMENEZ</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-2994dabb-a138-4257-8d80-9e8753a5b64e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2994dabb-a138-4257-8d80-9e8753a5b64e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9810385e-d060-46ce-aabf-fc16da71ac6a' class='xr-var-data-in' type='checkbox'><label for='data-9810385e-d060-46ce-aabf-fc16da71ac6a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MSA_PM1_AMS_JIMENEZ</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-60243fca-4e8f-4b47-ad97-dfa5b745494e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-60243fca-4e8f-4b47-ad97-dfa5b745494e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-23d3a60c-6ddc-466d-ac27-d2a2321b9811' class='xr-var-data-in' type='checkbox'><label for='data-23d3a60c-6ddc-466d-ac27-d2a2321b9811' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ClO4_PM1_AMS_JIMENEZ</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-780f0153-99d6-4246-92a0-7986a03b034f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-780f0153-99d6-4246-92a0-7986a03b034f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ab861f5b-eb23-4b1b-9ef3-010bd4c53f32' class='xr-var-data-in' type='checkbox'><label for='data-ab861f5b-eb23-4b1b-9ef3-010bd4c53f32' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Iodine_PM1_AMS_JIMENEZ</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-1c3671d9-436b-47fb-851e-fc5fc234e371' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1c3671d9-436b-47fb-851e-fc5fc234e371' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-92419265-4f15-415d-88f6-9d913150d7b0' class='xr-var-data-in' type='checkbox'><label for='data-92419265-4f15-415d-88f6-9d913150d7b0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Bromine_PM1_AMS_JIMENEZ</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-95e9343b-7d24-4ab2-86a7-8655dda35ed5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-95e9343b-7d24-4ab2-86a7-8655dda35ed5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6bfe717a-31b0-4158-9596-cb406c2da987' class='xr-var-data-in' type='checkbox'><label for='data-6bfe717a-31b0-4158-9596-cb406c2da987' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Seasalt_PM1_AMS_JIMENEZ</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ba70eabb-9f62-476b-9892-9395e48912f9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ba70eabb-9f62-476b-9892-9395e48912f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ffb20167-27e8-4d7a-9597-eb8f680881d6' class='xr-var-data-in' type='checkbox'><label for='data-ffb20167-27e8-4d7a-9597-eb8f680881d6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CloudFlag_AMS_JIMENEZ</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-5fac7ef9-595e-447c-93d0-7d16f340d1b0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5fac7ef9-595e-447c-93d0-7d16f340d1b0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ed9c15ff-1100-4632-8a84-b2c3a03ea3cf' class='xr-var-data-in' type='checkbox'><label for='data-ed9c15ff-1100-4632-8a84-b2c3a03ea3cf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>AmmBalance_PM1_AMS_JIMENEZ</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-aacb4593-8cdf-493d-b6a9-71a35c3a89da' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-aacb4593-8cdf-493d-b6a9-71a35c3a89da' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-23da684d-ffc9-4b0f-ad58-41a2ce9ba588' class='xr-var-data-in' type='checkbox'><label for='data-23da684d-ffc9-4b0f-ad58-41a2ce9ba588' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Density_PM1_AMS_JIMENEZ</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-5c1931e3-e6b1-41ce-bab7-fe73ba36c0de' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5c1931e3-e6b1-41ce-bab7-fe73ba36c0de' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d62d9fa-c24f-4b34-a278-07a71888901e' class='xr-var-data-in' type='checkbox'><label for='data-1d62d9fa-c24f-4b34-a278-07a71888901e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>OADensity_PM1_AMS_JIMENEZ</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-c637d251-7b18-4ee4-beae-7c26e7dbd210' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c637d251-7b18-4ee4-beae-7c26e7dbd210' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-728e0de4-5814-44c6-a863-724ec7f65fdf' class='xr-var-data-in' type='checkbox'><label for='data-728e0de4-5814-44c6-a863-724ec7f65fdf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>OSc_PM1_AMS_JIMENEZ</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e0a1b3f2-75b9-4f83-8491-33ed7771e3bf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e0a1b3f2-75b9-4f83-8491-33ed7771e3bf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1032cc9e-ccab-477f-b0ea-f56047d9b2eb' class='xr-var-data-in' type='checkbox'><label for='data-1032cc9e-ccab-477f-b0ea-f56047d9b2eb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>C6H10O5_JIMENEZ</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-8e1eee3c-9851-4c39-9561-12d65499bfda' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8e1eee3c-9851-4c39-9561-12d65499bfda' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-62e133b9-2ddd-47dd-beab-0e24cd51784f' class='xr-var-data-in' type='checkbox'><label for='data-62e133b9-2ddd-47dd-beab-0e24cd51784f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>C6H5NO4_JIMENEZ</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-f9dd3485-468a-48c6-b21f-ce65009bf321' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f9dd3485-468a-48c6-b21f-ce65009bf321' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-577d442e-a984-4da9-8a2c-24e3c694f297' class='xr-var-data-in' type='checkbox'><label for='data-577d442e-a984-4da9-8a2c-24e3c694f297' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Cl_ug/m3_DIBB</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-190ab8d2-f655-4f9f-9ec2-563f909e4b56' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-190ab8d2-f655-4f9f-9ec2-563f909e4b56' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-208881df-b550-418a-b348-044704c1461b' class='xr-var-data-in' type='checkbox'><label for='data-208881df-b550-418a-b348-044704c1461b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Br_ug/m3_DIBB</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e30f0981-67f0-4bf3-9e68-df5cac93604e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e30f0981-67f0-4bf3-9e68-df5cac93604e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5c453b2e-bce3-4453-8d5d-9665461d878b' class='xr-var-data-in' type='checkbox'><label for='data-5c453b2e-bce3-4453-8d5d-9665461d878b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NO3_ug/m3_DIBB</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-0c352336-f5c3-4815-b59d-c846c08af53b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0c352336-f5c3-4815-b59d-c846c08af53b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6664062d-ede2-4cee-9d4f-d297ff3033a4' class='xr-var-data-in' type='checkbox'><label for='data-6664062d-ede2-4cee-9d4f-d297ff3033a4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SO4_ug/m3_DIBB</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-b3b2a42d-ce77-4280-af63-5da52dd3aa96' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b3b2a42d-ce77-4280-af63-5da52dd3aa96' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3e890911-0660-4789-9afc-4749b66e0956' class='xr-var-data-in' type='checkbox'><label for='data-3e890911-0660-4789-9afc-4749b66e0956' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>C2O4_ug/m3_DIBB</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ca904147-bd81-44e1-a2f2-a9b33ae94b6b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ca904147-bd81-44e1-a2f2-a9b33ae94b6b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2f48f893-0e03-4d5c-b69b-3a764dda8e50' class='xr-var-data-in' type='checkbox'><label for='data-2f48f893-0e03-4d5c-b69b-3a764dda8e50' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Na_ug/m3_DIBB</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ca095b77-1407-4ffe-94c4-043611c0ad78' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ca095b77-1407-4ffe-94c4-043611c0ad78' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9ee0720f-eefd-4ec1-8f59-f30e43211d48' class='xr-var-data-in' type='checkbox'><label for='data-9ee0720f-eefd-4ec1-8f59-f30e43211d48' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NH4_ug/m3_DIBB</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-7f81310e-df14-4a67-aaa3-ad4cec38d08a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7f81310e-df14-4a67-aaa3-ad4cec38d08a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f9ac984d-6c5e-47c3-a5e9-9ac7e65043b7' class='xr-var-data-in' type='checkbox'><label for='data-f9ac984d-6c5e-47c3-a5e9-9ac7e65043b7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>K_ug/m3_DIBB</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-86dd3a79-9f02-46c7-aaa8-5bef26151cfd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-86dd3a79-9f02-46c7-aaa8-5bef26151cfd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6256bab2-bd60-4d4a-9d3f-1620257f3957' class='xr-var-data-in' type='checkbox'><label for='data-6256bab2-bd60-4d4a-9d3f-1620257f3957' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Mg_ug/m3_DIBB</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-7877773b-b26a-461c-9add-1f71ad2e9072' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7877773b-b26a-461c-9add-1f71ad2e9072' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bf1076f1-617e-4ae1-9178-67914315a276' class='xr-var-data-in' type='checkbox'><label for='data-bf1076f1-617e-4ae1-9178-67914315a276' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Ca_ug/m3_DIBB</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-26d46d85-c542-4190-a51a-5072d7af81f3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-26d46d85-c542-4190-a51a-5072d7af81f3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a74b4e09-abc7-46cc-a6d1-80f6ec1fd72c' class='xr-var-data-in' type='checkbox'><label for='data-a74b4e09-abc7-46cc-a6d1-80f6ec1fd72c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nCDP_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-cea9150b-c489-4f1b-9e28-c06e49159710' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cea9150b-c489-4f1b-9e28-c06e49159710' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e958c7e5-4895-488b-8991-01d1814e6658' class='xr-var-data-in' type='checkbox'><label for='data-e958c7e5-4895-488b-8991-01d1814e6658' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vCDP_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-84615702-f08f-42cd-9900-28f30eebdb2e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-84615702-f08f-42cd-9900-28f30eebdb2e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fca6a348-0f51-4b26-b372-96d056e4c2c0' class='xr-var-data-in' type='checkbox'><label for='data-fca6a348-0f51-4b26-b372-96d056e4c2c0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nCPSPD_stdPT_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-2603e227-69c3-4263-ba5d-669e87c5a65e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2603e227-69c3-4263-ba5d-669e87c5a65e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-02aca66c-ca34-41ee-9ac4-1351e2e6f669' class='xr-var-data-in' type='checkbox'><label for='data-02aca66c-ca34-41ee-9ac4-1351e2e6f669' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vCPSPD_stdPT_MOORE</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-22dd3078-7e29-4b83-a854-50339bf1f9b5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-22dd3078-7e29-4b83-a854-50339bf1f9b5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-20e001ab-6ab5-445f-89d3-aa5043ea57c3' class='xr-var-data-in' type='checkbox'><label for='data-20e001ab-6ab5-445f-89d3-aa5043ea57c3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Nacc_CAPS_WEINZIERL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.715 2.72 2.509 ... 4.831 48.99</div><input id='attrs-ea11dd2b-5c22-4c9d-9d87-cf28fdca46d9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ea11dd2b-5c22-4c9d-9d87-cf28fdca46d9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d6cf1b7b-625a-44d9-a881-b4dce65dd448' class='xr-var-data-in' type='checkbox'><label for='data-d6cf1b7b-625a-44d9-a881-b4dce65dd448' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 2.71542],\n",
+       "       [ 2.7196 ],\n",
+       "       [ 2.509  ],\n",
+       "       ...,\n",
+       "       [ 3.2624 ],\n",
+       "       [ 4.8314 ],\n",
+       "       [48.9871 ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Ncoa1_CAPS_WEINZIERL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.5679 0.5742 0.496 ... 1.765 37.51</div><input id='attrs-57602c49-730a-4783-b8f8-c07eb595952e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-57602c49-730a-4783-b8f8-c07eb595952e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c406baef-8581-4d96-8059-a4dcfd8b4db0' class='xr-var-data-in' type='checkbox'><label for='data-c406baef-8581-4d96-8059-a4dcfd8b4db0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 0.56792],\n",
+       "       [ 0.5742 ],\n",
+       "       [ 0.496  ],\n",
+       "       ...,\n",
+       "       [ 1.0364 ],\n",
+       "       [ 1.7652 ],\n",
+       "       [37.5138 ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Ncoa2_CAPS_WEINZIERL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.075 0.042 0.024 ... 0.0846 0.9748</div><input id='attrs-22caa6ca-06a9-4c37-8032-6e656a6501f8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-22caa6ca-06a9-4c37-8032-6e656a6501f8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-84abe2cb-4200-4216-a2dd-303ce8fb399b' class='xr-var-data-in' type='checkbox'><label for='data-84abe2cb-4200-4216-a2dd-303ce8fb399b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.075  ],\n",
+       "       [0.042  ],\n",
+       "       [0.024  ],\n",
+       "       ...,\n",
+       "       [0.024  ],\n",
+       "       [0.0846 ],\n",
+       "       [0.97476]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Ncoa3_CAPS_WEINZIERL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.03333</div><input id='attrs-33e01585-e573-42ba-a74c-ad7b8c500874' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-33e01585-e573-42ba-a74c-ad7b8c500874' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7413dee7-daba-489e-9cac-ad085dbea2bb' class='xr-var-data-in' type='checkbox'><label for='data-7413dee7-daba-489e-9cac-ad085dbea2bb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.      ],\n",
+       "       [0.      ],\n",
+       "       [0.      ],\n",
+       "       ...,\n",
+       "       [0.      ],\n",
+       "       [0.      ],\n",
+       "       [0.033333]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Ntot_CAPS_WEINZIERL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.36 3.339 3.03 ... 6.682 87.51</div><input id='attrs-d6bc946b-6a60-4841-9390-00cbf308324f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d6bc946b-6a60-4841-9390-00cbf308324f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ca5846e7-23ba-4840-bae3-31f877ac9651' class='xr-var-data-in' type='checkbox'><label for='data-ca5846e7-23ba-4840-bae3-31f877ac9651' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 3.36042],\n",
+       "       [ 3.3388 ],\n",
+       "       [ 3.03   ],\n",
+       "       ...,\n",
+       "       [ 4.321  ],\n",
+       "       [ 6.682  ],\n",
+       "       [87.509  ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cloudindicator_CAPS_WEINZIERL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 nan nan</div><input id='attrs-29e6ab18-bba5-4616-b407-c06358975ee9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-29e6ab18-bba5-4616-b407-c06358975ee9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-855f61fd-24ae-420d-96ea-e11ee8fe2b64' class='xr-var-data-in' type='checkbox'><label for='data-855f61fd-24ae-420d-96ea-e11ee8fe2b64' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 0.],\n",
+       "       [ 0.],\n",
+       "       [ 0.],\n",
+       "       ...,\n",
+       "       [ 0.],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jO3_O2_O1D_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 3.123e-05 ... nan nan</div><input id='attrs-8f8fa16d-715c-491d-beca-39c5440b72ab' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8f8fa16d-715c-491d-beca-39c5440b72ab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-59a533f0-66ee-4f2d-894b-5a5aaa8e8806' class='xr-var-data-in' type='checkbox'><label for='data-59a533f0-66ee-4f2d-894b-5a5aaa8e8806' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [3.123e-05],\n",
+       "       ...,\n",
+       "       [1.064e-05],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jNO2_NO_O3P_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 0.009019 ... nan nan</div><input id='attrs-2c23b08b-14f7-42f3-b7c4-e616513e5cbb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2c23b08b-14f7-42f3-b7c4-e616513e5cbb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-845091c5-2d7a-4463-a14d-3a1bf4d852c9' class='xr-var-data-in' type='checkbox'><label for='data-845091c5-2d7a-4463-a14d-3a1bf4d852c9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [0.009019 ],\n",
+       "       ...,\n",
+       "       [0.0060964],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jH2O2_OH_OH_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 7.155e-06 ... nan nan</div><input id='attrs-610a36fc-c96d-4fda-a5ee-b40068e80295' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-610a36fc-c96d-4fda-a5ee-b40068e80295' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7c1393f6-c98c-4c3a-b78b-0d5fd42c8f22' class='xr-var-data-in' type='checkbox'><label for='data-7c1393f6-c98c-4c3a-b78b-0d5fd42c8f22' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [7.155e-06],\n",
+       "       ...,\n",
+       "       [3.788e-06],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jNO3_NO_O2_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 0.02134 ... 0.02094 nan nan</div><input id='attrs-bef6e011-6705-4e67-aa87-9d47728f3b9b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bef6e011-6705-4e67-aa87-9d47728f3b9b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a93146f4-c625-4544-bbb1-2d5fb96e3d4f' class='xr-var-data-in' type='checkbox'><label for='data-a93146f4-c625-4544-bbb1-2d5fb96e3d4f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[     nan],\n",
+       "       [     nan],\n",
+       "       [0.021343],\n",
+       "       ...,\n",
+       "       [0.020941],\n",
+       "       [     nan],\n",
+       "       [     nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jNO3_NO2_O3P_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 0.1823 ... 0.1668 nan nan</div><input id='attrs-5ea536ff-8273-4ffc-93f9-bac4d3ec072c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5ea536ff-8273-4ffc-93f9-bac4d3ec072c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0f1a630a-73d8-41c3-a5a1-0977353096ce' class='xr-var-data-in' type='checkbox'><label for='data-0f1a630a-73d8-41c3-a5a1-0977353096ce' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[    nan],\n",
+       "       [    nan],\n",
+       "       [0.18227],\n",
+       "       ...,\n",
+       "       [0.16682],\n",
+       "       [    nan],\n",
+       "       [    nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jN2O5_NO3_NO2_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 4.276e-05 ... nan nan</div><input id='attrs-4b5bec13-254a-40fd-985f-059a75addc8a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4b5bec13-254a-40fd-985f-059a75addc8a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f8169434-5f21-46b6-88f2-77ff858b2632' class='xr-var-data-in' type='checkbox'><label for='data-f8169434-5f21-46b6-88f2-77ff858b2632' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [4.276e-05],\n",
+       "       ...,\n",
+       "       [2.271e-05],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jHNO2_OH_NO_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 0.001427 ... nan nan</div><input id='attrs-cc62d4e7-ba5c-4cc9-885f-18f401a62d8a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cc62d4e7-ba5c-4cc9-885f-18f401a62d8a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0ce60884-feca-4d02-b158-b003029a1f1e' class='xr-var-data-in' type='checkbox'><label for='data-0ce60884-feca-4d02-b158-b003029a1f1e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [0.001427 ],\n",
+       "       ...,\n",
+       "       [0.0009172],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jHNO3_OH_NO2_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 5.978e-07 ... nan nan</div><input id='attrs-e51b5e00-bd01-4020-9739-bc2565ad366a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e51b5e00-bd01-4020-9739-bc2565ad366a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d6d38aa8-735b-4b22-bb80-43860d90c699' class='xr-var-data-in' type='checkbox'><label for='data-d6d38aa8-735b-4b22-bb80-43860d90c699' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [5.978e-07],\n",
+       "       ...,\n",
+       "       [2.561e-07],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jHNO4_HO2_NO2_UvVisOnly_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 6.171e-06 ... nan nan</div><input id='attrs-bc1935ef-6a3b-4788-89cb-3d61106a460c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bc1935ef-6a3b-4788-89cb-3d61106a460c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-617ba180-a607-4239-8996-ba2aa112630e' class='xr-var-data-in' type='checkbox'><label for='data-617ba180-a607-4239-8996-ba2aa112630e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [6.171e-06],\n",
+       "       ...,\n",
+       "       [2.862e-06],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jCH2O_H_HCO_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 3.034e-05 ... nan nan</div><input id='attrs-6e01ea3a-1fa5-4465-935d-7664fef51b68' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6e01ea3a-1fa5-4465-935d-7664fef51b68' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-709470d0-eb3b-4f6c-bc70-056b12e4e1f8' class='xr-var-data-in' type='checkbox'><label for='data-709470d0-eb3b-4f6c-bc70-056b12e4e1f8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [3.034e-05],\n",
+       "       ...,\n",
+       "       [1.455e-05],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jCH2O_H2_CO_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 4.795e-05 ... nan nan</div><input id='attrs-1522c8eb-2afa-4402-8c3e-13b4218cd3af' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1522c8eb-2afa-4402-8c3e-13b4218cd3af' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-29d8082a-64cb-4d1d-8aed-cf4208ff87f9' class='xr-var-data-in' type='checkbox'><label for='data-29d8082a-64cb-4d1d-8aed-cf4208ff87f9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [4.795e-05],\n",
+       "       ...,\n",
+       "       [2.690e-05],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jCH3CHO_CH3_HCO_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 4.836e-06 ... nan nan</div><input id='attrs-88c75c1d-21e7-4939-8dbe-50eab96fb383' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-88c75c1d-21e7-4939-8dbe-50eab96fb383' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-23507bf6-24e9-44b5-b5b8-5536d89ea90f' class='xr-var-data-in' type='checkbox'><label for='data-23507bf6-24e9-44b5-b5b8-5536d89ea90f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [4.836e-06],\n",
+       "       ...,\n",
+       "       [1.932e-06],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jPropanal_CH2CH3_HCO_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 1.646e-05 ... nan nan</div><input id='attrs-ff60dfc3-0aa6-4262-a092-35143a5d5ac7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ff60dfc3-0aa6-4262-a092-35143a5d5ac7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1f2a39bf-f9db-4caf-8c58-e9b802536a19' class='xr-var-data-in' type='checkbox'><label for='data-1f2a39bf-f9db-4caf-8c58-e9b802536a19' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [1.646e-05],\n",
+       "       ...,\n",
+       "       [7.111e-06],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jCH3OOH_CH3O_OH_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 5.032e-06 ... nan nan</div><input id='attrs-c2c50804-8b1a-4ac8-96f3-4733c808925d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c2c50804-8b1a-4ac8-96f3-4733c808925d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-171155a0-477e-429e-ba6a-689e4a786b43' class='xr-var-data-in' type='checkbox'><label for='data-171155a0-477e-429e-ba6a-689e4a786b43' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [5.032e-06],\n",
+       "       ...,\n",
+       "       [2.669e-06],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jMeONO2_CH3O_NO2_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 8.795e-07 ... nan nan</div><input id='attrs-2051dba4-a1c3-4708-a783-1c612b3266b6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2051dba4-a1c3-4708-a783-1c612b3266b6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bfef1b4a-3661-4533-b891-91afc6cf1003' class='xr-var-data-in' type='checkbox'><label for='data-bfef1b4a-3661-4533-b891-91afc6cf1003' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [8.795e-07],\n",
+       "       ...,\n",
+       "       [3.784e-07],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jEthONO2_CH3CH2O_NO2_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 1.445e-06 ... nan nan</div><input id='attrs-02e35aa8-5ca6-4300-8811-9dfaf9877416' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-02e35aa8-5ca6-4300-8811-9dfaf9877416' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2f43b27e-a74f-4f64-9022-1abbc7aade64' class='xr-var-data-in' type='checkbox'><label for='data-2f43b27e-a74f-4f64-9022-1abbc7aade64' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [1.445e-06],\n",
+       "       ...,\n",
+       "       [6.317e-07],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jPAN_CH3COO2_NO2_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 5.156e-07 ... nan nan</div><input id='attrs-a11903f7-8d28-47ca-b79e-02f6878ab1fa' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a11903f7-8d28-47ca-b79e-02f6878ab1fa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4612ca4e-e696-412b-8ff6-943b7cbfed44' class='xr-var-data-in' type='checkbox'><label for='data-4612ca4e-e696-412b-8ff6-943b7cbfed44' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [5.156e-07],\n",
+       "       ...,\n",
+       "       [2.514e-07],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jPAN_CH3COO_NO3_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 2.21e-07 ... nan nan</div><input id='attrs-e1ce255a-36fb-40e9-8120-cc63f914eef6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e1ce255a-36fb-40e9-8120-cc63f914eef6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f59aceeb-0393-4372-b0b2-94636212353e' class='xr-var-data-in' type='checkbox'><label for='data-f59aceeb-0393-4372-b0b2-94636212353e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [2.210e-07],\n",
+       "       ...,\n",
+       "       [1.077e-07],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jMAC_NoProductsSpecified_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 4.732e-06 ... nan nan</div><input id='attrs-f7bf077a-9b26-43f0-be40-57ad63aece71' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f7bf077a-9b26-43f0-be40-57ad63aece71' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b3f6b98-7f73-4009-8444-e4df8ba22e03' class='xr-var-data-in' type='checkbox'><label for='data-9b3f6b98-7f73-4009-8444-e4df8ba22e03' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [4.732e-06],\n",
+       "       ...,\n",
+       "       [2.799e-06],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jMVK_NoProductsSpecified_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 4.201e-06 ... nan nan</div><input id='attrs-6f2d1814-3946-4f82-b5c5-a0afeb6c6a09' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6f2d1814-3946-4f82-b5c5-a0afeb6c6a09' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7d341e16-4ddf-41ba-9675-4b5447ced01e' class='xr-var-data-in' type='checkbox'><label for='data-7d341e16-4ddf-41ba-9675-4b5447ced01e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [4.201e-06],\n",
+       "       ...,\n",
+       "       [2.262e-06],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jAcetone_CH3CO_CH3_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 4.591e-07 ... nan nan</div><input id='attrs-fc3f5b0f-47e8-4d3c-b9ac-a548dc234c3f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fc3f5b0f-47e8-4d3c-b9ac-a548dc234c3f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2738f841-ef9a-4710-9f06-b529c460ac08' class='xr-var-data-in' type='checkbox'><label for='data-2738f841-ef9a-4710-9f06-b529c460ac08' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [4.591e-07],\n",
+       "       ...,\n",
+       "       [1.622e-07],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jMEK_CH3CO_CH2CH3_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 4.565e-06 ... nan nan</div><input id='attrs-08c9ffd4-22ab-4497-9a4b-fdc4bf021af1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-08c9ffd4-22ab-4497-9a4b-fdc4bf021af1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9a2788aa-1433-4a45-98e1-8daccad62d17' class='xr-var-data-in' type='checkbox'><label for='data-9a2788aa-1433-4a45-98e1-8daccad62d17' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [4.565e-06],\n",
+       "       ...,\n",
+       "       [1.941e-06],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jHydroxyacetone_CH3CO_CH3O_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 8.428e-07 ... nan nan</div><input id='attrs-bd9fd79a-08ed-4e64-adea-b99082d7b9b0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bd9fd79a-08ed-4e64-adea-b99082d7b9b0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b92d8ff8-03ec-4fb4-939d-defb7385a9bd' class='xr-var-data-in' type='checkbox'><label for='data-b92d8ff8-03ec-4fb4-939d-defb7385a9bd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [8.428e-07],\n",
+       "       ...,\n",
+       "       [3.677e-07],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jHydroxyacetone_CH3COO_CH3_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 8.428e-07 ... nan nan</div><input id='attrs-3952f7c4-eb42-4a78-ac33-78b95a7ffdc4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3952f7c4-eb42-4a78-ac33-78b95a7ffdc4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-45b48536-41be-4168-a7a2-ccba07f635f9' class='xr-var-data-in' type='checkbox'><label for='data-45b48536-41be-4168-a7a2-ccba07f635f9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [8.428e-07],\n",
+       "       ...,\n",
+       "       [3.677e-07],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jCHOCHO_HCO_HCO_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 7.097e-05 ... nan nan</div><input id='attrs-2676fa26-ffc7-4582-8790-8980bb6b352c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2676fa26-ffc7-4582-8790-8980bb6b352c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-44022f2f-2fb1-4790-a6db-125f134d965f' class='xr-var-data-in' type='checkbox'><label for='data-44022f2f-2fb1-4790-a6db-125f134d965f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [7.097e-05],\n",
+       "       ...,\n",
+       "       [4.647e-05],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jCHOCHO_H2_2CO_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 1.527e-05 ... nan nan</div><input id='attrs-67335b5b-0f8b-4644-b180-68b077397d72' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-67335b5b-0f8b-4644-b180-68b077397d72' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a5176800-8d40-49c5-a761-59f0abe75561' class='xr-var-data-in' type='checkbox'><label for='data-a5176800-8d40-49c5-a761-59f0abe75561' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [1.527e-05],\n",
+       "       ...,\n",
+       "       [7.643e-06],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jCHOCHO_CH2O_CO_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 2.761e-05 ... nan nan</div><input id='attrs-d64cd6e0-b0ca-415f-8436-f0143d3ba4b2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d64cd6e0-b0ca-415f-8436-f0143d3ba4b2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e76da1c2-5758-4daf-b61c-90c69fdd867c' class='xr-var-data-in' type='checkbox'><label for='data-e76da1c2-5758-4daf-b61c-90c69fdd867c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [2.761e-05],\n",
+       "       ...,\n",
+       "       [1.445e-05],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jCH3COCHO_CH3CO_HCO_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 0.0001324 ... nan nan</div><input id='attrs-d3d6a5ed-61cb-4cfb-9d0b-5f6abfc8669c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d3d6a5ed-61cb-4cfb-9d0b-5f6abfc8669c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b1ecb6be-ba9d-481a-b881-2efdd57a844d' class='xr-var-data-in' type='checkbox'><label for='data-b1ecb6be-ba9d-481a-b881-2efdd57a844d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [1.324e-04],\n",
+       "       ...,\n",
+       "       [8.382e-05],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>j23Butanedione_NoProductsSpecified_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 0.0002862 ... nan nan</div><input id='attrs-6aee4531-51d8-46c7-ad08-fb8f3142987b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6aee4531-51d8-46c7-ad08-fb8f3142987b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-088b8852-ade6-494b-afa2-d5b109ece143' class='xr-var-data-in' type='checkbox'><label for='data-088b8852-ade6-494b-afa2-d5b109ece143' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [0.0002862],\n",
+       "       ...,\n",
+       "       [0.0002192],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jCl2_Cl_Cl_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 0.002183 ... nan nan</div><input id='attrs-68e6f5e6-4594-47c2-a74d-7ce2dea1d4b5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-68e6f5e6-4594-47c2-a74d-7ce2dea1d4b5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-02a317fe-3e06-406e-be87-4a0f5065e1ef' class='xr-var-data-in' type='checkbox'><label for='data-02a317fe-3e06-406e-be87-4a0f5065e1ef' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [0.0021828],\n",
+       "       ...,\n",
+       "       [0.001355 ],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jClO_Cl_O3P_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 4.714e-05 ... nan nan</div><input id='attrs-8e03201e-e95e-4faa-96b2-bf6bac4fc39a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8e03201e-e95e-4faa-96b2-bf6bac4fc39a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d4c3669-264e-4d51-94c6-e5cec1c2eace' class='xr-var-data-in' type='checkbox'><label for='data-1d4c3669-264e-4d51-94c6-e5cec1c2eace' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [4.714e-05],\n",
+       "       ...,\n",
+       "       [1.665e-05],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jClNO2_Cl_NO2_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 0.0003279 ... nan nan</div><input id='attrs-67e0a40e-b8bd-49b6-937c-7fe8df21b46a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-67e0a40e-b8bd-49b6-937c-7fe8df21b46a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c8d727f9-5bbe-406a-bb17-f2c75e880975' class='xr-var-data-in' type='checkbox'><label for='data-c8d727f9-5bbe-406a-bb17-f2c75e880975' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [0.0003279],\n",
+       "       ...,\n",
+       "       [0.0001813],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jClONO_Cl_NO2_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 0.003833 ... nan nan</div><input id='attrs-8ed5a6b6-bd73-4fc2-aa0b-cfcf2b18bb16' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8ed5a6b6-bd73-4fc2-aa0b-cfcf2b18bb16' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8962e0ab-18df-4c6b-be62-49bd732a6861' class='xr-var-data-in' type='checkbox'><label for='data-8962e0ab-18df-4c6b-be62-49bd732a6861' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [0.0038329],\n",
+       "       ...,\n",
+       "       [0.002147 ],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jClONO2_Cl_NO3_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 3.937e-05 ... nan nan</div><input id='attrs-effa4ca9-bb85-4b78-ba98-2c9af06ddf01' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-effa4ca9-bb85-4b78-ba98-2c9af06ddf01' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0ad26df8-ff74-42c0-a928-326e0d5b7a46' class='xr-var-data-in' type='checkbox'><label for='data-0ad26df8-ff74-42c0-a928-326e0d5b7a46' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [3.937e-05],\n",
+       "       ...,\n",
+       "       [2.426e-05],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jClONO2_ClO_NO2_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 7.732e-06 ... nan nan</div><input id='attrs-258b0caa-fe70-452e-94db-0a5a60f22f9e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-258b0caa-fe70-452e-94db-0a5a60f22f9e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-66247f39-1133-45ee-9fc7-b315b86bd8d3' class='xr-var-data-in' type='checkbox'><label for='data-66247f39-1133-45ee-9fc7-b315b86bd8d3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [7.732e-06],\n",
+       "       ...,\n",
+       "       [3.824e-06],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jBr2_Br_Br_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 0.03258 ... 0.02658 nan nan</div><input id='attrs-7547094f-aaa7-4dff-b878-a4f72c7a13be' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7547094f-aaa7-4dff-b878-a4f72c7a13be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d5287cdd-ffb6-44e4-9b6d-9cfc87202255' class='xr-var-data-in' type='checkbox'><label for='data-d5287cdd-ffb6-44e4-9b6d-9cfc87202255' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[     nan],\n",
+       "       [     nan],\n",
+       "       [0.032581],\n",
+       "       ...,\n",
+       "       [0.026578],\n",
+       "       [     nan],\n",
+       "       [     nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jBrO_Br_O_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 0.0341 ... 0.01965 nan nan</div><input id='attrs-990b98a0-2491-4cc2-8785-4b117a9aa5fe' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-990b98a0-2491-4cc2-8785-4b117a9aa5fe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fd8d8f4e-b404-4f74-ad88-bd3f9c7b0c6c' class='xr-var-data-in' type='checkbox'><label for='data-fd8d8f4e-b404-4f74-ad88-bd3f9c7b0c6c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[     nan],\n",
+       "       [     nan],\n",
+       "       [0.034099],\n",
+       "       ...,\n",
+       "       [0.019654],\n",
+       "       [     nan],\n",
+       "       [     nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jHOBr_OH_Br_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 0.002128 ... nan nan</div><input id='attrs-07e30d03-73d2-455d-b1cf-c9114ecf181e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-07e30d03-73d2-455d-b1cf-c9114ecf181e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-131b5a1a-3f6b-41ac-8daa-e3bb9dfc680a' class='xr-var-data-in' type='checkbox'><label for='data-131b5a1a-3f6b-41ac-8daa-e3bb9dfc680a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [0.0021282],\n",
+       "       ...,\n",
+       "       [0.0014684],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jBrNO_Br_NO_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 0.02159 ... 0.01787 nan nan</div><input id='attrs-c63b9b01-b13b-4521-81ed-5420215d1b5d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c63b9b01-b13b-4521-81ed-5420215d1b5d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f886fdfc-2c5d-475d-9871-849649ab9dc0' class='xr-var-data-in' type='checkbox'><label for='data-f886fdfc-2c5d-475d-9871-849649ab9dc0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[     nan],\n",
+       "       [     nan],\n",
+       "       [0.021586],\n",
+       "       ...,\n",
+       "       [0.017867],\n",
+       "       [     nan],\n",
+       "       [     nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jBrONO_Br_NO2_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 0.01047 ... nan nan</div><input id='attrs-db3a348b-b52f-4be7-a6ca-34eea8ccda36' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-db3a348b-b52f-4be7-a6ca-34eea8ccda36' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fb790286-537b-4f95-961a-c628dc229af9' class='xr-var-data-in' type='checkbox'><label for='data-fb790286-537b-4f95-961a-c628dc229af9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [0.010473 ],\n",
+       "       ...,\n",
+       "       [0.0058755],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jBrONO_BrO_NO_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 0.01047 ... nan nan</div><input id='attrs-7eac8d85-aadd-445b-8b55-3dd30404f4ff' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7eac8d85-aadd-445b-8b55-3dd30404f4ff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-57a1e9d4-3a2a-4c8a-83fc-9734885ae108' class='xr-var-data-in' type='checkbox'><label for='data-57a1e9d4-3a2a-4c8a-83fc-9734885ae108' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [0.010473 ],\n",
+       "       ...,\n",
+       "       [0.0058755],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jBrNO2_Br_NO2_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 0.004586 ... nan nan</div><input id='attrs-d3186911-86e3-45d8-a2c9-6f8f046e38d7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d3186911-86e3-45d8-a2c9-6f8f046e38d7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-42bc911e-d4ef-463a-be11-920a47fcc38e' class='xr-var-data-in' type='checkbox'><label for='data-42bc911e-d4ef-463a-be11-920a47fcc38e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [0.0045858],\n",
+       "       ...,\n",
+       "       [0.0032388],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jBrONO2_BrO_NO2_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 0.0001995 ... nan nan</div><input id='attrs-50a622b7-3907-4d16-99ba-a58f33ca4b33' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-50a622b7-3907-4d16-99ba-a58f33ca4b33' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8a36c1b3-7db9-4991-8701-2cbefa146b06' class='xr-var-data-in' type='checkbox'><label for='data-8a36c1b3-7db9-4991-8701-2cbefa146b06' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [0.0001995],\n",
+       "       ...,\n",
+       "       [0.0001333],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jBrONO2_Br_NO3_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 0.00113 ... nan nan</div><input id='attrs-9df45b7e-36cd-4a7c-96b8-e1b8f9f029c4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9df45b7e-36cd-4a7c-96b8-e1b8f9f029c4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ae0a477b-ab24-4e2a-8441-1c9626e19524' class='xr-var-data-in' type='checkbox'><label for='data-ae0a477b-ab24-4e2a-8441-1c9626e19524' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [0.0011305],\n",
+       "       ...,\n",
+       "       [0.0007555],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jBrCl_Br_Cl_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 0.01055 ... nan nan</div><input id='attrs-8c8de5c5-87b0-4e3d-a4ef-4b69c3bbdb7a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8c8de5c5-87b0-4e3d-a4ef-4b69c3bbdb7a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b854cfb9-c569-45a0-aab7-aae7193d88e0' class='xr-var-data-in' type='checkbox'><label for='data-b854cfb9-c569-45a0-aab7-aae7193d88e0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [0.010548 ],\n",
+       "       ...,\n",
+       "       [0.0078975],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>jCHBr3_NoProductsSpecified_CAFS_HALL</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan 1.23e-06 ... nan nan</div><input id='attrs-0da0cf14-816d-44af-a24f-939bc6708fd8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0da0cf14-816d-44af-a24f-939bc6708fd8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-73f305e5-2400-4d77-85fa-8b073302eace' class='xr-var-data-in' type='checkbox'><label for='data-73f305e5-2400-4d77-85fa-8b073302eace' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[      nan],\n",
+       "       [      nan],\n",
+       "       [1.230e-06],\n",
+       "       ...,\n",
+       "       [5.015e-07],\n",
+       "       [      nan],\n",
+       "       [      nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>smoke_age_HOLMES</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-fe7aa67c-9202-4c83-b5e8-e4e4126164e6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fe7aa67c-9202-4c83-b5e8-e4e4126164e6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a0f2f66b-d411-4549-b054-7154e7629887' class='xr-var-data-in' type='checkbox'><label for='data-a0f2f66b-d411-4549-b054-7154e7629887' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>smoke_age_corr_HOLMES</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-37d21b58-2ac0-4e44-b46b-5cb9fc3e4cbb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-37d21b58-2ac0-4e44-b46b-5cb9fc3e4cbb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1e70f2cc-3226-4499-8a7c-261c3e9bb089' class='xr-var-data-in' type='checkbox'><label for='data-1e70f2cc-3226-4499-8a7c-261c3e9bb089' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>smoke_age_rise_HOLMES</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ac3b7b92-180e-48d0-b2f5-5c743c4925cc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ac3b7b92-180e-48d0-b2f5-5c743c4925cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-da942c92-0812-4370-94df-efc72619ce36' class='xr-var-data-in' type='checkbox'><label for='data-da942c92-0812-4370-94df-efc72619ce36' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>smoke_rise_HOLMES</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-5b6ce029-55da-41ba-939a-a0aa63b3ad2b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5b6ce029-55da-41ba-939a-a0aa63b3ad2b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c988847-2dc2-42d7-a87e-ef3a4115c62a' class='xr-var-data-in' type='checkbox'><label for='data-4c988847-2dc2-42d7-a87e-ef3a4115c62a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fire_distance_HOLMES</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-899235db-7d4a-4313-b6c7-42c75eaa9deb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-899235db-7d4a-4313-b6c7-42c75eaa9deb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7e10e7c4-2c03-4a48-b049-0d8320e4bc15' class='xr-var-data-in' type='checkbox'><label for='data-7e10e7c4-2c03-4a48-b049-0d8320e4bc15' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>smoke_agemethod_HOLMES</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-01a2679d-cb08-4411-b3f1-9039bf720a69' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-01a2679d-cb08-4411-b3f1-9039bf720a69' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3cd1f5e0-ac2f-4e8d-a400-c876ed82d5b2' class='xr-var-data-in' type='checkbox'><label for='data-3cd1f5e0-ac2f-4e8d-a400-c876ed82d5b2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan],\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       ...,\n",
+       "       [nan],\n",
+       "       [nan],\n",
+       "       [nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>no2</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.5819 0.5652 ... 1.571 1.573</div><input id='attrs-01ac6f65-0664-423a-a8a2-98cca73e9652' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-01ac6f65-0664-423a-a8a2-98cca73e9652' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d991f6b0-d4c3-4606-a26f-490137162538' class='xr-var-data-in' type='checkbox'><label for='data-d991f6b0-d4c3-4606-a26f-490137162538' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.5818704 ],\n",
+       "       [0.56521853],\n",
+       "       [0.54941907],\n",
+       "       ...,\n",
+       "       [1.44471902],\n",
+       "       [1.57144209],\n",
+       "       [1.57341623]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>no</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.1132 0.1121 ... 0.1672 0.1672</div><input id='attrs-83dac672-426a-4a79-83b9-888f366d809d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-83dac672-426a-4a79-83b9-888f366d809d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f784284-6f48-4203-b13e-9b27936a4743' class='xr-var-data-in' type='checkbox'><label for='data-9f784284-6f48-4203-b13e-9b27936a4743' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.11324515],\n",
+       "       [0.11211746],\n",
+       "       [0.1114473 ],\n",
+       "       ...,\n",
+       "       [0.16919538],\n",
+       "       [0.16716263],\n",
+       "       [0.167174  ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>o3</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>64.12 64.52 64.8 ... 105.2 105.3</div><input id='attrs-763a4656-c191-4608-8ac6-b592e8092f9c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-763a4656-c191-4608-8ac6-b592e8092f9c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ec4a7497-d66c-498a-a86a-6719a7d6017d' class='xr-var-data-in' type='checkbox'><label for='data-ec4a7497-d66c-498a-a86a-6719a7d6017d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 64.12415731],\n",
+       "       [ 64.52180596],\n",
+       "       [ 64.7970919 ],\n",
+       "       ...,\n",
+       "       [ 96.93075364],\n",
+       "       [105.22003383],\n",
+       "       [105.27778671]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_model</span></div><div class='xr-var-dims'>(time, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>305.7 304.8 303.8 ... 306.5 306.5</div><input id='attrs-55f4f093-c7da-41b5-96f7-6e6100ef1b08' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-55f4f093-c7da-41b5-96f7-6e6100ef1b08' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-52c92e94-8f46-4817-a6c3-29dea8b27442' class='xr-var-data-in' type='checkbox'><label for='data-52c92e94-8f46-4817-a6c3-29dea8b27442' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[305.71874853],\n",
+       "       [304.80247516],\n",
+       "       [303.83740318],\n",
+       "       ...,\n",
+       "       [307.12371814],\n",
+       "       [306.47521744],\n",
+       "       [306.47638168]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-df4f9c3c-5b8c-4197-b84c-a5acb01163ae' class='xr-section-summary-in' type='checkbox'  ><label for='section-df4f9c3c-5b8c-4197-b84c-a5acb01163ae' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-06aa9a63-0301-44c3-a107-2bfa0e3deaa7' class='xr-index-data-in' type='checkbox'/><label for='index-06aa9a63-0301-44c3-a107-2bfa0e3deaa7' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2019-09-05 17:37:05&#x27;, &#x27;2019-09-05 17:37:15&#x27;,\n",
+       "               &#x27;2019-09-05 17:37:25&#x27;, &#x27;2019-09-05 17:37:35&#x27;,\n",
+       "               &#x27;2019-09-05 17:37:45&#x27;, &#x27;2019-09-05 17:37:55&#x27;,\n",
+       "               &#x27;2019-09-05 17:38:05&#x27;, &#x27;2019-09-05 17:38:15&#x27;,\n",
+       "               &#x27;2019-09-05 17:38:25&#x27;, &#x27;2019-09-05 17:38:35&#x27;,\n",
+       "               ...\n",
+       "               &#x27;2019-09-05 23:08:35&#x27;, &#x27;2019-09-05 23:08:45&#x27;,\n",
+       "               &#x27;2019-09-05 23:08:55&#x27;, &#x27;2019-09-05 23:09:05&#x27;,\n",
+       "               &#x27;2019-09-05 23:09:15&#x27;, &#x27;2019-09-05 23:09:25&#x27;,\n",
+       "               &#x27;2019-09-05 23:09:35&#x27;, &#x27;2019-09-05 23:09:45&#x27;,\n",
+       "               &#x27;2019-09-05 23:09:55&#x27;, &#x27;2019-09-05 23:10:05&#x27;],\n",
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=1901, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-043c684f-2899-4a63-b676-964ab285db92' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-043c684f-2899-4a63-b676-964ab285db92' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset>\n",
+       "Dimensions:                                       (time: 1901, x: 1)\n",
+       "Coordinates:\n",
+       "  * time                                          (time) datetime64[ns] 2019-...\n",
+       "Dimensions without coordinates: x\n",
+       "Data variables: (12/646)\n",
+       "    Time_Stop                                     (time, x) float64 6.344e+04...\n",
+       "    Day_Of_Year_YANG                              (time, x) float64 248.0 ......\n",
+       "    latitude                                      (time, x) float64 38.79 ......\n",
+       "    longitude                                     (time, x) float64 -97.65 .....\n",
+       "    altitude                                      (time, x) float64 433.7 ......\n",
+       "    HAE_GPS_Altitude_YANG                         (time, x) float64 408.2 ......\n",
+       "    ...                                            ...\n",
+       "    fire_distance_HOLMES                          (time, x) float64 nan ... nan\n",
+       "    smoke_agemethod_HOLMES                        (time, x) float64 nan ... nan\n",
+       "    no2                                           (time, x) float64 0.5819 .....\n",
+       "    no                                            (time, x) float64 0.1132 .....\n",
+       "    o3                                            (time, x) float64 64.12 ......\n",
+       "    temp_model                                    (time, x) float64 305.7 ......"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "an.paired['firexaq_wrfchem_v4.2'].obj\n",
+    "paired_data=an.paired['firexaq_wrfchem_v4.2']\n",
+    "paired_data.obj#.coords"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "dcfb8cd9",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/qrasool/mm_developaircraftPR189_scatterviolin/MELODIES-MONET/melodies_monet/plots/aircraftplots.py:788: FutureWarning: \n",
+      "\n",
+      "The `scale` parameter has been renamed and will be removed in v0.15.0. Pass `density_norm='width'` for the same effect.\n",
+      "  sns.violinplot(x='group', y='value', data=melted_comb_violin, hue='group', palette=palette, cut=0, orient='v', scale='width', inner='quartile')\n",
+      "/home/qrasool/mm_developaircraftPR189_scatterviolin/MELODIES-MONET/melodies_monet/plots/aircraftplots.py:788: FutureWarning: \n",
+      "\n",
+      "The `scale` parameter has been renamed and will be removed in v0.15.0. Pass `density_norm='width'` for the same effect.\n",
+      "  sns.violinplot(x='group', y='value', data=melted_comb_violin, hue='group', palette=palette, cut=0, orient='v', scale='width', inner='quartile')\n",
+      "/home/qrasool/mm_developaircraftPR189_scatterviolin/MELODIES-MONET/melodies_monet/plots/aircraftplots.py:788: FutureWarning: \n",
+      "\n",
+      "The `scale` parameter has been renamed and will be removed in v0.15.0. Pass `density_norm='width'` for the same effect.\n",
+      "  sns.violinplot(x='group', y='value', data=melted_comb_violin, hue='group', palette=palette, cut=0, orient='v', scale='width', inner='quartile')\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Value of fill after reading from scatter_density_config: True\n",
+      "Processing scatter density plot for model 'wrfchem_v4.2' and observation 'firexaq'...\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x600 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x600 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x600 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1000x1400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1000x1400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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U9bAMNRERERERFadaBYni4uKwZ88e2NnZoWvXrsbx7Oxs3L59Gw4ODqhRo4bZenXr1gUAXLlyxTh2+fJlk+fKa51du3bhypUrhQaJ7t69i7t375qNX7x40eT/R/n4+JiU1yMiIiIiIiIiIiIiouqt2gSJ8vPzMXToUOTn5+N///ufsecQAKSnpwMAnJ2dLa5rGE9LS3vs6zxq6dKlmDFjRqHPF9aXKDw8HNOnTy90PSIiIiIiIiIiIiIiql6qRZBIo9Fg6NChOHToEAYNGoRJkyaVajuCIJR4WUOrp/JeZ+zYsejXr5/ZuKHueGE9iZhFREREREREREREREREBVX5IJFGo8GQIUOwceNGvPzyy1i7dq1ZEMaQwWPI9HmUpQyg4tbJyMgol3UeVVzZOPYkIiIiIiIiIiIiIiKikpBU9gQqklqtxiuvvIINGzZgyJAh+PXXXyGTmcfF7O3t4evri6ysLIv9fq5evQoAqFevnnGsfv36AEx7DlXEOkRERERERERERERERBWhygaJVCoVBg4ciD/++AOvv/46Vq1aBalUWujyYWFhAIC///7b7LkdO3aYLAMAwcHB8Pf3x5UrVxATE1Oidbp37w4A2LVrF3Q6ncnymZmZOHToEGxtbdG+ffuSHiYREREREREREREREVGpVMkgUX5+Pl588UX8+eefGD16NJYvXw6JpOhDHTduHADg888/R2pqqnE8NjYW3333HZRKJd544w3juCAIxnU+/vhjk6DPli1bcODAATRq1AjdunUzjgcHB6Nnz57GbRYUHh6O7OxsvP7667C3ty/9wRMREREREREREREREZXAU9OTaPPmzdi8eTMA4N69ewCAI0eOYOTIkQAADw8PzJs3D4A+4LN9+3Z4eHjA19cXM2fONNteaGgoQkNDjY87duyIDz74AF9//TVCQkIwaNAgqFQqrF+/HikpKfjmm28QGBhoso0PPvgA27Ztw++//4527dqhR48eiI+Px4YNG2BnZ4eff/7ZLDi1ZMkSdOzYEe+//z727t2Lhg0b4ujRo4iIiEC9evXw+eefl88JIyIiIiIiIiIiIiIiKsJTEyQ6ffo0Vq5caTJ248YN3LhxAwAQEBBgDBIZyr8lJSVZDBAZFAwSAcD8+fMREhKCb7/9Fj/88AMkEglatmyJSZMm4YUXXjBbX6lUYs+ePZgzZw7Wrl2LBQsWwMnJCQMGDMCMGTPQqFEjs3WCg4Nx/PhxTJs2DX///Te2b98OHx8fvP/++wgPD4ebm5tV54WIiIiIiIiIiIiIiKg0BFEUxcqeBJXdyZMn0apVK5w4cQItW7as7OkQEREREVEl4d8GRERERERUUlWyJxEREREREREREREREREVjUEiIiIiIiIiIiIiIiKiaohBIiIiIiIiIiIiIiIiomqIQSIiIiIiIiIiIiIiIqJqiEEiIiIiIiIiIiIiIiKiaohBIiIiIiIiIiIiIiIiomqIQSIiIiIiIiIiIiIiIqJqiEEiIiIiIiIiIiIiIiKiakhW2RMgIiIiIiIietqdOXMGmZmZlT0Nqzg6OqJZs2aVPQ0iIiIiqkQMEhERERERERGVUWZmJlJTUyt7GkREREREVmG5OSIiIiIiIiIiIiIiomqImURERERERERE5ejYsWOVPYUitW3btty29d1332HJkiWIiYlBbm4uFixYgAkTJkAQBHTr1g2RkZHltq+qIjQ0FCkpKTh9+jQkEv1nd1esWIE33ngDy5cvx8iRIyt3ggRA/32KioqCKIrGscjISHTv3h3h4eGYPn165U2ugo0cORIrV65ETEwMAgMDK3s65aK6fO+eVLGxsQgKCsKIESOwYsUK43hVvNYqgyiKaNGiBRwdHXHgwIHKng49hZhJRERERERERERW++233/Duu+9CqVRi/PjxCA8PR/v27St7Wk+033//HVFRUZg1a5YxQFSeYmNjIQgCA00lMHLkSAiCgNjY2MqeilF2djbWrFmDIUOGoEGDBrC3t4eDgwNat26N+fPnQ6VSWVxPEIRC/1l6TU6fPh2CIDy2IG5gYGCRcxQEAbNmzTJZx/D9KezfpUuXTJbntV/5BEFAaGhoZU+jWhIEATNnzsTBgwfx+++/V/Z06CnETCIiIiIiIiKiCiCRSGBnZ1fZ0wAA5OTkQKfTles2t27dCgDYtm0batasafLcxYsXn5hjf1KIooipU6eiUaNG6N+/v8lzL774Itq3bw8fH59Kmh096pdffkFOTs5j3eeBAwcwbNgwuLq6IiwsDAMGDEBKSgr+/PNPfPTRR9i4cSP27dsHGxsbs3UDAgIsBkhq1ar1GGZetAkTJiAtLc1sXBRFfPnll1Cr1ejTp4/FdcePHw8XFxezcQ8Pj3KeJVUkX19fXLx4Ec7OzpU9lSqrX79+aNSoEf773/9i4MCBEAShsqdETxEGiYiIiIiIiIgqgJ2dHRo1alTZ0wAAXLhwAVlZWeW6zTt37gCAWYAIABo0aFCu+6oK9uzZg8uXL2Pu3Llmzzk7O/Pm6RPG39//se+zRo0a+OWXX/DKK69AqVQaxzMzMxEaGoojR47g22+/xUcffWS2bmBg4BNbRm3ChAkWx3fu3Am1Wo0WLVqgdevWha7LMmRPP7lczp8Lj8GIESMwefJk7N27F88880xlT4eeIiw3R0REREREREQlZihVFRERAcC01JWBpbJDBUtc/fLLL2jTpg3s7e1NbgDn5OTgyy+/RPPmzY2ltjp06IBff/3VZFtHjx6FQqFA7dq1kZ6ebvLc3bt34e3tDUdHR1y9etU4fuLECYwfPx7NmjWDm5sbbGxsULduXXzwwQdISUmxeKyZmZn44IMPUKtWLdjY2KBBgwaYP38+bty4YXVpq59++gkAMHjwYLPnVqxYAUEQTHp1APob/4GBgcjJycGkSZPg7+8PpVKJOnXqYM6cOSb9cqZPn46goCAAwMqVK02+L49ud+fOnXjuuefg4eEBpVKJ4OBgTJo0yWK2h2EO6enpGD9+PAICAiCXy00CEnv27EGXLl1gb28PNzc3DBgwABcvXrRY0i0yMhKCIBQa0DDsr6D09HR89dVXCAsLQ61ataBQKODp6Yl+/frh8OHDFrdjuAbv3LmDN954Az4+PpBKpcZzvXLlSgBAUFCQ8TwV3G9oaKhVn8RPSUnBlClT0LBhQ9ja2sLZ2Rk9evTArl27SryN5s2bY/jw4SYBIgBwdHTEhx9+CABlLhEXGBiIGTNmAAC6d+9u8fVb0NKlS9G0aVPY2NjA29sbY8aMsXidlMYPP/wAABg7dmyZtmPNtQ8Ap0+fxvPPPw8XFxfY2dmha9euOHToUIn3V7C03aVLlzBgwAC4ubnB3t4enTt3LvJ7/uuvv6J79+5wdXWFjY0NGjZsiNmzZyM/P99s2aKuYYNjx45h8ODB8PX1hVKphI+PD3r27InffvvNbHtHjx7FoEGDUKNGDSgUCvj5+WHs2LHGgH9Bhutfo9Hgiy++QN26daFUKuHn54dJkyaZzNfwmgKAqKgok/NveJ2XphygNfMtTMH31r/++gtdu3aFk5OTyfW+efNmDBs2DPXq1TP+3GnZsiUWLlwIrVZrts2C72vWvD527tyJTp06mbxPXrp0qcjSl9aeg1dffRXAw583RCXFTCIiIiIiIiIiKjFD8GfFihWIi4tDeHi4VevPmzcPe/bsQd++fREWFma8oZaWloawsDCcOnUKrVq1wqhRo6DT6bBz504MGTIE58+fx+zZswEA7dq1wxdffIFJkyZhzJgxxhuiOp0Ow4YNQ0JCAlatWoW6desa9/vjjz/ijz/+QLdu3fDMM89Aq9Xi+PHjWLBgAbZv347o6Gg4Ojoal8/Pz0ePHj0QHR2NZs2aYejQoUhLS8Ps2bMRFRVl1TGLooi9e/fC19fX6gwVtVqNnj174s6dO+jTpw9kMhk2b96MKVOmIDc313jDPzQ0FGlpaVi0aBGaNWuGAQMGGLfRvHlz49czZ85EeHg43N3d8fzzz8PLywtnz57FvHnzsH37dhw+fNgsqyk/Px9hYWFITU1Fr1694ODgYAyo/P777xg8eDAUCgUGDx4MHx8fHDx4EB06dECzZs2sOtbCXLx4Ef/973/RtWtXPP/883B1dUVcXBy2bNmC7du3Y+vWrXjuuefM1ktOTkaHDh3g6OiIQYMGQRRFeHl5ITw8HJs3b8aZM2dMyplZKmtWEnFxcQgNDUVsbCy6du2KPn36ICsrC9u2bUPv3r3x/fff46233irDGQAUCgUAfUaGJWlpafj5559x7949ODs7o1WrVhb7EU2YMAGbN29GVFQURowYUWSWzscff4ydO3eib9++6NmzJyIiIrBs2TJcuXLF6tfAo+7fv48///wTDg4OGDJkSKHL7dixAxkZGZBKpahTpw7CwsLg5ORkskxJr30AOH78OObOnYsOHTrgzTffRHx8PDZu3IgePXrg1KlTaNiwYYmPISYmBh06dECTJk0wduxY3L17F+vXr0efPn2wdu1as4Dw6NGj8fPPP8PPzw8DBw6Es7Mz/vnnH3z22WfYu3cvdu3aZfb9LewaBvTvaW+//TakUin69euHunXrIiEhAdHR0ViyZAleeeUV43aWL1+OMWPGwMbGBv369UOtWrVw9epVLFu2DH/++Sf++ecfi+9NQ4YMwYEDB9CnTx84OTlh+/btmDdvHhISEoyB1ubNmyM8PBwzZswwK3tY2h5FpZ1vYTZs2IC///4bzz33HMaNG4eYmBjjc5988gkkEgnatWsHX19fpKWlYe/evZg4cSKOHTuGtWvXWtymNa+P9evXY8iQIVAqlXjllVfg4+ODw4cPF/k+WZpz4O/vD19fX+zZsweiKLLkHJWcSFXCiRMnRADiiRMnKnsqRERERERUifi3QeU4cOCAuHXrVnHr1q3i1KlTxalTp4pz5swxjlX2vzlz5hjnZRg7cOBAmY65W7duYmG3FQCI3bp1MxkLDw8XAYh2dnbiyZMnzdYZMWKECECcN2+eyXhubq7Yq1cvURAEk/V0Op34/PPPiwDE77//XhRFUZw+fboIQBw5cqTZ9mNjY0WNRmM2/v3334sAxC+//NJk/PPPPxcBiC+99JKo1WqN4zdu3BBdXV1FAOKIESMsHv+jLl68KAIQ+/XrZ/H55cuXiwDE5cuXm4wHBASIAMQ+ffqIOTk5xvH79++Lzs7OopOTk6hSqYzjMTExRc5r3759IgCxU6dOYlpamsU5jB8/3uIcevToIWZlZZk8l5mZKbq5uYkymUyMjo42eW7ChAkiABGAGBMTYxyPiIgQAYjh4eEW5xgQECAGBASYjKWlpYmJiYlmy8bGxore3t5i/fr1zZ4z7Hv48OGiWq02e95wvRWcW0GWru/C5t6tWzdREATxt99+MxlPTU0VmzVrJtrY2Ih37961uJ+S6t27t8m1XpDhWB/916xZM/Hs2bNmyxteixERERb3ZTg3/v7+YlxcnHFcrVaLXbp0EQGI//zzT5mO54svvhABiGPGjClyDo/+c3R0FL/99luz5Yu79g3fOwDiihUrTJ4zvAeMGzeuRHM37AuA+NFHH5k8Fx0dLcpkMtHFxUVMT083jhteX4MGDRJzc3NN1jF8PxYsWGAyXtQ1fP78eVEmk4murq7iuXPnzOYYHx9v/Pry5cuiXC4X69atK965c8dkub1794oSiUTs37+/ybjh+m/ZsqWYnJxsHM/KyhKDg4NFiURiti1L7/sGhX1/LL0OSzPfwhjOuyAI4o4dOywuc+3aNbMxrVYrDh06VAQgHjlyxOKcS/r6yMjIEF1cXESFQiGePn3aZFuTJ0+2+D5ZlnMwYMAAEYDF64KoMCw3R0RERERERESPzZgxY9CiRQuTseTkZKxevRpt2rQxltUysLGxwf/+9z+IomjyiW5DCSFfX19MmDABS5YswaxZs9CgQQN8++23ZvsNCAiAVCo1G3/rrbfg5ORkViJq+fLlkEgkmDt3LiSSh7dPgoKC8P7771t1zPHx8QAAb29vq9Yz+Oabb2Bra2t87OXlhf79+yMjIwOXL18u8XYWL14MQF/m69FsoZEjR6J58+aFfmp+3rx5sLe3NxnbsmULUlJSMGTIELOeMtOnTy+3PkvOzs7w8PAwGw8ICMDLL7+My5cvG89xQQqFAvPmzYNMVnGFdM6cOYOoqCgMGjQIL7/8sslzLi4umDFjBvLy8rBx48ZS7+Pbb7/F33//jZCQEIwaNcrs+Q8++ACHDh1CYmIiMjMzER0djUGDBuHMmTMICwvD7du3S7XfadOmmWQqyGQyvPHGGwCA6Ojo0h0M9Jl1y5YtA4BCM6y6du2K9evXIy4uDrm5ubh+/TrmzZsHAHj33XeNpeqs1blzZ4wYMcJkbNSoUZDJZFYfk7OzM6ZNm2Yy1rp1a2PW4R9//GEcX7RoEeRyOX788UfY2NiYrPPZZ5/B3d0da9asMdtHYdfw//3f/0Gj0eCzzz5D48aNzdbz8/MzWVatVmPhwoXw8fExWS4sLAz9+vXDn3/+iYyMDLPtzJ07F25ubsbH9vb2GDp0KHQ6HU6cOGHptJRZWeZbmH79+qF3794WnwsODjYbk0gkmDhxIgAUWj6wpK+PLVu2IC0tDUOHDjXLGpo6darFDMaynIMaNWoAAG7evGlx3kSWsNwcERERERERET027dq1MxuLjo429n6w1KtGrVYDAC5dumQy7uHhgbVr1yIsLAz/+c9/YGNjg/Xr15sFMwzbWLp0KdatW4cLFy4gPT0dOp3O+HzBG+mZmZm4du0a/Pz8LN5ADA0NNZZ5K4nk5GQAgKura4nXMXBxcbE4B8NN4NTU1BJv68iRI5DL5Rb7lQCASqVCYmIikpOT4e7ubhxXKpUWSyKdPHkSANCtWzez55ydndG8efMylyUzOHToEBYtWoQjR44gISEBKpXK5Pnbt2+blV4KDAw0luaqKEeOHAGgL/dm6dpNTEwEYH7tltTGjRsxYcIEeHt7Y+PGjRbLzc2fP9/kcevWrbFhwwYMGjQIGzduxLx587BgwQKr9/1o4A+wfN2tWLHCrJ9KaGhooaXG9uzZgxs3bqBly5YW9wHALBhWu3ZtfPjhh6hXrx769euH//73vxg9erTFwG9RLO1PLpfD29vbqtcSALRs2dKkRKVBaGgoVq5ciVOnTmHEiBHIycnBmTNn4OHhgYULF1rcllKptHiNFHYN//PPPwCAPn36FDtPwzUaGRmJY8eOmT2fkJAAnU6Hq1evolWrVibPlfQaKE9lmW9hLP3cMUhOTsZXX32F7du348aNG8jOzjZ5vrAga0nPzalTpwDoA5SPcnBwQPPmzc16jZXlHBiCeklJSRbnTWQJg0RERERERERE9NgYPuVckCGIEh0dXeSn+bOysszG2rZtC39/f8TExKB79+4ICQmxuO7gwYPxxx9/oHbt2ujfvz9q1KgBpVIJAFi4cKFJI/b09HQAhWf+WDqGohiygPLy8qxaD0Ch2TiGzAJLjdULk5ycDI1GU2yAKysryyRI5O3tbbG3RXmfp8L88ccfGDRoEGxsbPDss88iODgY9vb2kEgkiIyMRFRUlMn3r7z3XxTDtbt7927s3r270OUsXbvF2bhxI1599VV4eXlh3759qFOnjlXrjxs3Dhs3bsT+/fut3jdg+dqzdN2tWLHCYjCwsCCRIQuoNH2a+vbtC19fX9y+fRsXLlxA06ZNrVq/qNeTNa8loPjr3vD6SE1NhSiKSExMtCq4XHBbjzL0cvP19S12G4Zr9KuvvipyOUvXaEmvgfJUlvkWpqjz2KZNG8TExKBt27Z4/fXX4ebmBplMZuxzZem9BSj5uSnufdLSeFnOQW5uLgCYZJ8SFYdBIiIiIiIiIiJ6bCwFGww32yZOnIivv/7aqu2NHz8eMTEx8PDwwI4dO7B27VoMGTLEZJnjx4/jjz/+QI8ePbBjxw6TbAydToe5c+danM/9+/ct7vPevXtWzdGQCWC48VdZnJ2dodPpkJKSYtV6hTU/L815MpTu02g0FtdJT083u/n62WefQaFQ4Pjx42jYsKHJc2PHji00W+lxNG03zHXRokVWlyEsyrp16zB8+HDUqFED+/btQ926da3ehuG6ezQzorw9mgVRlISEBGzZsgUODg5mr9OS8vLywu3btyv8uIpT3HVvuDYM/7do0cKYfVdShV3DhhJlt2/fRoMGDYrchmH/6enpcHJysmr/laEi5lvYeVy2bBliYmIQHh5ulgl45MgRLFq0qMz7NhxDYdeLpfGynAPDz5mKzqKkqoVBIiIiIiIiIqIKkJOTgwsXLlT2NADo5/Ika9u2LSQSCQ4cOGDVehs2bMAPP/yAbt26YdWqVWjVqhXGjRuHtm3bmmRdXLt2DQDQv39/s3Jdx44dM37y2sDR0RF16tTBjRs3cP36dbNyb9bcFAeAxo0bQyqVlrrkWEkZSm8V9gn/9u3b46+//sL58+ct9jGxVsuWLQEAUVFRZuXB0tPTcfr0abN1DCX3LPXLuHbtGtLS0syCRNeuXUPjxo3NAkQ6nQ4HDx4s1dyLO1cl1b59ewDAgQMHyi1ItHr1aowcORK+vr6IiIhA7dq1S7Wdo0ePAoDZ+uV17KWxfPlyqNVqjBw50mKptuJkZGTg4sWLEAQBgYGBxvHKOKaTJ08iMzPT7DgM7w+G3msODg5o3Lgxzp8/j5SUFJMeP6XVvn17HD9+HDt37iw2SNS+fXucOHECBw4cwPPPP1/mfRdGIpGUy/l/XPMFHv5sGDhwoNlz5VUq03AdHDx40Ox9Misry+L7ZFnOwaVLlyCRSKzOsqPqTVL8IkRERERERERkLZ1Oh6ysrCfiX8HeO08iLy8vDB06FMePH8esWbMsZplcv34dMTExxsc3btzAmDFj4OHhgTVr1sDPzw+//PILsrKyMHjwYJOeNYabyY8GdxISEvCf//zH4pzeeOMN6HQ6TJ482eT8xcTEYPHixVYdn6E/z9mzZ80CUuXJ1dUVgiAU2rDc0Ih9zJgxuHPnjtnz2dnZxl4nJdG/f3+4urpi7dq1OH78uMlz06dPN5ZZKqhBgwZwcnLCli1bkJCQYBzPzc0tNMgSGBiIq1evmvQGEUURM2bMKHUg1lBOr6zN3Vu3bo0uXbpg06ZN+Pnnny0u8++//5oca1FWrFiBESNGwN/fH/v37y82QHTy5EmLGTXnzp3Dp59+CgAYNmyYyXPldezWEkURy5YtA6DPACvMvXv3jDfvC8rOzsaoUaOQl5eHZ555xqSEWHHXfkVIT0/HzJkzTcaOHz+ONWvWwNnZGS+++KJx/IMPPoBKpcKoUaOMpeIKSk1NtSrL6O2334ZMJsPMmTMtBp9v3bpl/Prdd9+FXC7HxIkTceXKFbNlVSqV1QF6S9zd3cvl/D+u+QIPfzZERESYjJ86dQpffvllueyjf//+cHZ2xpo1a3DmzBmT52bPnm3xeijtOcjPz8fp06fRokULY7YZUUkwk4iIiIiIiIiIKt23336Lq1evYtq0aVi1ahU6d+4Mb29v3LlzBxcvXkR0dDR+/fVXBAUFQa1W49VXX0VGRgb+/PNPY1+O3r1748MPP8S8efPw8ccfG5vEt2nTBp06dcKmTZvQsWNHdO7cGffv38eOHTtQv3591KxZ02w+H374ITZv3oyNGzeiZcuW6NWrF9LT07F+/Xp07doVW7duter4Bg4ciBMnTmDfvn0V9ul4BwcHtGvXDvv378ewYcNQt25dSKVS9OvXDyEhIejRowfmzJmDKVOmoG7dunjuuecQFBSErKwsxMXFISoqCp07d8bff/9d4v398MMPGDx4MLp06YLBgwfDx8cHBw8exLlz59C1a1ezfjhyuRwffPABpk+fjhYtWuDFF1+ERqPB7t27UbNmTYvfi4kTJ2LcuHFo2bIlBg4cCLlcjkOHDuHChQvo27cv/vzzT6vPVY8ePfDVV19hzJgxGDhwIBwcHODi4oJ3333X6m2tXbsWYWFhGD16NBYvXox27drBxcUFt27dwtmzZ3Hu3DkcOXKk2PJPERERGD16NHQ6Hbp3747ly5ebLePi4oIJEyYYHy9evBibNm1CWFgY/Pz8oFQqcfnyZezYsQNarRZjxozBa6+9ZrKN7t27QyKRYMqUKfj333+N2V1Tp061+titsW/fPly7dg0tW7ZEq1atCl3u0qVL6N69Ozp06ICGDRvCy8sLd+7cwe7du3H37l3Url3bGGwyKO7arwhdu3bFsmXLcPToUXTq1Al3797F+vXrodPpsHTpUpMyYaNGjcKJEyewZMkSBAcHo1evXvD390dKSgpiYmKwf/9+vPHGG/j+++9LtO9GjRphyZIlGDduHJo3b45+/fqhbt26SEpKQnR0NJydnY2BjwYNGuDnn3/GqFGj0LhxY/Tu3Rv16tWDWq1GfHw8Dhw4AE9PzzJnOvbo0QPr1q1D//790aJFC8hkMnTt2hVdu3a1ajuPa74A8Prrr+Orr77CxIkTERkZibp16+Lq1avYtm0bXnrpJaxfv77M+3BycsKSJUswbNgwdOzYEa+88gp8fHxw+PBhnDlzBt26dUNUVJSxFCdQ+nMQGRkJlUplMTOKqCgMEhERERERERGVo7Zt21b2FJ5KTk5OiIqKwg8//IC1a9di48aNyMvLg7e3N+rWrYsFCxbg2WefBQB88skniI6OxsSJE80CLl988QX279+PRYsWISwsDP369YNUKsXWrVsxdepUbN++HYsXL4avry/efPNNTJ06FY0aNTKbj1KpxJ49ezB9+nSsX78eixYtQmBgIKZOnYoXX3zR6iDR6NGjMX36dPzyyy8VWkJp1apVmDhxorE/kyiKqFWrlvFG+eTJk9GpUycsXrwYBw8exJYtW+Ds7AxfX1+89dZbVveJGTRoEP7++2/MmDEDv/32G5RKJbp27YojR45gzpw5ZkEiAJg2bRpsbW2xdOlS/PDDD6hRowZeffVVTJ8+3eL3YuzYsVAqlVi4cCFWrlwJW1tbdOnSBcuXL8fGjRtLFSTq1asX5s+fjx9//BELFiyASqVCQEBAqYJEtWrVwokTJ/DNN99g48aNWLNmDbRaLWrUqIFGjRrhvffeK1Hpp7i4OGPWWmFZSQEBASZBogEDBiAjIwNnz57Fvn37kJeXB3d3d/Tp0wdjxoxBv379zLbRsGFDrFy5EvPmzcOSJUuQl5cHoOKDRD/88AMA4K233ipyueDgYLz11luIjo7G1q1bkZaWBjs7O9SvXx//+c9/8P7771ssVVfctV/egoKCsHTpUkyePBnff/898vPz0bJlS0ybNg29evUyW/67775Dnz598P3332PPnj1IS0uDm5sb/P39MWnSJLOMr+KMGTMGTZo0wbx58xAZGYnNmzfDw8MDISEhePPNN02WHTZsGJo1a4b58+cjIiICu3btgr29PWrWrIlBgwZh8ODBZToXgL4vlyAI2Lt3L7Zt2wadTofw8HCrg0SPa74AULNmTRw4cACffPIJDh48aCzft2TJEjzzzDPlEiQCgCFDhsDV1RWzZs3C+vXrTd4nP/roIwAwK7NZmnOwcuVKKBQKjB49ulzmTdWHIIqiWNmToLI7efIkWrVqhRMnThhrAhMRERERUfXDvw0qx8GDB5GamlrZ07CKq6srOnfuXNnTeCrFxsYiKCgII0aMwIoVK0q83tixY7Fy5UrExsaalMqqqkaOHImVK1ciJibGpH8M0dOstK9/okdptVrUrl0bKpUKd+/eLdO2EhISEBgYiCFDhphl2hEVh5lERERERERERGVUmgbsle1pnPPTbubMmfj111/x+eef45tvvqns6RAR0WOQlpYGhUIBOzs745goipg9ezbi4+ML7Y1njS+++AJSqRSzZs0q87ao+mGQiIiIiEpFnX0b2nzrPzEtVbpCbu9bATMiIiKqPM2aNavsKdBTwNvbG6tXr8b58+eh0+lMelAQEVHV9M8//2Dw4MHo2bMnAgMDkZWVhX/++QenT59GQEAAwsPDy7R9URTh4+ODVatWwcfHp5xmTdUJg0REVCEOxgPhUcCMbkBn/8qezZPl8OHD+OCDD/D111+jY8eOlT0dolJRZ99G3J89IOryrV5XkCgR0HcvA0VERERULfXr189inxgiIqqa6tevj379+uHw4cPYsWMH1Go1/Pz8MH78eHz66afw9PQs0/YFQcDkyZPLabZUHTFIRETlThSB/x0GrqXo/+/kBwhCZc/qyfHNN9/g6NGj+PbbbxkkoqeWNj+1VAEiABB1+dDmpzJIRERERE+twMBAsMVz8VasWMGeLVTl8PVP1goKCsKqVasqexpEhWJeMxGVu/3xwNn7+q/P3tc/Jr2kpCT8/vvvAIANGzYgKSmpkmdERERERERERERE1RWDRERPsDwNkKM2/ZenKdm6j66XowZU2uLX0+osr6vVFb+uSgtkq4C5hwDJg8whiQDMO6LPLiLgp59+glar/0ZotVpMmTIFOl0JTi4RERERERERERFROWO5OarWEhMTcf/+fahUqsqeikVXMuyQrpabjCmlWoS4ZBW7bnSyEwDTGm9eNvkIsM8rcr10lQxXMu3Nxus6ZsNFUXSE6ma2DQ4nueBcYk3jmE7UZxP9vO8qWrhmFjvvqiQhIQHJycnGx5s2bcKmTZuMj0VRxLJly9C2bVvY2dkZx93d3eHl5VXi/djb26NWrVqwtzf/vj3tNHlJ0OYlQdSVMDpKj40q/Vq5ri9I5JDZekGqdC3TdomIiIiIiIiIqOQYJKJqKzY2Fv/++29lT6NIiXkuyNQqTcYUEg1uZycXssZDydlqPBokgjwHMkXRgZpMrQLJeeY3aR2zU5EtLTqYdi/fAXvv+0OACLHAvgXosOKKBzx9L1Wr3kSffPIJLly4UOxyb731lsnjxo0b48svv7RqX7GxsejUqRMcHBysWu9JpsqMgyr9amVPgwqhzSv+fai49TVy0+tVnXUTSrfGkNv5lGnbRERERERERERUMgwSUbV19eqTcfM5XydFjk5u8bkMrQLZWtPnFKIEqRqbYrebrVOYlXiTCwrYSopeN1srR5bWfD5pGiU0YtEVKs/leiNRYx6kECFBvMoV0Vm+qGubDEdpPmRC1a8/17NnT1y9ehVqtbpEywuCAJlMhmeffdbqfalUKsTGxqJJkyZWr/ukUmfGVPYUqBKoM2MZJCIiIiIiIiIiekwYJKJqSRRFaDT68lU6nQ4JCQm4f/9+pcxFDTnuSAMBABrIIIXGmIOTJgFUgmlQRypqcFuXUux2EyVKiI+k7djqsuEophe5ngpKpEmlZuO3tGlQIr/Q9UQAh23aAIIIi+lCog6b7wWgXf5V1NLGQIaqXz7M3d0d48aNw9q1a5GSkgKxiMZMgiDA3d0dr732Gtzd3XHmzJkS7UMQBISEhAAA0tOL/t4+TUSdFqL4oImWqIUqMxairmTBNno8NDlle89UZcZCp801PlY61wUEKUsLEhERERERERE9RgwSUbUkCAJ8fHxw8+ZNSCQS1KhRA05OToiPj0dGRsZjnk0+dPIcpMhqQC3YwEGbChsxBwCgkWqgFR65YSpqoNYWf7NcI9Oaj+nUUBdzo10tSKC1EMDRaNWQiIWvmyz1QbbEpfANCxJkSN2RILqjRv45mM+uanJ2dsbo0aOxbdu2IkvPNWrUCC+88ALkcjny8wsPxlmi0Wggk8mQl1d0v6mniSCRQmbrDU3OPUCQQm7vC1X6tYeBI6p0oq5svdxEnQqiVn+tS2S2gKAPTkvljmWeGxERERERERERlQyDRFRtGbIvbt68CQCws7NDgwYNkJqaivj4eIs36qVSKYRyaqojAsgVHJAhcYNa4gitxA4SAPkyZ9hp8yEAsEcedI8EZgToIJWYZ/o8ykk07z0khbrYdRUQLa6rEERIBcvrigBibJoDog4QiihJJ+oQa9McLdWHHu2WVKXJZDIEBQUVGSQKDAyEra1tibep1WqNmUkqlarKBYkAQOFcFzpVBnSaHAhSG8idakOdfh0idMZlhEKuSap4ZT/3D98FJAon49dSW88ybpeIiIiIiIiIiEqKQSKqtiQSCZo3b46AgACcO3cOaWlpAABXV1c4Ozvj/v37uHPnDrTah5kLMpkMfn5+cHNzK5c5XMt1g/ODfkT31A7I0+lfkl4yN9hJn57SWjfznZGZ5l78goIE6VIP2DbohUZ2iRU/sSfIoUOHIJFIoNPpzJ4TBAFqtRotW7Ys8fZu3bqFO3fuANAHiezs7KDT6aBSqaBQKMpt3pVJIlXCxqMFchOPQ9TmQyKzg9wpEOqMGIjQB8gkSjfI7WtW8kyrJ0lmXNnWl9k9/FpeIEhk41Gm7RIRERERERERUckV3YWeqBpwdXVF586d0aJFC9jY6Pv/SCQS+Pj4ICQkBJ6ensbsofz8fFy7dg0XL15ETk5OmfftIX+4DWfpwyyQdK2yzNt+XEQRiM7yhYDC++0UJEDElpSGyNHKoCvZKlXC5cuXLQaIAH2PrEuXLlm1PblcbvxarX4YUKxq2UQSmS1sPVpAkOiPVyJ3hNzB3/i8Ni8RmtyEypoelYFOo3//EyRyY8BIqnCCRPr0vP8RERE9DocPH0b79u1x+PDhyp6KRd999x0aN24MOzs7CIKAhQsXAtB/ECo0NLRS5/akCg0NRUhISKF/HzxpYmNjIQgCRo4caTI+cuRICIKA2NjYxzqf27dvw9bWFp999tlj3S8REVFVxSAREfR/wNSqVQthYWGoV68eJBL9S0MulyMoKAiNGzeGk9PDT7pnZmbi3LlziImJMblBby1naR4UEn2mkq1EA4Wg/1otSqEWn46X5y2VMxI1DhBLWEBOhIDbKmdEptdGvlg9khlVKhVu3bpV5DK3bt2CSlXyHi8Fs4UKrlfVgkQAIJE7wMajubG8mUTpArlDLePzmpy70OYlV9b0qNQeZIMxi4iIiKhI33zzDY4ePYpvv/22sqdi5rfffsO7774LpVKJ8ePHIzw8HO3bt6/saT3Rfv/9d0RFRWHWrFnGvzvJOr6+vnj77bcxf/58Y/l4IiIiKj3+RkJUgFQqRf369REWFgZfX1/juKFfUd26daFUPvyUe2JiIs6ePYs7d+6U6lNgggC4y7KNj91kOXCV5sJXkQG58OR/qsyQRYQSZhEVWBPRWb5QQFMR03riqFQq+Pv7o0ePHibBRgMvLy8EBAQwSFQEqcIZSvcQCA96XkmV7pDZ1TA+r86+BW1+WiXNjspCqmCQiIiIqDBJSUn4/fffAQAbNmxAUlJSJc/I1NatWwEA27Ztw5dffonp06cbg0QXL17EL7/8UpnTe+KIooipU6eiUaNG6N+/f2VPp8y+/PJLXLx40eRv58dl0qRJUKlUmDVr1mPfNxERUVXDIBGRBba2tmjZsiU6d+4MFxcX47irqyuaNm0KPz8/SKX6rAatVotbt27h33//RWpqqtX7cpPlwk6qhq8iAy3s78BDngOp8HTUYdNBQJZOCZQwi+ghAdk6BXRC9XgLcnBwwMKFCzF+/Hg4OjqaPV+zZk0sWLAADg4OJd5mwSBRVS43V5DMxh1K18YPH9t6Q2rraXyszoqHVpVZGVOrliRyB0AoZTagIIVEagsBEv12AAhSpUnAiIiIiICVK1caP4ym0+meuKCLoUdmzZrmPSIbNGgAf39/s/HqbM+ePbh8+bJZ2banlY+PDxo0aGBSCvtx7rtnz55Ys2YN0tPTH/v+iYiIqpLqUeuJqJQM/Ypu376NixcvIi8vz9ivyMPDA7du3UJSUhJEUUR+fj6uXr0KR0dHBAQEwM7OrvgdAJAIQLBNivGxhzwHd1XmgYQnkVQQ8ZLbeeTqin4rSVDZQwsJJNDBW6HPnPKQZz8V2VLlxVBKwlIgKCsry+pSEzKZDIIgQBRFk0yi3Nzcsk30CSez84ZSVCM/Vd/DSW5XE9Bpoc1PASBCnRULwSnY2OOGKo7Uxh1ebWZDk5uAlH+/Nnte7lwPzrVfMRvXafOgzU2EROH4INCkv/ZlzCIiIqKn3JgxY3Du3LlSr69SqcxKWV+5csUkSPTpp59ixYoVJsvI5XKTDxBZo0mTJvjxxx+tXm/69OmYMWOG8bGhhyugz5YxjHXr1g2RkZFm60VERCA+Ph7ffPMNLly4AE9PT2Nfm5ycHCxatAjr16/H1atXIQgCmjZtivfffx+vvfaacVtHjx5Fly5dUKtWLZw6dQrOzs7G5+7evYvmzZsjJycHJ0+eRN26dQEAJ06cwC+//ILIyEjcvHkTOTk58PPzQ9++fTF16lS4ubmZHWtmZibCw8Px22+/ISkpCYGBgRgzZgxefPFFBAcHY8SIEWbfk8L89NNPAIDBgwebPbdixQq88cYbWL58OXx9fTFz5kycOnUKtra2eOGFF7BgwQK4uLjg+PHjmDZtGo4cOQK1Wo0ePXpg8eLFCAgIMNtmSkoKvvrqK2zevBmxsbFQKBRo3bo1Jk+ejJ49e1p1rJaMHDkSK1euRExMDAIDA02O5c8//8SpU6dw9+5dyOVyNG3aFGPHjsXrr79utp3Q0FBERUVBrVZj7ty5WL58OeLj4+Hl5YVXX30Vs2fPNqnoYfDqq69ix44dWLduHcaOHVvoeSciIqKiMUhEVAxDvyIfHx9cu3YN165dg06nM/Yr8vb2Rnx8PDIyMgA87Ffk6emJWrVqWf2pKldZLhLU9tA+JT2JHKQqOEj1QYpcnQwKQWuSCSWK+j5EalECqaCDp1zfrN5dXrWDGYUpLEhkLUEQIJPJoFarTW4m5Ofnl2l+TwO5fS2IWjVUGdf1jx38AFEDrSoDEHVQZdyAwqkOJDKbSp5p1Se1cYcqM9bic7YerSB3NL9Zocm5B1Grz3iTKFlqjoiIqo5z587hn3/+qdB95Ofn499//63QfZREaGgoAH0wIC4uDuHh4VatP2/ePOzZswd9+/ZFWFgY0tLSAABpaWkICwvDqVOn0KpVK4waNQo6nQ47d+7EkCFDcP78ecyePRsA0K5dO3zxxReYNGkSxowZg99++w2APpg2bNgwJCQkYNWqVcYAEQD8+OOP+OOPP9CtWzc888wz0Gq1OH78OBYsWIDt27cjOjraJPM/Pz8fPXr0QHR0NJo1a4ahQ4ciLS0Ns2fPRlRUlFXHLIoi9u7dC19f3yIzrLZu3Ypt27bhhRdewLhx43D48GGsWLECsbGxmDVrFp599ll069YNo0ePxrlz57B161Zcu3YN//77r8kHz+Li4hAaGorY2Fh07doVffr0QVZWFrZt24bevXvj+++/x1tvvVUhx/r222+jUaNG6Nq1K3x8fJCUlIS//voLI0aMwKVLl/DFF19YXG/IkCE4cOAA+vTpAycnJ2zfvh3z5s1DQkICVq5cabZ8x44dAQC7du1ikIiIiKgMGCQiKiFDvyJ/f39cvHgRt2/fBvCwX1Fqairi4+ONN+kTExORkpKCmjVrwtvbu8SZIlJBhJssF4lq+wo7loqyM60u7qsd4CBRwUmaD0dpPrzlWWholwgAcJHmwluRjXxRClk1yiIqyFKQKDs728KSxVMqlcYgkU6ng0QiqfKZRAYKpyCIOjXUWfEAALljIMSMG9CpswBRC3WmPlAkSEv3qVoqOVXqBYvjStdGFse1qoflQCRyfZBIEKSQKs0/uUtERERPptDQUISGhiIyMhJxcXGYPn26VetHRETgyJEjaNGihcn4hAkTcOrUKcybNw8ffvihcTwvLw8DBgzAF198gYEDBxrX+/DDDxEZGYkNGzZg6dKlGDt2LGbNmoV9+/Zh5MiRGDZsmMn2p0yZgu+++85YOtxg6dKlGDduHL777jt88sknxvH58+cjOjoaL730EjZs2GD8m+6TTz5Bq1atrDrmy5cvIykpCf369Styua1bt2Lfvn3o2rUrAH3Qq1evXtizZw9eeOEFLFu2DEOHDjUu/9Zbb+HHH3/En3/+adLnaMSIEYiLi8Nvv/2Gl19+2TielpaG0NBQjB8/Hv369UONGjXK/VjPnTuH4OBgk7H8/Hz07t0bX331Fd555x3UqlXLbL3r16/j/Pnzxoyuzz//HM2aNcPq1asxZ84c+Pj4mCxfp04duLq6Yv/+/VbNj4iIiEw9HakKRE8QQ7+iTp06lahf0c2bN63uV+Quz4HwlPQlKihTq+9PlKVT4o7aCZfzPBGb72p83kaqgUKihaNUBVuJpvImWons7c2Df9nZ2cYyItYomKVmyCaqyj2JHqVwrguZneEPRQEKx0BIZLYAAFGnzzQSderCN0DlIj/totmYROEKqa232bioUz/MIpLZQpDor2Gp0hWCRGq2PBEREVVNY8aMMQsQJScnY/Xq1WjTpo1JgAgAbGxs8L///Q+iKGLt2rXGcUEQsGLFCvj6+mLChAlYsmQJZs2ahQYNGuDbb781229AQIBZgAjQB1qcnJywa9cuk/Hly5dDIpFg7ty5Jh/6CwoKwvvvv2/VMcfH6z/c5O1t/jtSQUOGDDEGiAB92erhw4cDAEJCQkwCRACMgbDTp08bx86cOYOoqCgMGjTIJEAEAC4uLpgxYwby8vKwceNG43h5HuujASJA/wG3d999FxqNBvv27bO43ty5c01K/tnb22Po0KHQ6XQ4ceKExXW8vb2RlJRUrf4OIiIiKm/MJCIqJTc3t2L7FSUm6jNoDP2KnJyc4O/vX2y/Irmgg6s0Fymap6evilqUIEdnnrXhJH34y7pS0D7OKT2RLGUS6XQ65ObmWgwgFaVg7Xm1Wg2lUgmVSmXMKqrqBEGA0rUhoFNDk5cECFLIHYP0wSFtPkSdCqqMGCicgyEIDEBUBE1uIrR5iWbjSteGJr0JDLSqDOPXEkWBUnO2LDVHRERUnbRr185sLDo6Glqt/u8FS5lJhg9FXbp0yWTcw8MDa9euRVhYGP7zn//AxsYG69evt/i7tVqtxtKlS7Fu3TpcuHAB6enpJh/WMlSLAPRlxK9duwY/Pz+LQY/Q0FCTvkzFSU5OBqD/cGFRLGXt1KxZs9jnbt26ZRw7cuQIAH3WkKVzafg71XAuy/tY4+Pj8b///Q979+5FfHy8WbWDgue5oNatW5uN+fn5AUChH7o0BJWSkpIsZicRERFR8RgkIioDQ7+iGjVq4Nq1a7h+/bpZv6K4uDhkZmYCADIyMnD+/Hl4eHgU26/IQ56DFI0tAPMbrU8ifRaROSfZwx45imqaPVSQpSARoO9LZG2QqOD1o1KpjF/n5eUVG4isKgRBAqVbU4jJp6HNT4UgkUPhFAxV+tUHWSu5UGfEQO5UG4JQ9QNnj5vKQhYRAChdGloc11koNQcAUhvP8p0YERFRJWjSpEm5bevevXuIjY0t9HnD3xplVZ5ztoahxFlBhiBKdHQ0oqOjC13XUj/Ptm3bwt/fHzExMejevTtCQkIsrjt48GD88ccfqF27Nvr3748aNWpAqdT/HbNw4UKT/p7p6frfWwo7z5aOoSi2tvqM9+IyXpydnc3GZDJZsc8V7FNqOJe7d+/G7t27C92X4VyW57HeuHEDbdu2RWpqKrp06YKePXvC2dkZUqkUsbGxWLlyZaF9VIs6PkMA8VGGAJTh/BIREZH1GCQiKgcymQwNGjRAQEAALly4gDt37gDQ9ytq2LChSb8iURRL1K9IKdHCWZaPeyoHpGtsYC9VwVGqMlvuSZGhsRwkcpQWCBIxk6jIIJG1f+gXzCSqrkEiABAkUti4hyAv6SS0qkzTQJGohU6TDXVWHOQOgRazW6j0LJWaAwCFq3mQSBR1+p5RAASJHBKZ/hqVKhwhkVp+/yAiInqa/Pjjj+W2rTfffBMrV66ERmP+ISuZTIYePXqU6/4eN0u/kxkCBBMnTsTXX39t1fbGjx+PmJgYeHh4YMeOHVi7di2GDBlisszx48fxxx9/oEePHtixY4fJB650Oh3mzp1rcT7379+3uM979+5ZNUcvLy8ADwM4Fckw90WLFpWoVFx5HuvXX3+N5ORkLF++HCNHjjR57tdff8XKlStLvK2SSE5OhkwmMylTR0RERNbhx6qJypGtrS1atWqFTp06mXwKytCvqFatWiXqVySKQJrGBukaJe6rHZAnypChVUJ8gtsUucjy0M4hHg1tE1BLkQ4naR4k0MHpQZBIIdFCwvvzRQaJrFVUkKi6ESRyKN2bGwMPglSpzx568GNOp8qAJvsmxCf5RfSUEUUd8lMvmY3L7H0hVZh/ClSnzgSgP//MIiIiIiraP//8A41GA5lMBhsbG0ycOBE2NjaQSqXQaDTGcmJVSdu2bSGRSHDgwAGr1tuwYQN++OEHdOvWDSdPnoSnpyfGjRuHa9eumSxneNy/f3+zig7Hjh0zK4nm6OiIOnXq4Pbt27h+/brZfiMjI62aZ+PGjSGVSs3K5VWE9u3bA0CJz2V5HqvhPA8cONDsuaioqBJvpySys7Nx+/ZthISE8MNgREREZcAgEVEFcHNzQ5cuXdC8eXPY2NgA0DccrVmzJkJCQuDp+fCmqKFf0aVLl5CTkwMAiM93xs18ZwACbB6UaFOLUuToCi9PV9lcZHlobn8PXZ1i8bzrZbzmcRajvY7DVar/Y0shsNQcUHiQKDs72+ptFfzjtmB5ieoYJAIAiVQJG48WEB5kpUhkdpA7BUF4ULJRm58KTc6dypxilaLJuglRYx7cLLzU3MN+RNKC/Yhs2I+IiIiooLy8PGMgITg4GCdOnMDXX3+NEydOGPvFXLp0qcr9zufl5YWhQ4fi+PHjmDVrlsUsquvXryMmJsb4+MaNGxgzZgw8PDywZs0a+Pn54ZdffkFWVhYGDx5s8kGqwMBAAOYBj4SEBPznP/+xOKc33ngDOp0OkydPNuldFBMTg8WLF1t1fM7OzmjevDnOnj1rFpAqb61bt0aXLl2wadMm/PzzzxaX+ffff5GQkGB8XF7HajjPERERJuM7d+7EsmXLrDiK4h07dgxarRbdu3cv1+0SERFVNwwSEVUQQRDg5+eH7t27o27dusaScoZ+RU2aNIGjo6NxeUO/opiYGNiJD2+8Oksf/vGXUUjfnyeVRAAMH+hSSlhqDkChfYeYSVQ+JDJb2Hq0gCDRB9AkcgfIHQOMz2vzkqDJtVxGg6xTeKm5RmZjoigag0QCBEjk+mCpIFWaBIyIiIhI32OlSZMmeOONN3Dy5Ek0aqT/2dqoUSOcPHkSI0eORNOmTavk73zffvst2rdvj2nTpqFRo0YYNWoUpkyZghEjRqBt27aoU6cOjh49CkD/IalXX30VGRkZWLFiBXx9fQEAvXv3xocffoiTJ0/i448/Nm67TZs26NSpEzZt2oSOHTvi448/xogRI9CkSRPY2dmhZs2aZvP58MMP0aZNG2zcuBEtW7bE5MmTMW7cOLRs2RJdunSx+vgGDhwItVqNffv2lfIMldzatWsRHByM0aNHo3nz5hg7diwmT56MoUOHomnTpggJCcGNGzeMy5fXsb7zzjtQKBR45ZVXMHToUHz88cd47rnn0KdPHwwaNKhcj3HXrl0ALGctERERUckxSERUwQz9irp3727yh4ehX1GdOnWMzVIN/YriLhxDZmoCdKIOthKNsZdPvihDnu7paSWmFiXI10mhEwElM4kAlG+5OalUaixfyCDRQxK5A2w8mkMQ9OdGonCG3KGW8XlNzj1o8iq+FnxVl59qIUgkSKFwrms2LGpzIYr69wCJ3BEQ9L9+yJhFREREZMbV1RUnT57Ezz//bNZn0t7eHsuXL8eJEyfg4uJSOROsQE5OToiKisI333wDDw8PbNy4EV9//TUiIiLg6OiIBQsW4NlnnwUAfPLJJ4iOjsaECRPw/PPPm2zniy++QNu2bbFo0SJs3boVgP53561bt+Ltt9/GnTt3sHjxYhw8eBBvvvkmdu7caVaCDgCUSiX27NmDiRMnIjExEYsWLUJkZCSmTp2KBQsWWH18o0ePhkKhwC+//FKKs2OdWrVq4cSJE/j8888hlUqxZs0aLF68GIcPH4a/vz+WLl2Kpk2bGpcvr2MNCQlBREQEOnbsiO3bt+P//u//kJGRgU2bNmHcuHHldnw6nQ6rV69Gs2bN0KFDh3LbLhERUXUkiGzQUCWcPHkSrVq1wokTJ9CyZcvKng4VISUlBefOnUN6erpxTKfT4d69e7h79y60Wn1AKEvigiybWvD09IRg64pUjS0cpflwkKogFZ6Ol22qxgbpWn25PV9FBlxkeVAKGvgoMqttf6Lc3FwMHjzYbHzQoEF4/fXXrd7e2bNnkZeXB4lEgtatWwMA3N3d0bFjxzLP9WmnyUtGfvIZiKK+XIYmNwGanLvG5+UOAZAqXSppdk83UafGvcPjAZ3aZFzhXA/uzSaZLa/JuWfM4JI71IJU6Q4AsHFvBpktexIREZU3/m1AVPFiY2MRFBSEESNGYMWKFSVeb+zYsVi5ciViY2NRo0aNiptgFffnn3+iX79+WLVqFYYNG1bZ0yEiInqqMZOI6DEr2K/IkEFkqV+RnS4dWnUeEu/EQnLnKHxwD86y/KcmQATo+ygZCBCRrVUgXWtTbQNEAIwNhx9Vmkwi4GHJOZ1OZ6zbXt0ziQxkNu5QujZ++NjWC9ICAQl1Vjy0qszKmNpTT5V+zSxABACKQvoRaQv0I5LI9eXlBEECqdKtYiZIRERE9ISaOXMmFAoFPv/888qeylNLFEWEh4ejdevWGDp0aGVPh4iI6Kn39NStIqpCDP2KfHx8cO3aNVy/fh06nc7Yr8jLywvx8fHQZsZBBjWgBlKyc6FzrQN3D3fIpE/HS1ct6uPQAkRjcKu69yYSBAEODg4mmWRA6YNEBctiqNVqyGQyBokKkNl5QymqkZ+qb/4st6sJ6LTQ5qcAEKHOioXgWBsSueVeUWRZYf2IlK7mQSJRp4ao1Tdnlshsjf2ipEo3CBLzgCkRERFRVebt7Y3Vq1fj/Pnz0Ol0xt61VHL37t1Dv379MGDAAAhCNf4EIhERUTl5Ou40E1VRhn5F/v7+uHjxIu7cuQNAX2u8YcOGSElJwc2bN5Gfnw87bSrupqcgMysT7m7ucHZxhkR4cv+gEEVA8yCTSC7oYPjVnb2JUK5BIkM2GqDvS2RrawutVgu1Wm2xrnp1JLevBVGrhirjuv6xgx8gavTZLaIOqswYKJzqQCKzqeSZPj1UqRfMxgSpDeSOgWbjJllECifj11Jb9iMiIiKi6qlfv37o169fZU/jqeXj44Pp06dX9jSIiIiqDAaJiJ4AdnZ2aNWqFYKCgkz6Fbm5ucHFxcXYr8hBl4YMwR2JSYlIS0uDp6cnHBwcKnn2lmkggaEwnkx4mD2kqOaZRAAsfs/KI5NIpVIZv87Ly2OQqACFUxBEUQN1ZhwAQO4YCDHjBnTqLEDUQp15AwqnYAhSZTFbIp06G+qseLNxhUt9CIJ5ZpDOQqk5AJDasBcRERERPb0CAwPBFs9ERERUFTy5aQhE1VBR/YqaNm2KQFcZhAd/iKg1aty5ewe3bt1Cfn5+ZU4bV3LdcS7HG3H5zkjV2EAjCpBCB295FtxlOfCU58BBmg+FRAsbZhKVa5DI0JMI0JebM2DJOXNK57qQ29d88EiAwjEQEpkdAH1JNFXGDYgW+uyQqfy0SwDMb4goXRqZjYmiDjq1vu+TIJEbz7dU4QgJA3JERERERERERJWOmURET5jC+hUpFArUre0PIU2GK/eykfsgCJCTm4P4+Hg4OzvBzb1y+hVdyPXCfbWjyZiPPAP93PR9YGop0+EqY9DCwFKQKDs7u1TbKiqTiMwpXBpC1KmhyU0EBCkUjkHIz7gGUZsPUaeCKuNBRpGEPx4Lo0ozLzUHWO5HpFNnwRBQksgfvkdIbVhqjoiIiIiIiIjoScBMIqInlKFfUffu3eHj42Mc93MSjUEkuUwfIBAhIi09HbGxsUhNTYVO1D3WuWZqzTMC5MLDOSgFlpgryN7e3mwsOzsbOp313zdmEllHEAQo3ZpCqnTVD0hkD8rMPXgtafOgzoyF+JhfQ0+T/NSLZmMShQuktjXMxnWqh723pArnh1+z1BwRERERERER0ROBQSKiJ5ydnR1at26Njh07wtnZGUqJFs6yfDg6OMLLPxgObjUhEQQAgE6nQ2JSIuJi40pdvsxaalGCHJ3CbNxJ+jBIoZSwxFxBljKJdDodcnNzrd6WXC6H8OD7XzCTqDTbqi4EQQIb92aQKvSZLYJEDoVjsLGfjk6TDXVmHANFFmhyE6HNSzQbV7o2NF6HBqIoPiw1BwESuf66F6RKk6wiIiIiIiIiIiKqPAwSET0l3N3d0aVLFzQNaQZ7hRR3VI5I1DhBdPRBQEAQnJweNoR/nP2KLGURAYCjVL9fqaCDVGBD14IsBYmA0vUlEgQBMpm+NFrBIFFl96l60gkSGZTuzY09cgSpEnKn2g8DReoMaLJvsRnxI1RplyyOW+xHpM019niSyB0BQf8rh8zG3SygRERERERERERElYNBIqKnSEK2gFuCP3watoeXhxsEAVCLUqgktqjhXQP+/v6wtbExLm/oV5SQcB8abcVk82RpzbOIAMBJpg9SMIvIXHkGiYCHJec0Go0xqMFMouJJpErYeLSEINUHOiUyO8gdAyFAH8DQ5qdCk3OnMqf4xMkvpB+RwlI/IlWG8WuJ8mEQm6XmiIiIiIiIiIieHOzMTfSUydMAUqkUTYK8Ibd3Q2JSIjKyNbCXqmGjtIGfnz8yMzOQmJSkDxo86FeUkZkJdzd3OLs4QyKUX3zYX5mONzyPI1OrRIZWiUytDTK0SrjJcgCwH5ElFREkys7OhiiKUKvVUCgU7ElUQhKZDWw9WiI38ThEnRoSuQPkjoFQZcYAALR5SRAkMshsvSt5ppVPFHXITzXPJJLZ+Zr0GzLQFgwSyfVBIkGQQKp0q7hJEhERPaXyNcDZ+xWz7RBvQMm//ImIiIioEPxVkegp4mUP2Mj0gSInJeBkK4fcpyZycl0gZMRBzNf3/3B0dIK9vQPS0tKQkpIMnSga+xWlp6fDw8Oj0EBFaSgkOrhLcuEuN89eYSaRucLOfXZ2dqm2J5fLjV+rVCooFArk5+dDp9NBImHCaHEkcnvYeLRAXuIJiKIWEoUT5A5+UGfdBABocu4BghQyG49Knmnl0mTfgqgxD2QqLWQRiTo1RK3+/UAis4Ug0V+jUqUbBIm0YidKRET0FBIBpFdQtWAWzyUiIiKiovDuIdFTRBCAAJeHj70exBqcHexQt14DBAUFGQMGEokEbm5uCAw07VekUqseW78iAFAwk8iMvb29xfGylpsDALVabfyafYlKTqpwgo17MwgPsuykSjfI7Goan9dk34Y2P7WypvdEyE+9aHFc4WIeJDLJIlIUKDVnW70DbURERERERERETxoGiYieMjUdAPmDD+L7OgJ13YCGHoCLrQBPT0+EhITAx8cHgkTfV0Umk6GGdw34+flZ7leUmFDu/YrSNUokq22RrlEiXydBvk4KHT/CaFTe5eYezSQyYMk560ht3KB0a6KPxgKQ2XpCZutlfF6dFW8S/Khu8lMt9CMSpFC41DMb1lkoNQewHxEREVUfe25Y9y8iBjh9r2L+RcSY7+9pkpmZiYkTJxo/ECcIAk6fPm3VNiIjIyEIAqZPn14hc6Tyo1KpULduXbzwwgsm49OnT4cgCIiMjKyciZGZwMBABAYGmoytWLECgiBgxYoVlTKnxyU0NBTCg78bq4rq8r17UhX2c6oqXmuVIScnBz4+Phg+fHhlT+WJxSAR0VNGKgHquQHNvIEOtYAWPoCkwM8LqVQKPz8/NG3SFK5ursZxWxtb+Pn5w6dGDchk+kqTIkSkpaUhNjYWqamp0Im6cpljjk6OTJ0SqVpb3FU74UquB67nuZfLtquCiuhJZMAgUdnIbL2gdGnw8LGdj0kPHXVWHHTq0pUFfJqJOjVUGVfNxhWOtSGR2pguK+qgU+tLXwoSOSQyOwCAVOEIiVRZ8ZMlIiKiKmXy5MlYuHAhmjRpgk8++QTh4eGoUaNGZU+ryhBFEc8++ywEQYAgCNBoSv4BwtOnT2P69Ono1KkTfHx8oFAo4Ovri9deew0nT54s1XwWL16M69evY/bs2aVavzgMGJbck3hzOjk5GcuWLcOLL76IOnXqwNbWFs7OzujcuTN++ukn6HTm9zRiY2ON17elf6+++qrZOiNHjoQgCIiNjX0MR4Ui52f4t2rVKpN1DN+fwv49ej+A137lMlyHI0eOrOypVEt2dnaYMmUK1qxZg2PHjlX2dJ5I7ElE9BTycXz4ta8jcCMV0Dzyu5CNjQ3q1qmLjIwMxMfHIycnB0Dx/Yo8PT0LLYdWUmpRn+okF3TGSLSCvYmMbGxsIJVKodWaluJjJtGTQW7vqw+KpF/TP3bwA0QttKp0QNRBlRkDhVMwJDLbSp7p46NKvwbo1GbjCgv9iHTqLBi6H0jkD9+spNW8pxMREVFx7OXFL1Mdbd26FfXq1cOff/5Z2VOpkr799ltERETAxsbG6r8fxo0bh6NHj6Jly5Z46aWX4ODggNOnT2PdunX4/fffsW7dOgwcOLDE28vOzsbnn3+OPn36oHnz5ibPvfvuu3j11Vfh7+9v1Ryp4uzdu/ex73PDhg14++23UaNGDYSFhcHf3x/379/Hpk2b8Oabb2L79u34/fffLQa3mjVrhgEDBpiNN2nS5DHMvGjh4eEWx7OysjB//nzIZDI8++yzVq1r+HAwPR3atm2LixcvwsODfzdXlLFjx2L69OmYOnUqdu3aVdnTeeLwHYPoKSeVAH7OQEwh7VKcnJzQuHFjJCUl4ebNm9BoNMZ+RU5OTkhKTkJGhr40lEqtwu07t2FvZwcPD08oldZ/6l8rCtDhQbmuAv2IlOxNZCQIAhwcHJCenm4yXt49iRgkKj2FYyBEnRrqzDgAgNwxAGJGjD5DRtRC/SBQJFSTzJj8NMv9iJQW+hEVLDUnVTg//Jql5oiIiAollwJ1mXhv0Z07d9C1a9fKnkaVdPnyZUyePBkfffQR1q1bh7i4OKvWHzJkCFauXIn69eubjK9ZswbDhg3DW2+9hb59+5r8vVKUtWvXIi0tzeIn7T08PHjz9AkTHBz82PdZr149bN68GS+88AKkUqlx/IsvvkDbtm2xadMmbNy4EYMGDTJbt3nz5k9sFk1h81q6dCkAoG/fvoVmUD6px0TWsbOzQ4MGDYpfkEpNqVTi1Vdfxffff4+rV6+ibt26lT2lJwrLzRFVAX5OpiXnHiUID/oVNStZv6LsnIf9ih7NdimOIYsI0GcSGSiZSWTCUsm50gaJZDIZJBL92zkzicqP0rku5PY1HzwSoHAMMJZO05dfuwHRQnZNVaSyECQSpDaQOwWZjevU+iCRAAESucODZZUmWUVERET0dMvKyoJCoUDnzp1NxrOzs6FQKCyWRlqyZAkEQcDPP/9sHDOUS8rPz8e0adNQt25dKBQKjBw50vicKIqIiooyllAKDQ012e6uXbvQt29feHl5QalUws/PD/3798eePXsszv306dN4/vnn4eLiAjs7O3Tt2hWHDh2yuKxGo8GSJUvQvn17ODk5wc7ODi1atMC3335rVtaqYCmh69evY9CgQXB3d4ejoyN69uyJc+fOAQDu37+P0aNHw8fHBzY2NmjTpk2p++x8+eWXEAQBixcvtvj8zZs3IZVK0aZNG4vHNnz4cAQFBWHGjBml2v/7779vFiACgKFDh6Ju3bpISUnB2bNnS7y9n376Cba2tujXr5/Zc4X1JDJcE0lJSXjrrbfg4+MDpVKJxo0b46effjJZduTIkejevTsAYMaMGSaluR7d7q+//oru3bvD1dUVNjY2aNiwIWbPno38/HyzuRnmcOfOHbzxxhvw8fGBVCo16e2ybt06tGrVCra2tvDy8sLw4cNx584diyXdiusNY+l1cOfOHcycOROdOnVCjRo1oFAoULNmTbz22ms4f/682TYKXq+XLl3CoEGD4OnpCYlEYtx/VFSUcX+WXn+WehIV5datW3j33XdRu3ZtKJVKuLu7o1+/foiOji7xNsLCwtC/f3+TABEA1KhRA+PGjQOAMvetEgQBK1euBAAEBQUZj93SsWo0GnzxxReoW7eu8f1n0qRJFq+T0vjhhx8A6DMgysKaax8AIiIiEBoaCkdHRzg5OeG5556zeB0VpmBpuyNHjuCZZ56Bs7MzHB0d0atXLxw/ftzieqV9z330Gi54TNb8jNi5cyeee+45eHh4QKlUIjg4GJMmTUJaWprZsobrPycnB5MmTYK/vz+USiXq1KmDOXPmQBQfNuaePn06goL0fzuvXLnS5PwbXuelKQdozXwLU/C99ZdffkGbNm1gb29vcr2vWLECAwcORO3atWFrawsnJyd06tQJv/zyi8VtGt7XrH19rFmzBi1btizR+2Rpz8Grr74KURRNfhchPWYSEVUBCilQ0xG4lVH0cjKpDH5+fvD09MTNm/FITU0D8LBfUWZmBhKTkqDRaIz9ijIyMuDu5g5nF2dIhOLjyiIAuaCFRpSaZBIpmElkojyDRIC+5Fx+fj4zicqZwqUhRJ0amtxEQJBC4RiE/IxrELX5EHUqqDJu6DOKJFX3x6lOnW3MqCpI4VIfgmD6x5lOk2MMnEnkjsCD9wyZjfsTV8+ciIiISs/BwQFt27bF0aNHkZWVZfzd9sCBA8bfR/fu3WvSIHrfvn0AgB49ephtb+DAgTh+/Dj69OmDAQMGwNvbG6GhoQgNDcWMGTMQEBBgzC4peOMqPDwcM2fOhIODAwYMGAA/Pz/cuXMHhw4dwurVq/HMM8+Y7Of48eOYO3cuOnTogDfffBPx8fHYuHEjevTogVOnTqFhw4dZ0mq1Gn379sXOnTvRoEEDDBkyBDY2NoiIiMB7772Hf/75B6tXrzY7ltjYWLRr1w4NGzbEyJEjERsbiz/++AOhoaE4dOgQevfuDRcXFwwePBipqan49ddf0bt3b1y5csXqUmqvv/46pk6dipUrV+L99983e37VqlXQ6XQYMWKE2XOzZ8/GqVOncOTIkVJVkCiOIXuoYGnsoqSnpyM6OhodOnSwej5paWno1KkTFAoFBg0ahLy8PPz+++948803IZFI8MYbbwCAsdTYypUr0a1bN7OAh8Ho0aPx888/w8/PDwMHDoSzszP++ecffPbZZ9i7dy927dpldlzJycno0KEDHB0dMWjQIIiiCC8vLwDAggUL8MEHH8DFxQWvv/46XFxcsHPnTnTs2BHOzs4oD/v378ecOXPQvXt3DBw4EPb29rh69Sp+//13bN26FYcOHTIr4QcA165dQ/v27VG/fn0MGzYMWVlZaNq0KcLDw7FixQrExcWZlDOzJihU0MmTJ9GzZ0+kpKSgV69eeOmll5CUlITNmzejc+fO+OOPP/Dcc8+V8uj1irvm7ty5g6VLlyI5ORnu7u7o0KEDQkJCzJYLDw/H5s2bcebMGYwfPx4uLi4AYPy/oCFDhuDAgQPo06cPnJycsH37dsybNw8JCQnGQFNpnTx5EidPnkRgYGChpeYAYP369YiJiYFCoUDDhg0RFhZm9hoq6bUPANu2bcOWLVvQp08fjBs3DhcuXMD27dsRHR2NCxcuwNOz5BUijh49ii+//BLPPPMM/vOf/+DatWvYtGkT9u/fj127dqFLly7GZUv7nmvpGnZ01H9A0ZqfETNnzkR4eDjc3d3x/PPPw8vLC2fPnsW8efOwfft2HD582Oz1qlar0bNnT9y5cwd9+vSBTCbD5s2bMWXKFOTm5hoD8KGhoUhLS8OiRYvMyh5ael2WRGnmW5R58+Zhz5496Nu3L8LCwkyCLG+//TYaNWqErl27wsfHB0lJSfjrr78wYsQIXLp0CV988YXFbVrz+vjqq6/w8ccfw9XVFSNGjICzszN2796NTp06FXocpTkHbdq0gVwux65du/Dll1+W+PxUB1X3rhZRNRPgDNzOMHQCKZqNjQ3q1q1X5n5FURmBuKdyhJM0H47SfDhJ8+Aiy4O/Mh2iCNRUZkAh6JAvSmHDTCIT5R0kUigUyM/Ph1arhVarhVQqZZCoHAiCAKVbU4hJp6HNTwEkMiicgqHKuApRq4aozYM6MxZyp9oQShBEfRrlp12CpXeW4krNSZROxq9Zao6IiKjqCQsLw6FDh7B//37jzd29e/dCJpOhc+fOJv1KdDodIiMjUbt2bQQEBJhtKz4+HufOnbNYTmzGjBkIDAw0+3T1rl27MHPmTNSuXRv79++Hr6+v8TlRFHH79m2zbf31119YsWKFSdBk6dKlGDduHBYvXoz/+7//M45//vnn2LlzJ8aPH4/58+cbMxe0Wi3eeust/Pzzzxg0aJBZj5OoqCjMnj0b//3vf41js2bNwrRp09CuXTu8+uqrWLJkibESQK9evTB06FAsWLAACxYsMJtzUXx9fdGjRw/s3r0b586dM+utsmrVKsjlcrz22msm49HR0fj888/xySefoHXr1lbtsySOHj2K8+fPw9fXt8T9Xo4cOQKdTodWrVpZvb8zZ85g9OjRWLp0qfH7NHHiRISEhGDu3LkmQSIXFxesXLkSoaGhFj+xv2LFCuP3dtWqVbApUHFj+vTpmDFjBr777jtMmDDBZL1z585h+PDh+Pnnn016wcTGxuKTTz6Bq6ur8YY/oM8Ce/nll7Fp0yarj9eSsLAw3L9/33hz3ODkyZPo0qULPvnkE/z9999m6x06dAhTpkwxu8nbqlUrREZGIi4urszlzDQaDV555RVkZ2dj//79JhmId+7cQZs2bTBq1CjExsaanG9r92G46dy7d2+Ly+zevRu7d+82GQsNDcXKlStNArTTp09HbGwszpw5gwkTJhQZGLt+/TrOnz8PNzc3APr3jWbNmmH16tWYM2cOfHx8SnU8wMNSc2PGjDG+X1jy6quvmjz28vLCd999Z1JyryTXvsHmzZuxc+dOk4D+lClTMGfOHPz888+YPHlyiY/h77//xjfffIN3333XOLZlyxYMGDAAo0aNwuXLl43HVtr33MKuYWt+RkRERCA8PBydOnXCX3/9ZRJYWLFiBd544w2Eh4dj4cKFJvu4c+cOmjVrht27d8PWVt+zODw8HPXq1cPChQsxdepUyOVyhIaGIjAwEIsWLSqXsoelnW9x2zxy5AhatGhh9ty5c+fMykvm5+ejd+/e+Oqrr/DOO++gVq1aZuuV9PVx48YNfPrpp/Dw8MDJkyfh5+cHAJgzZw6GDBmCdevWlds5sLW1RePGjXH69GlkZmaavWdWZ1XzjhZRNWQrB7wexG9EEVCVIHHH0K8oKCjI+IusoV9RYGCQyZuloV/R7du3oFLpU0PTNLZI09oiXuWC87neOJIVgCOZ+l+uBAFwkubDSZYPT3kOpEJJwlfVh6UgUXZ2dqm3V7DOt6HkHINE5UMQJLBxD4FUoQ96CBK5PnvoQRaNTpMNdWYsRFFX1GaeWpZKzQGAwrWR2Zi2YJBI/uB8CRJIlW4VMzkiIiKqNIYbiAWDQXv37kXbtm3x4osv4tatW7hy5QoAfYm35ORki1lEgP7TwNb2m/nmm28A6D/9XPDmH6D/oI+lG1adO3c2y6oZNWoUZDKZSckrnU6Hb7/9Fj4+PiY3KwFAKpVi/vz5EAQBa9asMdtHYGAgPvnkE5Mxwz7VajW++uorkxu+gwcPhlwux+nTp0t45KYM2370U9lHjx7FpUuX8MILL8Dd/WHDq9zcXAwfPhyNGjXCtGnTSrXPoqSmphozyB49d0WJj48HAHh7e1u9Tzs7OyxYsMBkX40aNUKnTp1w6dIlZGZmlnhbixYtglwux48//mgWsPjss8/g7u5u8fuuUCgwb948kwARoC+fpFKp8N5775kEGyQSidm1UBZeXl4Wb3a2bNkSYWFhiIyMNKk6YeDt7W2SKVQR/vrrL1y/fh3vvfeeWYnKmjVr4uOPP8b9+/dN3kus9cknn+DcuXPo06cPevXqZfKcnZ0dPvvsM5w4cQKpqalITU1FVFQUunfvjsjISPTo0aPUf4vPnTvXeAMcAOzt7TF06FDodDqcOHGi1MeTlZWFX3/9FTKZDKNGjbK4TP/+/fHnn3/i1q1byM3NxaVLlzBlyhSkpaVh8ODB2LFjR6n2/dprr5m9V7/11lsAYFVpQACoU6cO3nnnHbN5d+vWDdeuXcOBAwcAlO09t7Br2JqfEYaSnT/88INZ5snIkSPRvHlzrF271uIxfvPNN8YAEaB/Lfbv3x8ZGRm4fPmyxXXKqizzLcyYMWMsBogAy/3HlEol3n33XWg0GmOm8KNK+vpYu3YtNBoN3nvvPWOACNB/n+bMmWPx50hZzkGNGjWg0+ksfpikOmMmEVEV4ucMXEwCErL1n/tv4K4P1hTF0K/I1c0Vd+7cwf379yHqRMhkMvjU8IGLiwuSEhOR+yDgkJ2Tg5y4eDi7OCMDzc225yTNf7Bd0aQnEZkqmJFlkJ2dDZ1OV6o/FAoGidRqNWxtbaHRaKDRaMz+UCHrCRIZbNybIzfpBHTqbAgSJeROtaHOuAFR1EKnzoQm6yZkDv5Vrqxafqp5kEiicIHM1rRxqqhTQ9Tm6p+X2UKQ6Ms8SJVuECQluzlARERET48OHTrA1tbWeHMoJSUFZ86cwX//+1+TAFK9evWMy4SFhVncVrt27aze/z///ANBEArNGrDEUtaMXC6Ht7c3UlNTjWNXrlxBcnIy6tati1mzZlnclq2tLS5dumQ23rx5c7MbWjVr6vtc1qtXz+xGvlQqhZeXF27dulXi4yjopZdegpOTk/GT2YZ9G3pFGMr0GXz88ce4ceMGjh07VuJScCWVnZ2Nvn374urVq/jwww8xePDgEq+bnJwMAHB1dbV6v5bOKwDjzca0tLQSfVo8JycHZ86cgYeHR6GfwFcqlRa/74GBgcbycgWdPHkSANCtWzez52rXrg0/Pz/ExZmXdi6Nv/76C99//z2OHz+OpAdl5AtKSkoyy2xp1qxZhZQbLOjIkSMA9FlVljIorl69CgC4dOkSnn/+eau3v3DhQsyfPx/169e32CPFy8sLM2fONBnr2rUrdu3ahc6dO+Po0aNYtmwZxo8fb/W+Lb2nGK67gu8pCxcuNOuRMmDAgEJLjf3666/IzMzESy+9hBo1alhcZuLEiSaP69evjy+++AI1a9bEe++9h08//RR9+vSx4mj0SnpMJdGlSxeL9zdCQ0MRFRWFU6dOoVu3bmV6zy3sGrbmZ8SRI0cgl8vx22+/WXxepVIhMTHRWKrQwMXFxWIApbTnq6RKO9+iFPVzOD4+Hv/73/+wd+9exMfHIzc31+T5woItJb2WTp06BQBmQWQACAgIgJ+fH2JjY03Gy3IODIGrpKQki+tWV7xzSFQFaHT6UnPx6UBqHpD34HfB9HzApYTZ2jKpDP5+/vDy9CpRv6LktEzkOCnMtuMk1QeTlIK22ABVdWYpk0in0yE3N9diAKk4Bf/AM2QSAfpsIkv7IusJUgVs3FsgL+k4dJo8SGR2kDsG6gNFEKFVpQE5MsjtfYvd1tNCk5cEbV6C2bjStaFZMMwki0hRoNScrXWfCiYiIqKng0KhQOfOnbFnzx4kJSUhKioKOp0OPXr0QOPGjVGjRg3s3bsXb7/9Nvbu3QtBEAoNEhV2E7QoaWlpcHV1NfkEd3EK62sgk8mg1T4sxWAIWFy9etXYU8ISS+WiLe3D8KGtovZvKcujJGxtbfHyyy/jp59+wq5du9CnTx+oVCqsW7cOnp6eJjeJo6Ki8N1332H69Oml7oNRmKysLDz33HM4dOgQJk6ciHnz5ll9HEDpqiEUdV4BmHxvi5KamgpRFJGYmFjk992Swq7h9PR0AIVnSNWoUaNcgkSLFy/G+PHj4erqimeffRb+/v6ws7ODIAjG/jqWmsWX5rVnLcPracOGDUUuV5ry64sWLcLEiRPRsGFD7Nu3z6qMRJlMhjfffBNHjx7F/v37SxUkKur1XvC6W7hwodn3OTAwsNDX4Q8//ADgYQaPNd58801MmDCh1OW0SnpMJVHUdQ88fH2U5T23sGvYmp8RycnJ0Gg0xb7us7KyTAIO5fXeY63SzrcohZ3HGzduoG3btkhNTUWXLl3Qs2dPODs7QyqVIjY2FitXrrT43gKU/Foq7n3S29vbLEhUlnNgCHJZ8/tDdcAgEVEVkJwDXE3Rf+1pB2Q+eH9OyC55kMiguH5F+vTsFGQLlgMPjg8yiRTsQVSkwgI3WVlZpQoSWSo3BzBIVN4kMhvYuLdAbuJxiDo1JHIHyB0DocqMAQBo85IgCFLI7Cr+j63HQWUhiwgAFC7mpeZ0FkrNAexHREREVJWFhYVh9+7diIiIQEREBGxtbdGhQwfjc3///Tfy8/Nx4MABNG7c2GKmBYBSZWK7uLggOTkZubm55X6jx3Bj68UXXyy3njEVacSIEfjpp5+wcuVK9OnTB9u2bUNKSgrGjx9v8mGyU6dOQRRFhIeHF1pizLD8qVOnShxIysjIQJ8+fXD48GF8/PHH+N///mf1MRiuDcPN4spg+L63aNHCmAFUUoVdw4Zt3r9/H40bNzZ7/t69e2ZjhsyLRzOBAJhloxiWCw8PR40aNXDy5EmzbCFDJo818y5PhnOwZcsW9OvXr9y2O2/ePEyaNAlNmjTB3r17C31/KYphnbKUfi+JR29wF+X06dM4fvw4goKC0LNnT6v3ZWNjAycnJ6SmpiI7O7tSe67cv3/f4rjhujdcG2V5zy3sGrbmZ4SzszN0Oh1SUlKs2ndlqYj5FnYev/76ayQnJ2P58uVmmam//vqrWanT0nBy0t8/KOx90tJ1VJZzYPg5U5r3jKqMPYmIqgAve31PIgBwUgK2D8K/OeqHASNrGfoVBQYGmvQrcnd3R2BgEBzsbeGtugFnTQIUuhzjenai/pMdSqFiPjFRVRQVJCqNR8vNGbAvUfmTyO1h49ECguTB60LhBLnDw7q5mtz70OQmVtb0ylV+If2IlC4NTB6Log46jf7aFSQySGR2AACpwhESacWWryAiInoSXU2umH+5pUs2qTCGsnL79u3Dvn370KVLF+PvpT169EBKSgr+7//+D9nZ2YX2Iyqt9u3bQxRF7Nq1q1y3CwANGjSAi4sL/vnnn1Jn+DxOXbp0QXBwMLZs2YL09HTjTbtH+y81adIEo0ePtvjP8PfJqFGjMHr06BJ/+jwtLQ3PPvssDh8+jP/+97+lChABQEhICABYLCdVngzl+Cx9wt/BwQGNGzfG+fPny+3ma8uWLQHos7gedePGDdy8edNs3FByz9Jzx48fNxtLSkpCWloaOnbsaBYgysrKsjrgZVDUubJG+/btAcDYf6Y8fPnll5g0aRKaN2+OiIiIUt/sPXr0KAB96b+CyuvYS2Pp0qUA9BlBpQniXb16FampqXB0dDTJrKqMYzp48CB0OvM2BJGRkQBg7IFTEe+51vyMaN++PVJTU3H+/Ply2bcl5Xn+H8d8Da5duwYAGDhwoNlzlt7XSsNwHRw8eNDsubi4OIvvhWU5B5cvX4a7u7vF3oXVGYNERFWAIAABBbI4vQrEH1LKECMQBAFeXl4IaRaCGj41IEj0v6DIZDLUreGEXp430Um3H52yNqFrxq9om/Un1HfPITExEVJdKaNT1UR5B4kKKzf3aK1YKh9ShRNs3EIgCPofo1KlG+T2NY3Pa3LuQJtfMfWHHxdR1EFlIUgks6sJqdLFZEynzgJE/S//pllELDVHRETVU7a6Yv7pxMo+MlOtWrWCi4sLNm3ahMuXL5sEggxff/nllwAK70dUWu+99x4A4MMPP8Tdu3fNni9LQ2qZTIb33nsPd+/exfvvv2/xd+q7d+/iwoULpd5HeXv99deRl5eHJUuWYMeOHQgJCTFrQv7MM89g2bJlFv8ZgkJLly7FsmXLTJqHJyUl4dKlS2b9G1JTU/HMM8/g2LFjmDFjBmbPnl3q+Tdu3Bienp74559/Sr2NkjAcp6WbjgDwwQcfQKVSYdSoURazdlJTU60KugwdOhRyuRzffPONSTaJTqfDpEmTLN5Ab926NSQSCdauXWus7AHo+359/PHHZst7eXnBzs4Ox48fN/l7Uq1WY/z48aXuu1HcuSqp/v37Izg4GN999x22b99ucZkjR46YHGtRZs2ahU8//RStWrXC3r17iy0xd/ToUZO/kQ2ioqLw9ddfAwCGDRtm8lx5Hbu1srOzsXbtWshkMowaNarQ5W7cuGHxPS45ORlvvPEGAODVV1816U9cGcd09epVLFmyxGRsy5YtiIqKQp06ddClSxcAFfOea83PCEN/pzFjxuDOnTtmy2ZnZ5f5vcnV1RWCIJTL+X8c8zUIDAwEAERERJiM79y5E8uWLSuXfQwZMgQymQzffPONyfkRRRFTpkyxGFgr7TmIiYnB/fv3ERoaWuX6SZcVy80RVRE+DsD1VECtBVyUQJqN/n9nK8vNWVKifkWJSZBq9XVEU9NScTXlFnS+HvDy8uIbrwWFBYlKm+ZeVE8iqhhSGzco3ZoiL+UsIIqQ2nhC1GmhydWnQquz4gFBCmmB/jxPE032LX3w5xFK16JLzUkVDyPWLDVHRERUtUkkEnTr1g1btmwBAJMgUUBAAIKDg3H9+nVIpVJ069atXPfds2dPfPbZZ5g1axbq16+PAQMGwM/PD/fu3cOhQ4fQvn17rFixotTb/+yzz3DmzBl8//33+PPPPxEWFgZfX18kJCTg6tWrOHToED7//HM0amT+u1FleP311zF9+nSEh4dDrVabZRGVxbfffosZM2YgPDwc06dPN46/9NJLOHHiBIKDg6HT6UyeMxgwYECJytYJgoAXX3wRP/zwA86fP2+x5FB5qF+/Pnx9fbFu3TrI5XL4+/tDEAQMHz4cAQEBGDVqFE6cOIElS5YgODgYvXr1gr+/P1JSUhATE4P9+/fjjTfewPfff1+i/QUGBmLOnDn48MMP0aJFCwwePBjOzs7YuXMn0tLSEBISgrNnz5qs4+Pjg9dffx0rVqxA8+bN8fzzzyMjIwPbt29H165djU3eDSQSCd5//33MmTMHTZs2Rf/+/aFSqRAREYGUlBR0797d7AZvSfTo0QMbNmzASy+9hD59+sDW1hYBAQEYPny4VduRy+XYtGkTevXqheeffx4dO3ZE8+bNYWdnh5s3byI6Oho3btzA3bt3YWdnV+S2Vq5ciWnTpkEqlaJLly5YvHix2TKBgYEmZbEmT56M8+fPIzQ01Jg58O+//2Lv3r0A9EGnjh07mh37V199hTFjxmDgwIFwcHCAi4sL3n33XauO3Vrr1q1DRkYGXnrppSL7Re3fvx9vvvkmunXrhuDgYLi5uSE+Ph47duxAWloaWrdujblz55qsU9y1XxF69+6NDz/8EDt27ECzZs1w7do1bNq0CTY2Nvjpp5+MpRWB8n/PteZnRI8ePTBnzhxMmTIFdevWxXPPPYegoCBkZWUhLi4OUVFR6Ny5M/7+++9SnwsHBwe0a9cO+/fvx7Bhw1C3bl1IpVL069fPmElZUo9jvgbvvPMOli9fjldeeQUDBw6Er68vzp07h7///huvvPIK1q9fX+Z9BAcHY+bMmfj000/RrFkz4/vk7t27kZKSgmbNmpm9T5b2HBgyyyxlRlV3DBIRVRFSCeDvpM8cCnAG6nsAV8q5nHPBfkVxcXHGT3cY+hUlpqQjIy0ZoqiDoMlDXFwcEhIS4O/vX2hDv+qqsL5Dpc0kkkgkkMvlUKvVDBI9RjJbTyhdGiI/Vf+JJpldDYg6DbT5+hefOjMWglMwJHLr+0xVtvxC+xE1NBvTqfVBIgECJHJ9AFSQKiCRV179ayIiosrUvILaE7apWT4fAitPPXr0wJYtW+Dq6mqWudKjRw9cv34drVq1qpC/B2bOnIn27dtj8eLF2LZtG7Kzs+Hl5YXWrVvj9ddfL9O25XI5Nm/ejNWrV2PFihXYtm0bsrKy4OnpiaCgIMyaNQtDhw4tpyMpu8DAQHTt2hVRUVGQyWSPZW4xMfq+nNevXy+0eXhgYGCJexu98847+OGHH/DLL7+UumxdcaRSKf744w988skn+O2335CZmQlRFNG5c2fjjfLvvvsOffr0wffff489e/YgLS0Nbm5u8Pf3x6RJk8yyTorzwQcfwMfHB1999RVWrFgBR0dH9OrVC3PnzsWQIUMsrrN06VJ4eXlhzZo1+O677+Dv74/3338fkyZNwm+//Wa2/KxZs+Dp6Ylly5Zh6dKlcHZ2xrPPPovZs2cX2n+qOG+++Sbi4uKwbt06zJ07FxqNBt26dbM6SAToywmeOXMGX3/9NbZt24bly5dDIpHAx8cHLVq0wIwZM4rNCAIeXnNarRYLFy60uEy3bt1MgkTDhw/HH3/8gejoaOzYsQNqtRre3t545ZVX8O677xqzWQrq1asX5s+fjx9//BELFiyASqVCQEBAhQeJfvjhBwDAW2+9VeRyrVq1wrBhw3DixAmcPn0aGRkZcHR0RJMmTfDKK69g7NixJiXpgZJd++WtXbt2mDZtGj777DN8++23EEURYWFh+Pzzz9GmTRuTZSviPdeanxGTJ09Gp06dsHjxYhw8eBBbtmyBs7MzfH198dZbbxX6WrXGqlWrMHHiROzYsQNr166FKIqoVauW1UGixzVfQP/ajYiIwNSpU7F9+3ZoNBo0a9YMmzZtgouLS7kEiQBgypQpqFWrFr7++mssX77c5H2yZ8+eFn+HKM05WLlyJTw9PRkkskAQRfEJS1in0jh58iRatWqFEydOGGveUvUjivrScwCg1QEHb+oziypmXyISExNx69YtY0PNW/lOUGlF5GQkwyn9PGSiCja6HNiKWXBxcYGfn1+5N5V9WiUmJmL06NFm4yNHjsRLL71Uqm2eO3cOOTk5EAQBrVu3hiAIcHFxsfhLL5UvVWYcVOlXjY/VWXHQ5qfpHwhSKJyCIZE9Xdd+8r8LoEp9JJ1fkMK7w0JIZA/vTuk0OcZjl8odIXfS1/OW29e0mHVEREQVj38bVL49Nypmu09ikIioPPXq1QtnzpxBTExMtfjbMTQ0FFFRUeCtOapKIiMj0b17d7PsQyJrZWRkwNvbG82bN8eRI0fKtK2zZ8+iWbNmmDVrFqZOnVpOM6w62JOIqAopWNVNKgFqVWCVK5N+RTW8IQLQQAKJVAp3dzd4BjSA1t4HeRJ9BkVaWhrOnTuH+Ph4Y1CpOivvnkQAjJ8UEkXR2OyRmUSPh8IxAArHQONjuYP/wywaUQt1xg3otE9Pny5Rp4Yq/ZrZuNwxyCRABJiWmpMoWWqOiIgIAJyVFfNPwirOVMXNmzcPSUlJZn1MiIio6kpMTDTexzLQaDT48MMPkZeXVy6ZP9OmTUOtWrXw4YcflnlbVRHLzRFVYX5OQFxaxTa4lUll8PcPgKObN5KvJCMrOxty6GBrY4tafn6wywEyb6VArVZDFEXcu3cPSUlJ8PX1rdb9imxsbCCTycwCZmUJEj3al0ihUCA/Px+iKFbb8/w4KZzrQNSpoM6+A0CAwjEAqowb0GlyIIoaqDNuQOFcB4JEXuy2Kpsq4zqgM2/uqnQtvNQcAEjk+si0IEggVbpV3ASJiIiecG18K3sGRE+npk2b4ueff0ZmZmZlT4WIiB6TjRs3Ytq0aXjmmWfg5+eHlJQU7N+/H1euXEHLli3LXOoxJycHLVq0wIQJE6pFlmppMEhEVIUppICvI3Azo/hly0xmg5o1fZGTkw1N2i1Ao+9P4u3miCC3ENy9exf37t2DTqeDRqOp9v2KBEGAvb090tPTTcbLI5MIgPETGKIoIj8/HzY2rEvyOChcGkLUaaDJTXhQZq428tOvQdTmQdSpoMq4AYVTMATJk/3jN//RMnMPKF1My8eJOjV0Gn1vMkFqYwyASZWuECTSip0kERERURUUGRmJyMjIYpdzcXHBhAkTKnw+laGs/aSIiOjp0q5dO3Tr1g2HDx9GQkICRFFEUFAQpk6dismTJ5f5npadnV2p+7NVF0/2XSoiKjN/Z+BWBlDRFY7zHyTE2NnZI7BmPeRnJOD2rdtQClpIJVLUqlULnp6euHXrFpKTkwEAubm5uHz5MlxcXODv71/tAhkODg4VFiRSqR5mgeTl5VW7c1tZBEGA0q0JxOQz0OYlGwNFqoxrELUqiNo8qDNjIHcKhiA8uRVfVWkXzcYEqQ3kBUrqAaal5qQFS83ZstQcERERUWlERkZixowZxS4XEBBQZYNE1UlJAoJET5vQ0FD22SKrtGjRAhs2bKjsaVRrT+4dKiIqF7ZywMty+5tSi0sDLiUBSTkPS9k5KfVZS+52gLeDAH8fbzRvFoL6wQHGUmdKpRLBwcFo1KgR7O3tjdtLS0vDv//+W+36FVnqS1TemUQA+xI9boIggY1bU0gVD0qvSeRQONU2Zg/pNDlQZ8ZCFHWVOc1C6dTZUGfGmY0rnOubZUBpVeal5gD2IyIiIiIqrenTp0MUxWL/xcbGVvZUiYiIqIpgJhFRNRDgDNzNBFJzgfR8IMgFKEuLmt0xwJFb+q+lgj4wVNMBeK+tfqxjLUAqAbQ6GaSSxggKCsT58+dx//59APrgSKNGjZCcnIybN29W235F5R0kerQnkQGDRI+fIJHBxr05cpNOQKfOhiBRQu4YBHXGDYiiFjp1JjRZNyFz8H/irvP89MuwlHv4aD8iUdRBp9Ffr4JEBonMDgAgkTtAIlVW+DyJiIiIiIiIiKjsmElEVMWptUByjr7k3M0MICMfSMsv2zYTsx9+rRWBhGzg/oMxG5k+QAQ8/N/e3h5t27ZF+/bt4ejoCEBflsvDwwMhISGoWbOm8Ua5oV/RuXPnzEqxVTWWgkTZ2dkWliyZosrN0eMnSBWw8WgJiUxf6k8is4PcMRAC9Ne6VpUGTc7typyiRapU81JzAKBwNe1HpFNnAQ+yoQpmEclYao6IiIiIiIiI6KnBIBFRFZaZDxy8CVxPBVwKtKRJKH0cAgCQmGM+5qFPIoCd3Pw5A09PT3Tr1g1NmzY1BjSkUn2/opCQELi7uxuXNfQrunLlSpUNchQsuWeQnZ0Nna50ZchkMpkx2MZyc08GiVQJG4+WECT6F4ZE7mDS10eblwxNzr1Kmp1l+akXzMYkChfIbGuYjJn0I1IU6EfEUnNERERERERERE8NBomIqjAHBaCQ6r92Uur7EwFArlofQCqNfI2+ZN2jPB8EieyLCBIB+gyiwMBAhIWFoXbt2tW6X5GlTCKdTofc3NxSb9MQfGMm0ZNDIrODjUcLYz8ficIJcgd/4/Oa3PvQ5CZW1vRMaPKSoM1LMBtXujQ0K4unU+uDRAIESOT6a1mQKiCRO1b8RImIiIiIiIiIqFwwSERUhQmCvh+RgXeBxJUEC9lAJZFcSPzCECSyLSZIZCCXy9G4cWOEhobC29vbOG7oV1S7dm1jjx1Dv6KzZ88iISEBomjeL+VpZClIBJStL5EhSKTVaqHVagEwSPQkkCqcYOPeDIKg/7ErVbpCbl/T+Lwm5w60+SmVNT2jwkvNmfYj0mlyIOr02WoSuQPw4LhkNh5PXI8lIiIiIiIiIiIqnKyyJ0BEFcvHAbiRCqi0gLNSn1kklQButqXbnocd8N/O+pJzidkP/s8BfB+0JCkuk+hRDg4OaNu2LRITE3H+/HlkZmYa+xW5urri7t27uHv3LkRRhEajQWxsLBISEv6fvfsOj6rOAj7+vVMy6T2BEEoC0hFpSpESiQJBEARXVFZk7fu+AqKuZS2h+aoriiJiWXVBUcEKiko1FEMHQUEpAgkd0nuZzNz3j2EuM8wkmSQDgXA+z5MnN7f+ZjL1nnvOoXnz5gQHB1d/gEtYVUEix8BZTTj2JTKbzej1egkSXSL0pjBM4VdTmv0bqCp63yhU1UJF8WkAzIVHQTGg96m/x3VZrvsgkSn0vCCRQ6k5nZSaE0IIIYQQQgghhLhsSZBIiAZOr4Nmwba+RBH+cEM8nK59ogo+emgZZvtxp6qeRFWx9ytKT09n7969WoCjadOmREVFcezYMbKysgAoLi5m7969hIWF0axZM3x9favZ+6XpQmQS2bOvwFZyztfXF7PZjMViQa/X13q/wjsMflGYwjpQlr3n7N+NUa0VWEptj21zQRpKcEutfNvFpKpWyt0EiQz+TdCbQp3m2UvNga18HoCi6NCbwi/oGIUQQgghhBBCCCGEd0mQSIgrQNNgWwZQkAksVsguAbPF+8dRFPCtw6uKvV9RbGws+/fv5/Dhw6iqqvUrio6O5siRIxQVFQGQk5NDbm4ujRo1okmTJhgMl9dLWmVBIvvtq43zM4nsSktLnXo9ifpj9I8Bq5my3P22vwOagmrFUpYDqJQXHMYn+Cp0hlqm+9VSRdExrGbXAOX5peZUqxlrha3upKL3RdHZApN6UxiKTgKRQgghhBBCCCGEEJcT6UkkxBXAqLcFiOBcZpG3qCocy7eVnjNboKTCNq8uHPsVRUdHa/ODgoIaVL+iyoI23swkspOSc5cWY2BzfILiHf5uht4YZPtDtWLOP4TVUnZRx1RWST+iqkrN6aXUnBBCCCGEEEIIIcRlTYJEQlyBmgaDzku95cstkFkMxwtswaINR+HnNDiaX+2m1QoMDKRnz5707NlTy7qx9yvq3LkzTZo0QVFsN8Ter2jPnj3k53vh4BfBhSg3V1Umkbi0+IS0whgQe/YvBWNQHDqDPwCqWoE5/yCq1Vz5DrzMXak5FD0+IW2dZlnclJoD0PtGXrCxCSGEEFeyX45A4ie231eigoICJk+eTHx8PEajEUVR2LlzZ432sWbNGhRFYcqUKRdkjMJ7ysvLad26NcOGDavvoXisssdXQkKC9n31Ytq+fTuKovDhhx9e9GMLIYS4PEmQSIgrkI8eYoO8s68yh7J1PmcrTakq+Hjx1SU6OpoBAwbQqVMnLVPG3q+oc+fOhIef64Ni71d04MCBSz4wEhTk/p9QUFBQ6306BonKys5lopSUlNR6n+LC8Qlth8G/ke0PRYdPcEsUva3Hlmo1U55/CNVaccHHoVrNlOUdcJlvDIpHZzjX80tVrVpJOkVn0IJaOmOg03pCCCGE8A5VhVc2wF/Ztt+XUdK81zz11FO88cYbdOrUiaeffprk5GQaN25c38NqMFRV5aabbkJRFBRFoaLC88+eO3fuZMqUKVx//fXExMTg4+NDbGwsd955Jzt27KjVeGbPns3BgweZMWNGrbYX0L17d2699Vaee+65Ol2AKIQQ4spxeTXwEEJ4TfMQW+ZPXb9nljl8hzA5vKL4G13XrQudTkd8fDxNmzZl3759pKWlaf2KrrrqKgoKCkhPT6e4uBi4PPoVmUwmDAaDyxexuvQkciw3J5lElz5FUTCFdUS1VmApzbJl7gS3pDz/L1RLOaqlFHPBYYzBLVGUC9fvpzz/IFjLXeabzutHZDUXgmoFQGc8l0Vk8JNSc0IIIcSFsO4I/HbaNv3badvfA1rU75gutu+++442bdrw/fff1/dQGqQ5c+aQkpKCr69vjb8zPPzww2zevJlu3boxatQoAgMD2blzJwsXLuSrr75i4cKFjB492uP9FRUV8eKLL5KUlESXLl1qeEsuPR9//LH2/fRie+aZZ7juuuuYPXs2//73v+tlDEIIIS4fkkkkxBXKzwjR7qud1YhjJpHJ4Ry2t4NEdkajkU6dOrntV9SxY0etDAVc+v2KFEVx25eoLld76XQ6LSAmPYkuD4qiwze8s9bfR9EZbRlFOtv/0VpRjLkgDfVscOZCqLwfUQenv6UfkRBCCHHxqCrM3Aj6s9Wq9Irt70vsI+0Fd+LECWJiYup7GA3Svn37eOqpp3jiiSdo1KhRjbe/66672Lt3L9u3b+ftt9/mlVdeYfny5SxYsICKigoefPBBp+8k1fnss8/Izc1l/PjxNR7Lpah58+a0a9euXo597bXX0qFDB9577z0sFkv1GwghhLiiSZBIiCtY3NlzvFYVsopr94WzwuG8tT2TyNcA+gv86lJZv6KoqKjLql+Ru75EdS0JYC85ZzabtcCYBIkubYpOj29kF3TGs49lnckpe8hqLqSi8OgFC3S660ek6E0Yg+Kc5lnP9iNSUNAZA86u54PO6KX6lUIIIUQDMXKR689Hv1a/3Y6T59ZP/MSWPWQ5+/ZvUc9lE7nz0a/uj3shFBYW4uPjQ9++fZ3mFxUV4ePjg6IofPLJJ07L5s6di6IofPTRR9o8e8+WsrIyXnjhBVq3bo2Pjw/jx4/Xlqmqytq1a7VyaAkJCU77XbFiBcOHDyc6OhqTyUSzZs0YMWIEq1atcjv2nTt3cvPNNxMaGoq/vz/9+/cnNTXV7boVFRXMnTuXXr16ERwcjL+/P127dmXOnDlYrc4X8KSlpaEoCuPHj+fgwYPcdtttREREEBQUxKBBg9i9ezcAp0+f5r777iMmJgZfX1+uvfZa1qxZ48nd7uKll15CURRmz57tdvnRo0fR6/Vce+21bm/b3XffTXx8PFOnTq3V8SdOnEjbtm1d5o8dO5bWrVuTnZ3Nb7/95vH+PvzwQ/z8/Ljllltclk2ZMgVFUVizZg2ff/453bt3x9/fnyZNmvDYY49ppbZXrlzJgAEDCAoKIiwsjHHjxpGdne32eMeOHeORRx6hZcuWmEwmIiIiuOWWW9i6davb9e3/u0aNGuHn50eXLl2YN29epbfHXU+i8vJy5syZw9ChQ2nRogUmk4mwsDASExP54Ycf3O4nLi6OuLg4iouL+de//kXz5s21ihovv/xypd8RxowZw5EjRyp9LgghhBB2l179JSHERWMyQEkFHMy2BXt0Ogiroq3I2nTYkwFR/md/Amy/mwXbAk3dGkOxGS5mb87o6GgiIyNJT09n3759mM1mrV9RVFQUR48e1b4U2PsVhYWF0axZM3x967+HyoUIEjlmUlVUVGA0GiVIdBlQdEZ8I7tSmrENa0UJOr0fxqB4zPmHULFiKc+FIj3GwKZePa7VXIS5IM1lvk9IWy2bCcBaUYJqtZUw1BkD4WwAy+AbWS8NeYUQQohL2a+nXOd18yAZpqDc/bZ29myi/s1dP3MfK6h6W28KDAzkuuuuY/PmzRQWFmqfadevX6+VPF69ejV33323ts3PP/8MQGJiosv+Ro8ezbZt20hKSmLkyJE0atSIhIQEEhISmDp1Ki1atNCyS+Li4rTtkpOTmTZtGoGBgYwcOZJmzZpx4sQJUlNTWbBgATfeeKPTcbZt28Z//vMfevfuzf3338+RI0f4+uuvSUxM5Ndff6V9+3Olds1mM8OHD2f58uW0a9eOu+66C19fX1JSUpgwYQKbNm1iwYIFLrclLS2Nnj170r59e8aPH09aWhrffvstCQkJpKamMmTIEEJDQxkzZgw5OTl8/vnnDBkyhP3799O8efMa/R/GjRvHc889x/z585k4caLL8k8++QSr1co999zjsmzGjBn8+uuvbNy4EZPJVKPjesJ+4ZpjOeyq5OXlsXXrVnr37l3leN566y1++uknRo4cSUJCAitWrGDWrFnk5OSQlJTE3Xffzc0338zDDz/Mhg0b+OSTT8jIyOCnn35y2s+OHTsYNGgQ2dnZDB48mFGjRpGZmcnixYvp27cv3377LUOHDtXWz8rKok+fPhw6dIi+ffvSt29fTp48yT//+U9uuukmj++X7OxsJk2aRJ8+fbjpppuIiori5MmTLFmyhGHDhvHee+/x4IMPumxnNpsZNGgQJ06cICkpCYPBwOLFi3nmmWcoKSlxG+jr06cPYAukDh482OMxCiGEuPJIkEiIK1CF1RYYOl5gm7ZnA50pqjpIdCAbtp90nmfQwTtDIdIPGnmhfF1t2PsVxcbGsn///hr1K4qNjUWvv3C9XqpzITOJwHalmj1IpKqqnMy/xOn0Jnwju1KSsQ3VUo7OGIAxuAXl+YcBsJRloej0GPy9V3KlPG8f7rqTmcLOLzWXd26cUmpOCCGEqBeO2UT13Zto4MCBpKamsm7dOu1k+urVqzEYDPTt25fVq1dr61qtVtasWUPLli1p0cJ14EeOHGH37t1ERka6LJs6dSpxcXFMmTLFaf6KFSuYNm0aLVu2ZN26dcTGxmrLVFXl+PHjLvv64YcfmDdvnlPQ5L333uPhhx9m9uzZvPPOO9r8F198keXLlzNp0iRee+017TuDxWLhwQcf5KOPPuK2225j5MiRTsdYu3YtM2bM4Nlnn9XmTZ8+nRdeeIGePXtyxx13MHfuXHQ6W+mFwYMHM3bsWGbNmsWsWbNcxlyV2NhYEhMTWblyJbt376ZTp05Oyz/55BOMRiN33nmn0/ytW7fy4osv8vTTT9OjR48aHdMTmzdvZs+ePcTGxrqMqTIbN27EarXSvXv3KtdbtWoV27dv1wJ6ZWVldOvWjY8//pjFixezYsUKBgwYANgeB0OGDGHZsmXs3LlT63NUUVHB7bffTlFREevWrXPKiDtx4gTXXnst9957L2lpadqFhc888wyHDh3i0Ucfdfo/PfLII/Tu3dvj+yYsLIz09HSaNnW+8CsnJ4frr7+ep59+mrvvvhs/Pz+n5SdOnOCaa65h5cqV2rLk5GTatGnDG2+8wXPPPecSkLNnkK1bt87j8QkhhLgySbk5Ia5AegUyS2zZP0E+tv5EACVmKCirfLuMItd5Uf6gU8Dfx3XZxebj41OrfkUZGRn11q/IXZCoqMjNHV0Djl8O7Fdyqqpao3rgov7oDP74RnbVsnh0xmB8As9dVVpRcoaKkgyvHa+yfkQ+oe2d/raXmgPQ+QQDtn5KelO418YihBBCiOpdKr2J7BlBjsGg1atXc91113Hrrbdy7Ngx9u/fD9hKvGVlZbnNIgKYNm2a2wBRVd566y0AZs6c6RQgAlsZ6vNPwgP07dvXJavm3nvvxWAwOJUYs1qtzJkzh5iYGKcAEYBer+e1115DURQ+/fRTl2PExcXx9NNPO82zH9NsNvPqq69qASKwlQQzGo3s3LnTw1vuzL7v+fPnO83fvHkze/fuZdiwYURERGjzS0pKuPvuu+nQoQMvvPBCrY5ZlZycHC2D7Pz7ripHjtjqKFbXG2nSpElOGV8mk4kxY8ZgtVoZPny4FiAC2+Ng7NixAOzatUub/8MPP3Dw4EEmTJjgUjKxSZMmPPnkk5w+fVp7bJvNZj799FOCgoJcgpU9evTQjuEJk8nk9rEZFhbGfffdR05OTqXl7t566y2n4FF0dDQjRowgPz+fffv2uawfEhKCr68vR48e9Xh8QgghrkySSSTEFUhRoEUI7M20/d0oANJybdNniiGokuz+jGLXeZH+tt/+l9Crib1f0ZkzZ9izZw+FhYVav6Lw8HBOnjzJyZMnUVUVs9nM4cOHOX36NM2bNyc4OPiijjUgIMBlXlFREVar1enLY004lmdwDAyVlpZekFISwvv0xiB8I7pQmrkDVbWiM4VhVC2Yi2xXxFYUn0BR9Oh96x6gKcv9w2WezifEKVtJtZqxVpQAoOh9UXS2QKTeFIaiq79MPCGEEOJKdKlkE/Xu3Rs/Pz+tjFx2dja7du3i2WefdQogtWnTRltn4MCBbvfVs2fPGh9/06ZNKIrCkCFDPN7GXdaM0WikUaNG5OTkaPP2799PVlYWrVu3Zvr06W735efnx969e13md+nSxSUw0qRJEwDatGlDUJBzL0e9Xk90dDTHjh3z+HY4GjVqFMHBwSxYsICXX35ZO/bHH38MoJXps3vyySc5dOgQW7Zs8bgUnKeKiooYPnw4Bw4c4PHHH2fMmDEeb5uVlQXYgiVVcZdpZL9/q1rmeP9u3LgRsJUGPD/oA3DgwAEA9u7dy80338zevXspLi6mX79+hISEuKyfkJDgEqSryp49e3j11VdZt24dJ0+edCkN7i4LLjQ0lFatWrnMb9asGYDT49dReHg4p0+f9nhsQgghrkyX0GldIcTF1CQIDuVAuQVCTOCjt01brLYMI915VcnKKiDPTZZRlD1IdAlkEp2vtv2K7I1ALwZ3mURWq5WSkhK3ASRPOH7ZOz9I5O5Ljbg06U2hmMKvpjT7N1BV9L6RqGoFFcW2L3nmoqOg06P3qf3/tKI0C0vJGZf5ptD2TqUJreXnsoj0UmpOCCGEqFbXxq7zmga5zjtfoBH8zvYNrYq73kRNg9wf90Lx8fGhb9++rFq1iszMTNauXYvVaiUxMZGOHTvSuHFjVq9ezT//+U9Wr16NoiiVBokaN675wHNzcwkLC3Mpy1WVyj4LGwwGLBaL9rc9YHHgwAG3vV7s3JWJdncMg8FQ7fHtFQBqys/Pj7/97W98+OGHrFixgqSkJMrLy1m4cCFRUVEkJSVp665du5a3336bKVOmaKXXvKWwsJChQ4eSmprK5MmTmTlzZo1vB1BtL9Wa3r/2ZY73r/3/++WXX1Z5LPv/Ny/PVna5siynmjx+N23axMCBA6moqCAxMZFbbrmF4OBgdDodO3fuZMmSJZSVuX7xruqxAzg9fh2VlJTU6DkihBDiyiRBIiGuUDoFmgXDwRzbF8s2kVBqhsBKgj3FZlv20Zki5y+tUZdgJpGj6voV5efnc+TIEZd+RY0bN6ZJkyYXvF+RuyAR2L6Q1DZI5NiTyPHLUHVfuMSlx+AXhSmsA2XZe87+3RjVasFSaksDNBekowS3RGesXUOw8txKSs2d14/I4qbUHIDet2ZlYYQQQogrxWLPEyicFJqrDxCB+2yie7vafi6mgQMHsnLlSlJSUkhJScHPz0/rzzJw4ECWLVtGWVkZ69evp2PHjk4loR3Vpm9maGgoWVlZF+QkuP2E/K233so333zj1X1fCPfccw8ffvgh8+fPJykpiaVLl5Kdnc2kSZOcLiD79ddfUVWV5ORkkpOT3e7Lvv6vv/7qcSApPz+fpKQkNmzYwJNPPskrr7xS49tgf2zYAzgXkv3/u2TJEm655RaP168sI+fUqVMeH3vGjBmUlJSQkpJCQkKC07KXXnqJJUuWeLyv6litVnJzc4mPj/faPoUQQjRMl+hpXSHExdA02PYltFkw+Bvhl6Ngdn8BEmF+8EJ/23RRua30XEaxbVuwbX8ps/cratGiBXv27CEjw9bTJTg4mI4dO5KZmcmxY8cwm82oqsrJkyfJzMykadOmREZG1uqLqyeqChJVV4+7MlVlEonLj9E/BqwVlOXa6owbA2JBtWApywFUygsO4xPcCp3Bv8b7LstxLTUHtkwiO1W1YjXbrqJUdAbtODpjIDqDb42PKYQQQgj3VNWWHaRXbEGg6rjLJrrY7GXlfv75Z1JSUujXr592wVJiYiKfffYZ77zzDkVFRZX2I6qtXr16sXTpUlasWMGIESO8uu927doRGhrKpk2bMJvNXi/L5m39+vWjVatWLFmyhLy8PK302fn9lzp16sR9993ndh+LFi2isLCQe++9F0VRnPoYVSU3N5fBgwezZcsWnn32WWbMmFGr29C5c2cAtyX8vK1Xr14ArF+/3qMgUbt27fD392fnzp3k5eW5ZPWsWbPG42P/9ddfhIeHuwSIwJbp5U379u1DVVWvZ40JIYRoeGrX8EII0SAY9dAhytaDSK87F/CpToAPxIXCtU2gcSD4GmzbXw6CgoLo1asXPXv21AI09n5FnTt3pkmTJlpAyN6vaM+ePeTn51e121qrKkhUW0aj0ek22EmQ6PJlDGyGT3C8099649maNaoVc/4hrBY39SCroKpWynNdv4Qb/GPQm0K1v63mQlCtAOiM514kDFJqTgghhPCqdUds2UGeBIjAOZuovnTv3p3Q0FC++eYb9u3b5xQIsk+/9NJLQOX9iGprwoQJADz++OOcPHnSZbm7vi6eMhgMTJgwgZMnTzJx4kRKSkpc1jl58iR//OH+gpv6MG7cOEpLS5k7dy4//fQTnTt3pmtX59SyG2+8kQ8++MDtjz0o9N577/HBBx9ovW4AMjMz2bt3L5mZmU77y8nJ4cYbb2TLli1MnTq11gEigI4dOxIVFcWmTZtqvQ9PjRgxglatWvH222/z448/ul1n48aNWrUJo9HI2LFjKSgocOlhtG3bNj799FOPjx0XF0d2dja//fab0/wPP/yQ5cuX1+yGVMN+X95www1e3a8QQoiGRzKJhBCapsGQlmvrSVQdVQUVW9m6Sz2LyB17v6K0tDT279/v0q/oyJEjWvPPC9mvqLIgUVFRUZ326+PjQ1lZmVM9a3dfbsXlwye4FarVjLnwGKBgDIpDLTiE1VyEqlow5x/EJ6Q1is6zJ2RF0XGs5gLX44Q6l5qzmivpR+QnQSIhhBDCW+xZRAq2z9ieUqjfbCKdTseAAQO0ElmOQaIWLVrQqlUrDh48iF6vZ8CAAV499qBBg3j++eeZPn06bdu2ZeTIkTRr1oxTp06RmppKr169mDdvXq33//zzz7Nr1y7effddvv/+ewYOHEhsbCxnzpzhwIEDpKam8uKLL9KhQ4fqd3YRjBs3jilTppCcnIzZbHbJIqqLOXPmMHXqVJKTk52CJKNGjWL79u20atUKq9XqEkABGDlypEeZLIqicOutt/L++++zZ88eOnbs6LXxn89oNPLNN98wePBgbr75Zvr06UOXLl3w9/fn6NGjbN26lUOHDnHy5En8/W1Z9P/v//0/Vq9ezRtvvMG2bdvo27cvJ0+eZNGiRQwdOpTvvvvOo2M/+uijLF++nL59+3L77bcTEhLCtm3b+OWXX7jtttv46quvvHY7V6xYgV6v93qmnRBCiIZHgkRCCI2PHmKD4KgHSTNFZls/Ix+9LQMp0McWLIr0t2UWXQ50Oh0tW7akadOm7Nu3j/T0dK1fUevWrS9Kv6ILkUkEti8+ZWVlWCwWrFYrOp3ObQNUcXnxCWmLaq2govgUKDp8guIpy/sL1VKKajVTnn8Qn+CrUHTVPwnLKulHZApr7/S3tdz2gqCgoDPa+mQpeh90Rg+6bwshhBDCI+UWOFFQswAR2NY/WWDb3lRPn8ETExNZsmQJYWFhLpkriYmJHDx4kO7du7uU6PKGadOm0atXL2bPns3SpUspKioiOjqaHj16MG7cuDrt22g0snjxYhYsWMC8efNYunQphYWFREVFER8fz/Tp0xk7dqyXbkndxcXF0b9/f9auXYvBYLgoYzt8+DAABw8eZOrUqZWOy9NyZ//n//wf3n//fT7++ONa9TWqic6dO7Nr1y5ef/11li5dyv/+9z90Oh0xMTF07dqVqVOnEhl5rv9mZGQkqamp/Pvf/+b7779n27ZttG3blnfeeYe4uDiPg0RDhgzh+++/Z8aMGSxatAi9Xs91111HSkoKhw4d8lqQKC8vj8WLFzNs2DCnrDAhhBDCHUVV1Zp+DhWXoB07dtC9e3e2b99Ot27d6ns44jJWWgGpR6r/gppVfC6YFBsMUWfbofRoAqGXaZuSgoICp35FAKqqOvUrsjMajV7pV5SZmcm9997rMn/8+PGMGjWq1vv966+/yM7OBuCaa67BZDJhNBoZMmRIrfcpLg2qaqUsaxcVpbamvrbg0F+oFlv/KZ3BD2NwKxSl6iBm9u9vUpaz+7y5Ohr1eVPrNWStKKE8bz8AemMQxuCWABgDmmAKuzSumhVCCOFKvhtcnk4UQFYtEr8j/SBGrt0QDcTgwYPZtWsXhw8fxs/Pr76Hc9l66623mDhxIuvWraNfv371PRwhhBCXuMvken8hxMXia4DoQDhdTSJLmeXctMnhXLTfZfyqYu9XdPr0afbs2UNRUZHWryg8PJwTJ05w6tQpVFXV+hWdPn2a5s2bExzsYUOn81SWSVRQ4FoGrCbsDYMBysvLMZlMmM1mLBaLVzKgRP1RFB2m8M6oWb9iKctF0RnxCW5Fed4BVGsF1ooSzAVpGIPiURT3zcJUq5mys8EfR8bgllqACJxLzekcS81JPyIhhBDC65oE2X6EuJLNnDmTrl27MnfuXB5//PH6Hs5lqaSkhJdeeonRo0dLgEgIIYRHLpNW80KIiynOoRKEVbXVSD+fU5DobGDIoKu/Mhfe1KhRIxISEujYsSNGo62/i16vp1mzZnTu3JmwsDBtXXu/ogMHDtSqnJvJZMJgcL3T6tqTyD5usAWJ7EpLS+u0X3FpUHR6fCOuQWcMPPu3D8bgllr2kNVciLnwCJUlC5fnHwJruct8U+j5pebytGmdjy0Qqig69KYwhBBCCCGE8Larr76ajz76CF/fy7Q8xSUgLS2NBx98kJkzZ9b3UIQQQlwmGsDpXCGEtwWZIMgHDmRDRjE0DYKw8zL9yypsvxUFfM6Gm/2NNBi17VcUExNDTEyMx9k6iqIQEBBAXl6e0/y69iQ6P5PIrrS0lICAgDrtW1waFJ0R38iulGZsw1pRgk7vhzEoHnP+IVSsWMvzKMvZg95N76CS0xvd7lNvCsNckI7OGIjOJxhrha3mjaL3RdEZtXU86XkkhBBCCCFqbs2aNaxZs6ba9UJDQ3n00Ucv+HjqQ137SV3p2rdvz5QpU+p7GEIIIS4jcpZHCOGkxAzpeXCqCE6djVOk5YFeB0fz4PM9cFcnWw+ikgrQKeBjALOlYQWJ7Hx8fLj66quJi4tz6lcUHBxMx44dnfoVqarKiRMnyMjIqFG/osDAQK8HiRwziRx7KUkmUcOi05vwjexKScY2VEs5OmMAxuAWlOcfxlpeQN5fC0C1VL+js/IOfGybUAxEdH5Cm6+XUnNCCCGEEBfFmjVrmDp1arXrtWjRosEGiYQQQghxcUm5OSGEk52n4Vg+BBjPBX22HIfJK2DWZjhZCHO3werD0CgAusXAgBa2n6vC63fsF5K9X9F1112nZeLY+xV17tyZmJgYLSBk71e0Z88ej3oLuetLdCEziUTDojP44xvZVcv00RmD8QlsjtVSUqMAkRO1gorSM+eO4XOu55beN7JO4xVCCCGEEJWbMmUKqqpW+5OWllbfQxVCCCFEAyFBIiGEk+bnzgUTfbYqWd7ZVjv27iYlFbA6DYx68DsbSDLqwfcKyE2sql/R1Vdf7dKv6M8//+Svv/6qsl+RuyBRfn5+ncYpPYmuLHpjEL4R12g9iXSmMAx+jeq0T2uFrZSiojOgM/jb9msMRGeQ+vBCCCGEEEIIIYQQDYUEiYQQTmKCwOdsO50Qk62UXJ6buIJeAQVbxtGVxt6vaODAgcTFxWkZRL6+vrRu3Zp27drh7++vrZ+dnc1vv/3GsWPHsFhcMzvcBYnOLz9XU3q9XuuLJOXmrgx6UyimiKttjcJwLhFXK6oVsGUm2Rmk1JwQQgghhBBCCCFEg3IFXPcvhKgJnQLNQ+CvbNu55mh/yHWTBGO2wp4MuDb24o/xUmHvV9SiRQv27NlDZmYm4Nyv6OjRo1RUVDj1KwoICNACOAAVFRUu+y4rK+PAgQPodOdi+aGhoURERNRofCUlJZJJdAUx+EbiG9aR0uzdXtunUz8iPyk1J4QQQgghhBBCCNGQSJBICOEiNgjS8yDKHzpFQqlrDAOAb/fCP3tc3LFdioKDg+nduzenTp3ijz/+oKioSOtXFBYWxsmTJzl16hSqqmI2m3nzzTc5evRotft9/PHHnf7u2LEjL730ksfjMhqNlJSUaMc1Go0SJLoCGPwbY7KaMRek13lfCgo649keXHofp6wiIYQQQgghhBBCCHH5k3JzQggXRj30bQYdouC3jMrXS8uDTccv3rgudY0bNyYhIYEOHTpgMNhi8AaDwaVfUdeuXZ0yiaqjKApGo5GbbrqpRuPx8fHRpu0l5yRIdGUwBjbDEFj3ND/FGAhn+xwZfCO10opCCCGEEEIIIYQQomGQIJEQwi29DlQV3tpqK0Hnjk6BmRtt6wkbnU5Hq1atSExMpEWLFi79ikJCQujcuTP3338/MTEx1Z501+l0NGnShFmzZjFw4MAajaWkpMRpP4Cc5L+CGAOa1nkfOuO53lp6Xyk1J4QQQgghhBBCCNHQSLk5IUSl1h2B305Xvtyq2pavOwIDWly8cV0OfHx86Ny5M02aNGHjxo2ALZsnPz8fgJiYGGbNmsWzzz7LwYMHK93P9ddfz8SJEzGZTDU6fmlpKUVFRQD4+/vj6+sL2PoaCeEpRTmX8abofetxJEIIIcSlryznD6zmovoeRo3ojAGYwjrU9zCEEEIIIUQ9kiCREMItVbVlCekVsFSRKaRT4NUN0K8Z6CQ30UVubq42nZGRgXo27SoqKgpfX18yMzMr3VZRFDp16lTjABHgtN+IiAhtumnTumeXiCuIY5BI8bxEohBCCHElspqLsJTn1fcwhBBCCCGEqBE5pSuEcMueRVRVgAhs2US/n4HPd1+ccV1OVFUlPT1dm87IONfgKSoqip07d5KXV/mJBJ1OV2WWUVWysrK0aXuQSKfTERMTU6v9iSuTU2BIJ9eVCCGEEEIIIYQQQjQ0EiQSQrhwzCLyhALM+016E50vMzOT4uJiAPLz8ykrKwMgODgYX19fli5d6nY7vV6PTqfDYrGwd+/eGh+3sLDQ6Vg+Pj4AREdHYzQaa3NTxJVKOfcxQTKJhBBCCM+VZu26pH8uJwUFBUyePJn4+HiMRiOKorBz584a7WPNmjUoisKUKVMuyBiFcJSSkoKiKHz11VdO8+Pi4oiLi6ufQQkXlb0uJCQkNPhevmlpaSiKwvjx4+t7KF51JfzvLmXjx49HURTS0tK0eQ31sVYfvvnmGxRFYfXq1Rdk/xIkEkK48DSLyE4F9mfZthPnOL4xnjlzRpuOjo7mxIkTbNu2zWWb8PBwXn/9dRo3bgzAsWPHKC8vr9Fx3WURgZSaE7XgGBiSIJEQQggh6sFTTz3FG2+8QadOnXj66adJTk7WPiuLulNVlZtuuglFUVAUhYqKCo+33blzJ1OmTOH6668nJiYGHx8fYmNjufPOO9mxY0edxuXuZOPFoigKCQkJtdrWarUyefJkunbtyujRo707sLPq8765nFyqJ6dr87yZMmWK9hx197Ns2TKXberyOK6pefPmVTk+RVHQ652/T9r/P5X93HHHHS7Hkcd+/bI/DtesWVPfQ7kijRo1im7duvHYY49htVq9vn+pHSOEcGLPIlKwBX88pWDbrn9zkAs3oLS0lNOnTwNQXl6u9SYyGo2Ehoby4Ycfut0uKSmJ+Ph43njjDd577z0OHTpEeXm5lg1UHavVqgWJFEUhLCxMO26jRo3qeKvElUY5m0mk6AxyRZYQQghRG4oOnd63vkcBgNVSCqr3TypcaN999x1t2rTh+++/r++hNEhz5swhJSUFX19fSktLa7Ttww8/zObNm+nWrRujRo0iMDCQnTt3snDhQr766isWLlx4wQIll6qFCxeya9cuvvjiC5fPzxfq6m9RO9dddx1//vknkZGRF/W4dXne3HPPPW6z0a666qoLPOqqdenSheTkZLfL1q9fz88//0xSUpLb5ddccw0jR450md+pUydvDlFcBC+99BJPP/00sbGx9T2UBuvpp5/m9ttvZ+HChdx1111e3bcEiYQQTsotcKKgZgEisK1/ssC2vUleWThy5Ajq2fp7GRkZ2nRUVBSlpaVuvyAYDAYGDx4MgK+vL5MmTcJqtaLTeZ70mZ+fr139FxYWhsFg+2fExMTUaD/i8qc3haHoTKjWsppvrOjR6f3OZQ9JFpEQQghRKzq9Lz4hret7GACU5x3AWlFc38OosRMnTtC/f//6HkaDtG/fPp566imeeOIJFi5cqPVT9dRdd93F/Pnzadu2rdP8Tz/9lL///e88+OCDDB8+3OML3hqCt99+m7CwMG655RaXZa1ataqHEYnK+Pv7065du4t+3Lo8b8aPH3/RsoNqokuXLnTp0sXtst69ewPw4IMPVrqtlAJtGGJiYqQP9gV2yy23EBYWxty5c70eJJIzhkIIJyYDfH8HLL0TpifAC/3g//SAoVdBUisY2QbGdIBxV8OzfeG9m+GdobBwlG07CRDZSjbYv2CpqqqVmlMUhaioKFJSUrReRY769etHaGio07yaBnYqKzUnV3JceYwBsbQYvpomCfOI7PockV2fI6Sd+w/mvpE9zq3T5h+EXPV3dD5B5zKJJEgkhBBCCAeFhYX4+PjQt29fp/lFRUX4+PigKAqffPKJ07K5c+eiKAofffSRNs/eP6KsrIwXXniB1q1b4+Pjo50IVRQFVVVZu3atVoLo/BOkK1asYPjw4URHR2MymWjWrBkjRoxg1apVbse+c+dObr75ZkJDQ/H396d///6kpqa6XbeiooK5c+fSq1cvgoOD8ff3p2vXrsyZM8el1ItjaauDBw9y2223ERERQVBQEIMGDWL37t0AnD59mvvuu4+YmBh8fX259tpra12656WXXkJRFGbPnu12+dGjR9Hr9Vx77bVub9vdd99NfHw8U6dOrdXxJ06c6HKiG2Ds2LG0bt2a7OxsfvvttxrvV1EU5s+fD0B8fLz2vz8/gyI7O5tnnnmG9u3b4+fnR0hICImJiaxYscJln2VlZcyaNYuuXbsSFhaGv78/zZo1Y/jw4axcuRI4VzILcHrMedrPau/evWzYsIGRI0diMplclrvrSWQ/5rx580hJSSEhIYGgoCCCg4MZOnQoe/bsueD3jeMYfvjhB/r3709wcLBTJlRBQQGPPfYYTZs2xdfXl3bt2vHaa69x6NAhtyXdquoN43g8RykpKTz44IN06NCB4OBg/Pz86NixI8nJyZSUlLjsx7H01ccff8y1115LQEAAcXFxTJkyhfj4eADmz5/v9L+0H7c2vcqWL1/O0KFDiYyMxGQy0apVK/71r39plUM8caGeN3Y1fRynpaVxxx13EBkZia+vL927d+e7776r9fEd7d69m02bNhEbG8vNN99cp315+tgH2+vb//t//4/WrVtr7wv/+te/tN7NnrCXtjt06BCvv/467dq1w9fXl6ZNmzJ58mTy8/Pdbnfs2DEeeeQRWrZsiclkIiIigltuuYWtW7e6rFvVY9iuuLiYV155hR49ehAUFERgYCDt27dn4sSJWvUax3VfeuklunTpQkBAAIGBgfTu3ZvPP//c5diOj39P3hfj4uK094obbrjB6XF1/n3maTnAmoy3KvbX1ry8PCZNmkSLFi0wGo3a4/3EiRNMmzaN66+/nsaNG+Pj40OTJk248847XV5jwfn9vCbPj7y8PB599FGn18nXX3+90tfJ2twHJpOJkSNHkpqaWqse5lWR07lCCBdNgmw/eaVQWgH/LxUqzqtMMaAFjOkEnaLrZ4yXsjNnzmilGvLy8jCbzQCEhIRgNBpZunSp2+2GDx9ep+NaLBZycnIA0Ov1hISEALasJMeAkbhyGANiUfQmVKvtMagYTKDzAatznytF74MxqAUAqtWMtaLIvsD2SycfF4QQQghxTmBgINdddx2bN2+msLCQwMBAwFZWyP7Zd/Xq1dx9993aNj///DMAiYmJLvsbPXo027ZtIykpiZEjR9KoUSMSEhJISEhg6tSptGjRQju54njyLDk5mWnTphEYGMjIkSNp1qwZJ06cIDU1lQULFnDjjTc6HWfbtm385z//oXfv3tx///0cOXKEr7/+msTERH799Vfat2+vrWs2mxk+fDjLly+nXbt23HXXXfj6+pKSksKECRPYtGkTCxYscLktaWlp9OzZk/bt22snmL799lsSEhJITU1lyJAhhIaGMmbMGHJycvj8888ZMmQI+/fvp3nz5jX6P4wbN47nnnuO+fPnM3HiRJfln3zyCVarlXvuucdl2YwZM/j111/ZuHGj24BGXdmzIIxGY423TU5OZvHixezatYtJkyZpF9I5XlCXnp5OQkICaWlp9O/fn6SkJAoLC1m6dClDhgzh3XffdcpcGDduHF988QWdOnVi3Lhx+Pn5ceLECX755ReWL1/OTTfdpJXMOv8xB3iUvWEPNvXp06fGt3np0qUsWbKEpKQkHn74Yf744w9+/PFHtm7dyh9//EFUVNQFu2/svvzyS5YtW8bQoUN5+OGHOXz4MGALsCUmJrJ161auueYaxo4dS25uLjNmzGDt2rU1vq2VeeWVV9i7dy99+vTh5ptvpqSkhNTUVKZNm0ZKSgo///yzVinD0cyZM1m1ahXDhw9n4MCB5ObmkpCQQG5uLm+++aZLObPKMl6qM23aNJKTk4mIiODmm28mOjqa3377jZkzZ/Ljjz+yYcMG7Tt4bVX3vPnll1/Yvn07FRUVxMXFkZiY6FIuryaP4/T0dK677jpatmzJ3XffTXZ2NosWLWLkyJGsXLnS7et1Tbz33nsA3HfffS49iexOnDjBe++9R1ZWFhEREfTu3ZvOnTu7rOfJY9/urrvuYv369SQlJREcHMyPP/7IzJkzOXPmjBZo8tTkyZNZt24dt99+OyNGjGD58uW88cYbrF+/nl9++QVf33MlZXfs2MGgQYPIzs5m8ODBjBo1iszMTBYvXkzfvn359ttvGTp0qMsx3D2GAXJycrjhhhvYtWsX7dq1495778XHx4e//vqLjz76iFGjRmltBXJzcxk4cCC//vor3bt3595778VqtbJ8+XLuuusu9uzZw4wZM1yO7en74qOPPsrixYtZu3ZtpWUPa6K2461MWVkZAwcOJCcnh8GDBxMYGKiNcd26dbz88svccMMNjB49moCAAA4cOMBXX33Fd999R2pqqtvXhZo8P0pLSxk4cCA7duyga9eujB07lry8PF588UXWr1/v1fugT58+/O9//2PlypXezYZURYOwfft2FVC3b99e30MRDcgvR1R15UFVbTNHVZu/4fxz19equudMfY/w0rRp0yb1u+++U7/77jv11VdfVZ977jn1ueeeU+fPn69OnTpVxVadz+mnXbt22ja1/fnf//6nHevNN9/U5u/Zs6e+7xJRjypKc9SCoyvVgqMr1dwDn6kHFnVQ938a5/RzZMVt2jqZv89RM3bOVDN3vq7NKz4j7y1CCHE5ke8G9aP49BbtvTNj50w1Y+dMNWv3XG1eff9k7Z6rjUt7jz+9pda39/nnn1cB9YcfftDmPfHEE6rBYFATEhLUpk2bavMtFosaERGhtmzZ0mkfAwYMUAH16quvVjMyMtweB1AHDBjgMn/58uUqoLZs2VI9duyY0zKr1aoePXpU+zslJUX73D1v3jyndd99910VUB9++GGn+cnJySqgTpo0Sa2oqNDmV1RUqPfee68KqN9++602//Dhw9oxZsyY4bSvadOmqYAaEhKiPvTQQ6rFYtGWffrppyqgPvroo25vf3VuuukmFVB///13l2Xt2rVTjUajmpmZ6TR/y5YtqsFgUJ977jltXosWLVRANZvNtRqHo02bNqmAGhsb63Tf1cQ999yjAurhw4fdLh8wYICqKIr6xRdfOM3PyclRr7nmGtXX11c9efKkqqqqmpubqyqKonbv3t3teM6/fyp7zFVnzJgxKqDu2LHD7fIWLVqoLVq0cJr3v//9TwVUvV6vrlq1ymnZ008/rQLqyy+/7DTfm/eN4xgURVF/+uknl/29+OKLKqCOGjXK6bF76NAhNSwsTAXUe+65x2UMlZ1ytB/vf//7n9P8gwcPqlar1WX9Z555RgXUzz//3Gm+/Tnq7+/v9j63PyfPH5ud/XUhOTm52rH//PPPKqBef/31am5urtvbM2nSJLfH8VRVzxv7bT3/x2Qyqc8995zb+62qx7Hj69WUKVOcli1btkwF1CFDhtTp9hQXF6uhoaGqTqdTjxw5UuUYzv9JSEhQ09PTXbbx5LEPqN26dVOzsrK0+YWFhWqrVq1UnU6nnjhxwqPx248VERGhpqWlafMtFos6atQoFVCnTZumzTebzWqrVq1UX19fdf369U77On78uNqkSRO1UaNGaklJiTa/usfwnXfeqb0/OT73VFVV8/Pz1ZycHJfxzpw502m9kpISdfDgwaqiKE7HqMv7YkpKSpX3meP/p7LnYU3HWxX7+1diYqJaWFjosvz06dNqfn6+y/zt27er/v7+6uDBg53m1+b5YX+fv+OOO5yej0eOHFEjIyO9eh/s3LlTBdTbbrvN/R1SS1JuTghRKb3i/NuRRQWd9LF3UVxcrJWXKysrIy8vD7BdERQaGlppw91hw4bV+diZmZnatOPVRE2bNq3zvsXlyykLSNGh6FyvSlMtZY5/2H47lDpUdFJuTgghhBDO7FfQOvbaXL16Nddddx233norx44dY//+/YCtxFtWVlalV6VPmzatxs3j33rrLcB2Bfb5pZUVRXH7Gbhv374uWTX33nsvBoPBqRSQ1Wplzpw5xMTE8NprrzldAa/X63nttddQFIVPP/3U5RhxcXE8/fTTTvPsxzSbzbz66qtOJaXHjBmD0Whk586dHt5yZ/Z9n391/ObNm9m7dy/Dhg1zqipQUlLC3XffTYcOHXjhhRdqdcyq5OTkaBlk59933rJr1y7Wrl3Lbbfdxt/+9jenZaGhoUydOpXS0lK+/vprwFbCW1VVTCaT23Le3qq6cOTIEQDtyv6auPPOO12eH/ZsH3dlqipT0/vG0S233MKQIUNc5v/vf/9Dp9Pxn//8x+n+i4+Pd5vBVlstW7Z0W6Lu8ccfB3BbKg/ggQceoGvXrl4bhzv2ko7vv/++S7bQ+PHj6dKlC5999lmt91/d8+aaa67ho48+4tChQ5SUlJCens5///tfQkNDmTFjBs8++2ytjhsXF8dzzz3nNG/w4ME0b968Ro87d7744gtyc3NJSkqiWbNmLsv9/f15/vnn2b59Ozk5OeTk5LB27VpuuOEG1qxZQ2JiIkVFRbU69n/+8x/Cw8O1vwMCAhg7dixWq5Xt27fXaF/28mV2Op1Oex13LJ/6ww8/cPDgQSZMmOBSirVJkyY8+eSTnD592m1/aneP4TNnzrBo0SLtfej8166goCAtiyorK4sFCxZw7bXXas8XO19fX1555RVUVXX7GPX0fdGb6jLeqsycOZOAgACX+dHR0QQFBbnM79atGwMHDmTNmjVaFrSjmjw/5s+fj06n08rA2jVr1oxHH33UZd91uQ8aN24M2ErKepPUjxFCVCo6AEJ9waSHovNeLy1WCRK5Y/9iAJCRkaFNR0dHc/LkSbcfSMLDw2tVksCR2WzWauL6+PhoJT/s9azFFUw591avKAYUxfWtX7WcKz+nqmdrSzr2IXKzjRBCCCGubL1798bPz08rI5ednc2uXbt49tlnnQJIbdq00dYZOHCg23317NmzxsfftGkTiqK4PaldmR49erjMMxqNNGrUSCvbDLB//36ysrJo3bo106dPd7svPz8/t/0AunTp4nKCt0mTJgC0adPG5USVXq8nOjqaY8eOeXw7HI0aNYrg4GAWLFjAyy+/rB37448/BnDpgfDkk09y6NAhtmzZUqtScFUpKipi+PDhHDhwgMcff5wxY8Z4df92GzduBGyletz1WLF/D7P/f4KCghg+fDjff/89Xbt2ZfTo0fTt25eePXvi7+/vtXHZ+8OGhYXVeFt3j037iXXHx2Z1anrfOHL3PCwoKOCvv/6iWbNmtGrVymW5vSSkNxQVFfHmm2/y7bffsn//fgoKClBVVVt+/Phxt9vV5vWjpjZu3IjRaOSLL75wu7y8vJyMjAytZFpNePK8ufXWW53+bt68Offffz/dunWjV69ezJw5k8cee6zGwXZ3r1dge+zZH0tgK6N5fg8poMp+Tu+//z4ADz30kNvl0dHRTJs2zWle//79WbFiBX379mXz5s188MEHTJo0yYNb4sxbzyeAAQMGuMxr2bIlzZo1Iy0tjdzcXEJDQ7X7Ky0tze39cuDAAcD23Du/P5O7x/DWrVuxWq3079+/2teprVu3YrHYLvZ0d2x7AMTd897T90Vvqst4K2MymbjmmmsqXf7DDz/w7rvvsm3bNjIzM6moqHBanpmZSUxMjNM8T58f+fn5HDx4kGbNmrktw3d+0BDqdh/YA6COF4p7g5z1EUJUquXZz7a+bl4pKqxQSR/KK5bVatWCRFarVfsArigKkZGRfPzxx04fcu2GDBnitrZyTWRlZWn7joyM1K5cOP+qSnHlOT+TCHeZRI49is4GiRRFMomEEEIIUTkfHx/69u3LqlWryMzMZO3atVitVhITE+nYsSONGzdm9erV/POf/2T16tUoilJpkMh+VWxN5ObmEhYWhp+fn8fbVNYvxGAwaCdr4NzJ/gMHDlR5ArywsNCjY9g/61d1fHdXMXvCz8+Pv/3tb3z44YesWLGCpKQkysvLWbhwIVFRUSQlJWnrrl27lrfffpspU6bUui9LZQoLCxk6dCipqalMnjyZmTNnenX/juz/n5UrV2p9gCobk92iRYt45ZVX+Oyzz7QMKl9fX26//XZmzpyp9fypC/tjsbS0tEaPS6j6ceP42KxObe4bO3fPQ3tljMqyo2rz3HXHbDYzcOBAtmzZQqdOnRgzZgxRUVFaIHPq1KmUlZW53dZbY6hKVlYWFRUV1QbECgsLaxQkquvzplu3blx33XWkpqaycePGGvc5ruo1yWo915g6LS3N7W2vLEj0xx9/sGHDBpo2beq2B09VDAYD999/P5s3b2bdunW1ChJ56/kEVT/209PTycvLIzQ0VHvuffnll1Xuz9Pnnr0vkSfndOzH3rp1a5XZP56+Z4Hr+6I31WW8lWnUqJHbTESwZQJOmjSJsLAwbrrpJpo3b46/vz+Komh9rty9vnj6/LBfsF3ZY8Xd/LrcByUlJQA1fp+pjgSJhBDVerQX/HbaljmkV8Cggwg/ySQ63+nTp7U3ltzcXO2LXmhoKBaLhVWrVrlsYzAYGDx4cJ2PbX+DAedyCVJqTjhnBOmdg0Zn2cvN2bKIVJft3GUfCSGEEEIMHDiQlStXkpKSQkpKCn5+fvTu3VtbtmzZMsrKyli/fj0dO3YkOjra7X4qO7FTFftJuZKSEq+fKLGfGLr11lv55ptvvLrvC+Gee+7hww8/ZP78+SQlJbF06VKys7OZNGmSU7bQr7/+iqqqJCcnk5yc7HZf9vV//fVXjwNJ+fn5JCUlsWHDBp588kleeeWVOt+mqtj/P2+++abH5c78/PyYMmUKU6ZM4ejRo6xbt4558+bx8ccfk5aWxtq1a+s8LvvjOysrq1bZRN5Qm/vGzt3z0L6/06dPu93m1KlTbufbS2NVVFS4XBBpP/ntaMmSJWzZsoV77rnHJWPl5MmTVQZnavP6UVMhISFYrVays7O9tk9vPW/sj7valmbzREJCgtsLXivz3nvvAXDffffVquTkxbhNnjp9+jRt27Z1mW9/7NufI/bfS5Ys4ZZbbqnRMdw9hu2l5CrLoHNkP/bkyZN5/fXXa3Ts+nAhxlvZ60BFRQXJyck0btyYHTt2uGQLOWYE1Za9ek9lr5Pu5tflPrCf/6vsM1VtyVkfIUS1xnSExoFgPu8iAmlq5iwtLU2btvclAtsLd0pKCsXFxS7b9OvXr85fIEpLS7UPT/7+/tqX5PDwcK9/YRaXH0VRUHRGVKsZRdFX3ZNIPXc1jOL4DFckk0gIIYSoDaullPK8A/U9DMA2Fm+zl5X7+eefSUlJoV+/fvj4+GjLPvvsM9555x2Kiooq7UdUW7169WLp0qWsWLGCESNGeHXf7dq1IzQ0lE2bNmE2m71els3b+vXrR6tWrViyZAl5eXlaf6Lz+0x06tSJ++67z+0+Fi1aRGFhIffeey+KonicDZGbm8vgwYPZsmULzz77LDNmzKjbjTnLfmLZ3ZXsvXr1AmD9+vW16onTrFkzxo4dy5133km7du1Yt24d2dnZWgkfnU5XqyvoO3fuzMqVK9m7dy9XXXVVjbf31IW8b84XFBTEVVddxaFDhzh48KBLybk1a9a43c7+Hffo0aPEx8c7Ldu2bZvL+n/99RcAo0ePdllW2wBeVfdTTfXq1YsffviBPXv20LFjxzrvz1vPm4qKCnbs2AHYSqA5qu3juK5KS0v55JNP0Ol0lb7eVGfz5s2A623y5v/UU2vXrqV///5O8w4dOsTRo0eJi4vTgjmOz72aBoncue6669DpdKxfv57i4uIqS845rnsheev+v1jjBVtJttzcXEaNGuUSICosLNSeP3URHBxMy5YtSUtLIy0tzaXk3C+//OKyTV3uA3sJOm9nBMs5XiGER9y9WEgm0TlFRUVaPdDS0lIt3dRkMhEUFMTSpUvdbjds2LA6H1uyiER1tHJxig7cZRLZy82pDh/2HErMucs+EkIIIYQHVCvWiuJL4sfxYhBv6d69O6GhoXzzzTfs27fPKRBkn37ppZeAyvsR1daECRMAW1P7kydPuiz35OrryhgMBiZMmMDJkyeZOHGiVtrF0cmTJ/njjz9qfQxvGzduHKWlpcydO5effvqJzp07uzRCv/HGG/nggw/c/ti/R7z33nt88MEHTo3mMzMz2bt3r0v/g5ycHG688Ua2bNnC1KlTvRYggnPfa9w15u7Rowf9+vXjm2++cWoc7+j333/XLtzLyMjQTjo7KioqoqCgAL1e75TtEhERUauG4AkJCYCtX9aF5M37xhP/+Mc/sFqtPPXUU04llg4fPszs2bPdbmPvsfLf//7Xaf7q1av5/PPPXda3n1RNSUlxmn/o0CGeeuopj8fqKCwsDEVRvNLcffLkyQA88MADnDhxwmV5UVGRx//3mj5vCgoK2Llzp8t8s9nMY489Rnp6Ou3atXPpLVPbx3Fdffnll+Tk5DB06FCn15Hzbd68mfLycpf5a9eu1TIr/v73vzstq+qxf6G8+eabpKena39brVb+9a9/YbVa+cc//qHNHzFiBK1ateLtt9/mxx9/dLuvjRs3ur142J2oqCjuuOMOTpw4wVNPPeWSyVVYWKiVg4yOjmbs2LFs27aN6dOnu/TbATh48CCHDx/26NiV8db9f7HGaz+Wv78/27ZtcyrdZjabmTRpktf6+owbNw6r1cozzzzj9L86evQob7zxhttx1fY+sL/W3HDDDV4Zu52c9RFCeMSeuVlaAQXloAAhvmAy2JaF+4LxCk42cPzQcH4W0a5du9w2om3bti2tW7eu87Ed39Tsb9o6nU5rkCsEZ8vFKYoeRXGXSWT7cK46nTySTCIhhBBCVE2n0zFgwACWLFkC4BQkatGiBa1ateLgwYPo9Xq3zb/rYtCgQTz//PNMnz6dtm3bMnLkSJo1a8apU6dITU2lV69ebhute+r5559n165dvPvuu3z//fcMHDiQ2NhYzpw5w4EDB0hNTeXFF1+kQ4cO3rtRdTBu3DimTJlCcnIyZrPZJYuoLubMmcPUqVNJTk526kEyatQotm/fTqtWrbBarW77k4wcObJWVzsnJiby6quv8sADDzB69GgCAwMJDQ3lkUceAeCzzz5j4MCB3HfffcyePZuePXsSGhrKsWPH+O2339i9ezcbN24kOjqa48eP06tXL9q3b0+3bt1o1qwZ+fn5LF26lFOnTvHII49o5YLsx164cCEjRoyga9euGAwG+vfv75JNcL6BAwcSGhrK8uXLvRowu5D3jScef/xxFi9ezNdff023bt0YPHgweXl5LFq0iP79+/Pdd9+5bPOPf/yDmTNn8tJLL7Fr1y46dOjA/v37+emnn7j11lv5+uuvndYfPnw4V111FbNmzWL37t107dqVI0eOsHTpUm6++Wat929NBAYG0rNnT9atW8ff//53WrdujV6v55ZbbqFz58412ldiYiIvv/wyzzzzDK1bt2bo0KHEx8dTWFhIeno6a9eupW/fvixbtqzafdX0eZOVlUXXrl3p0qULnTt3JiYmhoyMDNasWcOhQ4eIjIzk888/10r8OY65No/junr//fcBePDBB6tc76mnnmLPnj0kJCRoF7j+/vvvrF69GoDp06fTp08fp22qe+xfCH379qVLly6MGTOGkJAQli9fzq5du+jevTtPPvmktp7RaOSbb75h8ODB3HzzzfTp04cuXbrg7+/P0aNH2bp1K4cOHeLkyZNVZgU5mjNnDrt372bOnDmsXr2aQYMG4ePjw+HDh1m+fDnfffedFpyeM2cOBw4c4IUXXuCTTz6hb9++NGrUiBMnTvDnn3+ydetWPv/8c5fMvpq44YYb0Ol0PPPMM/z+++9axuBzzz1X431djPGC7XPKxIkTefnll7n66qsZMWIE5eXlpKSkkJ2dzQ033OASnK6NJ598ksWLF7Nw4UL27dvHoEGDyMvL44svvqB///4sXrzY5Tla2/tgxYoVhIaGev3iGwkSCSE8oj/7WlZshuP55+bnna1a0TP2yg0SWa1W7UoKq9WqBW0URSEyMpIPP/zQ7XbeyCIqLCzU+iAFBwdr5T2io6Mv+bIY4uLRMoEUnfueRNZy29UujkEihw8wkkkkhBBC1IxvxDX1PYSLJjExkSVLlhAWFuaSuZKYmMjBgwfp3r17pQ2g62LatGn06tWL2bNns3TpUoqKioiOjqZHjx6MGzeuTvs2Go0sXryYBQsWMG/ePJYuXUphYSFRUVHEx8czffp0xo4d66VbUndxcXH079+ftWvXYjAYLsrY7Fc4Hzx4sNKeMXFxcbUKEg0ePJjXXnuN//73v8yaNYvy8nJatGihnQxu2rQp27dv56233uLrr7/m008/xWKx0LhxYzp06MCECRO4+uqrtTFMnTqVNWvWkJKSQmZmJuHh4bRt25aXX36ZO+64w+nYb775JoqisHr1apYuXYrVaiU5Obnak+v+/v6MHz+eN954gz///JP27dvX+HZf7PvGEyaTiVWrVjFlyhQWLVrEm2++SVxcHM899xy33nqr2yBRVFQUa9as4V//+hfr1q1j7dq19OjRg5UrV3L48GGXIFFAQAA///wzTz/9NGvWrGH9+vW0bNmS559/nscee4xFixbV6r765JNPmDx5Mj/99BOfffYZqqrStGnTGgeJwBbUuP7665k9eza//PILS5YsISQkhNjYWB588EHuuusuj/ZT0+dNeHg4EyZMYMuWLSxfvpzs7Gx8fHxo1aoVTz31FI899pjbgF9tH8d18eeff/LLL7/QtGlThg4dWuW6d999N99++y1bt27lp59+wmw206hRI26//XYeeeQR+vXr57JNdY/9C+H111/n22+/5b///S9paWlEREQwadIkpk2bhq+vr9O6nTt3ZteuXbz++ussXbqU//3vf+h0OmJiYujatStTp04lMjLS42OHhYWxYcMG3njjDRYtWsT777+PXq+nWbNm3HvvvU4XKQQHB7N27Vref/99PvvsM77++mtKS0tp1KgRrVu3ZtasWdx00011ui/at2/P/PnzmTlzJnPnzqW01HZCsDZBoosxXrvp06cTFRXFBx98wHvvvUdISAg33XQTM2bMqLQ/X035+fmRkpLCCy+8wFdffcWsWbOIj4/n3//+N/369WPx4sUun4Nqcx/s37+fTZs2MWnSJI+DjZ5S1Jp0HhOXrB07dtC9e3e2b99Ot27d6ns4ogHafBwKyiCzGI6dDRI1C4GIsy1vejeFAJ/6G199On78uFbHNCsri4MHDwK2rB5/f38efvhhl9TgsLAwPvjggzoHctLT07UmePHx8URFRQG20h+SSSTsSjN/paLUVpYw54/3KM10rQPe+Pq3sVpKMRfYvrQY/Bth8GsMgG9kVwy+ntWlF0IIUf/ku0H9KDmzFUt5Xn0Po0b0PiH4RV9b38MQosFIS0ujXbt2PPTQQ7z55pv1PZwLLi0tjfj4eO655546Ze4JcakZP3488+fP5/Dhwy49ZoSoif/+9788+OCDvPvuuzz00EN12tfjjz/OnDlz+PPPP116dtWVXBoshPCIPafAMdTh2JPoSu5PlJaWpk3bAzZgy+b54osvXAJEAElJSXUOEKmqSnZ2NmDLWrKn+hoMBho1alSnfYsGRnfusabo3UdzVWuZU08iRZGeREIIIURN6IwB9T2EGrscxyzEpSwuLo6JEyfy1ltv8eSTTxIbG1vfQxJCCHERnDhxwuVi7aNHjzJ9+nSMRiO33HJLnfZ/8uRJ3nnnHSZMmOD1ABFIkEgIUYXSCigxg1WFvDLILYVshx57jnEh5QoNEhUUFGiBmpKSEq0Rnp+fHwaDgVWrVrlsYzAYGDx4cJ2PnZeXh9lsBiA0NFRrthoTE4Nef4XW/hNuOQd83AeJrJZyp+c0ikO5OelJJIQQQlTLFHZp9KYRQtSv5557joCAANLS0iRIJIQQV4jRo0djNpvp3r07oaGhpKWlsXTpUoqLi/nPf/5DTExMnfaflpbGU089xaRJk7w0YmcSJBJCVOpEARzKsU0fzLGVm3PkeEL5Ss0kSk9P16bPnDmjTUdFRZGSkkJRUZHLNn379tWyfuoiKytLm3asa2tv+iiEneKUSeTrdh3VWg6OwSQcAkOKfFwQQgghhLgY1qxZw5o1a6pdLzQ0lEcfffSCj8db5s2b51SBoTJdunRh5MiRF3w8F1JwcLDX+lwIIYS4PIwbN45PP/2Ub7/9lpycHAIDA+nVqxcTJkzwyvta79696d27d90HWgk56yOEqJQ98PNHBuzJgKJyW1ZRqB/46uFvHWzTqgpGXdX7aogsFgvHjh3TpjMzMwHQ6XRERETwww8/uN1u2LBhXjl2To4tgqfX67UGeL6+vkRESO8YcR7H4E9l5eYsZc4BJJ1DJpFOMomEEEIIIS6GNWvWVNrM3lGLFi0uuyDR2rVrq13vnnvuueyDRFeSuLg4t+XVhbjczZs3T/psiRr55z//yT//+c/6HkatSZBICFEpe5Bo3RHYesJ5WYgJnu9v+32lOn78uFbuLTs7G4vF1s8lIiKCPXv2cPToUZdt2rRpQ5s2bep87NzcXKxWKwDh4eHozp7Qj42NRblSa/+JSjlnErl/0qqWMlSdY58sySQSQgghhLjYpkyZwpQpU+p7GF7nSXaUEEIIIerHFXjtvxDCU/ZYg95NzKHCeuWWmLOrqtTc0qVL3W4zfPhwrxzbnrUEOGUOSc1r4Y6iOxfkqTRIZC0H1XpuxtnAo6LoJfAohBBCCCGEEEII0UBJkEgIUSl7cMjg5pXCop4LIl2J8vLyyM3NBaCoqEjrPeTv709hYSFbt2512SYsLIw+ffrU+dhms5n8/HwAfHx8CAoKAiAwMFArOyeEE4dyczpdJT2JLM5BIsW+jZSaE0IIIYQQQgghhGiwJEgkhKhUuB90bgSNAlyXWa7wTCLHpquOWUTR0dH8+OOPbusyDxkyBKPR6DK/prKysrT9R0REaFkeTZs2rfO+RcPkmEmEvrIgURmqajm3DfZMIik1J4QQQgghhBBCCNFQyZkfIUSlfA22nyA31amu5HJzFRUVHD9+XJvOysoCQK/XExAQwMqVK122MRgMDBkyxCvHz87O1qal1JzwiEOQSGfwtNycLYNIkUwiIYQQQgghhBBCiAZLgkRCiGr932vhhjg4VQh6HRgU2+8rNUh07NgxLBZbxkVWVhZWq+3EekREBOvXr9dKzzm6/vrrCQsLq/OxS0tLKSwsBGyl7fz9/QEIDw/XpoU4n2M2kE5XSZDIIZNIQQHOPsElk0gIIYQQQgghhBCiwZJyc0KIakUHQIsQiPSHMF9bZpG/UTuFfMVJT0/XpjMyMrTpqKgoli5d6nabYcOGeeXY9qwlsAWG7CSLSFTFsdycYvRzu45qLTuXSaSc+3igKJJJJIQQQgghhBBCCNFQSZBICOERd1lDV2ImUU5ODvn5+QAUFhZSXFwMQGBgIH/99RdHjhxx2aZNmza0bdvWK8fPzMzUpu2l5hRFoUmTJl7Zv2igHLKBFF0lQSJLOdh7EjmWmNNJJpEQQgghhBBCCCFEQyVnfoQQHlHOBoROFEBphS1AFOUPBj34GyC+7pXULgtpaWna9OnTp7XpqKgo3n//fbfb3HzzzV45dmFhIWVlZQAEBQVhMtnKhkVHR+Pj4+OVY4iGSVEUFJ0B1VqBovfBlgeoOq2jWstRtZ5EkkkkhBBCCCGEEEIIcSWQIJEQwiP2rKGicigy26bPFNmCR8GmKyNIZDabOXHiBAAVFRVkZ2cDoNfrMZvNbNmyxWWb0NBQ+vbt65Xj248HEBkZqU03bdrUK/sXDZyiBypsped0RrCWOy1WLaXYA0eKZBIJIYQQF5256DiWspwab6c3hWEMkNLDQgghhBCidqTcnBDCI/qzQSJ7noHCuewi5QopO3f06FGsVts9kJmZiaraTqhHRUWxfPly7W9HQ4YMwWg01vnYqqpq/YgURSEszBaVMxgMNGrUqM77Fw2fvS+RouicehTZqZZzQSNFMomEEEKIi8pcdJz07xM5umx4jX/Sv0/EXHS8vm/CBVNQUMDkyZOJj4/HaDSiKAo7d+6s0T7WrFmDoihMmTLlgoxRCEcpKSkoisJXX31V30Px2Pjx41EUxalyRlpaGoqiMH78+Is+nokTJxIWFuZUbl0IIcSFI0EiIYRH7JlE9jiIY2DoSulNlJ6erk2fOXNGmw4KCmLFihUu6+v1eoYMGeKVY+fn52M221K4QkNDMRhsJ/ljYmLQ6+UkvqieYu9LpOhRdK6BS1sm0VkOmUTuAkpCCCGE8C5LWQ6qtaxW26rWslplIF0unnrqKd544w06derE008/TXJyMo0bN67vYTUYqqpy00032coTKwoVFRUeb7tz506mTJnC9ddfT0xMDD4+PsTGxnLnnXeyY8eOOo3LXdDiYlEUhYSEhFpta7VamTx5Ml27dmX06NHeHdgV5N///jfl5eUS2BVCiItEzvwIISplscLhXLCqkFkMR/Ns/YjgygsSZWVlUVhYCNgCNqWlthPqQUFBbN68maKiIpdt+vbtS3h4uFeO73gFVUREhDYdGyulRYSHHII97oJEVovjiSmHa0gkk0gIIYQQ9ei7776jTZs2fP/99/U9lAZpzpw5pKSk4Ovrq33H8dTDDz/M5s2b6datG6NGjSIwMJCdO3eycOFCvvrqKxYuXHjFBUoWLlzIrl27+OKLL1Au85IbsbGx/Pnnn4SEhFz0Yzdu3Jjx48fz3nvv8eSTT9K8efOLPgYhhLiSSCaREKJSVhXScuFIHpwqhKySc8t89GDUg14Hhsv7s69HHK9gc8wiioqKYunSpW63ufnmm71ybIvFQm5uLmDLTgoNDQXAZDI59SYSoipKNUEi1bFHkUNgSMtAEkIIIYSoBydOnCAmJqa+h9Eg7du3j6eeeoonnniiViWs77rrLvbu3cv27dt5++23eeWVV1i+fDkLFiygoqKCBx98kPLy8up31IC8/fbbhIWFccstt9T3UOrMaDTSrl27env+3XPPPVRUVPD+++/Xy/GFEOJKctkEib766ismTJhAv379CA4ORlEU/v73v1e5zYYNGxg6dCjh4eH4+/vTuXNn3njjDSwWS6XbzJ8/n+uuu47AwEBCQkJISEio9AQwQElJCcnJybRt2xZfX1+io6O5/fbb+fPPPyvd5tixY9x77700adIEk8lEXFwcjz76KDk5DbdEgLg86c++QuzLgg93wnf7YfE++H4/fLsXYoPghji4uoG3xCkrK+PUqVMAmM1m7blqMBg4fvw4R44ccdmmdevWtG3b1ivHz83N1V63wsPD0els/5jY2NjL/uo0cfE49RZyW27OoSeRzuHjgZSbE0IIITxyevPTHF0+qlY/pzc+Ubdjb3yidsfd/HStjldYWIiPjw99+/Z1ml9UVISPjw+KovDJJ584LZs7dy6KovDRRx9p8xISElAUhbKyMl544QVat26Nj48P48eP15apqsratWu1cmjnlwFbsWIFw4cPJzo6GpPJRLNmzRgxYgSrVq1yO/adO3dy8803Exoair+/P/379yc1NdXtuhUVFcydO5devXoRHByMv78/Xbt2Zc6cOVqvUjvH/i0HDx7ktttuIyIigqCgIAYNGsTu3bsBOH36NPfddx8xMTH4+vpy7bXXsmbNGk/udhcvvfQSiqIwe/Zst8uPHj2KXq/n2muvdXvb7r77buLj45k6dWqtjj9x4kS333nGjh1L69atyc7O5rfffqvxfhVFYf78+QDEx8dr//u4uDin9bKzs3nmmWdo3749fn5+hISEkJiY6LYUeFlZGbNmzaJr166EhYXh7+9Ps2bNGD58OCtXrgRg3rx52vcrx8ecp/2s9u7dy4YNGxg5ciQmk8lleVxcHHFxcRQWFjJ58mSaNWuGn58fXbp0YfHixYDt++a0adNo3bo1vr6+tGrVirfffrvSYy5fvpyhQ4cSGRmJyWSiVatW/Otf/9IuMjzfqlWr6NevHwEBAYSHhzNy5MhKz19V1pNo//79PP300/To0YOoqChMJhMtWrTggQcecPvd2LEnWE2ef9dddx3x8fF89NFHbvv/CiGE8J7L5szPjBkz2LVrF4GBgTRt2pS9e/dWuf6SJUsYPXo0vr6+jBkzhvDwcL7//nsmT55MamoqX375pcs2TzzxBK+99hpNmzblgQceoLy8nIULFzJ8+HDeeustHnnkEaf1y8rKuOmmm0hNTaVHjx5MmjSJo0eP8uWXX/LDDz/w888/07NnT6dtDh48SJ8+fThz5gwjRoygXbt2bNmyhTfffJNly5aRmprqVEpKiPpkDz/klsLuM67L82tXNv2yc/ToUe1LYEZGhvYBNSoqyuXLr92wYcO8FsDJysrSph1fH5o2beqV/YsrhENgSNH5uCx27IOgOGUSSbk5IYQQwhPlufspzfq1fo6dt++iHi8wMJDrrruOzZs3U1hYSGBgIADr16/X+miuXr2au+++W9vm559/BiAxMdFlf6NHj2bbtm0kJSUxcuRIGjVqREJCAgkJCUydOpUWLVpoJ6odAwXJyclMmzaNwMBARo4cSbNmzThx4gSpqaksWLCAG2+80ek427Zt4z//+Q+9e/fm/vvv58iRI3z99dckJiby66+/0r59e21ds9nM8OHDWb58Oe3ateOuu+7C19eXlJQUJkyYwKZNm1iwYIHLbUlLS6Nnz560b9+e8ePHk5aWxrfffktCQgKpqakMGTKE0NBQxowZQ05ODp9//jlDhgxh//79NS6pNW7cOJ577jnmz5/PxIkTXZZ/8sknWK1W7rnnHpdlM2bM4Ndff2Xjxo1uAxp15eNj+7xpNLpenFSd5ORkFi9ezK5du5g0aZJWScH+G2z9YhMSEkhLS6N///4kJSVRWFjI0qVLGTJkCO+++y4PPvigtv64ceP44osv6NSpE+PGjcPPz48TJ07wyy+/sHz5cm666Sa6dOlCcnKyy2MO8KhHkT3Y1KdPn0rXMZvN3HTTTWRnZzNixAjKy8v5/PPPGT16NCtWrODNN99kx44dJCUlYTKZ+Oqrr3jkkUeIjIxkzJgxTvuaNm0aycnJREREcPPNNxMdHc1vv/3GzJkz+fHHH9mwYYNTqbivvvqKMWPG4OPjw5gxY4iJieGXX36hd+/eXHPNNdXePrtvvvmGd999lxtuuIE+ffrg4+PD7t27+fDDD/nuu+/Yvn272++qNXn+2fXp04dPP/2U3bt3c/XVV3s8RiGEEDVz2QSJZs2aRdOmTbnqqqtYu3YtN9xwQ6Xr5ufnc//996PX61mzZg09evQAYPr06QwcOFCrjXvHHXdo22zYsIHXXnuNVq1asXXrVsLCwgD417/+Rffu3XniiScYNmyY0wfS119/ndTUVG677TYWLVqkXd0/ZswYRo4cyb333svvv/+uzQf4P//n/3DmzBlmz57NhAkTtPmPPfYYs2bN4tlnn+Xdd9/1yn0mRF0piu1HX0mso8Lqfn5Doqoq6enp2nRGRobT8i1btrhsExIS4nJVZW2ZzWby8vIA2xesoKAgAC3bUQhPOZaNcxskspgdVtY5TF42HxWEEEIIcRENHDiQ1NRU1q1bx9ChQwFbYMhgMNC3b19Wr16trWu1WlmzZg0tW7akRYsWLvs6cuQIu3fvdltKeerUqcTFxblkcqxYsYJp06bRsmVL1q1b59SrU1VVjh8/7rKvH374gXnz5jkFTd577z0efvhhZs+ezTvvvKPNf/HFF1m+fDmTJk3itddeQ6+3XThjsVh48MEH+eijj7jtttsYOXKk0zHWrl3LjBkzePbZZ7V506dP54UXXqBnz57ccccdzJ07VztPMHjwYMaOHcusWbOYNWuWy5irEhsbS2JiIitXrmT37t106tTJafknn3yC0WjkzjvvdJq/detWXnzxRS0bxNs2b97Mnj17iI2NdRmTJ6ZMmUJaWhq7du3i0UcfdckgAlspsvT0dL744gv+9re/afNzc3NJSEhg0qRJ3HLLLTRu3Ji8vDy+/PJLunfvzubNm7X/pZ39orwuXbrQpUuXSh9z1bFnxHTv3r3SdU6cOEG3bt1Ys2aNFpy7++676d+/P6NHj6Z169bs3r1bC4g98cQTtGnThpdfftkpSJSSkkJycjLXX389P/zwg9N3w3nz5vGPf/yD5ORk3njjDcCW/ffQQw+h0+lYv3690/998uTJ2nqeuPvuu5k8ebJLcPGnn35i2LBhzJgxw+15rZo8/+yuvfZaPv30U9atWydBIiGEuIAum3JzN9xwA61bt/boyvwvv/ySzMxM7rzzTqc3Pl9fX2bMmAHYUt0d2d+MnnvuOS1ABLarlP7v//2/lJWVOaXFq6qqven95z//cQoEjRgxgn79+vHHH384pY0fPHiQFStWEB8fz//9v//X6fhTp04lICCAjz/+mMLCwmpvoxAXi04BQyWvFOYrIEiUmZlJcXExAHl5eZSV2bItgoODWbVqlUuZCYAhQ4bU6oo5d7Kzs7XMpYiICO01ULKIRE059STSu8skcig35/jxQHoSCSGEEMINe0aQYzBo9erVXHfdddx6660cO3aM/fv3A7YSb1lZWW6ziMCWEVHTXptvvfUWADNnznQKEIGtXJm7z8t9+/Z1yaq59957MRgMbN26VZtntVqZM2cOMTExTgEisPUIfe2111AUhU8//dTlGHFxcTz9tHMZP/sxzWYzr776qtP5gzFjxmA0Gtm5c6eHt9yZfd/28mx2mzdvZu/evQwbNsypGkFJSQl33303HTp04IUXXqjVMauSk5OjZZCdf995y65du1i7di233XabU4AIbNlGU6dOpbS0lK+//hoAnU6HqqqYTCan+97OW9Vc7KXWquvv9OabbzoFWPr160d8fDx5eXm88sorThlTcXFx9O3bl99//92pdYK9xOD777/vcvHg+PHj6dKlC5999pk2b8mSJWRnZ3PXXXe5BAanTJlSowsQY2Nj3WafJSUl0aFDB7fl/sDz55+jxo0bA7bqHkIIIS6cBnnmJyUlBbCdqD1f//798ff3Z+PGjZSVlWlvbFVtk5SUxPTp07V1wBbwOXLkCG3btiU+Pt7tNuvXryclJYWBAwc6HWPQoEEuH0yCgoK4/vrrWbFiBZs3b670w7MQF1v/5kAl5X+vhEyitLQ0bdoxiyg0NFQrJ+BIr9e7fR2pLcdSc45fnM//IixEtRxLyLkJEmE1o6qqLRCpc1hXJ+XmhBBCCOGqd+/e+Pn5aWXksrOz2bVrF88++6xTAKlNmzbaOvbvxuc7v0y7JzZt2oSiKDX67O0ua8ZoNNKoUSOnHsH79+8nKyuL1q1bM336dLf78vPzc1sGv0uXLi6BkSZNmgDQpk0brTKAnV6vJzo6mmPHjnl8OxyNGjWK4OBgFixYwMsvv6wd++OPPwZw6Sfz5JNPcujQIbZs2eK1C9vsioqKGD58OAcOHODxxx93KY/mLRs3bgRsWUPusn3s39vs/5+goCCGDx/O999/T9euXRk9ejR9+/alZ8+e+Pv7e21c9u9ujhceny80NJSWLVu6zG/SpAmHDx92m4XUpEkTLBYLp06d0r4Hbty4EaPRyBdffOH2OOXl5WRkZJCVlUVERAQ7duwAYMCAAS7rhoSE0KVLF9auXVv9jcR20fSnn37KvHnz2LVrFzk5OU4BLHupwfN5+vxzFB4eDtgu3hRCCHHhNMgg0b59tnrMrVu3dllmMBiIj49nz549HDp0iPbt21NUVMTx48cJDAzUrlJwZN+P/Sqo6o5Rl21WrFjB/v37Kw0SnTx5kpMnT7rMtzcarKzhYExMDDExMW6XCVEVvQ4CTRAbZAsK6XW28nO+BvD37neKS05paSmnT58GbB+y7c0/jUYju3btcpv116dPH69diVZWVqYdw8/PT/sCY2+0KkRNKE49idzVnVdBtZzNHHI4sSE9iYQQQgiP+IS2qfW21oriOvUV8glpi85Q88+HdRmzj48Pffv2ZdWqVWRmZrJ27VqsViuJiYl07NiRxo0bs3r1av75z3+yevVqFEWpNEjk7nt4dXJzcwkLC8PPz8/jbSrLljAYDE4nue0n+w8cOMDUqVMr3Z+77wPujmEwGKo9vr2XU035+fnxt7/9jQ8//JAVK1aQlJSk9VeOiooiKSlJW3ft2rW8/fbbTJkyhS5dutTqeJUpLCxk6NChpKamMnnyZGbOnOnV/Tuy/39Wrlzp9sI9xzHZLVq0iFdeeYXPPvtMy6Dy9fXl9ttvZ+bMmURFRdV5XPbHYmlpaaWPy6oeA5Utty9zfIxkZWVRUVFR5eMTbPdBRESEVsK8siynmjwHH3vsMd544w1iYmIYPHgwsbGx2u2dN2+eVq79fJ4+/xyVlJQA1Oh5LoQQouYaZJDI/uZX2RuQfb79hG9N17+Y25zvvffeq/JDwN///ne385OTk2tcT1cIu2ubwJp7YJ3DZ71wP+jWwOOOR44c0Uq9ZWRkaNORkZFO5ScdDR8+3GvHd8wicgw8Sak5URtKdZlEgGo128rSnc12VRQdinLZVKYVQggh6lWjni/XetvS7N0cXVb7z5GNes/EN7zmvV/qauDAgaxcuZKUlBRSUlLw8/Ojd+/e2rJly5ZRVlbG+vXr6dixI9HR0W7340lZ+fOFhoaSlZVFSUmJ108g27+b33rrrXzzzTde3feFcM899/Dhhx8yf/58kpKSWLp0KdnZ2UyaNMkpW+jXX39FVVWSk5NJTk52uy/7+r/++qvHgaT8/HySkpLYsGEDTz75JK+88kqdb1NV7P+fN998k4kTJ3q0jZ+fH1OmTGHKlCkcPXqUdevWMW/ePD7++GPS0tI8zqKpiv3xnZWVVWU2kTeEhIRgtVrJzs72eH1AuwjyfKdOnfJoP/Ye2506dWLDhg0umXGff/65R/vxlP07cWWvHUIIIbyjQQaJqmM/0VvTD6I1Wb82x/Bkm4ceeohbbrnFZf6ff/7J3//+dxYsWED79u1dlksWkagrnVL13w2NqqraFVCqqnLmzBnA9vzMyMhwe3XUVVddRdu2bb02BseUenuQSFEUrVyFEDXi0JNIp/d1u4pqNQN+5wJKuivyY4IQQgghPGSvgPHzzz+TkpJCv379tFJTiYmJfPbZZ7zzzjsUFRV5vaR6r169WLp0KStWrGDEiBFe3Xe7du0IDQ1l06ZNmM1mr5dl87Z+/frRqlUrlixZQl5entaf6Pz+L506deK+++5zu49FixZRWFjIvffei6IoHldHyM3NZfDgwWzZsoVnn31W6wNdV/ayee4yTHr16gXA+vXrPQ4SOWrWrBljx47lzjvvpF27dqxbt47s7GyttJlOp6s0s6UqnTt3ZuXKlezdu5errrqqxtvXRK9evfjhhx/Ys2cPHTt2rHb9bt26AbZssnvvvddpWV5ensc9sQ4dOoTVamXQoEEuAaJjx45x6NAhz26Ah+wlA72d+SaEEMJZg7w82H6FhD1z53z5+flO61W3vrsMoJoeo7bbnC8mJoZu3bq5/NgDQ+3bt3e7XIJEoq6utCDR6dOnKS0tBWxffOyp/aGhoSxbtsztNsOGDavVVZDuFBUVaccPCgrS+qdFR0dXWuNZiKooDgEf9+XmALXCthx7JpEEiYQQQghRue7duxMaGso333zDvn37nAJB9umXXnoJqLwfUW1NmDABgMcff9xtSfbjx4/Xet8Gg4EJEyZw8uRJJk6cqJW8cnTy5En++OOPWh/D28aNG0dpaSlz587lp59+onPnznTt2tVpnRtvvJEPPvjA7Y89KPTee+/xwQcf0KxZM227zMxM9u7d69IXJicnhxtvvJEtW7YwdepUrwWI4NxFckePHnVZ1qNHD/r168c333xTaYWH33//XbvQLyMjg82bN7usU1RUREFBAXq9XivpZj+2u+NWJyEhAbD1y7rQJk+eDMADDzzAiRMnXJYXFRU5jWPEiBGEhYXx2WefsW3bNqd1p0yZUul5qvPFxcUB8MsvvzgF0goLC3nggQeoqKio6U2p0qZNm9Dr9fTv39+r+xVCCOGsQZ79adu2Ldu2bWP//v0uTf8qKio4fPgwBoNBaxYYEBBAbGwsx48f5+TJky4BlQMHDgC2JpOOxwDnnkMXYhshLhU6Bcoq4M9MUBRbubmcUluk+apwiAmqdheXFcdMIfuXC7Bl8mzZssVl/ZCQEPr16+e141dWas7eqFSImnIM+ChVZhIBurOZRFJqTgghhBBV0Ol0DBgwgCVLlgA4BYlatGhBq1atOHjwIHq9ngEDBnj12IMGDeL5559n+vTptG3blpEjR9KsWTNOnTpFamoqvXr1Yt68ebXe//PPP8+uXbt49913+f777xk4cCCxsbGcOXOGAwcOkJqayosvvkiHDh28d6PqYNy4cUyZMoXk5GTMZrNLFlFdzJkzh6lTp7qUsR81ahTbt2+nVatWWK1WtyXuR44cWasskMTERF599VUeeOABRo8eTWBgIKGhoTzyyCMAfPbZZwwcOJD77ruP2bNn07NnT0JDQzl27Bi//fYbu3fvZuPGjURHR3P8+HF69eqlXVTbrFkz8vPzWbp0KadOneKRRx4hODjY6dgLFy5kxIgRdO3aFYPBQP/+/asNVAwcOJDQ0FCWL1/u1YBZZffPyy+/zDPPPEPr1q0ZOnQo8fHxFBYWkp6eztq1a+nbt692gWNgYCDvv/8+Y8aMoV+/fowZM4aYmBh++eUXdu/eTf/+/Vm3bl21x23cuDF33HEHCxcupEuXLgwaNIi8vDxWrlyJr68vXbp08TgrqTp5eXls2bKFxMTEKi+mFkIIUXcNMkg0cOBAPv30U5YtW8add97ptGzdunUUFxfTv39/7cp8+zaffPIJy5Yt4x//+IfTNj/99JO2jl2rVq1o3rw5+/fv5/Dhw8THx1e7zQ033ADAihUrsFqt6HTnTr4VFBSQmpqKn5+fljotxCXnbJKMqtp+zGcvHLKo9TekC6G4uFgLDJWVlWlXVfn4+PDLL79gtVpdthk8eLDXylCoqqoFiRRF0coeGAyGWjX1FQJwKh1XeZCoAgUF+5Nd0V3apVWEEEKIhkJvCkPRmVCtZTXeVtGZ0JsubP+TqiQmJrJkyRLCwsJcMlcSExM5ePAg3bt3vyAneadNm0avXr2YPXs2S5cupaioiOjoaHr06MG4cePqtG+j0cjixYtZsGAB8+bNY+nSpRQWFhIVFUV8fDzTp09n7NixXroldRcXF0f//v1Zu3YtBoPhoozt8OHDABw8eLDS3slxcXG1ChINHjyY1157jf/+97/MmjWL8vJyWrRooQWJmjZtyvbt23nrrbf4+uuv+fTTT7FYLDRu3JgOHTowYcIErr76am0MU6dOZc2aNaSkpJCZmUl4eDht27bl5Zdf5o477nA69ptvvomiKKxevZqlS5ditVpJTk6uNkjk7+/P+PHjeeONN/jzzz/dtgLwpqeeeorrr7+e2bNn88svv7BkyRJCQkKIjY3lwQcf5K677nJa/7bbbmPZsmVMnTqVL774ApPJRP/+/dm4cSMvv/yyR0EigA8//JCWLVuyaNEi3n77baKiorjllluYNm0ao0eP9trtW7RoEaWlpfzzn//02j6FEEK4p6j2RjiXkTVr1nDDDTcwduxYFixY4LI8Pz+fVq1akZ+fT2pqKj169ACgtLSUgQMHsnHjRj7//HOnDwIbNmzg+uuvp1WrVmzdulVrMpiWlkb37t0pKipi7969Wmot2NLm//3vf3PbbbexaNEiLeizZMkSRo4cSYcOHfj999+dgkGDBw9mxYoVzJ49W0uPB3jssceYNWsWDz30EO+++26N75MdO3bQvXt3tm/frtWaFcLbfjwAf2TYpiP8oNnZ73kdoqBJA8ok2rt3r5bZd+zYMS19Pzo6mmeffZaCggKn9fV6vVOJhrrKy8tj3759AISFhdG6dWvA9kXo/C/eQtRE0fGfUVUrJZk7yP3jHZflgc2H4xPcEtPZxtcG30h8I7tc5FEKIYSoK/lucHkyFx3HUpZT4+30pjCMAZJtLsSlIC0tjXbt2vHQQw/x5ptv1vdwLms9evSgsLCQPXv2aD2qhBBCXBiXTSbR4sWLWbx4MQCnTp0CYOPGjYwfPx6AyMhIZs6cCUBwcDD//e9/ue2220hISOCOO+4gPDyc7777jn379nHbbbcxZswYp/336dOHxx57jNdff53OnTtz2223UV5ezqJFi8jOzuatt95yChCBLbCzdOlSvvrqK3r27EliYiJHjhzhyy+/xN/fn48++sgpQAQwd+5c+vTpw8SJE1m9ejXt27dn8+bNpKSk0KZNG1588UXv33lCeIljtx3H1jsNqT+R1WrlyJEj2nRGhi0qpigKf/75p0uACGyvH94KEEHlpeaaNm3qtWOIK5TOAJZydHo/t4tVq/lcqTn7+kIIIYS4KIwBsRLsEeIyFxcXx8SJE3nrrbd48sknpVx4LS1evJjt27fz/fffS4BICCEugsvm7M/OnTuZP3++07xDhw5x6NAhwFbv2B4kAlvd27Vr1/Liiy/y9ddfU1paylVXXcXrr7/OxIkT3TaXf+211+jcuTNz5szh/fffR6fT0a1bN/71r38xbNgwl/VNJhOrVq3i5Zdf5rPPPmPWrFkEBwczcuRIpk6d6rY2catWrdi2bRsvvPACy5Yt48cffyQmJoaJEyeSnJyslZUS4lLxVzZkFoNVhQPZ5+Y7PoXcPJ0uW6dOnaKszFbmIycnB7PZ1qMlNDSUTz75xO027l4fastisZCTY7uCVK/XExoaCthebyIjI712HHFlUhQDKuXoDJWUm1PN2DqN2deXL2RCCCGEEELUxHPPPUdAQABpaWkSJKqlkpISZs2a5dXv2kIIISp3WZabE66kpIS4UPZkwMmzyTN/ZEKZ2RYwahcJTUPAqIMWoRBiqnI3l42NGzeSmZkJ2MrO5efnA7Y+Qe4y/Vq1asXrr7/uNvBcG1lZWRw8eBCwZUi2bNkSgJYtW9KxY0evHENcuUrObMFSnk9F8Skytj3vstw/ZgB+jXrhE3wVAMagFphCWl/sYQohhKgj+W4gxOVrzZo1rFmzptr1QkNDefTRRy/4eLxl3rx5pKWlVbtely5dGDly5AUfjxBCCCHOuWwyiYQQ9UMHlFbAo8uhwgqOUeWJ18HjvetrZN5XWFioBYhKSkq0AJHJZOKnn35yu82wYcO8FiACyM4+l67lmDkkV6AJr9AZAVD0Pm4Xq1YzimQSCSGEEELUmzVr1jB16tRq12vRosVlFyRau3Zttevdc889EiQSQgghLjIJEgkhqqRTQK+A2eq6rMLNvMtZenq6Nm3vRQRgMBjYtGmTy/ohISH069fPa8c3m83k5uYCYDQaCQoKAiAgIEArOydEXdiDPorOfeqfaq1w6kmkSE8iIYQQQoiLasqUKUyZMqW+h+F1nmRHCSGEEKJ+6KpfRQhxJVMU0FfySlFuubhjuZAsFgtHjx7Vpu1BIkVR2Lx5M1ara0Rs8ODB+Pi4z8iojZycHOwVQCMiIrQMpaZNm3rtGOLKZg/6VJ5JVIHTRwPJJBJCCCGEEEIIIYRo0CRIJISoUoARIvxtGUXna0iZRCdPnsRsNgO2YI3FYouABQYGsnr1apf1dTodSUlJXh2DvdQdSKk5cYEoBoffbp7UqtkpMKQokkkkhBBCCCGEEEII0ZDJ2R8hRJVig20/Rh2UnZc51JCCRI6l5s6cOaNN//XXXxQUFLis36dPHyIiIrx2/LKyMgoLCwHw8/PD398fgLCwMAICArx2HHFlU86WklMUBUXng2otc1quWs0oOofrR3SSSSSEEEIIIYQQQgjRkEmQSAjhkbuuhowiW6DIoIPGgdC3WX2Pyjvy8/PJzs4GoLi4WAvW+Pr6smrVKrfbDBs2zKtjyMrK0qYdg0+SRSS8SdEZz/2hM4JLkKgCkEwiIYQQQgghhBBCiCuFnP0RQnhkygD4/QyctsVPuLoRNGogCS6VZRHl5uZy+PBhl/VbtmxJ+/btvToGd0EiRVFo0qSJV48jrnCOpeT0RtSK85ZLJpEQQgghhBBCCCHEFUV6EgkhPKZ3aGHippvJZamiooJjx44BYLFYtGCNTqcjNTXV7TbDhw9HUbx3DxQXF1NSUgLYeiCZTCYAoqKitGkhvMExk0jR+bgsV60VKA4fDSSTSAghhBBCCCGEEKJhk7M/QgiPlVugoAwUBYrKId8AOgUCjLZ5l6MTJ05QUWFLp8jOzsZisTVe0ul0bN682WX94OBg+vXr59UxZGZmatORkZHadNOmTb16HCGcMoncBYnUCud1FMkkEkIIIYQQQgghhGjIJEgkhPBYRjEczDn3d+DZc8wDAK1QagABAABJREFU4y/fzCLHUnOnT5/Wpnfs2IHVanVZf/Dgwfj4uJ5cry1VVbXsJUVRCAsLA0Cv19O4cWOvHUcIOC+TSO8uk8gMimO5OfmYIIQQQgghhBBCCNGQSbk5IUSdXa4BotzcXHJzcwEoLCykuLgYAKPRSEpKisv6Op2OpKQkr46hoKAAs9kMQGhoKEaj7SR+48aN0esli0N4l+KUSeSmlKFDkEhRdCiKfEwQQgghhBBCCCGEaMjk7I8QolZ0ZyNDinL5lppzzCLKyMjQptPS0igoKHBZv3fv3k7l4LzBsdRceHi4Ni2l5sQF4ZAZ5D6TqAJFp7evcLFGJYQQQgghhBBCCCHqidSREUJUSVVtvYhUoKzi3Hx7YOgyjQ9hNps5fvw4ABUVFVrJN51Ox5o1a9xuM3z4cK+OwWq1kpNjq9+n1+sJDQ0FwMfHh6ioKK8eSwgARXEMErlmEqlqBfbrRxQpNSeEEEIIIYQQQgjR4MkZICFElfLLYOsJ23RB+bn59kwi3WUaJTp+/DgWiwWArKwsrf9QXl4ehw8fdlk/Pj6e9u3be3UMubm52hjCwsK08nKxsbEol2t6lrikKTo9iqJDVa1ug0RYzWhJxpJJJIQQQgghhBBCCNHgSZBICFElexDoaD4cy4czRWBVwUcPzUOgZ2z9jq+20tLStOkzZ85o05s3b3a7/vDhw70euLFnLwFERERo07Gxl+mdKi4Pih5UKzq9r/vlqgXQSyaREEIIIYQQQgghxBVAzgAJIapkDxIt3AN7z7XPYekBaBcBI9vVz7jqIjs7W+s5VFBQQElJCWArO7dlyxaX9YOCgujXr59Xx1BRUUFubi4ARqOR4OBgAAICAggLC/PqsYRwpOiMqFYzis5NJhGgWstQ9D4okkkkhBBCCCGEEEII0eDp6nsAQohLmz1IZHCTRGO2XtyxeEt6ero27ZhF9Pvvv2tl5xwNHjwYk8n9CfXays7ORlVVwJZFZM9SkiwicaEpOlvwRzG4zySyWs7WlZRMIiGEEEIIIYQQQogGT4JEQogq2Sus6d28WlyOQaLy8nJOnLA1WTKbzWRnZwOgqirr1693WV+n05GUlOT1cWRmnkvLciw117RpU68fSwgnitH2q9JMIluQSDKJhBBCCCGEEEIIIRo+CRIJIapk1EGrMAh1k3RQYbn446mrY8eOadlCWVlZWjZPeno6+fn5Luv36tWLqKgor46hrKyMwsJCAHx9fQkICAAgNDRUmxbiQtEyifSVBIksZWdXlEwiIYQQQgghhBBCiIZOgkRCiCrpdRAfBsFuzidfjplEaWlp2vTp06cBWxbRL7/84nb9YcOGeX0MWVlZ2nRkZKQ2LVlE4qI4G/zR6X3cLrYHiezBJCGEEEIIIYQQQgjRcMllwkIIjzzYDW6Mh8O5YNBBz1jwvcxeQTIzMykqKgIgPz+fsjLbyfCcnByn4JFdfHw8HTt29Po4HINE9lJziqLQpEkTrx9LiPMpZ3sNKbpKgkRny81JJpEQQgghhBBCCCFEwydngIQQHuncCFqEQuBxW5Doutj6HlHNpaena9NnzpzRprdu3ep2/WHDhqHYmzJ5SXFxMSUlJQAEBgZiMtlStCIjI7VpIS4k5Wzwp/Jyc2d7EunkI4IQQgghhBBCCCFEQyfl5oQQHrO/YOi8Gze5KMrKyjh58iQAZrOZnJwcwBa02b59u8v6QUFB9O/f3+vjyMzM1KbtWUQgpebERVRdJpG93Jwi5eaEEEIIIYQQQgghGjq5TFgI4bEjeXCiwFZm7lCOLVgUYISogPoeWfWOHDmCqqoAZGRkaNN//PEHVqtrc6VBgwZ5PbNHVVWt1JyiKISHhwOg1+tp3LixV48lRGW0cnOVZRJp5eYkSCSEEEIIIYQQQgjR0EmQSAjhsROFcKYIfM4GiQAaBV76QSJVVTly5Ig2nZGRAUBFRQUbNmxwWV+n0zF06FCvj6OgoACz2QxASEgIRqMRgMaNG2MwyMuxuDjOlZurJpNIZ7xoYxJCCCGEEEIIIYQQ9UPKzQkhPHY2+cbphUN/GZSey8jIoLi4GIC8vDzKymwnwQ8fPkx+fr7L+r169SIqKsrr47BnEYFzqbnY2MuwwZO4fOlsGUKKrppMIp1kEgkhhBBCCCGEEEI0dBIkEkLUmOIQGLoc+hOlp6dr0/YsIlVV2bRpk9v1hw0b5vUxWK1WsrOzAVt5udDQUAB8fHwuSEBKiMrYM4SqzSSScnNCCCGEEEIIIYQQDZ7UNxJCVCuzGMoqzv3tGF2+1INEpaWlnD59GoCysjJyc3MBOHXqlFPwyC4uLo6OHTt6fRy5ublYLBYAQkND0ettJ+CbNGmCTifxenHxaMEfxYDt2ezck8ueSWQvSyeEEEIIIYQQQgghGi45AySEqNahHMgvAy0e5BAYUi7xIFF6ejrq2Tp5GRkZ2vTOnTvdrj9s2DCUC3CjHEvNRUZGatNNmzb1+rGEqIy56DgVxacxF5wNkOr0YHUOEllKszEXpFPqtxdFsQUw9aYwjAFSFlEIIYQQQgghhBCioZEgkRCiWjoFDmTDzlNwIAuOF0C7SGgZBs9cX9+jq5yqqhw5ckSbtpea27dvH9u3b3dZPygoiAEDBnh9HBUVFVoGk9FoJDg4GAB/f3/CwsK8fjwh3DEXHSf9+0RUa1mV65Vl76Ise5fTPEVnosXw1RIoEkIIIYQQQgghhGhgpMaREKJaOgWO5MGyg3AwF0otsPM0fLPXNn2pOn36NKWlpYCt3JvZbAZg3bp1btcfNGgQJpPJ6+PIycnRMpgiIiK0TCXJIhIXk6Usp9oAUWVUaxmWshwvj0gIIYQQQgghhBBC1DcJEgkhqqVTQF9JBTaz1f38S4FjzyF7X6L8/Hxt2pFOpyMpKemCjCMzM1ObDg8P16ZjYyUrQwghhBBCCCGEEEIIUX8kSCSEqJZOsf24U15xccfiqeLiYs6cOQNAWVkZ+fn5AKSkpLhdv2fPnkRHR3t9HGVlZRQUFABgMpkIDAwEICQkRJsWQgghhBBCCCGEEEKI+iA9iYQQ1WodXnmQaPMJaB91ccfjifT0dLKyssjNzeXUqVNkZmaiqip//PGH2/W7du3KwYMHAQgNDSUiIsIr48jKytKmIyMjtWkpNSeEEEIIIYQQQgghhKhvEiQSQlTL1wCrD7tftuA3uKczKJUEkeqD1WrlyJEjvPrqq5UGhc43d+5cbbpjx4689NJLXhlLdna2Nm0PPCmKIqXmhBBCCCGEEEIIIYQQ9U7KzQkhqrXuCBzJd7/sQLZt+aUkIyOD8vJyBg0ahNFo9Hg7RVEwGo3cdNNNXhlHcXExxcXFAAQGBuLr6wvYMopMJpNXjiGEEEIIIYQQQgghhBC1JZlEQogqqSrM3Ah6BSyq63K9Ylvev/mlk02Ul5cHwMCBAzEajXz44Yfk5OSgqm5uwFk6nY6YmBieeeYZmjdv7pVxZGZmatOO5euk1JwQQgghhBBCCCGEEOJSIJlEQogqrTsCv512HyAC2/zfTl9a2UT27B2AsLAw7r//ftq3b1/lNtdffz1vvPGG1wJEqqpq/YgURSE8PBwAvV5P48aNvXIMIYQQQgghhBBCCCGEqAsJEgkhKuWYRVQVezZRFYk6F1VJSYk2XVZWho+PD61atap0fUVR6NSpk1dLwOXn52M2mwEIDQ3Vyt41btwYg0GSOIUQQgghhBBCCCGEEPVPgkRCiEpVl0Vkd6llE9mDRBUVFVgsFgBOnDhR6fo6nY6DBw96dQxSak4IIYQQQgghhBBCCHGpkyCREMItT7OI7C6VbCJVVbUgUXl5uTY/PT3d7fqKomCxWNi7d6/XxmCxWMjJyQFs5eVCQ0MBMJlMREVFee04QgghhBBCCCGEEEIIURcSJBJCuOVpFpHdpZJNVFZWhtVq1abBllFk7w90vrCwMACOHTvmFFSqi9zcXG0M4eHh6HS2l9rY2FgUxcOomxBCCCGEEEIIIYQQQlxgEiQSQriwZxHVNJyhUP/ZRI79iOxBH7PZTEhIiNv1n376aRITE2nRooXXgkQZGRnadGRkpDYtpeaEEEIIIYQQQgghhBCXEumeLoRwUW6BEwVQ01iPCpwssG1vqqdXl+LiYm3anknk5+dHr169WLZsmcv6zZs3Z9KkSVitVi3jpy7Ky8spKCgAbOXlAgMDAQgKCqo0UCXExaA3haHoTKjWshpvq+hM6E1hF2BUQgghhBBCCCGEEKI+SZBICOHCZIDv74Css0k5JwvglyOwdD+Yz0aODAr4GOCxntAh+ty2kX71FyAC50wie5AIIDs722XdoKAg/P39AbwSILIfRz2bShUREaGVl5MsIlHfjAGxtBi+GktZDhXFpzAXpFN4dBmlmdvOW1NHZI8p+EV21eboTWEYA2Iv7oCFEEIIIYQQQgghxAUnQSIhhFtNgmw/ACEm2JMBWaWu6zUOgqujXefXF3fl5gAyMzNd1m3UqJHXj+94HMdSc7GxcoJd1D9jQCzGgFjMplAAdD7usttUfAKb4xve6aKOTQghhBBCCCGEEEJcfNKTSAjhkcr6E9Vn/yF3HMvN2YNERqOR06dPu6wbHe3d6FZxcbF2/ICAAHx9fQFbsMjPz8+rxxKibs6+/bt9YqugWi7mYIQQQgghhBBCCCFEPZEgkRCiWkYd+OjdL7vEYkRaJpHFYsFsNgNgtVopKipyWdfbmUSVZRFJqTlxqVEU29u/Ukn412qVIJEQQgghhBBCCCHElUCCREKIasVUUVLuUssksgeJHEvNFRYWul3Xm0EiVVXJysoCQFEUwsPDAVuvo5iYGK8dRwivUHTOv12oqBIoEkIIIYQQQgghhGjwpCeREMIjYX4woAUUlYNFhVBfW6WqiEuoiprZbKaiogJwDhLl5+e7Xd+bQaL8/HwtcykkJASj0QhATEwMBoO81IpLjXLe7/OpgBWoJIVQCCGEEEIIIYQQQjQIcuZSCOGRTtHw8Uj4MwPyyqDXJVhBzV0/IoDc3Fy363szSORYai4iIkKbllJz4pKkZRJVEiRSVVTVWmkISQghhBBCCCGEEEI0DFJuTghRI4py6fUhsrOXmgMoKyvTpnNyctyuHxUV5ZXjWiwW7Rh6vZ6wsDAATCaT144hhDcpWpm5KjKJVCk3J4QQQgghhBBCCNHQSSaREMJjVhWsVii32H6sKugVMF4iFakcM4kcg0T2XkGOwsLCMJlMXjlubm4uVqsVgPDwcHQ62wn42NhYlMoyNYSoT9UFiVSr7UcIIYQQQgghhBBCNGgSJBJCeGz9EUjLhbxSMJ9NMmgUCFdH1+uwNJVlEjmWgrPzZqm5jIwMbVpKzYnLgy04VFkQUwVUCRIJIYQQQgghhBBCNHhSbk4I4TG3LxiXUO05xyCRvSeRTqfjzJkzLut6K0hUXl5OQUEBAD4+PgQFBQEQFBRESEiIV44hhLdVW25OVSWTSAghhBBCCCGEEOIKIEEiIYTHFMV2Sll1CAxdQjEirdycqqqYzWYAKioqnLKK7KKjvZP+lJ2djXr2DomMjNQyMySLSFzS7EGiSsshWlGlJ5EQQgghhBBCCCFEgydBIiFEjTkGhtRLKEpkzyQqLy/XAjeFhYVu1/VWJpFjKTvHUnOxsbFe2b8QF4ZkEgkhhBBCCCGEEEII6UkkhPBAVjHsPG07b6wozkGiS+U0ssVi0UrMOWYO2UvBnc8bQaLi4mIteykgIAA/Pz/AllFknxbikqRlEFWWSSRBIiGEEEIIIYQQQogrgWQSCSE8Ul4BmcWQUwK5pZBRBKUVEOpb3yOzcdePCCA3N9ft+t4IEmVlZWnTkZGR2rSUmhOXOntPIqXScnOqlJsTQgghhBBCCCGEuAJIJpEQolqKAml58HKq67K5QyE+9KIPyYU9owecg0Q5OTku6+p0OqegTm2oqqqVmlMUhfDwcG3fMTExddq3EBee7rzfzlQpNyeEEEIIIYQQQghxRZBMIiFEtRQqL0p1qXDMJHIsN+eY7WMXERGBwVC3GHlBQQFmsxmAkJAQjEYjADExMXXetxAX3NlMIqrIJLp0ikkKIYQQQgghhBBCiAtFgkRCiGpVeh75ElJZkMie7ePIG6XmHPcbERGhTUupOXE5UBTl7BO7kie3qqJapdycEEIIIYQQQgghREMnQSIhRLVMeojyd79MVS/uWCrjWG7OHiRSFIWMjAyXdesaJLJYLFoZO71eT2hoKAAmk4moqKg67VuIi0VBV0UE2Crl5oQQQgghhBBCCCGuABIkEkJUy88I8WHul10iMSKnTCJ7T6LS0lIqKipc1o2Ojq7TsXJzc7FYbFkW4eHh6PV6AGJjY20ZGkJcDhQdlWcSgSrl5oQQQgghhBBCCCEaPGmcIYTwSNNgeKE/5JbCmSJoHQF6BTpdIokz9kwis9mMeja9qbCw0O26dc0kklJzokFQlEqDmioqqFJuTgghhBBCCCGEEKKhkyCREMIj0QFwX1c4lg97M2FACzDq63tUNlarVSsx59iPqKCgwO36dQkSmc1m8vPzAfDx8SEoKAiAwMBAQkJCar1fIS42pcpMIik3J4QQQgghhBBCCHElkHJzQogasZ9Stl4qdeawlZWzZw85Bony8vLcrl+XIFFWVpZ2rMjISC0TQ7KIxOWniiARKqoEiYQQQgghhBBCCCEaPMkkEkJ4LK8MskogpxROFdoyiXQKNA6s33G560cEkJOT47KuwWAgLKySBksekFJzosFQdFBpDy0pNyeEEEIIIYQQQghxJZAgkRDCY0dybaXmjuRBgBF89GDS13+QyN6PCJyDRFlZWS7rRkVFof//7N15nBx3fef/d1X1Md1znxodliwbbGxsg29igjHmCDG2sRdzBRPANkuybCAQCIH1/sAcCSGLIRsCATZsrvWaKwYCARaMD2KMDfgESz50ayTNffZZXfX9/VHTNd3qaqlnNJdGr+fjoVV19beqv8PujLX1ns/n4yysT142mw0/q7m5WalUSlIQFpWPgeNFUAVXr92cod0cAAAAAADACYB2cwAaZ80VHpS7za2Gx8iVlUSV7eYqq37KjrXVXFlPT094TBURjkuWMzuXKArt5gAAAAAAAE4EhEQAGlZZdzA7lif8eyVFtZvzfT+ykmihIZExJgydLMtSV1eXJMm2bW3YsGFB9wRWVv2ZRIZKIgAAAAAAgBMC7eYAHJVvpMm8NJGfO2cO+3slVbabK1cS5XI5+X7tQ+6+vr4Ffcb09LRc15Uktbe3Kx6PS5L6+/sVi/GjFMcfq+48IimoJGImEQAAAAAAwFrHk00AR1XypV8dPOzkbDrkr4KUqFxJVCqV5HnBg+2ZmZnItQutJKpsXdfd3R0e02oOxy3LDv5EoZIIAAAAAADghEBIBOCoLEkzRemXB6RcSRrJSocyUndKetWzV3ZvxpgwJCq3mpOCyp8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nIiqJgDXOdV09/fTTkoK5ROUqolwup7vuuivymje96U1qbm6WJOV9R0U/pmw2q5P9X+uU0hPqPflMDRTaddDr0pZ17fMdVSRJyrrMJQKWUnHyGRmvKEnyi1PyikHAa1kxxVL9kqTMwI/lF2tDGKepT+n1L162vQbVRH0qzc5GKuWoJgIAAAAAAFgOPJ4F1rhnnnlGrutKkkZGRpTLBSU8P//5z5XJZGrWb9myRS9/+cvD11NekwqFgjw/mGmSSqXU7hTVnh7W5f22Nm9uX/DexvNSPy3ngEXnFSflZgaCF8aTW9FOLta8UZYdk1ec0sy+H0Re33rKa2TZy/tPBKepW15uSMZ48grjiqXWyXKSQTVRfkxOU9ey7gcAAAAAAOBEQLs5YA3L5/PauXOnpGD+0MBA8NB4ZGREP//5zyOvuemmm+Q4Tvh6qpQMgyVJSqfm2k+1ts5zENFhBmekg9PSE8PSwNTR1wM4OmN8Fca3ha/d7KCMHwTFdrxVTrJDkjSz97syXr7m+njbs9TUfe6y7LWSZTlyUn3h61Jubn5ScXrnsu8HAAAAAADgREAlEbCGPfnkk/L9YAbJ4OCgisWg9dQ999wjz/Nq1l900UV63vOeF74u+rZyflzZbDY8l0qnwuPWtgUMI5K0f0qaLkpPSDqzJzhX8KSNx5Y5AZDkzuyV7wZzx/xSVl5+OHjDshVv3ihJKmUPKXvgnsjr2065TtZCekguAqepp6KaaGK2mqhJXmFCpfyoYk3dK7IvAAAAAACAtYpKImCNmpmZCecPlUolHThwQJK0Y8cObdu2rWZ9LBbTDTfcUHVuykvKyISVRLZtK5lMSpLSzWnFnIXlzLlSMI+oWJKKs1nVRF7yzYJuB2CWX8rJndoVvi5Vtpmbbd8mSVO7vinJr7m+qed8JdpOXfJ91mNZ9mHVRIPhsTtFNREAAAAAAMBiIyQC1qht27bJmCB1OXTokDzPk+/7+slPfhK5/sorr9SGDRuqzk15TSoWiuE8onQqLUtBhUFb68KqiCSpJT53nAm6YMnzpenCgm8JQFJxYruMCb5fvfyw/FIQ8FpOk5ymoGyvOPmUCqOP1F5sOWrd+p+Wa6t1OU09sqwggPYKE/K94GvwipMq5UdXcmsAAAAAAABrDiERsAaNj4/r0KFgnkexWAyPH374YQ0ODtasb2tr0+te9zr5Rtqd79CIm1bWiynjHdZqLlXRau4Y5hG1JOaOK4Oh8drxKAAaVMoOhiGK8V2VsnPf6/HmTbIsW8b4mtr59cjrmze8RLGKKp6Vcng1kZetrCbasRJbAgAAAAAAWLOYSQSsQZXt5AYGBuT7vnK5nO69997I9W9605vU0tKiaS+haS+paS+pjBfXpNek6dy0fDly5CmdTofXLHQekSQ1JyTLkoyRZmYriZpikr0yY1CA457xXRUmnwxflzL7w4oiJ9ktO94sScoP/1Lu9O6a6y0npZbNr1qWvTbCaeqenU1UkleclOPlZDspecUplfIjis1WRQEAAAAAAODYLGpIlM1mNTg4qFwup9NPP12O4yzm7QE0YGhoSKOjQTVBLpfTyMiIJOm+++5TJpOpWb9lyxa94hWvkBTMICrL+HEVja29pV55yT71eQOKJ4ISoGOZRyQFYVBHUpIltSak89dLnamjXgagjuLUDhmvKEnyi1PyilOSJMuKKZbulxQESdO7/jXy+pbNr5Idb1mezTagXE1Uygaz1LzsIdmtWyUFs4kIiQAAAAAAABbHMYdExhj94z/+oz7/+c/roYcekjFGlmVp586d2rNnj+666y5J0vr16/X2t7/9mDcMoD5jTFUV0f79+2WM0ejoqB588MHIa2644YYw0J0qBSGRLynvx1VySxq3+zQeX689Oke/HnG1MTGpsxLSmebYKn+2dMwd50sLvw9wovOKk3Jn9gcvjCc3sz98L9a8QZYd/Kc+c+AueYXamT5OslvNGy9flr3Oh9PULS8/LOO78opTckpZ2bF0UE2UG1Ys1bvSWwQAAAAAADjuHVNINDMzo9e+9rX6f//v/0kKHlBX6u7u1kc+8hFZliXHcXTttdeqp4ff/gWWysDAgKamggqCmZkZjY+PS5LuvPNO+b5fs/6iiy7SueeeK0nKejGVTBAW5b2YfFnK5wuacTrD9Tk/rmfyPRof9nTVIraGG89L6xfevQ44YRnjqzA+Fwy72UEZP+jhaMdb5CSD71/fzWhm7/ci79G69VpZdnzpNztPlmXLaeqdqybKDc5VE03vJCQCAAAAAABYBPaxXPyWt7xFP/zhD8NwyLKqnxqfeeaZuuCCC2SMked5+rd/+7dj+TgAR+D7vrZv3x6+3rdvnyRpx44deuqpp2rWO46jt73tbeFrI0vNTlGSUdYP2spNFGNy7aaaa8/qW9zhQWO5Rb0dcMJwZ/bJd2ckSX4pKy8/PPuOpXjzpnDdzN7vyZSyNdfHW7aoqffC5djqgjhN3WGA5RWn5M9+DV5xWqXc8JEuBQAAAAAAQAMWHBL96Ec/0h133CHLsmRZVk0VUdlVV10VHt99990L/TgAR7F7927lckHaMjExoenpafm+rzvvvDNy/ZVXXqmNGzeGr5sdV6c0jes5qWE1O0Wl7KLG/XTktWevO6Z8uUa+RMs5YL78Uk7u1M7wdSkzEB7H0utkOUH7yFJuWJkDP4m8R+spr5VlLe7382IqzyYq87KD4XFxasdKbAkAAAAAAGBNWfCToX/4h3+QFLSYSyaTuvnmmyODogsuuCA8fuyxxxb6cQCOwHVdPf3005KC78n9+4OZJA8//LCGhoZq1re2tur1r3995L2KJqaUXVKHPy7HL8oyXtX7toye073IX4CoJgLmqzixXWb2+9PLj4RVNpbTJKdprhXb9O47pMO+jyUp2f08JTtOX57NHgMn2TVXTeTOVRP57gzVRAAAAAAAAMdowSHR/fffLyloMffxj39cH/3oRyPXbd68WVLw4Hrv3r0L/TgAR7Bjxw4Vi0VJ0ujoqLLZrPL5vO65557I9W9605vU0tIS+d6UF1QfZLNZPavwkH57+ut6UewhPTc1qHYnr5PbSkotwfiS8fzi3xNYq0q5IZXyo5Ik47sqZQ+F78WbN4XVQcWpncoP/yLiDrbatr5mObZ6zIJqonXha6/iay1O7ahbyQwAAAAAAICjiy30wkOH5h7SvPzlL6+7Lh6fe5o8PT290I8DUEc+n9fOnUHLKd/3NTAQtJz66U9/qmy2dgbJ5s2b9Tu/8zt171cOicqt62IqaUtLRmcm98iypOeec/5ifwmSpHEqiYCGGN9VYeLJ8HUpMxBWFDnJbtnx5mCdMZra+fXIe6TXX6pYev3Sb3aROMlOeblBGd+V507LKWVlx9Ly3Rl5+WHFKlrSAQAAAAAAoHELriSy7blLLav+EPt9+/aFx6lUaqEfB6COp59+Wp4XPCAeGhpSoVDQ6OiofvGLqOoB6cYbb5TjOJHv5X1HRT8mI6NsLgiYHNtRIpmQJKXTzUono689VvmSlC1K0wVp76TkUxwARCpO7ZDxCpIkvzglrzgpSbKsmGLp/nBdYfRhuVPP1FxvOUm1bLmq5vxqZlm2YhXVRKWqaqKdVBMBAAAAAAAs0IJDor6+ud/affDBB+uu++pXvxoe9/f3110HYP4ymYz27NkjSfI8TwcOHJAk3XnnnfJ9v2b9hRdeqHPPPbfu/aa8JklSoVAIr0+lUrIUBMGtba2Lun9Jcj1pOCvtmpC+v0N6YEB6alSapP0cUMMrTsmdCWaOyXhys/vD92LNG2TZQYGw8Uua2vXNyHs0n/S7chJtS77XxWYnO2XZQWDtu9Py3czs8Yy8XO3sNQAAAAAAABzdgkOiCy+8UFLQzub/+//+P/3qV7+qen9iYkJ/+Zd/qa985SuyLEuWZemiiy46tt0CqLJ9+/bwN+gPHjyoUqmknTt36qmnnqpZ6ziO3va2tx3xflOl2VZz2bneb+l0Ojxua1v8B8sFTxqYCkKhiYpgaIyQCKhijFFh/InwtZsdlPFcSZIdb5GT7Azfyx68NzI4sRMdatn4sqXf7BIIqonmfkGllBsMj4vTu6gmAgAAAAAAWIAFh0SveU0w8NqyLB04cEAXXXRRVdu58847Tx/60Ifk+3744Oa66647xu0CKJuYmAgrh1zX1aFDh+T7vn70ox9Frn/Vq16lTZs21b2f69vK+cEMsXKrOUlKp4M2kZYltbYsfiVROi7Zsz86Zgpz55lRBFRzZ/bKd2ckSX4pKy8/PPuOpVjz3Pe2X8pqZu+/Rd6j9eRrZDnJpd7qkjlyNdHgkS4FAAAAAABAhAWHRNddd53OPvtsSUFQZIwJwyBjTBgOlauInv/85+vqq69enF0D0LZt28LjgYEB+b6vhx9+WMPDwzVrW1tb9YY3vKHm/LSX0ECxVdNeQhOzVURGRrlckNA4tqNEIjifTjfXnWV0LGxLag6e+cr1g8oiSZosSF5txzzghOSX8nKndoavS5mB8DiWXie7IviZ2feDMEyqFGvepNS631rajS6xmtlEuYrZRFQTAQAAAAAAzNuCQyLbtvW1r31NfX19VWHQ4X+MMerr69Ptt99eVWkEYOGGh4c1MjIiScrn8xoeHlY+n9c999wTuf73fu/31NLSUnN+otSkMTet3flOPZ7t17Cb1njOyKuYR1S2FK3mylric8dhNZGRZtwl+0jguFKc2C5jggTVy4/ILwXVfpbTJKepN1zn5ceUGfhx5D3aTnmtLGvB/9lfNaqriWbmqqvcDNVEAAAAAAAA83RMT4tOP/10Pfjgg7r66qvDSqLD/1x11VX6+c9/rmc/+9mLtWfghGaMqaoi2r9/v4wx+o//+A9ls9ma9SeddJJe+cpX1pz3jTTtBdUHvqSMH1fGT2h3JqXR2EaVFKuaR9Tatvit5spaZiuJUnGpJSk9b5106Rap/fjtigUsmlJuSKV8EAob31UpO1c9E2/eVBX8TO/+luTXpqvJzucq2Xnmku91OViWpVi6spqoYjbR1E6qiQAAAAAAAOYhdqw3OOmkk/Stb31LAwMDuueeezQwELTA2bBhg1784hcfcQYKgPk7cOCAJicnJUmZTEZjY2MaGxvTgw8+GLn+xhtvjGwTl/UT8kzwcDnnxSUFlX5Dbov2pJ8ny3ha501rc2ZaJyUndW7z0oVE6bh0Vp8Us6WkI/U2L9lHAccV45dUmHgyfF3KDIQVRU6yS3Z87pvFndmr3NDPI+5iqXXr2poJaCc6ZdmDMn4xrCay4y3yS1mVcocUT69f6S0CAAAAAAAcF445JCrbuHGjfu/3fm+xbgcggu/72r59e/h63759kqQf//jH8v3aAT4XXHCBzjvvvMh7TXlzZTpZv9zvzWjctAdHlqNDpQ4dmunQQ5mNevkStqmyLCk2242y4ElZNwiOgBNdcWqHjBf0YPSLU/KKQUBsWY5iFUGIMUZTO78uqbaKJrXuEsVb1tYvbATVRP1yZ/ZKCmYTJeLPkiS5U7sUS/XT4hYAAAAAAKABx/9wAuAEsmfPnrCl3OTkpKamprRr1y499dRTNWsdx9ENN9xQ9162jBzLly8pNxsS5QqupuyumrVbWgqK1xYjLZmx3PJ9FrBaecUpuTNBECzjy83uD9+LNW+UZc/9nkdh/NcqTmw//BaSnVDrya9e6q2uCDvRIcuZbZnpZuS708FxKatS9uBKbg0AAAAAAOC40VAl0b333rtoH3jppZcu2r2AE0mpVNLTTz8tKaga2Ldvn3zf149+9KPI9VdcccUR2z32J2a0Lj6jIbdZE6WUsl5cE4WYFFExdFbv4nwNjRrPS5valvczgdXEGKPC+BPhazd3SMYLZg3Z8RY5yc6KtZ6md3498j4tm15RtXYtsSxLsdS6imqiQSXiQVtMd3qXYun+qnlNAAAAAAAAqNVQSHTZZZctStsWy7JUKpWO+T7AiWjnzp0qFIK2U2NjY8pms3rkkUc0NDRUs7a1tVVveMMbjnpPy5Jc46grllNXLKfflLoi6wvP3Zg45v3PxziVRDjBlTL75LszkiTfy8nLDc++YynWXB3+5g7dF1k5Y8db1bzpd5Z6qysqqCYakvHyYTWRHW+VX8qplD2oePPGld4iAAAAAADAqjavX7E1xhzzn5Xw05/+VK95zWu0fv16JZNJrV+/Xq94xSv07//+7zVrf/azn+mKK65QV1eX0um0zjnnHH32s5+V53l17/+P//iPuuiii9TS0qL29nZddtll+u53v1t3fS6X04c//GGdfvrpampqUl9fn173utdp27Zti/L1Yu0pFArasWOHpGAu0f79+5XP53X33XdHrn/jG9+o1tbWo97XGGl6djaRkdEp2Qd1wcz39KziI9oQn5ItXy2Oq03ty9hrTlLRkzLFZf1IYNXwS3kVJ3eEr0szFW3m0utkO3PzxHwvr+k934m8T8uWV8uONS3dRleBcjVRWSl7KDx2p3fLmNpZbQAAAAAAAJgzr5DIsqwF/1kpH//4x3XppZfq3nvv1Stf+Ur9yZ/8ia666iqNj4/XPGD/9re/Ha699tpr9c53vlPFYlHvec976lZlvO9979Nb3/pWHTx4UG9/+9t1/fXX6/HHH9dVV12lz33uczXrC4WCXv7yl+ujH/2o2tra9O53v1sve9nLdMcdd+iCCy7QAw88sBT/M+A49/TTT4dVeMPDwyoUCvqP//iPcD5RpZNOOkmvfOUrG7pvzo+rZIIfA/l8Xsb31eqP68zYHl3VtV1v7X1Ib372mFbiW3gsv/yfCawGxYntMib4xQQvPyq/FHyfW05STlN178fMvv8nvzhZc49Yer3S63976Te7CtiJdllOEIb5pax8d2r2OMdsIgAAAAAAgKNoqN2cpCNWAVmWVff9lQyIvva1r+m///f/rpe97GX613/915rKCtd1w+OpqSnddNNNchxHd999ty644AJJ0sc+9jFdfvnl+sY3vqHbb7+9Kiz62c9+pk9/+tM69dRT9Ytf/EKdncHch/e///06//zz9b73vU9XXnmlTj755PCaW2+9Vffdd5+uu+46ffWrX5VtBw/oX//61+uaa67RDTfcoMcffzw8D2SzWe3Zs0eS5HmeDhw4oLGxMT344IOR62+44QbFYo19a095cxUJuexcj7dUOiVJitu+nt23MpUIEznppDbJ84PKolR8RbYBLKtSblil/IgkyfhuVcgRb95UNWPHK0wos/+Hkfdp3foaWdbyVgCulLnZRMHPyVJ2UIn2YKhZMJtoPbOJAAAAAAAA6mjoqcmuXbsi/9xxxx1Kp9Myxuiqq67St771LT366KN65JFH9K1vfUtXXnmljDGKxWL6h3/4B+3cuXOpv56Q7/v6wAc+oFQqpdtuuy2y9VY8PvfU+etf/7pGRkb0xje+MQyIJKmpqUkf//jHJUmf//znq67/whe+IEm6+eabw4BIkk4++WS9853vVKFQ0Fe+8pXwvDFGf/d3fydJ+tSnPlUVBL361a/Wi170Ij3xxBN1W4jhxLR9+3b5ftAy6dChQ3JdV3feeWd4rtL555+v888/v+F7T1aGRLm5qqR0KgiJLNtSa2vLQre+IL6RZorSE8PSLw9Id++Rfl07dglYc4xfUmFie/i6lD0QVhQ5yS7Z8ervxek935Hxa/syJtpPV7LrnKXd7CpTU01ULFcT5VXKHljJrQEAAAAAAKxqDYVEW7ZsqfmTSqX09re/XblcTjfddJO+/e1v6+qrr9bZZ5+tc845R1dffbW+853v6MYbb5TrunrXu961rFVFP/vZz7R792696lWvUmdnp773ve/pL//yL/XXf/3Xuv/++2vW33XXXZIU2abr0ksvVTqd1v33369CodDQNb/7u79btUaSduzYob179+r000/X1q1bG7oGJ7bJyUkNDAxICirfDh06pF27dunJJ5+sWWvbtm644YaG713wHRX9oOLIyCiXD/q7xZyYEokgPGpubpZtL281wp5J6Zkxad+UdHAmmJs0VZBKjBbBGlec2iHjBf+N8YtT8goTkiTLchRLr69a62YGlDv0H5H3aTvltStaxbsSLMtSLN0fvi7lBsNjZhMBAAAAAADU13C7ucN94hOf0MjIiCzL0o033lh33Y033qi///u/1/T0tD7xiU/oi1/84kI/cl5+8YtfSJL6+/t1/vnn67HHHqt6/9JLL9U3vvEN9fYG8x3KD92f/exn19wrFotp69at+s1vfqOdO3fqjDPOUCaT0cDAgFpaWtTf319zTfk+Tz31VHjuSJ9R75rDHTx4UAcP1s5Y2LZtW9Xfh1u/fr3Wr18f+R5Wr8r/+zx48KBc19WPfvSjyLVXXHGFTjrppIbvPenNtZHL5/NhZVK51ZwktbW2zXfLx6w5Lk3OziOaKUqpmGQkTeSlnvSybwdYFl5xSm5mf/DC+HKz+8P3Ys0bZNnV/7me3vVNBd8Z1Zr6Lla8dctSbnXVchLtKjlNMl4+rCayE21BNVHmgOItm1Z6iwAAAAAAAKvOgkOi7373u+FxVNursspZRT/8YfTshKUwNBT0p/rCF76gU045RT/5yU904YUXas+ePfqTP/kT/fCHP9RrX/vasLXb5GQw+Lu9vT3yfuXzExMTC1q/0GsO98UvflG33HJL3fevv/76yPMf/vCH9ZGPfKTudVh9RkZGNDw8LEkqFAoaHBzUI488Ev6/7UotLS164xvfeNR7DhabFbN8tTkFTZXqzCNKzYVEUW0al1pLYu44U5R6Z4OhcUIirFHGGBUntgVlc5Lc3CEZL5iZZ8db5CS7qtYXxrepMPZ47Y2smFpPvnbJ97uaxdL9cqd3S5JKuUNKJIKguzi9KwjbmE0EAAAAAABQZcEh0YEDB8J2Nl/84hf1W7/1W5HrynN7jDEaHByMXLMUPM8LP/eb3/ymzj77bEnSc5/7XN1xxx067bTTdM899+j++++vu/dK5bBrvi185rO+kc94xzveoauvvrrm/LZt23T99dfrX/7lX3TGGWfUvE8V0fGnsopo//79yuVydedV/d7v/d5RAx3fSMOlZhljaa+xNOw2K227Sjtu9TyidJDErMQ8IimoHHJsyfODSiJjJMuSxnNHvxY4HpUy++QVpyVJvpeTlxuefcdSrLm6+sUYX1M7vx55n+aNL1WsqXspt7rqBdVEKRkvJ7+UC6uJjFdQKTOgeEvj1ZYAAAAAAAAnggWHRJ2dnRocHJQxRv/8z/+sAwcO6G1ve5u2bt0qy7K0c+dOfeUrX9FPfvITWZYlY4w6OzsXc+9H3Z8knXLKKWFAVJZKpfQ7v/M7+vu//3s9+OCD+q3f+q2wiqdc7XO4qalgCHZ53dHWR1UNzfczohytbdwZZ5yh8847r+77OD4cPHgwrCjLZrMaHR3Vfffdp2w2W7N206ZNkXOxDjfjJWVMEEDm/LgKJqaCF1PetzSWd5TU7DyieFDKsxLziKQgEGpJBC3nfCOl4tLGVqkrdfRrgeONX8qrOLkjfF2aqWgzl+qT7SSr1ueGfq5SZl/NfaxYi1o2X7F0Gz2OBNVEuyRJbvagkmE10W7F0htkrcDPNQAAAAAAgNVqwSHRS17yEv3f//t/wwDozjvv1J133lmzrrI65vLLL1/4Tufp9NNPlyR1dHREvl8OkXK5XLj+l7/8pZ566imdf/75VWtLpZJ27dqlWCymU045RVLwAH3jxo0aGBjQwYMHa4Kbp59+WpJ02mmn1eyp3syhqGtw4vF9v6qKaN++fRobG9ODDz4Yuf7GG29ULHb0b+VJb+5hc9aPh8cHc0k90PJqpbwprbNHZBdK2hCfUlvb8s8jKutLB23m0nFpc3vwB1iLipNPypig8tXLj8ovBUGw5STlpPqq1hqvqOld34q8T+uWK2XH6McoSU6iTV4sJb+UC+YTFSdlJ9qDaqLsgOItm1d6iwAAAAAAAKvGgpvz33zzzUokgoqDclAU9afcOi0ej+u//bf/tji7bsCll16qWCymZ555RsViseb9X//615Kkk08+WZLCAOsHP/hBzdp7771X2WxWl1xyiZLJuQftR7rm+9//ftUaSTr11FO1efNmPfXUU9q1a1dD1+DEs2/fPmUyGUlBddnk5KTuvPPOsIVipfPOO68m1IxijDQ9GxL5kvJ+ECrF5OtgIWhTl3PatNs6RT+cOE3/OHyelFy5ZKY5EVQT2bSZwxpWyg2rNNtazviuStmD4Xvx5k0183MyAz+WXxyvuY/T1Kf0+hcv7WaPM06qPzx2s4fC4+L0bhm/9mcpAAAAAADAiWrBIdEZZ5yh22+/XclkMgyDov4YY5RMJnXbbbdFzspZKj09PXr961+viYkJ/fmf/3nVez/60Y/0wx/+UO3t7WGbruuuu049PT26/fbb9ctf/jJcm8/ndfPNN0uS/vAP/7DqPn/wB38gSfrEJz6h8fG5B3e7d+/W3/7t3yqZTOptb3tbeN6yrPCaP/3TP5Xv++F73/72t/XTn/5UZ555pl78Yh72nag8z9OTTz4Zvt63b592795dda7Mtm3dcMMNDd3XNbYSVvBgNOfFZRSEtynb1SG/q2Z9q1PUhq7VUZUwng9CLmAtMX5JhYnt4etS9kBYUeQkO2XHq+eBecVpzez7fuS9Wrf+J1n2gguD1yQn0RZWVhkvL78wMXtcVCk7sII7AwAAAAAAWF2O6anSNddco4cfflgf+tCH9J3vfKem0sFxHF199dX6+Mc/vqwBUdmtt96qBx54QLfccovuuusuXXjhhdqzZ4/uuOMOOY6jL3/5y2E7ura2Nn35y1/Wddddp8suu0xveMMb1NXVpe985zt68skndd111+n1r3991f0vueQSvfe979Wtt96qc845R9ddd52KxaK++tWvamxsTH/zN38TViqVvfe979V3v/tdfeMb39DFF1+sl770pdq7d6++/vWvK51O6ytf+Ypse8HZHY5zO3fuVKFQkCSNjY1penpaP/rRjyLX/u7v/q42b26sbVLC9vWs1Jhc39b2XI9mvITyJq6cb6toNdWsP6UlK9uuDY9WQsmXZopSa/Loa4HjRXFqp4wXfK/77pS82RDDshzF0htq1s/s/TcZL19zPt52qpp6mEMXxUmtk1+eTZQbVDLZIak8m2gjs4kAAAAAAAB0jCGRFMzZ+eY3v6mZmRn96le/0uDgoIwxWrdunc4//3y1trYuxj4XpK+vTw888IA+/vGP64477tD999+v1tZWvepVr9IHP/hBveAFL6haf8011+iee+7RJz7xCX3zm99UPp/Xs571LN16661617veFbbOq/TpT39a55xzjj73uc/pS1/6kmzb1nnnnaf3v//9uvLKK2vWJ5NJ/fjHP9YnP/lJ3XbbbfrMZz6jtrY2XXPNNbrlllt05plnLtn/HljdisWinnnmGUnBLK99+/bp0Ucf1eDgYM3a5uZmvfGNb5z3ZziWL9uS1iUy8oylX010R647o8ePPL9SxvOERFg7vOKU3My+4IXx5WbmKltizRtqqoJK2UPKHrw38l5tW6+L/G8TyrOJ0vJL2bCayE52yHhFuZn9SrRuWektAgAAAAAArDjLGBo5rQUPPfSQzj//fP3qV7/SeefxW+XHo9/85jfauXOnJGloaEhPPvmkPv/5z4fziSrddNNNuvrqq+f9GdNeQrvzneHrA6MzemY6qTFnvSYTG5VXUrZ8/flvz6i3s23hX8wi601Lz+s/+jpgtTPGKD/8oLzitCSplD2oUm5IkmTHW5RoO7XmmrHffF6F0Ydrzjf1nK/OM/9gaTd8nPOK03Kng5+rlpNUsuM5wbEdV7r/t6kmArBm8f83AAAAANAohhgAq0Aul9Pu3bslBXOJBgYGdN9990UGRBs3btQVV1yxoM+ZKlWX4/i5CfW7WfW7u7Rl3cmasdo17qfV3bF1QfdfKuW5RBRM4HhXyuwLAyLfy4UBkWQp1rypZn1x8qnIgEiWo9at/2kJd7o2OIlWebFm+aWMjFeQXxiXneyU8V25mX1KtJ680lsEAAAAAABYUQsOif7pn/5pQdf9/u///kI/EliznnzySfl+0OJtcHBQQ0NDeuCBByLX3njjjYrF5v+ta4w05c3NH/KNr3w+J0mKOTElEwklldPJbTHZ1uqai1Xypemi1EbLORzHfK+g4tTO8HVpZn94HEv1yXaq/x+4MUZTO78Rea/0hssUS/UtzUbXmFh6Xfi/ezCbKKimdKf3KN68qaa9HwAAAAAAwIlkwU9G3vrWty5oDgIhEVBtampK+/YF80lc19XBgwd15513yvO8mrXnnnuuzj///AV9Ts6Pq2Tmwp9CviB/tttkKp0Kz6/kHLF6Sr709KjUnAiqik7tlPqaV3pXwPwUJ7bL+CVJklcYlV/KSgraoDkRgU9++Jdyp3fVnLeclFo31868QzQ73iq7oprIK4zLCauJ9lNNBAAAAAAATmjHXC5gjGn4D4Ba27dvD48PHjyonTt3Vp0rs21bN95444KH1E951VUKuVwuPE6n0+FxW9vqmUVU8qXtI9Kvh6RfHZT2T0mZojSeO/q1wGpSyg2rlBuWJBnfVSlzMHwv3rxJ1mHVe8Z3Nb37XyPv1bL5CtnxlqXb7BoUS88NNSvlBsNjd3pPGNwBAAAAAACciI45JLIsq6E/AGqNjY1pcDB4YFkoFHTw4EH96Ec/ilz7yle+Ups3b17wZx0eEmWz2fA4nQpCIsu21NKyeh4+x+wgKJKkGTdomScF1UTA8cL4JRUm5oLfUvaAjAkqBZ1kZ2Tgkzlwl7z8SM15J9ml5o0vXbrNrlF2vEV2LCg/LFcTSUEY587sW8mtAQAAAAAArKhjComoHvr/2fvvKEn2u77/f34qdpqesDubd29OSlcIBSsLgYQAISN/BQJZ/gqujI1/BFk2B9vnxxESBmEbgwQGRzAC25ifQZYBYwmLo4AEQhIgULh57928ezfMTupcVZ/fHzWdtnt2Zme6p7tnXg+dOVtdXdX1mdnbvTr1mvf7LbI9Dz/8cGv7/Pnz/NVf/RWXLl3qOS6fz/O2t73tll47soaL9QKl2Kcau9SSdnfJrnlEnofv+wAUCoWxm0dUCNI/kwTKa7/wv1qHem83PpGxVF9+ChvXAEgay8S1RQCMcfFyR3qOTxolVs/8Qd/Xmrr9zRjHH9pad7N1q4lWz2CTxiiWJCIiIiIiIiIyclu+G5wkybpfV65c4U/+5E/4nu/5Hqy1GGP49V//9b4zVkT2qkuXLnH9evrb7JVKhfPnz/OpT32q77Hf/d3ffctt4FbikKuNPE9V5/hS6TDXGlnKsYe1N8wjyrbnERWnxqfVXFMzJIK01VyTqolkEsT1ZRqltUoVm9AonW895+WOYJze0YCrZ/4AG5V79vuF28gcePHQ1rrbOX6hVbWVVhMtpNuqJhIRERERERGRPWwoJQP79u3jpS99Kf/tv/033v3ud5MkCX/v7/09Hn/88WFcTmTiWGt55JFHWo/Pnj3Ln/zJn1AqlXqOPXr0KN/6rd96y9dYjtrt5VaSkJUk5HJUoG4dVkv95xFNFadu+TrD1hkSrdQhdOFgIf1TZJxZa6kvPtrqkxhVnsHGadLpeHnczFzPOVHlCqULn+z7elN3fmfP7CK5NV72xmqi9O+msXpW1UQiIiIiIiIisicN/W7T933f9wFQr9f5F//iXwz7ciIT4ezZs6yurgKwsrLC008/zec///m+xz700EOtdnCblVhYTdKQKLKm1WouMDHXoxy/F30jX8m+mvP+PUTBLDB+84iaMh7sy8KxItw2DS8/Ac89ADOZUa9M5Oai0jni+jIASVwhqlxee8bgFY71PWfl1EfARj37w7kHCWfuG9ZS9wzHz3dUE9VvqCY6M8qliYiIiIiIiIiMRG+fmwG7cuVKa/uP/uiPhn05kbEXxzGPPfZY6/HZs2f5xCc+0bcd4/Of/3xe+MIX3vI1VuOQxBoAKkk7YMo5DR6vzBEZn6v+ca76x3l8CYqrVb7z2Pmxm0fUdHy6vb1Sg2kFRDLmkrhGfflk63G0eq617WUP4Li9/xHXl5+meuWLfV7NYerO/2cYy9yTvOwh6o0ngbSayA3nAENj9Sx+4YRmPomIiIiIiIjInjKUO8LWWkqlEn/+53/Oj/zIj2CMwVrL5cuXNz5ZZJd7+umnqVbTgTrXr1/na1/7WlfruSbHcXjnO9+JMeaWrxFZB8ekbZQ6Q6Ks0+BstXfuUDn2OTo7GcmLZhHJJKgvPoZN0oqguHaNZG3GkHEC3OyBnuOttaw89dt9Xyt3+JX4ucPDW+we011N1OioJopUTSQiIiIiIiIie86WK4lc99YHgszOzm71ciK7QqPR4Mkn099gt9Zy5swZPv7xj/c99g1veAO33Xbblq4z51eY8SqsxCELUQaP9P1qgatJ79yhI8EKczO94dE4WqjA7TOjXoXI+qLKlVZrOZs0iEoXW8/5hWN95wrVrv0V9eUnevYbN6Rw25uGt9g9StVEIiIiIiIiIiKpLVcSWWtv6csYwzd+4zcOcu0iE+fJJ5+k0UiHo1+9epXPf/7zXLp0qee4fD7P2972tm1dyzFpKDTnVTkaLHMoWOF8vQj0ViYdzyyTL+S3db2dslhNZy6JjCObRNSX2u0ko/JFrE1bSbrhLI7fG9LaJGL56Q/3fb38sTfgBpMR4E6StJoo/bvoqSZaUTWRiIiIiIiIiOwd22o3Z4zZ1BdAsVjkPe95z0AWLTKJqtUqTz31FJDOJTp58iSf+tSn+h773d/93RSL278xvBKnLeSMAc9YZtwyt9W+RiFe6DruvtlobOcR3SixsFwb9SpE+quvPE0SpT0Rk8YKce16+oRx8XJH+p5TvvQZ4sozPfudYIb8sdcNba17nZc71NqOys+QxurQKJ3FxvURrUpEREREREREZGdtud0cpNVEm/Hyl7+cX/qlX+Lee+/dzuVEJtpjjz1GkiQAXL58mU9/+tOsrq72HHfkyBG+9Vu/ddvXSywsx2HXvmzjOnfWznFn7UuExf3Ui/dwuZHn9n2TMY+o6XoFZiZrybIHxPXl9kwbm9AonWs95+eOYJzef3KTqMzq6d/r+3pTt/9NHDfs+5xsn+PlcPwiSWMZmzSIqwu4mX2t2UTB9N2jXqKIiIiIiIiIyNBtOST6tV/7tZu/sOcxMzPD8573PI4fP77Vy4jsCqurq5w9exaAKIr42te+xp/92Z/1Pfahhx7C97c/D6OUBCS2u7VcuVJubc9mPYrZa9yTvUax+MC2r7eTrlfhjlEvQqSDtZb64qOw9ssTUeVyqxrF8fK4mbm+562e/RhJozcs9vJHyR582fAWLAB4uYPUl5aBtdlEmRtmE7nBaBcoIiIiIiIiIjJkWw6J3vGOdwxyHSK72iOPPNKqvLt48SIf//jHieO457gHH3yQF73oRQO55nLUW4FQqVRa29lsFgDHcSZmHlHTYhVWarBYg3Id7ts/6hXJXheVzhHX07DBxlWiVvs4g1c41vecuLpA6fwf9X2ueMdbMBPSAnKSOV4OJyiS1JvVRNdwM/uxNlY1kYiIiIiIiIjsCdtqNyciG7t+/TqXLl0CoF6v84UvfIFHHnmk5zjHcXjnO9/ZmuO1HbZPq7kkSahW0lkpvue3qpWmpgoTM49opQYLFVipp3OJCmu/5H/bDGT0aSYjksQ16ssnW48728x52QM4bv/eiCun/hckjZ79weyzCOeeM/B1Sn9e9iD1erOa6DJuOAfGobF6Fq9wXC3/RERERERERGRX2/KdYdd1cV0Xz/M4c+bMusddu3aNhx56iIceeoh3vvOdW72cyMR6+OGHW9tnz57lD//wD/se9/rXv57bb799INesJB6Rdbv2VatV7Npg9lwu19o/NVUcyDV3Qj1OW81FCax2zJVfrI5uTSL1xcewSQRAXLtG0igBYJwAN3ug7zmN1TNULvdrOWko3vGdw1qq9NGsJgLSaqLatXR7rZpIRERERERERGQ32/Lv3jdbZ21kdXWVD33oQ63qiF/91V/d6iVFJs4zzzzDwsICkLZ6++QnP9mqKuqUz+f523/7b2/rWstRQIzDlFtjOe6tXOicR9RsNQdQLE5OSFToGA+y2lGAsVCBQ4WdX49IVLlCVLkMpAFDVLrYes4vHOvbMs5ay/JTvwP0/juaPfhS/HXa08nweNlDN1QT7QPjEK2ewy+cUDWRiIiIiIiIiOxa22rQtJm2WM0wyVo7kDZaIpPCWtvVVu7kyZN84hOf6HvsW9/6Vqanp7d1vatRnlIcAJaFKIdHQtZt4JsEgEq5NyRyHIdcPtfv5cZS6EHgphVFpTokFhyTVheJ7DSbxNSXHms9jsoXsTadNeaGszj+VN/zate/Sn2xt+UkTsDU7X9zKGuVm3O8LE4wTVJfwiYRce0abmY+rSZaOU04c++olygiIiIiIiIiMhTbGkSymWqic+fObXiMyG50/vx5VlZWgLSi7g/+4A9YXV3tOe7w4cN827d927auFVlDKU5nDDWsy3IcshBnudZIA6AkSahWa8DkziNqalYTWQvltWoi16Qt6ER2Un3lKZIoTSiTxgpx7Xr6hHHxckf6nmNtzMpTv9P3ucLRb0rn4chIeNlDre2ochls+qESlc6RxLVRLUtEREREREREZKg2XUn06U9/mk9/+tN9n/vgBz/IzMxMz/5KpcJHPvKR1uPmjWmR3S5JEh599NHW4y9/+cv82Z/1mz8CDz300LbfGytxCKSVeuWk/VpZp0Ep9vk/C3czFeaZjS5yItce5jM1Qa3mmgpBGg4VAjg6BQ8eSquLRHZS3Fhpz6uxCY3S+dZzfu4wxun/z2vl0p8SlS/07Hf8KfLHv2Uoa5XNcbwMbjBDXF/EJhFR9Rpedh5rExorpwhn7hv1EkVEREREREREBm7TIdGnPvUp3ve+9/W0jLPW8gu/8AvrntdsM2et5cCB/gO8RXabU6dOUalUAFhcXOT3fu/3iOO457gHH3yQF7/4xdu+3nLUnpfRGRLl3AZPVedYSKZYCJ/L6fC5fJWIo4srvKRwlmdNTV5INJdNvwCMUUAkO89aS/36o2k5G2nViV2rNHG8PG5mX9/zkrjKyunf7ftc4bY34Xi9s8RkZ7nZg8T1RQDiyjN4mTkwLlHpPP7U7ZpNJCIiIiIiIiK7zpb6TN3YZs5au+5XM1QyxvDqV796+ysWGXONRoPHH38cSN8bn/3sZ3n44Yd7jnMch4ceemggs7oi0qQksoZakma/gYnxTcLZ2vQNx3qcrs0SuEzUPKJ+lmrpXCKRnRSVzhPXlwCwcZW4cnntGYOXP7bueaVz/5dk7bxObvYQuUOvGMZS5RY1q4kgbQ0YVa+tbafVRCIiIiIiIiIiu82WQqIbb2obY9b9aoZFU1NT/PiP//hAFi0yzk6ePEmjkQ7LuXLlCr//+7/f97jXv/713HHHHQO55l2ZBe7NXmXKrZMxEZC2mrMWztV7q4Vm3ApHZsOJm0d0I2thsTrqVcheksQ16stPth43SuewpEmll51ftxoori1SOvt/+z5XvPP/Wbc9new8N3ewtR1XLoNNq0Cj0nnNJhIRERERERGRXWfTd6VmZma47bbbWo9Pnz4NpAHRkSNH8LzelwqCgPn5eV760pfyQz/0Q13ni+xG1WqVp556CkjnEv3BH/wBFy9e7Dkul8vxtre9baDXDp0YzyQcClaJbRrkXo3y1GzvvKNj4RJTU1MDvf6oXK+228+JDFt96XFskgaxce0aSaMEgHEC3OzBdc9bOf172KQ3YAim7yWce3A4i5UtcdyO2UQ2JqpexcseXKsmeppw5v5RL1FEREREREREZGA2HRK9613v4l3velfrseM4rYqiP/mTP+HEiRODX53IhHn88cdbs4fOnDnDxz/+8b7HvfWtb2VmZmag146tYTUJAHBNuwfbYfMMl5M5YtMOi44HSxSnjg70+qOyUIG7Zke9CtkLoupVovIzANikQVRqB8DGyxOtnl3nvMtULn2m73O5Y68bSMtJGSw3d6hjNtEVvMz+tdlEF/ALt2t+lIiIiIiIiIjsGtvqb3PjbCKRvaxUKnHmzBkAvvrVr/IzP/MzrK6u9hx36NAh3vjGNw78+itxgLXdN5trictynOXZlT/GIcbufxYXoxmOZcrk8/mBr2EUlmsQJ+BOduc8GXM2iakvPtp6HJUvYtfakGEcrv3Vz4CNbvl1Fx/+DwQv+inczL5BLVUGwHFD3HCWuHa9fzXR7AOjXqKIiIiIiIiIyEBs+bZqkiStL1URicCjjz7aCk7/+3//76ysrPQ97qGHHsL3e1vAbddK3P2b7dbC51ePUXKKPB0+yLy5zt8oXuDNcw8zO53bNdULmkskO6Gx8jRJlP6HljRWiGvX0yeMi+PlthQQAWAjkkZvmCyj19k+MK5cac8mKl8kiSqjWpaIiIiIiIiIyEDpd+9FBmBxcZELFy4AcPXqVb7yla/0Pe55z3seL3nJSwZ+/cSmlUSdztWnuRoVAFjx9rOaa88E2y3ziJquV9OfwWIVVjRXXgYsbqxQX03n8GETGqXzref83GGM2VZRroypZjURsFZNdGVtO60mEhERERERERHZDTZ1Z+snf/InW9v/8B/+Q4rFYte+W/Ge97xnS+eJjLNHHnmktf1rv/ZrfY9xHId3vvOdQ6ngKSUBsW1nvtbCF1ePYkiwOGATHnMe4Ln2MYyBYrE48DWMQqkOq3V4pgRnltKg6FABnnNg1CuT3cJaS/36o+mbCogql7FxmkQ6Xh4nnFMl0C7mZg+2qsbiylW8zDwYl0b5Iv7UHThedsQrFBERERERERHZnk2FRO9973tbN7a/93u/l2Kx2LXvVigkkt3k/PnzPProo63KoWq1yp/+6Z/2PfYlL3kJSZJw8uRJZmZm2LdvcDNIluOw6/G5+jRX1qqIADAOC3aac/Vpbs+tks/tjnlEZ5ahFoEB5nPgGLWek8GKSueJ60sA2LhKXLm89ozByx/bNW0bpb+0mmiOuLbQqibysofA2rXZRM8a9RJFRERERERERLZl0z1yrLV9b4Y1Z7Bshm6myW7z3d/93Xz2s5/d1LGf+9zn+NznPgfAs5/9bH7mZ35mW9e+2siSdxtkTMRy1A6J2lVEFkv7PWewfHH1KM85cGHXvBcLQRoSWdKKomII1QjKDcgNfuyT7DFJXKO+fLL1uFE6hyX9N8/LzuN4mfVOlV3Eyx4gri0A/aqJbk9nUomIiIiIiIiITKhNzyRa76ayMWZTXyK70Xd+53fi+5tPI4wx+L7P6173um1dt2EdLtaLPFnZx5dLB7ncKFBJPKxtVxF1BkQAFsOVqMAzDK6CadRyHTH3ar29vay5RDIAjZXT2KQBQFy7RtIoAWCcADd7cJRLkx1k1qqJYG02USWdTYS1NFbPjHBlIiIiIiIiIiLbt6lKohMnTrSCHs/zevaJ7FWvfe1r+cAHPsD73/9+Ll68eNPKOsdxOHz4MP/sn/0zTpw4sa3rNpJ2vruaBCzHIctxyKxb7ltF1GSwfOLiDK+8F3bD29ftiLnjpL19CwWOIuuKq1fTDRsTlS629qdt5jb9OxayCzRbzkH634WXOwgY4triSNclIiIiIiIiIrJdmwqJTp06tal9InuN53mcOHGCD37wg/z0T/80f/3Xf73usS9/+cv5kR/5EcIwXPeYzTN9ty83Ct2ziG5gMZxdcfnaFXjOgQEsY8RmMun3sVKDgwWIEkgs5INRr0x2g2YVkU0irI0BcPwp3GBqlMuSEYiql1vbTjBD83PX8XfHfDcRERERERER2bv0q9Ai21AsFgHIZDI88MADNz32Oc95zoACIugomqFZNGMt/HXpMIabl9EY4COP7p5qG8+B/Xl4xQl4ze3w/EPpbCKRbVsLhpoBEaSt5mRvietLJPVlAIzj4ecPt57z88dGtSwRERERERERkYHYVCVRP7/xG7/R2n7LW95CLqfBzbL3TE21KwrOnz+PMaZvyznHcTh58uQAr9yuHmpe7VqU41q88W+1W+DUErummghgfxactR/Jfn0UyQBYa7E2aT5oP7Eb+jTKplkbE5XOtx77uaNg3HQ7fwQ3nB3V0kREREREREREBmLLIdH3fu/3tmYSveY1r1l3xsrp06e58847ATDGEEXRVi8pMnby+TyO45AkCU8//fS6M4mSJOHRRx8d2HVdkzDl1rBAPXGo4HOyum/dWUQ3alYTPXt+d9zznlfHJxk021mv197WLKK9JSpfarUddP0pnHAGAOP4BMW7R7gyEREREREREZHB2NbdrvVuiPc7rvklsps4jkM+n6der3PhwoWbHnvu3Dnq9fpArpt1Im7PLHJHZpGj4QoRLotxdlMBEXRXE006Y1Q9JEPQ0WKuu5JIIdFekURl4upVAAwOXqHdWi6YuRfjqvWgiIiIiIiIiEy+od/tGtRNcZFxVSwWqdfrnDhxghe84AXs27ev55hCocBtt902lPdDYuGLq0dhg1lEN9ots4nmsulcIpFBsp2VRF1VRfqPbS+wNqGxerb12M0das2jcsM5/Nzh9U4VEREREREREZkoA7nbZW7Sr+qTn/zkIC4hMrampqYoFAp88IMf5O1vfzsHDx7sOaZarfKzP/uzFAqFgV8/xrCahLDJKqImCyxUIUo2PHSszauKSIaho5LIdrSb61dJ5PgFMFvs3mq89HwZK3H1KjauAmDcDF52f7ptHMLZ+0e5NBERERERERGRgdr0Xa1f+IVf4Bd+4Rf6Pvfyl78cz+t9qUqlwuXLlzHGYK0ll9PdXNl9pqamgLT1XDab5cCBAzz88MNdx0RRxKVLl9ad3bUdroG/Nfc1Kkn7PXj+/HniOMY4huPHjgPp/KQ7br+je+0h+O7Al7SjFBLJMNh12s2ZPmGsm9nHgRf9FEljFYClJ3+TxspTXcc4wQxzz/6hnnMdv4Cb6a0+lNGxcY2o8kzrsV84TjOE96fuwPH0oSMiIiIiIiIiu8emQ6LFxUVOnTrVs99ay7lz5zY83xjDXXfddUuLE5kEzZAIaIVE/Zw6dWooIZG1UHDrFNy0lV0cx1xvpMOGsmGWeb8MwMHZKW6bGfjld1wjhnIEUwHMZiDcYgGHyE11tJjraj23zkwiN7OvFfZYG/V93p+6bbBrlKFolM63/v7dzP5WKOT4Bf0dioiIiIiIiMiuc8u3V5ut5Wznb1bfpN1cp7e85S23ejmRsZfL5XBdlziOyeVy64ZEp0+fHsr17Q2VDbVarbUdBu3B6tlsdijX32nXq3BhBRwDz56HS6uwLzv5FVEyXroqiejYXick6pTUl3v2qaXcZIhriySNFQCM4+PnDrWeC2fux2zi719EREREREREZJLc8t0Oa21XQNS572Zf3/7t384/+Sf/ZGALFxkXxpjWrKEwDJmZmSEMw57j+lXiDYK94XG9Xm9tBx3r2C3tHpfWMrDEQmThq5fhj89M/mwlGTOd1UMdb7KNfinCWttqO9fJ8YuDWpkMiU0iotL51mM/fwyMu7Z9FDecGdHKRERERERERESGZ9OVRK95zWu6Hr/vfe9r3Sz7kR/5EWZmZnrOCYKA+fl5XvrSl/LsZz97WwsVGWfFYpGlpSWMMeRyOebn53vaMA6rkoibVhK1Q6LdUEnUiKG0loFlPAjXqodmMuDpF/xlkNZrN7fB71bYuAJ92s05/lSfo2WcROVLrVaBblDECdJgz7gBwfTdo1yaiIiIiIiIiMjQbDokevWrX82rX/3q1uP3ve99WGsxxvDud797KLNWRCZFv7lEN4ZEly9fplQqkc/nt3292Bpi62Cw1K0htgaz1niuXm+HRMFau7kgDHDdye/HttT+1ih2FGvN744iKRkjXe3mNjGTqKnZquxGbqCQaJwljRJx7RoAxrh4+WOt58Lp+zCOP6qliYiIiIiIiIgM1ZZHvr/jHe9obTdbbYnsVf1Con5Onz7Ns571rG1fbyHKcqmeXvNyI0c5ScOg48EStbV2c57ntYKhXHZ3pCildic9pjPt7QPbz91EunVVD91CSFTvHxKpkmh8WZvQKLVDfS93sBUKeZl9eLmDo1qaiIiIiIiIiMjQbTkk+rVf+7VBrkNkohWL7XkjuVxu6CGR7Wox195uNBokSXpDO1yrIoLd0WoO4MQ07M9BJUqrh8oNmArT1nMig7ReJZHZsJJoue9+hUTjK65ewcZVABwvh5uZB9KKomDm/lEuTURERERERERk6HRrVWQAMpkMvu/TaDRuWkl06tSpgVzP2o7tjv31Wo0GAYveARpBFrdewDcx06ZALYJwwt/xxkA+gPv3w33708qiRrLxeSK3bL12czfMALtR0ljtu9/xi333y2glcY2o/EzrsZc/2tr2i3fieLsjYBcRERERERERWc+mbhnfeeedA7mYMYaTJ08O5LVExs3U1BQLCwuEYUg+n6dYLLK83F1VcPr06YFcq7OSqHO7Ua9Rcqf5au41aYes62tPLMA/+Hp44ZGBXH7k5tfay+WDmx8nsmUdSaztjGI3qCSK6+tUEmkm0ViKSudoRu1uZh7HS1tzOn4Bv3B8hCsTEREREREREdkZmwqJTp06hTEG21m+sAXG3Pw3sEUmWTMkgvZcon4hkbV22+8Fu852rVEjpv+MsNDd1iXHhufATGbj40S2Y+vt5tabSaTZfeMmri20Kr+M6+N3zB4KZ5+14d+1iIiIiIiIiMhucEt3QIwxW/4S2e2mptqVAuu1nCuVSly9enXb1yq6NQ4HyxwKVtjnVZhxq8y4Ver1OrHpn/0GE95qrml/Dhx9pMiwdYREthUSbfwfXr+QyHgFjNklKe0uYZOIqHSh9djPHYO1vyO/cBw3UHtAEREREREREdkbNn3beLtVRCK7XbHYvqmYy+VuOpdofn5+W9fKuw3ybgOApShDYGISm3ClVifx+7+td0slUbPVnMgw2a45RGv//m2isiTp025OVUTjJypfaFWLueEMzlooZNyQoHjXKJcmIiIiIiIiIrKjNhUS/cRP/MSw1yEy8TZTSQRpSPSiF71oYNdtziRq1BtYLPE6b+vdEBIZA/s1R152Qp92c5tpP9ZsX9ZJVSnjJWmsEtfSgW3GuHi59rC2cOZ+jLNLyi5FRERERERERDZBIZHIgARBQBiG1Go1stks+/btw3EckiTpOu706dMDvW6zxq9erwGwPzrHYdeQnZqhYR32HTiMF+aZ3gVzfPZnwdWYENkJfWcSbabdXL9Koqk+R8ooWJvQWD3beuzlDmMcP93OzuNlt1flKSIiIiIiIiIyaXb012UXFxeZmZnZyUuK7KipqSlqtRq+7xOGIfv37+fy5ctdx5w6dWqg12yGRLV6HYDQVjiSWaUQpvsfvOM4YTjQS+6o1Tr4DoSeWs3JzulqN9fc3qCSyNqkbyWRQqLxEVcuY5P0s9LxcriZfQAYxyOYvm+USxMRERERERERGYmh/06+tZaPfvSjvPWtb+Xo0aPDvpzISG1mLtH58+dpNBoDvGpa3VCv1Vt7gjAAwHVdgiAY4LV23tlleOQqPH4VVmrpl8jQdYREdi2K3ajdXNIo0Y5t25xAIdE4SOIqUaUd2nuFY63toHgnjrcLyi1FRERERERERG7R0CqJHnnkET70oQ/xX//rf+XSpUtYazFm41Y9IpNsM3OJ4jjm3Llz3HHHHQO5ZrJ2T7pWS9MTxxh832+tYZLfd5UIalG6bZw0MDq7DMeKcP/+0a5NdjfbbDfXWVG0YUjU22oOwPE1k2jUrLVEq+dohnhe9gCOmw44c4MiXv74CFcnIiIiIiIiIjI6Aw2JFhcX+e///b/zoQ99iD//8z8H0hszInvFZkIiSFvODSokAkOSJDSitDopCELMWnVRNpsd0DVGY7na3p7J9N8WGYpmONQZEm1QfNuv1Ryo3dw4SGoLJFEJAOMGeNmD6RPGEMzcP9FhuoiIiIiIiIjIdmw7JLLW8rGPfYwPfehD/P7v/z61Wq0rGGreeFFYJHvBZkOi06dPD+yaFqjV2z3Ywo4BRLncZIdESx2t5Ypr35YxsG+yvy2ZAM1KItvZPm6DIGH9SiKFRKNkkwaN8sXWYz9/rFUV5ueP4waq9BIRERERERGRvWvLIdGN7eSAm4ZDc3NzfPM3f/N21ioy9jzPI5vNUqlUyGazTE1NkclkqFarXcedOnVqW9dZjkIi64CBlThkqVanbkICW+uaQZTN5rZ1nVGKkrTdHEDWg9BNt+ey4LujW5fsEX0qiTacSVRf6bvf1UyikYpKF2At9HPD2VZo53gZguKdo1yaiIiIiIiIiMjI3VJItFE7uc52Lc0ZRD/0Qz/Ed33Xd/Gyl70Mx7n5DTaR3aBYLFKpVPA8jzAMOXDgAGfOnOk6ZruVRFejHKU4DYOuNHIs1SIqzjRBfLmrkig7wZVEngPP2g/LNSiEaRGHtTA/ubmXTJJmJVFzNhGwcbu5/iGRZhKNTlxfIa4vAmCMi5c73HoumL4P4wxtNKOIiIiIiIiIyETY9N2Rt771rRu2k7PWksvlKJfLred/9Ed/lBMnTgxwySLjbWpqimeeeQZot5y7MSS6du0aKysrXe3pboW9YbvRaNCMaIMwDY9838f3/C29/rjwXdiXg5cchawP1yowE258nsh2pP+eNSuJttluzrgYb3LD2klmbUJUOtd67OUPY5z0M9HLHcTLzo9qaSIiIiIiIiIiY2PTpT2//du/TbVabQVEneGQ4zi87nWv49d//ddbredE9qqdmUtkurajKAIsruPyl5Xb+OzybXyhdILffxz+8CT89TPbuNSIZTyYCtPKooN5CPWL/zJsHS3m4BbazTVWe/Y5fmHD82Q44soz2KQOpH8PbrgPAON4BNP3jnJpIiIiIiIiIiJj45Zut95YNfR1X/d1vP3tb+d7vud7OHTo0FAWKDJpisV2a6lcLrduSHTq1Cme85znbOkazeKGBEjimDiJ8YAwDHmisp/VJIQKcD097vkH4cGDW7rUyB3Ij3oFsud0tpjrqiS6edgT13sriZrzb2RnJVGFqHIZAIPBzx9rPRcU78ZxVZIoIiIiIiIiIgK3GBJBe9bQm970Jt7//vfzwAMPDGNdIhOrUChgjMFaSzabZX6+f0ujU6dObfkatqOSqBFFABgsYRgS2d4b2ZNcfaOQSHaa7awk6qoquvWZRAqJdp61tqvNnJs7gFkLhdxgGi9/dFRLExEREREREREZO7fcA6dZTfR7v/d7POc5z+GFL3whv/iLv8jly5cHvjiRSeQ4Dvl8mmxkMhnCMGRmZqbnuO20m7stvM692avcnVlgJrrMdHSZfLxIEAb9QyJ3y5caKd+Faf3Cv+y0jkoi29FubqNKIoVE4yGuLZBE6WxE44Z42bUySmMIZu9v/f8YERERERERERHZQkjU1Gw595d/+Ze8+93v5tixY7zxjW/kt37rtwa5PpGJ1JxL5LouYRj2bTl3+vRpkiTp2b8ZgZMQOjGhE0GjjE8DjwjfD4joTYQmNSSaz4Hu58pOs+u0mzOs/x+jTSLsWjDRyQ2KfY6WYbFJg6h8sfU4bTOX/r0FhdtwFdqJiIiIiIiIiHTZdEj04Q9/mG//9m/H87xWy7nml7WWKIr46Ec/yt/+23+767d09Ru7shc1QyJYfy5RtVrddgWexVCv11qP3SCLb2IMtuu4YELbzc3nRr0C2ZM6Wsx1tZ67SSVR0ljtu9/xCwNblmwsKl1oVYK54Vzr5+94WfypO0a5NBERERERERGRsbTpW8dvfvObefOb38zVq1f5L//lv/Abv/Eb/PVf/zXQHQQ1A6SmV77ylbzxjW/kjW98I6997WsJgmCAyxcZT8Viu3ogm832DYkgnUt06NChLV8nSSy1WhoS+Z5P6MJDB/6CmZkZ7rjrXmox1KLJmUlkLazWIR+A58A+hUQyAl2VRHRs3zQkWu673/FVSbRT4voycX0RAGNc/Nzh1nPBzP0YZ0JLKkVEREREREREhuiW283t37+fd7/73XzpS1/iS1/6Ej/8wz/M/v37W+3nmgFRs8LozJkz/Lt/9+/4tm/7Nvbv3z/wb0BkHHVWEm0UEm1Hvd4gWWuHFYbt4T25XA7fhUKQBi2FCclmSw04eR2+dgWWanClDPHWOvKJbF1n9VBHUd7NKmOTeu88IgAnUHuznWBtQlQ613rs5Y+Ck6bjXu4QXmbfqJYmIiIiIiIiIjLWtjyTCODBBx/kF37hFzh//jz/83/+T970pje12tF1tqRrPi6VSoNat8hYy+fzOE769srlcszNzeF5veU8p0+f3tZ1ypVKazsI20lQNpfd1uuOytJa57w4gSiBrzwDnzoNK7WbnycyUOu1m7vJP5lxY52QSDNwdkRUvoRNGkDa4s8NZwEwjk8wfc8olyYiIiIiIiIiMta2FRI1eZ7Hd3zHd/C//tf/4vz58/zcz/0cDz74YE91kcheYYyhUEhnYYRhiOu6fSvptltJVK5UW9thRyvHXHZCQ6K1b8cAU2vfjmvS9nMiO6Wr3dymZxKp3dyoJFGZuHoFAIPBLxxrPRdM343jhuudKiIiIiIiIiKy5w0kJOq0Xjs6kb2m2XLOcZx1W85dvHixNVNoKzoriZrt5oxjCDOZLb/mqJQbUF+7N18I05lEAPtz4Chnlp3UVT202ZBote9+VRINl7W2q82cmzuIcdLPQjecxc8fHdXSREREREREREQmwsBDok6d7eg+/OEP86Y3vWmYlxMZK8Viu4JgvZAoSRLOnj275WtU1iqJDAbP99NrZbI4N7mZPa46W8oVO37xfz6/82uRvW29SiLDzWYS9akkcnyMqliGKq5eJYnSsNy4Gbxs+jlrjEM4c/8olyYiIiIiIiIiMhF25E6y53m8+c1v5iMf+chOXE5kLDQriWD9kAi2NpfoVHWGpytFLkSzrDhzVDPzVJKwda1JdCAPd8+lodDBtWDIGNg/md+OTLLOSqJNt5vrnUnk+lNqtzpENq4TVS61Hvv5Y7AW5PlTt+H4SphFRERERERERDbijXoBIrvVZkOiW51LZC2sxCG1Wo2yKVBzsjh+lrp1ydMgm5vMVMUYKARwZApefDStLCo1wJ28oiiZdB3BkMW2999iSKRWc8PVKJ9v/V254b5WKOR4OfypO0a5NBERERERERGRiaHbryJDks1m8TyvtV0oFMjlcj3H3XJItPZnvV6j9Vvznt96vt81JsmBtV/+nwrhUGG0a5G9ab12c9xiuzknKPY5UgYhri+1fubG8fDzh1vPhbMPYCaw5aaIiIiIiIiIyCiokkhkSIwxTE1Ncf36dcIwxHEcDhw40BMK3Wq7Obt2o7pWaw/x8X0fA3ylfJD/8YVpMh4ELoQuhB78vRdAzl/nBcfM/GRnXLIbdIREthUSmZu2jksaqz37VEk0HNbGRKXzrcd+7igYN93OH8ENZ0e1NBERERERERGRiaOQSGSImiGRMabVcu7GkGhxcZHFxUVmZmY29ZrNSqJavd4KjNKKpYgaAdervTeyJ2UsSs6HfDDqVcheZ7uqh9becTdrNRfXsEmtZ79CouGIypewSQNI5z454QwAxvEJinePcGUiIiIiIiIiIpNH/VhEhmizc4lutZoocGLiagmXGNeA77k4WKzTP2EJ3Vt6+ZGZ15x5GQd92s3drH1Zv3lEoJBoGJKoTFy9CoDBwSscaz0XzNyLcZUyi4iIiIiIiIjcCoVEIkO02ZDoVuYSecZyd/AM85XHOBCd5oh7jRPhEkWvhnV6e8r5DjgTUkl0QK3mZBz0nUl0s3lE64REgUKiQbI2obF6tvXYzR3CrAXjbjiHnzu83qkiIiIiIiIiIrIOhUQiQ1QstgfX53I55ufn+x53KyERQLlcbm0HQdjaTvqERJNSRRS6UAw3Pk5k2LrazTW3b1pJtNx3v+MX++6XrYmrV7FxFQDjZvCy+9Nt4xDO3j/KpYmIiIiIiIiITCzNJBIZojAMCYKAer1ONpvF933m5uZYWFjoOu5W281VKhUALIYwbCcrd8wYHB9qEdRjqMXpnJ9xVYvSKiffTVvNTcrsJNnlOkIiuzaT6Obt5lb77nfVbm5gbFwjqjzTeuwXjtOs7vKn7sDxVIYoIiIiIiIiIrIVColEhmxqaopr164RBAGu63LgwIGekOjMmTPEcYzrbq7spzMkCoL2DI5vuc/Dm5DKIYBLq3C9Cnkf9mWh3BjvUEv2BttsN9dZUbSlSiKFRIPSKJ1v/X24mf2tUMjxC/hTt41yaSIiIiIiIiIiE03t5kSGbDNzier1OpcuXdr0a3a1mwvTkMgPfDx3cnLfxMJyPd2uxnClDH96Fr60+R+DyHA0w6HOkOgm/1xqJtFwxbVFkkb6MzaOj5871HounLn/plVeIiIiIiIiIiJyc7qzIjJkmwmJ4NbmEjVDIs8LWsFQLpvd+iJHoFSHeO0e/FSYtp2DtKpIZJSalUTNVnPATXshNgOMTsbNYvrMCJNbY5OIqHS+9djPHwPjrm0fxQ1nRrQyEREREREREZHdQSGRyJAVi+3h9blcbt2QaLNzier1OnGc3sQOM5nW/mxusmZyLNXa2zPtsUocyO/8WkS69Kkkulm1Styn3ZxazQ1GVL6EtREAblDECdLPU+MGBNN3j3JpIiIiIiIiIiK7gkIikSG7sZJodnYW3++tMNhsJVFzHhFAJtsOhrITVknUDImMSSuJAHwXpsP1zxHZEc1KouZsIuCm7eYaqz371Gpu+5JGibh2DQBjXLz8sdZz4fR9qtQSERERERERERkAhUQiQ+b7Ppm1ip9sNosxhvn5+Z7jNhsSdc4j6qwkyk1YJdE9c3C0CEenwFvr5DWfu2lXL5Ghs9ZiW5VEm2w3V1cl0aBZm9AonWs99nIHW6GQl9mHlzs4qqWJiIiIiIiIiOwqkzPlXmSCTU1NUa1W8X0f3/c5cOAAFy5c6DrmmWeeoVKpbFgRdK0C5/x7Acusc4JKbRpjLPc7mZueN24CNw2FHtiftpi7WoZcMOpVyZ7X0WKOjplE67Wbs9b2nUmkkGh74uoVbFwFwPFyuJk0WDfGJZi5f5RLExERERERERHZVVRJJLIDbmw5128ukbWWM2fObPha5XIFawzWODh+QIzB8ULM2jD3SWKA/bm0zdzhKbWakzHQ2WKuMzBaLySKK93nrHEVEm1ZEteIys+0Hnv5o61tv3gnjjdZrTVFRERERERERMaZQiKRHVAsFlvbuVyub0gEcPr06Zu+jrWWajUd5uN7fuvGdRCGJBZOL8GlVbhegXIDouRmrzZ6xQyEqmeUMWI7g6GuqqL+/1z2azUH4ATFvvtlY1HpHM0qLjczj+OlrTQdv4BfOD7ClYmIiIiIiIiI7D66PSuyAzZTSQQbzyWq1Wo0b1uHYbvsJgxClmvwk3/ce853PQu++a5bXfHOOJgf9QpEbtBRFWTprCTqP5Moaaz23a92c1sT1xZaP1Pj+vgds4fC2Wet2/ZPRERERERERES2RndbRHbAjSFRLpejUCj0HLdRJVG5XG5tB2FA2rANwjBYt2ooGOMudPO5Ua9ApFtXMGQ7ZhKtV0nUWKeSSCHRLbNJRFRqz2rzc8dgrY2mXziOq+osEREREREREZGBU0gksgNc1yWXSxORbDadp9GvmujUqVPYjhvTN6pUKni2QSFe5GA2YsqpkXfqHCiuHxKFYxoSFQLI+qNehcgNko5Kok3MJIrrK333O4FColsVlS9g1yq53HCm1bLPuCFBcUzLIUVEREREREREJpxCIpEd0pxL5LouYRj2DYlWVlZYWFhY9zXK5TKBrTIbP8MdhSoHghIHwyr3zAesFy2NayXRvFrNyTjqmkO0cUiUNNYJiXxVvdyKpLFKXLsOgDEuXu5I67lw5n6Mo+64IiIiIiIiIiLDoJBIZIdsdi7RzVrOVSoVAIwxZDIZLJDJZjDGUIv7nzNOlUSVqN3BS63mZBzZjplEXe3m1p1J1C8kMji+UtDNsjahsXq29djLHcY4aZmhl53Hy86PamkiIiIiIiIiIruefjVXZIdsNiQ6deoUL3jBC3r2x3FMrVZrnZ/etDbksmnacnQKvu/5UI+gFq99RXBgTO5VRwk8fg1ck66pHkNiwel/711kNDoqibraza07k6g3JHL8PMaMUTo75uLKZWxSB8DxcriZfQAYxyOYvm+USxMRERERERER2fUUEonskM6QKJfLsX//fowxPTOI1qskqlarrWObc40SIJtLt+ey8IrjQ1j4gKzU0sKMyEIjgb+6BK4Dz54fnyBLpLuSaBPt5urLPfscX/OINiuJq0SVy63HXuFYazso3onjZUaxLBERERERERGRPUPt5kR2SKFQaLWsymazeJ7Hvn37eo47depU3/ObreYgDZkAsLQqicbdUq29PR2mf8YJ5P3RrEekrwHMJFJItDnWWqLVc7A2Uc3LHsBx09DbDYp4+TFOvUVEREREREREdgmFRCI7xHEcCoUCAJlMOkeoX8u5s2fPEkVRz/5yudzablYSWUxre5wlNq0kAvCcdjCU9SEfjG5dIjdar5LIsPmZRAqJNiepLZBEJQCMG+BlD6ZPGEMwc/+6c6BERERERERERGRwFBKJ7KBmyznHcQjDsG9IFEURFy5c6NnfGRI1K4lczyMIxj9lWa1DvNZVrxhC896v2szJ2OmsJNqg3Zy1CUljtWe/ExSHsbJdxSYNGuWLrcd+/ljrZ+znj+PqZygiIiIiIiIisiMUEonsoM65RNlstm9IBP1bzjXbzbmu2wqGcvnJSFkKAdw5C/tysL+jO96ByeiUJ3tJRzBk6ZgX1ickSholwPbsVyXRxqLSBVir2nLD2dbPzPEyBMU7R7k0EREREREREZE9xRv1AkT2kmKx/dvxuVxu3ZDo9OnTXY+jKKLRaADgZYusxn7a/MqfotxIK3OyY/xudkxaQTSTgVedgFIDrlbSfSLjZL12c/RpN5c0lvu+hkKim4vrK8T1RQCMcfFyh1vPBdP3YZwx/jATEREREREREdlldCdGZAfdWEk0PT1NEATU6/Wu426sJOpsNdfIHuTp6lz6ID/D1Wvp5vMPDWXJA7UvC54L0y5MZ0a9GpE+OkIi2wqJTN/5OP3mEYFCopuxNiEqnWs99vKHMU46pMzLHsDLzo9qaSIiIiIiIiIie5LazYnsoFwuh+Okb7tsNosxpm810Y2VRM1WcwCZTLa17QdpKc6kzHfXDCIZd7aremitlVyfVnMASb1/SOQGConWE1eewSZpKO74BdxwHwDG8Qhm7hvl0kRERERERERE9iRVEonsIGMMU1NTLC0tkclkWiHRuXPnuo67fPkypVKJ/NrMoc5KoiCToba2HYYh9bV72n92DhZrELrpV+DCVAj37duJ72xjhu55RCJjqU+7ObNeSLRuJVGx7/69LokqRJXLABgMfv5Y67mgeDeOq/6TIiIiIiIiIiI7TSGRyA5rhkTGGLLZ7E3nEj3rWc8CuiuJwjCkZiEIAxzHhSQtCfzjM/DYte7XOFaE9716WN/JrZnJgu+OehUiG+g7k6h/qZ7azW2etbarzZybO4BZC4XcYBovf3RUSxMRERERERER2dPUbk5khxWL7SqDjUKipmZIFAQBjptmu7lsjlZjLAO1qPc1wjEKZeZVRSQTwFrb8WDtHbZuJdFy707jYjz9x36juLZAEqUVkcYN8bIH0yeMIZi9v+/MJxERERERERERGT5VEonssKmpdpXBzUKiU6dOAVCr1YjjuHX8fr/MtFvjtkOzLGShGqV1DrW49zXGKSTSPCKZCB2VRHZtJtF67ebiPjOJHL+gwOMGNmkQlS+2Hqdt5tKfUVC4DVeVVyIiIiIiIiIiI6OQSGSHdYZEuVyOTCZDsVhkebm7KqFZSdTZai6Xy5F1IrJOxB3zOWzUDof6hUTBCEOiaK0Iw3OgGEJGnzYyAWwzJGq1muMmlUT9QiIFHjeKShda4ZsbzuH4BQAcL4s/dccolyYiIiIiIiIisuep3ZzIDstms3ie19oG+lYTnT59Gmst5XK569ymqakpOhpjUe/Xbm6Ewcz1KnztCjy5AFGcVjyJjL1mONQZEt3CTCLHL/Y5cu+K68vE9UUAjHHxc4dbzwUz92OcMSp3FBERERERERHZg/S7/SIjUCwWWVhYIAxDXNflwIEDPPnkk13HlEolrl692lNJBGCMoVAokCy0j3//a9NqonqczieqxZAPduTb6WupCtbCah2uVeGzZ9KKohceAUfduGRMNSuJbGcEaxzi6jWSxmrXsXF9qfcFjENjpT1PzPELuJl9Q1nruLM2ISqdaz328kfBSf9vh5c7hLdHfy4iIiIiIiIiIuNEIZHICExNTbGwkCY8N5tL9JnPfIZ7770XSIOhTCYDQKFQwHGcrkqifACnr8BvfhXe9hx41vxQv4WbihIoNdLtwIPs2ieNMQqIZMz1qSRKGitc+6t/CXbjcrj69a9y9fpX2zuMx4EX/dSeDIqi8iVskn4QOH4BN5wFwDg+wfQ9o1yaiIiIiIiIiIisUbs5kRHonEt0s5Dok5/8ZKuSKAxDHMfpOj/pSImshQ8/AhdX0z+t7Xm5HbNca19/OmzvP5AbzXpENq1VSdQOiWxU3VRA1P/1op4KpL0gicrE1SsAGAx+4VjruWD6bhw3XO9UERERERERERHZQQqJREbgxpBo3759rQCo05kzZyiVSkC71Ryk7eoAOkuJvnYFTq11vzq1lD4elaVae3um417wfH7n1yKyWdZabLOCKOmYSaTqt1tire1qM+fmDmKc9IPADWfx80dHtTQREREREREREbmBQiKREWiFPKThj+u67N+/v+c4ay1f/vKXgTRMamqGTLZ1HHzk0fa9bEP6eFTVREcKcGQKpjOQ89N9+aC9LTKWOlrMdSWw+qfylsTVqyRRWgFp3AxeNq2UNMYhnLl/lEsTEREREREREZEbaCaRyAgEQUAYhly4cIGrV69y8eJFpqamuHz5cs+xf/7nf85tt92G7/tUq1UAHnjgga5Wc51VRJDe3m5WEz2nfye7oQo9OODB0Sm4YxaulsFVNYaMu7VWc+l2ZyWRQqLNsnGdqHKp9djPH6MZX/tTt+H4KicUERERERERERknColERmRqaoqf/dmf5eGHH77pcYuLi/zqr/5q177f/B8f4b/9/qd5ZjUNhH7nkfQ2bGftQ7Oa6NnzYEYU0MznIePBseLGx4qMmu0MhrqqipRwblajfL71s3PDfa1QyPFy+FN3jHJpIiIiIiIiIiLSh349WmREpqameP3rX4/vb74HmzEGzw/4hr/1Tp5ahIur8PnzcHa5OyCC7mqiUXAdmMtufJzI2OioJLJ0VhIpJNqMpLFKUl8GwDgefv5w67lw9gGMKrJERERERERERMaO7tiIjEixWOS1r30tH/jABzhw4ABmgxvRjuNw5MgRfvLff4TX/a3/N60csvBn59avcxjlbKKCD47urcsE6QqGemJX2Ui8FhABeLkjYFwA/PwR3HB2VMsSEREREREREZGbUEgkMiKFQgGAEydO8J73vIcHHnjgpse//OUv54Mf/CD7D6RDhhwD51fgcnn929mjrCYqRzt/TZHtME7QsZ1pPxFVRrCayWMct+NRO3BzM/t3fjEiIiIiIiIiIrIpColERiSXy7W2i8Uit912202Pv/vuuwnDkLi2SrVaxVr43E2qiJpGVU3UiKEeb3ycyLhw3LA9Q8fPYdb+iUwUEm2K40+1tpPaUms7rl4dxXJERERERERERGQTFBKJjEgmk8F109+8D8OQixcvrnusMYbHHnsMgMDELC4u8rUrcKm0cVOskVYTNXb+miLb0W6LZlqBkbUqi9sMx8thnHTGWtJYbc14iipXsKPoeSkiIiIiIiIiIhtSSCQyQvl8ehM6DEPOnz+/7nHWWp588kkApt0a89E5Pv7U5mf+jKqaqFTf2euJbJcbzrW2TUdljGyOE0wDYLEkazOKbNIgqV0f5bJERERERERERGQdColERqjZci6KIq5evXlLpitXrrCyskLgxHz5UsxXr0CyydBnFNVEiYXLJbi0Cievw3V17JIJ0K4kolVJJJvnBsXWdtxYbm1H1RGUMoqIiIiIiIiIyIYUEomMULOSqF6vc+jQIR588EGCIOg5rlAocODAAa5evYq18HvX7sVs2Giu205VE0UJPHwFvvwMfOECfPUyPH0drikkkglgHB83SCuIHC+HMe6IVzRZjFeAtZ9ZUl+h2RAzqlwe4apERERERERERGQ93qgXILKXNUOiQqHAj/3Yj3Ht2jUWFxc5ffp013FJkvDOd76Ter1OhMP1OItlk73m1lhgoZqGOP4Q73t7DsRJul3rGOWi1nMyKZxwjri+km77BRw3mwYfazN2bonxcPzCgFc4vowxuEGRuHYda2OS+gpOUMTGNeL6clelkYiIiIiIiIiIjJ5CIpERarabA8hmswAcPny4JyQql8usrKzgui5O0uDHjn6GujvFS17yN/jieTZdUzQVDjcgago9KDegHqdt5xwDpcbwrysyCG44S2MlfQ86/hROMMX03W/H+Hm8jplFTUlUZuGrvwg2uuEZh33P+1HczL4dWPX4cIJp4rUZRHF9CWctGIorVxQSiYiIiIiIiIiMGYVEIiPUrCQCyGQyABw6dKjvsZcuXWJ6epqVlRVmZ1ygyonMEkv7p6neeG96xJohEaTVRFkfKo12YCQyztxgBowBa1tVQE4wheMX8Kdu63tO7vCrKF/4xA17EypXv0gwfddwFzxmHH8KjAM2IakvAccBiKqX99zPQkRERERERERk3GkmkcgIZbNZjElTkzAMgZuHRADXr19v7bt8+TJZf8iL3IJMR7VSda1DlzHd7edExpVxPNxgOt12Q4yTvsmSqIy1Sd9z8sdeT79/UisXP0PSWB3aWseRMU4aFEHacm7t+08aJZJGaZRLExERERERERGRGygkEhkhY0yr5Vyzkmhubo4gCHqObYZES0tLrX3PPPMM2TGsB8wHsC8HR6fgjhl4+XH4htsZy0BLpB83nG1tt2YK2QQbVfoe72X2kT3w4p79NqlT6qkw2v0628rF9eXWdlS5PIrliIiIiIiIiIjIOhQSiYxYMyRyXRfP83Acp281UTMkqtfrlMtlIK0q8mwda9Mqnah/kcOOKwRwvAjzeQjdNBwyajMnE8TtmD3UComApLGy7jn549/cd3/p/CdJ4trgFjcBHL8dEiWNxdZ2XL0ygtWIiIiIiIiIiMh6FBKJjFi/uUQHDx7sOW5lZYWVlfQG9bXry5yrFXmqOsufnlzmy5fhkauw0L/IYaRKjVGvQOTWOcE0xqR9E5ut04Cbto7z88cI557bs99Gq1QufXbwixxjxvFa4ZqNGyRRGmzH9eU9F5iJiIiIiIiIiIwzhUQiI9YZEm00l+iZZ54BYHlpgetRllIcsLi0jLXp8/V4uGvdilKD1vpEJoUxDk44k247PsZN35s3m0sEUDj+LX33l879X2yyt4ZyOWtznQCSRrvlXFxRNZGIiIiIiIiIyLhQSCQyYs12c9AOiQ4fPtz32CtX0pur5VIJJ6mn28uLWNIUpjMkasTwxAL8nyfhF78A7/nUaMIaa6G6t+6Nyy7RNZfIa7acsySN0rrnBNP34Bfv6tkf1xaoXPnioJc41tyOkCiutWepaS6RiIiIiIiIiMj4GMOR9yJ7S792c/v378f3fRqN7l5tV69eBcBaS728jFfYD0lErVYhE+ZaIdEfnoT/+WjvjKKrFZjPseNKjXQukcgk6ZxL5PoF4to1IJ1L5AZT651G4fi3cP1rv9Szv3T2Y2QPvARj9sbvZxjHx/FyafVVXMUmNYwTEtevY5MGxtGHgoiIiIiIiIjIqO2NO1UiY6yzkqgZEjmOw5EjR3qOPX/+fGu7unq9tV0vp3NSanFauTOT6Q2IAJ64NqhV35pSfTTXFdkOx59qBRnN+Tpw87lEAOHcc/FyvdWAUfkCtYWvDHaRY87pqiZaazlnLVH16ohWJCIiIiIiIiIinRQSiYyY67qtcKjZbg76t5y7evUqtVo69L26soBvIvJunbB+lcMFOFFMj7tnrudUAJ683n//sJUaGx8jMm6MMbhrc4lwPIybvk9tXLnpfCFjHPLH39D3udWzHxv0Msda11yi+mJrO1bLORERERERERGRsaCQSGQMNFvO+b6P67oAHDx4sO+xy8vpb+Pn65c5lpzmzsx19ieXmQlqzGbBGJjLpl83emJhOOvfSGdIlIxgLpLIVnW2nHP8dou5JFp/LhFAdv7FOGFvWttYfpL60pODW+CYc9ywFa4lURmbpB8GcXUBm8Q3O1VERERERERERHaAQiKRMdDZcq5ZTTQ/P9/32GvX2j3jFhcXAQhM3Npu6qwmcg3cNQvPO7CzIc1qHa6U4NGr8MUL8OnT8KVLO3d9ke1yw9n2dlfLuZWbnmccj8Kx1/V9bq9VE7lBsbWdNNKQ29qYuDai1FpERERERERERFq8US9ARNqVRJCGROVymf379+O6LnHc/dv2Fy9e5P777wfSkOjYsWMEJmZpcYmDB9rVR3/jKBydgrvn4I4ZCNwd+Va6PFOClbQ7Hvtz4DtQ1nwimSCOX8C4ATau4/jt9+lGc4kAsodeycrp/429oeqotvDXNErn8fNHB77eceQE07DWXi6uLeGG+wCIKpfxsv3DcBERERERERER2RmqJBIZA50hUXM+ked5HDt2rOfYp59+unV8uVymXq/jOzHLy8skHe2bnncQvu0euG/faAIigLDjurW1ES61GBrqMiUTpNVyzrg4Xlr1Z+Naq3Xaehw3JH/ktX2fK539w4GucZw5Xg7j+MBaBZZNPwDi6lWsTUa5NBERERERERGRPU8hkcgY6NduDuD48eM9x164cIEgCFqPl5aWCExMkiQsr9y8BdZOy3TUKlaj9nY56j1WZFx1tpzrmku0Qcs5gPzRbwAn6NlfufIF4uq1PmfsTk4w3dpO6mst55IGce36qJYkIiIiIiIiIiIoJBIZC/0qiQCOHDnS9/jO+UOLi4u4xuKapGcu0ah1VRJ1VA+V1HJOJkirkoi0/VzTZlrOOf4UuUOv7H3Cxqye//hA1jcJ3I6QKK4vtberV0axHBERERERERERWaOQSGQM+L6P76ftmDoriQ4dOtT3+PPnz7eOX1paIkkSAhOPXUjUWUlkgX05ODEN+d7CCpGx5XhZHC+bbvt5DAbYXEgEkD/2Ovr9c1u5+JlNv8akM14eY9LUOKmvwFqbuahyBWvtKJcmIiIiIiIiIrKnKSQSGRPNaqIgCDAmvQk9OzuL4/S+TZ966immp9PfzE+ShJWVFQInpl6rU6mUd27RG/DddCbS8w7C3bPwdYfg3n0wHW58rsg4abecMxg/fa/apEES1zY818vsI3vgxT37bVKndOETg1zm2DLG4ARFACxJKxyzcY2ksTzKpYmIiIiIiIiI7GkKiUTGRDMkMsa0qomstRw7dqzn2JMnT7ZCIovh8vUSjcRhJQ547OIqlcbOrXsjWR8ck84kijWjXibUdlrOAeSPv6Hv/tL5T2wqaNoNnGCmtd3Vcq6ilnMiIiIiIiIiIqOikEhkTORyudZ2MyRKkoTbb7+959jz588ThiENJ8O54F4eWZ3hmUaBa1GOcws1SmMUEnUqj+m6RDbitCqJ0jlDTXaTIZGfP0o497ye/TYqUbn02e0vcAI4fgFM+n87ko6QKKpcHtWSRERERERERET2PIVEImOiWUkEkMlkWtsnTpzoOTZJEs6dO8d0Pg2TGlGDpFEFoFKpUGlEfa9RbsBXLsNHHoUrpUGufnPGNbwS2Yjjhq0KIsfLtefrNFY2PVOnsF410bn/i036v2d3E2OcVsBmbdyqwkqi8p6ZzSQiIiIiIiIiMm68jQ8RkZ3QGRI1K4kAjhw50vf4kydP8oIXvADnUkJiHOqVVcjNYYGFpVWOT88AcL0Cf/AkPLkA55aheTt7Lguvzvd96aFRSCSTzA1nW2GG4+WJG8tYG2PjKsbLbnh+MH0PfvFuGstPdu2PawtUrnyR3MGXDmXd48QNpltVRHF9qRW8RZUrBB1t/EREREREREREZGeokkhkTHS2m+usJDp48GDf40+ePMnMzAyuTZOXaqk9/H1hqV0m5DnwyVNwtiMggjQ02mnl+s5fU2RQuuYSBbc+lwhuUk109mNYu/uHdqWVRAaApNExl6iquUQiIiIiIiIiIqOgkEhkTGQyGVw3bWHVWUnkOE7faqKTJ0+SzWbJ+enjaqWCa9OWVSurpVYLrKkQDvapGBpFSKRKIplkbjgDJg04jL+1kCicey5ervf9HJUvUFv4yrbXOO6M4+H46QeSjRskURmAuL5MElVHuTQRERERERERkT1JIZHIGGlWE3WGRNVqlbvuuqvn2DNnzlCv1zk8ZZiJLjPXOMf+6BzHgyUOuYuUSu1qonvmek7nchmWdviebKkBmxzfIjJ2jOPjrs3Ucdxsey5RtLrpuUTGOOSPf3Pf51bPfmwwCx1zTjDT2k7q7QpIVROJiIiIiIiIiOw8hUQiY6Q5l8hxHIIgANYPieI45vTp0xyd8ZlKrpOzqySlK7gmvVm9uLjYOrZfSBS6cKnUu3+Y4gSuluGZEjx9fWevLTII3S3n0sAIm2DXKmI2Izv/Ypyw903ZWH6S+tIT217juHODYms7rrdbzkUVhUQiIiIiIiIiIjvNG/UCRKStGRJB2n6uXq8TxzG333573+NPnjzJXXfdheM4JElCdeU6uYMWg2FxaZFjx44BaUg0k0n/vGcO7p6DY1Pg7lBMvFBJg6F6DCs1mF4buXR4CjL6FJIJ4oSzsHIq3fYLxLVFIK0marZR24hxPArHXsfyyf9fz3OrZz/G3PQ9g1ruWDKOj+PlSaISNq5ikxrGCYnr17FxHeMGo16iiIiIiIiIiMieoUoikTHSbDcH3S3n+s0kAnjqqadwHIdiMf3NfNuoUKvVACiXytTrdQAO5OFffxP8wNfDN94Bt03vXEDUVIvSVnO1uL2vVN/ZNYhslxvMYEz65nG2OJcIIHvolRivN1SqLXyZRun89hY5AZzOaqLaWjWRtUTVqyNakYiIiIiIiIjI3qSQSGSMdFYSdYZEvu9z4MCBnuNPnjwJwMzMDACebVBabfeQW1pKb74ak36NSme1UDVqb5caO78Wke0wjosTTK9thxjXByBplLA22fTrOG5I/shr+z5X2gOziZo/Q4Cko+Wc5hKJiIiIiIiIiOwshUQiY+TGdnNNtVqt71yiU6dOEUUR09PpDVfPNiiV2iHR4uJ4DP4J3fZ2ZyVRWSGRTKCuuUTe2lwiLDa6tSFf+aPfAE5va7XKlS8SVa9tZ4ljz3FDjJt+xiVRGZukHwZx9Ro2iW92qoiIiIiIiIiIDNCeCon+y3/5LxhjMMbwK7/yK32P+dM//VO+9Vu/lbm5OXK5HM973vP44Ac/SByvf9Pq13/913nxi19MoVBgenqa17zmNfzv//2/1z2+UqnwEz/xE9x3331kMhkOHDjAd33Xd/HII49s+3uUyZbNZjFrJT+dlUTVarVvSNRoNDh79ixhGJLL5XCIqFUrRHFarrO8vEJyC9UNw+I64K8FRZ2VRAqJZBK54Wx7exst5xx/ityhV/Y+YWNK5z6+5fVNCrermmgZAGsT4truDshERERERERERMbJngmJzp49yw//8A9TKBTWPeZ3f/d3edWrXsUf//Ef8+Y3v5kf/MEfpF6v8+53v5vv/u7v7nvOj/7oj/K93/u9XLx4ke///u/n7W9/O1/5ylf49m//dn7pl36p5/harcbrXvc6fvInf5Jisci73vUuvumbvomPfOQjvPCFL+Tzn//8wL5nmTzGmNZcos1UEkE6lwjSlnMG8GhXE8VxzMryynAXvUkzGZjLpvORHtgPLzsOX3do1KsSuXVOUMQ4aQ9Fs42QCCB/7HX0+6e4cukzJI3xeO8OS9dcoo6Wc1Hl8iiWIyIiIiIiIiKyJ+2JkMhay/d93/exb98+fuAHfqDvMcvLy/zdv/t3cV2XT33qU/zqr/4qP/uzP8tf/dVf8dKXvpTf+Z3f4bd+67e6zvnTP/1Tfu7nfo677rqLL3/5y3zgAx/gl3/5l/mLv/gL5ubm+NEf/VFOnTrVdc7P//zP8yd/8ie85S1v4fOf/zz/8l/+S37zN3+T3/md36FcLvPQQw+RJKOv/JDRaYZEruvieemN6Gq1yp133tn3+OZcombLOdc2KJfKAFgLS0uLQ17x5hydghPTcDAPOT/9GuWcJJGtMsZpVcEYx8e4adVfEpWx9tZapXmZfWQPvLhnv03qlM5/cvuLHWOOl8M4zZlOK7D2s4ur125pvpOIiIiIiIiIiGzdngiJfvEXf5FPfOIT/Nqv/VrXzJdOv/3bv83Vq1f5nu/5Hl74whe29mcyGX7qp34KgH/7b/9t1zn/7t/9OwB+/Md/nNnZdvuh22+/nR/8wR+kVqvxn//zf27tt9by7//9vwfgX/2rf4XjtH/8f/Nv/k1e+cpX8vDDD/OpT31qe9+wTLR+c4kajQbFYpF9+/b1HH/y5EnqiUM1PMCyf5gVZ5ZztTynqkXq1mVxcXGnlr5pJbWZkwnnZtrvRaermujW5hIB5I+/oe/+0oVPkMS1W1/cBHE6Ws7FzZZzSYO4Nh7z1EREREREREREdrtdHxI98sgj/NN/+k9517vexate9ap1j/vkJ9Pf2H7DG3pv1r3qVa8il8vxuc99jlqttqlzvuVbvqXrGEhv5p85c4b77ruPO+64Y1PnyN7TGRJ1ziVar+XcU089RTUyXGoUSYpHiUxAw7rU6g0i61Ct1qhWq+teb7EKz9z6fe1t0SwimXRO11yidtu0rbSI8/NHCeee17PfRiUqlz6ztQVOiO65RO2Wc7FazomIiIiIiIiI7Ahv1AsYpiiK+Dt/5+9w4sQJ3v/+99/02MceewyAe+65p+c5z/O44447+NrXvsZTTz3FAw88QKlU4vz58xQKBQ4d6h2s0nydxx9/fFPXWO+cG128eJGLFy/27H/kkUe6/rzR4cOHOXz48LqvK+Oj2W4OekOiO++8ky984Qtdx9dqNa5ePAP791PI57m6spjur1aJcgEAi4uLrf9OL6zAEwvw5EL655UyvPAw/IMXsmNW6zt3LZFhcLwCxvGxSQPHbwe7W5lLBFA4/gZqC1/u2b967uPkDr+mNQNptzFeHmNcrI1J6itgEzAOUfUqgbUY9aQUERERERERERmq3XnXac1P/uRP8qUvfYnPfvazZLPZmx67tJT+BnNzrsuNmvubrbtu9fitnnOj//Af/gPve9/71n3+7W9/e9/9P/ETP8F73/vedc+T8dGv3RysX0kEcPqpJ9i//+vI5nJ4ZgFI5xhFNj1/aakdEv3Hv4Szy93nP3k9nV+0U/djVUkkk84YgxvOElUug3FxvCxJVMHGVWwS3XKoE0zfg1+8m8byk137k9oClStfIHfwZYNc/tgwxuAE08S1BSwJSWMVJyhi4xpJY7mr0khERERERERERAZv14ZEX/jCF3j/+9/PP/7H/5iXvvSl2349ay3ALf9W860cv5lr/P2///d505ve1LP/kUce4e1vfzv/9b/+Vx544IGe51VFNDnWqySqVqvrhkRPPXWSI38jATyyocf1CKI4otqw4MPyygpxHOO6LvfM9YZEi1W4WoH5XN+XH7hqBHEC7q5veCm7mZuZS0MiwPgFiCpAWk3khjO3/HqF42/g+td+qWd/6ewfkj3wNzBmd75hmiERQFxfwgnS9n1R5bJCIhERERERERGRIduVIVGzzdy9997LP//n/3xT5zSreJrVPjdaXl7uOm6j4/tVDd3qNfrZqG3cAw88wAte8IJ1n5fx57oumUyGarXaVUlUrVa57bbbmJ6e7vlv6KmnnuIbTEwdl9l8yNXrVQwWW1uCXIhNLMvLy8zOznL3HHziVO91n7i2cyERQKkBxXDj40TGlRvOtbf9KeLKFWDrIVE491y83BGi8oWu/VH5ArWFr5DZ9+C21juuHL8AxgGbrM0lOg6Q/jyn+7dnFRERERERERGRwdiVv5a8urrK448/ziOPPEImk8EY0/pqtmr7/u//fowx/MN/+A8BuO+++4D+84CiKOLpp5/G8zzuvPNOIG0JdvToUVZXV/vOCHriiScAuPfee1v7bnaN9c6RvanZcs73fVzXBdJ2c8aY1n+DnU6ePMlR7zrPzj3DC/atsj86z1SygClfaR3TbGN4z1zP6UDacm4nqeWcTDrHy2HccG07jyGtAk0aK1t6PWMc8se/ue9zq2c/trVFTgBjHFw/rR6yNm7NdUqi8pZnPImIiIiIiIiIyObsypAoDEPe+c539v36uq/7OgBe8YpX8M53vrPViu61r30tAB/7WO+NuD/+4z+mXC7zspe9rKv9183O+ehHP9p1DMBdd93FiRMnePzxx3n66ac3dY7sTf1aztXrday1fVvOlctlFq5cxDHpuaFn1/ZXSJIEgMWlRQDmsrBvbUTXoTy88gR83/PhW+4e3vfTlFhYqcHVMnzlMvzFRfjMaXimNPxriwxDq5rIOBg/fd/apI6N61t6vez8i3HC3iS3sfwk9aUntrzOcddsMQdpy7mmqHKl3+EiIiIiIiIiIjIguzIkymaz/Mqv/Erfr+Y8n3e84x38yq/8Cm9961sBeMtb3sL+/fv5rd/6Lf78z/+89VrVapUf//EfB+Af/IN/0HWdH/iBHwDgp3/6p7l+vV2GcerUKX75l3+ZMAz5vu/7vtZ+Y0zrnB/7sR9r3bwH+N3f/V0+85nP8KxnPYtXv/rVg/xxyARqVhJBOySy1lKv19edS3Ty5MnW9lwhTYEslkolnZPSqDcoldM05v/zQvjg6+GnXwvf+yC84vjOtJprxHDyOpxbhtOLcL0CtRjKW7ufLjJybqYd6Dh+obW91QoY43gUjr2u73O7uZooDYnWKrE6QqK4enlEKxIRERERERER2Rt2ZUi0FcVikf/0n/4TcRzzmte8hr/7d/8uP/ZjP8bzn/98Pve5z/GWt7ylFSg1vexlL+Mf/aN/xMmTJ3ne857Hu9/9bn7wB3+QF77whSwsLPCv//W/5vbbb+865x/9o3/Ey172Mn7nd36Hl7zkJfzTf/pPedvb3sZb3vIWcrkc//k//2ccR38te11nJdGNc4k2FRIVs63t1dX2zerF64sA3D4DUyOYBxS4YNL7wFSj9v6SWs/JhOqcS+R4U63tJNp6m7TsoVdivHzP/trCl2mUzm/5dceZMW4rZLNJgyQqAxDXV0ii6iiXJiIiIiIiIiKyqymN6PAd3/EdfPrTn+ZVr3oVH/7wh/k3/+bf4Ps+P//zP89v/dZvYZp3tzv83M/9HB/60Ic4dOgQ//E//kd+4zd+g2c/+9n8/u//Pj/0Qz/Uc3wYhvzRH/0R73nPe1hcXOQDH/gAH//4x/mO7/gOvvjFL/KSl7xkJ75VGXP9KokgnUt08ODBruebnnrqqdb2XDHbmo9SKrV7uS0tLfWct5OMgTAdsUQtBpt2xVNIJBPLcUMcLw11HT+HWftndTuzdBw3JH+kf9vR0q6uJppubSf15da2qolERERERERERIbHG/UCdtp73/te3vve9677/Mtf/nL+z//5P7f0mu94xzt4xzvesenjs9ks73vf+3jf+953S9eRvaMzBLqxksgYw1133cWXv/zlrnOefPJJrLUYY8h66X9n5UqZKI6o1WqEYcjq6iqNqIHv+Tv2vdwo46VVRNZCPUlDo5LazckEc8PZtcoXg/Hz2MZKWg0TV3HczIbn95M/+g2Uzv0hNul+c1Quf4HC7d+Bl9k3gJWPFzcoEq1l2nF9ES93CEjnEvmFEyNcmYiIiIiIiIjI7qVKIpEx5Ps+vp8GOTdWEgF9W86trKxw9erV9HwTdwVNXdVEi6OtJmpWEgEkCcxm4egUxMn654iMM7cjsBnEXKL0dabIHnpln2cSSuc+vuXXHWfG8XHW2uzZuIaN08+7uL6IjZUki4iIiIiIiIgMg0IikTHVDHmCIGi1OmyGRHfeeWffc5pziRwDM1PtuUSlUsdcosXFYSx30+aycO8+eO4BeN5B+PrDcN9+cPVpJBPKDWZa24MKiQDyx14Hxu3ZX7n0GZLGyrZee1w5QbG1HdfXAm1riapXRrQiEREREREREZHdTbdlRcZUMyQyxhAEAZC2m4P+lUTQDomshTBwwS9QNTkq1TpxHAOwtLxEYkdXthN6kPPTUEiziGQ3MG7QCoccL4dZC3aSxiq2OXhrC7zMPrLzL+rZb5M6pfOf3PLrjjO3ay5Ru+oxrigkEhEREREREREZBoVEImMql8u1tptziZIkoV6vc+TIEbLZbM85jz35NI9V9vG1ygEu1Kap5o6y6s4S4VAupy3n4ihmdXV7FQ6DollEslt0t5xba/VoY2xc2dbr5o+/oe/+0oVPkKy1Y9tNjBti1uY4JVEZm6RJclxbwCbRKJcmIiIiIiIiIrIrKSQSGVOdM4WaIRGkLeccx+GOO+7oOefUU09STzysNXgmJmyGS8ZjdZ25RFECT12HPzwJv/xF+PFPQrL14odbokoi2S3ccLa17fjtlmnbbTnn548Szj2vZ7+NSlQufWZbrz2uuquJlgGwNiGuXhvVkkREREREREREdi2FRCJjqjMkCsOwtX2zlnOL1xdYvn4VAM8kBIGPMQ4xLuVSGUua/jTnEn3yFPzwR+GnPwv/42H4y0twcRUu7VChUZRATcUBsgu4wQyszQ4b5FwigMLxb+m7f/Xcx3dldY3TERLF9cXWtuYSiYiIiIiIiIgMnkIikTHVr90cpJVEAHfeeWff8y6eegwA1yQY4xAGIYnxiJOYaiUNmCqVCrV6jZkM1PuMJ3piYVDfxcbKqiaSXcA4XqsCxrghxvEBSKISdpszwILpu/GLd/fsT2oLVK58YVuvPY4cL4tx0jlsSWMVbDpPLa5e3fbPUkREREREREREuikkEhlTmUwG13WB7kqiZkjUr5II4OKpRwHwTXozNZMNifEAKJXbLecWFxe5e7b3fIAndzAkUss52S26W86tVRPZBBttby4RQGG92URn/3BXBidO0G7ZFzdbziURcW0HP5xERERERERERPYAhUQiY6xZTdSv3dzx48cJgqDnnCunHmHWq3AkWGHeL3FboUEhuQ5AqdQdEk2FcCjf8xKqJBLZAjeca213t5xb2fZrh3PPxcsd6dkflS9QW/jKtl9/3LjBTGs76Wg5F1fUck5EREREREREZJAUEomMseZcIsdxWoFQMyRyXZfbb7+955wLpx7jWLjMwaDErFch70MuTM+t1WpEUTrDZHl5mSSJuWdf+1zHwO3T8PyDEO9QccJKLQ2KLpfg+vYLLkRGxgmmMSb9Z9Xxp1r7BzGXyBiH/DrVRKtnP7bt1x83xsthTFoBmdRXYa1aKqpewVo7yqWJiIiIiIiIiOwq3qgXICLru3EuUb1eJ45joijC8zzuuusuHn/88a5zLl++zPLyMsVikcDE1PHI5XNUa2m4tFpaZWZ6BptYlpeXedGRWeaycM8c3DEDmR36VDi7lLaas8D1dGnM52A2uzPXFxk0YxyccJa4eg3j+Bg3xMY1kqiMtUkrQNqq7PyLWD31v3parjWWn6S+9ATB9D3bev1xYozBCYrEtQUsCUljFScoYuM6SX0JN5wZ9RJFRERERERERHYFVRKJjLFmJRHc2lyikydPAhCYuOd1yqVya3txaYlnz8Ob7oUH9u9cQARQjdKvWgTxWmHAqlrPyYTrmkvkNd93lqRR6n/CLTCOR/7Y6/s+txuriZxgurUdd7Sci6pqOSciIiIiIiIiMigKiUTG2HohUbPl3Hoh0VNPPQVA4KQhUSaTwXPTBKhcLpGstW5aXFwc+Jo3K+wIpGppBzyqDUjUSUomWOdcIrez5Vy0/ZZzANlDr8B4hZ79tYUv0yidH8g1xoXjF2Ct+iqpL5PWHUJcuTzCVYmIiIiIiIiI7C4KiUTG2I3t5pqalUQnTpzA83rLf5qVRP5aJZHBkMunr5VYS6WSDv+p1+pUKuWe83dCV0iULhNLOp9IZFI5/hTG8QEwfjvktY2Vwby+G5I/+g19nyvtsmoiYxxcvwiAtXFrtlMSVYgH9PMUEREREREREdnrFBKJjLFsNosxBujfbs73fU6cONFz3o3t5qC7KqlUare+uj6iaqKM296udARDJYVEMsGMMa15OelcojTcTaIKNokGco38kddinKBnf+XyF4iq1wZyjXHR3XJuqb1dUcs5EREREREREZFBUEgkMsYcx2lVE3VWEjXbzUH/lnMXL16kVCq12s0B5LI5DGngVFpth0SjajmX8SDnw2wWDuThuQfhpcdgPrfxuSLjrLPlnNPVcm77c4nS1yyQPfzKPs8klM59fCDXGBdOMAVrn1tpy7lUpJZzIiIiIiIiIiIDoZBIZMw1QyLXdVut5TYKiQCefvppPGNxjG2dn81mAWhEDer1tBqptLpKFA+mwuFWhB7cuw9um4bpDBzMQz4Ax+z4UkQGyg1n29t+e35Qs13aIBSOvg6M27O/fOkzJLuoFZsxbjqbCLBJgyRK22MmjVWSqDLKpYmIiIiIiIiI7AoKiUTGXGebuGY1UaPRII7TKqE777yz73kPP3GKhSjLahRwpZHjYr1AtmPGUamU3my1FpYWl/q+xk4pN9J1iOwGjl/AuMHadvv9O8iQyM3sIzv/4t4nkjql858c2HXGgdvRci7pbDlXVcs5EREREREREZHtUkgkMuY6Q6J+c4nuuOMOHKf3rfzVJ85wvlZkNfEpJQE165HNt1tfdc4lWlxa7Dq3GsHDV+B3H4NLg7uvvS5robLzxUwiQ9NqOWdcHC8NZ21cxSaDG7qVP/7NffeXLnyCJK4N7Dqj5gTF1nbnXCK1nBMRERERERER2T5v1AsQkZvLdVT/3BgS5XI5wjDk+PHjnD59uuu8C08/BoBnktY+x8/iez6NqEGlUiFJEhzHYWlxiaWq5aNPGp5YgDPLkKxV9uR9OFRg6Fbr6Ywikd3ADWeJypeAdC5RZ5u0znZ02+HnjxLOPUht4a+79tuoROXSZ8gf/aaBXGfUjOPjeHmSqISNa9i4hnFD4toiSVzDccONX0RERERERERERPpSJZHImOvXbg7alUTQv+XclQunqVcrXSFRZB3yhfT1LJZSOa0miqKIRrXEHz0Np5baARHAEwsD+1Zuqjy4AguRkWtVEkFrpg4MtuUcQOH4G/ruXz33cWyye8rznI6Wc3F9sb1dvTqC1YiIiIiIiIiI7B4KiUTG3HqVRNVqtbV911139ZxnbcLFM0/gcUNI1BE6dbacq64ucqxIjycWdmZeUEkhkewijpfF8bJr2zkMBhh8SBRM341fvLtnf1JboHLlCwO91ii5HS3nkvpyaztWyzkRERERERERkW1RSCQy5lzXbVUQrVdJ1C8kgrTlnOckOFgCE+NgyWazOCa9YV0ulbGkCdDi4iL3zPW+xlINrlYG9d2sr1wf/jVEdlKrrZxxMP5aBV9Sxw54XtB61USlsx/D2qTvc5PGuCHGTT//kqjcmu0U167vqoopEREREREREZGdppBIZAI0q4l838d1XaC7kuiOO+7oe97qmb/mublLnAiXOBKsUPRqOMYhu/Z6URy1XqdcLnN7sfdma+DAM4MtfuhLlUSy2+xUy7lw7rl4uaM9+6PyRWoLXxnotUbJ7Wg5l9SXgLRiMq5eG9WSREREREREREQmnkIikQnQ2SKu2XKuXq9j1/rA5XI5jh7tvUl8+uknCRzbNZfoxtcrl8qt7YPuEsUAXnAIvutZ8P99Bfybb4HnHBjot9MlSmC1DpdW4avPwF9ehC+cH971RHaK06wkAhx/qrU96JDIGIf88W/u+9zq2Y8O9Fqj1D2XaKm1HVXVck5EREREREREZKu8US9ARDZ2Y0hULpex1lKv11uh0Z133sn5893pypkzZ6jX6wROTBS3M+F8rnsu0b59+wCwlWv8/Ov3sdaNbkc8U4Ira6ORMh4UgnS7EYPv7tw6RAbNcUMcv0DSWE3nEhkXa+OBh0QA2fkXsXrqfxHXFrr2N5ZPUl96gmD6noFfc6c5XhbjBNiknv4Mkwgcj7h6DWsTjNHvvYiIiIiIiIiI3CrdURGZAM12c9CuJILulnP95hLFcczp06cJTNy13/f91utUa1WiOG0zt7S0jGVnZ5iEHUFQpaPbXVnt52QXcDuriby1uUQ2Iomq652yJcbxyB97fd/ndm01UWMZAJtEPeGYiIiIiIiIiIhsjkIikQnQWUmUyWRa27VarbXdLyQCOHnyJP4NIdGNr1kqpaU8SZKwsryy7fXeikxHPWOtIyTSjCLZDbrmEgWdc4kG/z7LHnoFuLme/bWFr1C58kUaK6fX/ZqUuT795hIBxBW1nBMRERERERER2Qq1mxOZAOuFRBtVEgH8xV/8BS/+pjf3vmYuz8JC+tv3pdUS08X05uvS0iLT0+0bsQ9fgd/8KrztOfCs+e19H/10VhLVOrKs1frgryWy09xwBowBazF+R0gUrQKDfUPZxirE/SuUFh/5jzc/2XgceNFP4Wb2DXRNg2a8HMZ4aTVWfQVsAsYhqlwhmLGYneyVKSIiIiIiIiKyC6iSSGQC+L6P7/tAd7u5zkqiQqHAwYMHe8792te+1tNuDiCTzeA46UdAuVImsWmbucXFxdYx1sKHH4GLq+mf1g7k2+niu+CufRLVIghcmMlA1h/8tUR2mnF8XH8KAMfNYkyaiiaNEnbAb6h01tEW20XaaCizkgbNGNNqOWexrYosmzS6KotERERERERERGRzFBKJTIhmNVEQBK3flu8MiaB/NdHq6iqr16/07DeY1msmSUK1klYgVKu1VoXS167AqbX7rqeW0sfDcKIId8/BvfvgZcfhhUfgeHE41xLZad0t59LACBtj48qIVjTZnKD94RB3BEORWs6JiIiIiIiIiNwyhUQiEyKXS2eNGGMIggDobjcHcOedd/Y99w9+98OAJbaGRtJ+2xf6zCWCtJrIWvjIo9Bs3mRIHw+jmmg6A4UAPAfKmkUku4wTzra3O1vOTUDlzjhy/AKY9HMsqS8D6YdSXB1Sii0iIiIiIiIisotpJpHIhLhxLlGtViNJEi5dutQKeJpB0o3+6BOfInzB22lYB4PlULBKYXqOwvQ+DAaLpVQqMT+fzkhZXFzkqnOoVUUE6W3YZjXRcw4M7dukVIdiuPFxIpPCDWYwxsHa5IaQaAWyQ3wz7VLGOLh+kbi+iLUxSWMVx58iiSrEjZVWez8REREREREREdmYQiKRCXFjSLS0lCY4P/dzP8djjz1203NLK4v8j594S9e+2+9/Pt//E/+BTCakUq1Sb9RpNBr4vs/yygr/+5JdC5C6feRRePY8DGs+fEmVRLLLGMfFCaaJa9cxTohxfWzcIInKWJtgjIp6b5UTTBPXF4G05ZyzFgzFlcsKiUREREREREREboHuTIlMiM4qoTBsl9q84hWvwPf9W3glg+sHvPAb/iYA+Xy7sqFZkXS2WuT8Sm9ABMOdTQRqNye7k9vZcs5rziVKsFF5RCuabOlspzSpTlvOpaKKWs6JiIiIiIiIiNwKhUQiE+LGSqKmr//6r+cDH/gAR44cwWxQ3mOMw/Sh23nop36Tr3vVt/a8bqm0irXwxdWj0DciGu5sIlBIJLuTG861tntazsktM8ZtVQ/ZJK3KgnTOUxLXRrk0EREREREREZGJopBIZEJ0Vg+5rtvaTpKEEydO8MEPfpBXvOIVN32NO1/8Lfyt932E2SN3d72uWfuN/CiOOVef5kpUoPlb+jfqnE00DLV4OK8rMkpOUMQ4aYfXzpAo7qiCkVvjBsXWdiMYYfMAAQAASURBVNIodWwreBMRERERERER2SyFRCITorNKqF/FUCaT4dnPfvbNXoE7Hng+h/KWnLNeuY7hi6tH+0wiuvGo4VUTNWJIhlSlJDIqxjitlnPG8XG8tH2kjavYuD7KpU0s47VbcNq40tpO6gqJREREREREREQ2SyGRyARphkOdIVGSJK3tkydPrnuu6zosnv4qBbeO77TPsWv/A7jmHORKVMCuU0XUPme41UT1GKJEredkd3Ez+1vbTkcVTNxQNdFWGDekNZeoY7aTKolERERERERERDbPG/UCRGTzHMchjuOukMh2lPM89thj654bxzFnn/hyz/7m+RZ43H02BrthSATtaqJnz8MGo5A25VoZFqppOFSNIOOl13jtHYN5fZFR6wmJypcASOrL0PGcbI4xDsbNYOMKNq6BjcG4ColERERERERERG6BKolEJki/SqJmyFOv1zl37lzf84IgAODyhdM06jcMdV/LmBbcwyw5c5sKiJqnDbKaqJFAqQ61KA2JmtfQjCLZLRw3bM3RcdwsxvEBSBqrWJvc7FRZh+NlW9tJVF37s4JNVIYoIiIiIiIiIrIZColEJshGIdGJEycoFAo9591zzz184zd+I0dP3EnU6J5/Ym3abO7p8MFbHjI0yNlEfsenUdRxv7yukEh2ka5qIr/Zcs6q+mWLTEdI1DWXqLE6iuWIiIiIiIiIiEwchUQiE8Rx0res6dN/rVAo8MEPfpDZ2dme54Ig4F3vehfv/dlfJpuf6nounUjkUHXyt9zXzdJuEbddntvebigkkl2qMyRyO+YSJfXtzyVy/AKYLXaRNV56/oRx3M5Kos6QSKGbiIiIiIiIiMhmaCaRyATpFw4lSTtRcRyHRqO3zZLvp22tsp6F6IYnLTgkvLD0UbzcLPPz8wAcOnSQ/fvmN1zTVAi+u+FhG+qqJOoIhmo3rldkgrlBEeOG2LiG4xcwa1PABhFquJl9HHjRT/VU0SRxjYUv/2tavSXX+NP3MH3nW4E0YHIz+7a9hp1mutrNlVvbcX0FfxQLEhERERERERGZMAqJRCZIMyRqVhT1E0W9qYrnpW/10PSW5TTb1WVsmSnHZd7PA3CsEHNwZrsr3jzfgayXVhRNZ+C2GQjXtkV2Ey+zn0bpPBgHx58ibixjkwZJVMbxctt6bTezr2/Y40/dTmPl6a590eo5vMJxjJncomJjHIybwcZViGukQZhRJZGIiIiIiIiIyCZN7p0hkT2oXzhkbxgIdLOQyDcxxnQfb1lnoNAttp7bLt+F+/bDXbNwrAj3zMGJaSgEO7oMkaHrmksUDrbl3HqCmft69tm4QrR6dmjX3CmOmybJFttqOZdEJWyiXpUiIiIiIiIiIhtRSCQyQZqVRJ1t5zrbzcH6IVFsDZXEo5a4LEYZrjRyWAs2aYdETkdFgTPC6gK1mJPdzA3nWtU7jt8REjWGGBJN94ZEALWlx4Z2zZ3S2XLOxmtziawliVbXOUNERERERERERJoUEolMkH4h0Y36hUSRk+Hh8gFOVvexGGVYjDOUkoB4bR5K/4u1N62FUh1OL8FfXISvXt7Wt7GhepJeU2Q3Mo6LG86ubfuYtUqYJKpgk96ZYoMQTN8Npnd4WH3x0aFcbyc5XXOJKu1ttZwTEREREREREdmQZhKJTJBmu7nOkGgz7eYCv/1W90y78qhh3a40xjjt121WEv3iF+Dxa1DpeNn798NzDmzxm9gEa6GRQNB7T1tkV3Az80TVa+l2ME1UqQJpy7l+M4W2y3Ez6Vyi5ZNd++tLT2BtjOkTIE0K43ZWElVb20l9GfKjWJGIiIiIiIiIyORQJZHIBOlXSdQZEllr+4ZEod9+q/sdIVFkHToLiUxH+VAzMKrF3QERwLXy1tZ/K9RyTnazrrlEQbvlXDzUlnP39uyzcZXG6pmhXXMnGMfDOOnwMtvorCRSuzkRERERERERkY0oJBKZIBtVEvULiAACr10l4Jn2MPeGdbvO7+xi1wyM9rd/Sb9loQLJkNvB1TVzXnYxx8vg+IW17VyrkidprGJtcrNTtyycub/v/vri7plLZEmwcQ0Y7s9SRERERERERGS3UEgkMkE6w6Hm9qZCIt9rtZnznfRPB4u1dM8kMr2VRPtzva8XW1is9u4fJIVEstt5mfnWthNMpxs2IWmUhnI9v3jXOnOJJj8k6pxLZKO01NHahCQazs9SRERERERERGS3UEgkMkG2GhJ5nse8v8rRYJl7MgucCBc5Hiyxz6+s326O9UMigCtDbjlXU0gku5ybbbeccztaziVDajnnuCH+1B09++vLT2CTye7v2DmXKI47Ws7VV0axHBERERERERGRieFtfIiIjIvthET7/faN07zToJL4PeebPpVEx6bgRUdgXxbmc7Avl7agmx/SQPgogUYCV0oQumlF0WwWiuFwricyKo5fxDg+Nmng+AUMBoslqS9D/uhQrhnO3Edj+cmufTau0Vg9TVC8ayjX3AndlUSaSyQiIiIiIiIislkKiUQmSHMmEdx6SNQpdOKOkKhjZkefmUTHp+EHvn5by960WgSPXE23n1mFpXS0CPfuU0gku48xBjezn6h8EYyL8QvYxgo2qZNEVRwvM/BrBtP3AX/Qs7+++PhEh0TG8THGw9rohpBoOFVZIiIiIiIiIiK7hdrNiUyQjSqJGo1G3/N83+96HJj+YZJjOkIox/Q9Zpj8jnEpjY7sqjrZnbBE1uVlOlvOTbW2hxVuBMW7wPT+fkht6dGhXG8nmbVqImtjbJJ+FiaN1a7PSBERERERERER6aaQSGSCdIZETVutJGpK1rmB2hkY7RTHgLv2LXaGRHXNJ5Jdys3Mwdr72umcS1QfTkhk3ICgeGfP/sbSkxM/l6hfyzmbRNiOGUUiIiIiIiIiItJNIZHIBOlsN9e53bTZkGi9SqLO6qE+edSO8NaqiaKOkKimkEh2KeP4uMHs2naIcdO+iklUGlpoE0zf27PPJnUaK6eGcr2dYtx2SJTE5fZ2fWUUyxERERERERERmQgKiUQmSL9KoiRppylbqSSySf9KIjOCSiIAf+2ySQLNpamSSHYzL9tuOddVTdQYTrgRzNzfd39t6bGhXG+ndFUSNTrnEikkEhERERERERFZj0IikQkyqEoi11g8k4ZLne3qnD4zj3bavhwcK8LtM/CcA/Dy4/DiIyNZisiOcDvnEvnDbzkXFO/sO5eovjjZIZFxQzBpKWLS0WIuVkgkIiIiIiIiIrIuhUQiE8T0CXE6K4kajUbf83zf79kXOGmgFFvoV0s0qpBoNgP7czCTgZwPWR9cfVLJLuZ4ORwvl277ecxa0BE3VrA2udmpW2Icn6B4V8/++vJJbNL/M2RSOG4GAJs0Wt/LsMI2EREREREREZHdQLdeRSbIRsHNRpVEtcTlciPPuVqRy/U8Z2vTXEr2E+OvvX77I2FUIVGn2nBGsoiMnXY1kWm3nLMxNiqve852BDP39e5M6jRWnh7K9XaK6Ww5F1fTP5MGSVwb1ZJERERERERERMZab78ZERlb/drNdbaL2ygkqluXZ+oFAGIcYgzWQmw8PNvorlRy2tuJhaeuw9Xy2lcl/fPrDsE33jG47+9GNc0ikj3Cy+ynsXoGANefIq5dByCuL+P4hYFfL5juExIBtcXHCabvHfj1dorjZWl+bCRRGcefSrfryzjZ+dEtTERERERERERkTCkkEpkg61X3WGsxxmwYEoWm/bzP2kwiLInx0p5zHS9vOh4Y4F9/Dho3dL6azdz693Ar6gqJZI9wwhmM42OTRivYAEgay8Dgh3IFxTvA8eGG9nL1xUfhtjcO/Ho7xbi51nazkgggaayAQiIRERERERERkR5qNycyQfrNJIL2XKKNQiLfJBiTVh55TjOBse12c/SvJDIG9rW7OLVcGU4nrBZVEsleYYyDm5lLHzgejp8HwMa1obRKS+cS3d2zf9LnEhk3pJl2J1GltT9prIxoRSIiIiIiIiIi400hkcgE6Ww316+qaKOQyBgITZq8eGatLMhCbNye1+wMjAD25+hxbdghkWYSyR7SnksEjl9sbSf15aFcr29bORtRX35qKNfbCcYYnLW5RDaugU0/7xQSiYiIiIiIiIj0p5BIZIKsV0nUnEvUaPSvAPB9v7UdOBFgyTgRRbdGjhKZpLT2os3X7g2h9vUJia5XIUp69w+K2s3JXuKF+9I3H+AGHSFRYzghUThzf9/99cXHhnK9nWLcdtljs5ooiarYuD6qJYmIiIiIiIiIjC3NJBKZIBuFRBtVEgEcC5YxgcUxEJiYhl0hseXu1+xTpdRZSeQYmMvC/ixUGjAVbvlbuimFRLKXGDfADaaJa4sYN4NxA2xcJ2mUsDbGrFX8DYo/dTvGCbBJd3hSX5rwkMjLwlqHPhtXwC8AEDdW8Nx9I1yZiIiIiIiIiMj4UUgkMkHWaze3UUjkuu2by+7aTCKA0OlOYZy113RMb5Hhi47AXTNpRdFsBtwh1iEu1aDagEYCM5l0NlHgwIOHhndNkXHgZvYT1xaBtOVcHF8FLEl9BTecGei1jOPhF++mvvhw1/768lPYuI5xg4Feb6c0281BWknU/PRLGquQUUgkIiIiIiIiItJJ7eZEJsggKok6hSYisR394lqVRL3Hzufgvv1pRdEwAyKAhQpcXIWrZTi3DEtVWK4N95oi48DrmEu0My3n7uvdaSPqyyeHcr2dYNxMa7vZbg40l0hEREREREREpB+FRCITZKshUedMok7BDZVEhvUriXaS13H55syjegzW9j9eZLdw/AKOl2ltm7V/ppP6cut9PkhBv5AIqC89PvBr7RRjnFZQZOMqkP7cFBKJiIiIiIiIiPRSSCQyQbbabu5mlUQ2ad94NjepJNpJfscnU2Mtx7JoRpHsDW6rmsjgBOk8HWtjbFQe+LX8wm0Yp3eoWG3x0YFfayfd2HIOSGc7Jf0/I0VERERERERE9iqFRCITZKNKokaj0fe89UIi3yQYOqoT1l5yHCuJQCGR7A1uR8s5Z8gt54zjEUzf07O/sfI0Np7cHo/GbYdENu5sObc6iuWIiIiIiIiIiIwthUQiE6QzGOq0USWR67p99xsDrq23H6+lROtcZsd0VhJZoBDAXHbdw0V2FTecw5j0Pev47ZAorg9nLlEwc2/vThtP9Fwix8u1tpOG5hKJiIiIiIiIiKynf3mBiIylznZznds3C4k8z1s3XALwbI1mXtw8zoy4kmgqhGfNpxVFJ6bh/v0bnyOyWxjj4GbmiCpXMI6P4+VIojI2rmLjOsYNBnq9YPr+vvtri48Rzj5roNfaKWZtrhPcWEmkkEhEREREREREpJMqiUQmyEbt5vqFRL7vr/t6iU3PrZksZWeKunV7XnsUHAOBm/5Z0wgR2YO6W85NtbbjIYQc/tQJjJvp2V9femzg19opxrgYJw3TbNQOiYZVjSUiIiIiIiIiMqkUEolMkM7qoU4bVRLdqJa4PFLez9fKB7nKflbcOcpOkRppoLTZkKgRw6VVWK1vfOxWaQ6R7EVdIVFHy7lkCCGHMe46c4lOkcTVgV9vpzRbzlksdu37sFEZa5ObnSYiIiIiIiIisqeo3ZzIBOkMb/oFRpsNiTyTEK1VDbk2PcdgiJuVRE7/kOh6FX77YbhWhqsVWFy7f/z/Pg9efdutfS+bVVNIJHuQ44a4wRRxfQXHy2EcH5s0SBorWJsMvCVkMH0ftYWvdO+0MY2lJwnnnjPQa+0U42WhvghAElVw3QzWJiSNVdygePOTRURERERERET2CFUSiUyQ9Sp8mpVEjUaj57l+IZFrLJ5J0xeX9jmNpHs2Uc9rGfj8eXjyejsgArha3tz6t0IhkexV3dVEzZZzlqSxOvBrBTP39d1fW3p84NfaKcbNtraTSHOJRERERERERET6UUgkMkHWqyRKkrR90mYriQBCJ01fjE0wNgFjaKxVEjnrhESFAEK3d/+1Su++QbE2bWsnste4mfn2djDd2h5Gyzm/cKIrVGmqLz468GvtFMdrz1mysUIiEREREREREZF+FBKJTJD1ZhI13VJIZNJjbWJxbZrCxBisBdYJiYyB/bne/VeGWEkEqiaSvcnxpzBusLZdwJC+L5PGMOYSOQTT9/bsb6ycJokmcy6RcXyMk85Zs12VRIOvxBIRERERERERmVQKiUQmSGclUed2s93crYREBbfOnF9mNrnCvug8+5PLnAiWMGb9SiLoHxJdG3JIVFdIJHuQMQav2XLOODh+ASCdTRQNvnwvmOkNiSChvvzEwK+1U5rVUdbG2KQGQFJfaX1mioiIiIiIiIjsdf3vHovIWOqsJNpsSOT7ft/XmvZqTFPjcrxALYkokW0XEN0kJDpcgCsl2JeD+Vz65/7eLlUDVY/TlnO1GLIeuIq3ZY9wM/M0ShcAcIJp4rVWaUljGccb7BsvnLmffo3Y6ouPkZl77kCvtVMcL9uqvLJRFROEaWAUlTF+fsSrExEREREREREZPYVEIhNkkJVEXcdQ7553ZNZPYb7zWenXsK3W4eIKNBK4Wm5XMH39YZgdciglMi7ccBZjHKxNcIIilNL9SX0ZsgcHei0vfwzj5bBRd2ngJM8lMh1BWhJVcNZmOyWNFRyFRCIiIiIiIiIiajcnMkmGERIlSYJn6zdcaBuLHKBSI60i6pxJpNZzspcYx8MJZ9e2fYybASCJytikMdhrrTeXaPUMSTTknpJD4rjtkKgz/GpWZImIiIiIiIiI7HUKiUQmyFbazW0UEllr8WwD42yukmin+B1LaCTt7ZpCItljvMx8a9tdq4SBdLbOoIUz9/XZa6kvTeZcIuMGYFwAkrg9x2kYPzsRERERERERkUk0+jvBIrJpw6gkstbikODRTl9uMpJox3gdn06RQiLZw9zMvta2ExRb2/HarJ1BCqb7hURQX3p84NfaKc3ZTTaJWtVXiSqJREREREREREQAhUQiE2VYIRFAYNrnmjGoJHIdaBY3NTqCoVrvtyiyqzleFscvrG3nMM3KmMYK1iY3O/WWefmjGK/Qs782yXOJulrOpdVENmmQRNVRLUlEREREREREZGyM/k6wiGzaRu3mGo3eGSW+76/7es3zAHza545DJRHAVAjFEKZDuH0G7tsPx4obniay63iZ/a3tVjWRTUgapYFexxiHcKZ3LlG0enbg19opzUoiuKHlnKqJREREREREREQUEolMkkFXEnWGRAHjVUkEcMcM3DkLR6bS7eNFmMmMelUiO8/tCIlcv52UJkNpOdcbEoGlvjyhc4m83koiGM7PTkRERERERERk0ozHnWAR2ZT1QqKmWw2JksRSMXlWnFlWnSKX6gXO1Ypcq69ffTQqdc0ikj3MCaYxjr+2PdXan9SHEBLN3N93f33xsYFfaycYJ4S14LurkqiuSiKR/z97dx5nV17X+f91trvWvldqSdJJdzrpBnpvpEWgAQV+jCC2uODMgAuCKCOtICKKKLuCjYriIDwGUAFZRmCUvcEO3emk9+7se+173X056/f3x6ncqkrdSipJpdbP8/HoR586y73fqlTdSs77fj4fIYQQQgghhBDiwsNKhBBrymLt5oIgnEty6SFRwJS5BaXpRLQEqPBcN7h4flx0YaoIkyWYLIb/vfQaaEks+dO5JI4P8bWXXQmxIjRNw4i14BVHQDPQrRoCN48KHAK/jG4sX4mdmeisPP5c63UukaZp6EacwCugfAeUD5qBL+3mhBBCCCGEEEIIISQkEmI9uVAlURAE+P7CcpsLhUSaBqZycbUolhbgogANV104JHpqDP7mwML9N7RevZCo7EP91XloIdYF81xIBBiRukqIEzhZ9PjyhUSaphOp30V58rF5+73CEIFbQLeSy/ZcK0Uz4+CFM5UCr4Ru1aB8m8C30Y3oKq9OCCGEEEIIIYQQYvVIuzkh1pFqLeZg8YAILl5JZCknfGzA0sKKJOcilURNi9yPnixe8LIrIu3mxGZnxJrCZBfQI3PmEl2VlnO7quxVOJn12XJubqVVMG8uUb7a6UIIIYQQQgghhBCbhoREQqwjc9vNzd0GcF236jWWdeEebSYzIZGuVUIi0HAvEMo0L1ItNFmqvn852As76QmxqWi6hRFpmNmOos1UwAReARUs7w9IpL5aSAR2+viyPs9K0cx4ZVvNm0u0/AGbEEIIIYQQQgghxHoiIZEQ60y1aiKlVNV5RHDxSiJzppIIIK67xDWXxtiFy3YSVvjf+aSSSIiry4i1VLZ1a0410TLP1wnnEtUt2O9k1ulcIiNGWC8JgTf7QhV4UkkkhBBCCCGEEEKIzU1CIiHWmXMh0dywKAiCywqJlFLEggId7hl2an3sik/SHimwJamwjAuvoyW+cF+pejHTsrAlJBICc05IZFzFlnOaplVtOecVhvCd5Q2kVoKm6TNBESjfBhVWTQbr8HMRQgghhBBCCCGEWE6L3z0WQqxJuq4TBMGCdnOXGxIZ+BjKR9MgqodJzGKzj+Z6yTVhC7jmBLQmoDkO0avwiuIF4PphldJwLqwoipvQXrP8zyXEWqdbSXQzQeAV0a0kmmaglI/v5jCVWtLP7lJF6q+jPPHIgv1O5jjx1luX7XlWim7G8WdazQV+ufJ1VIGLpl+4LacQQgghhBBCCCHERiUhkRDrzHK2m1NKVbZ1XSeieYs+x/nu6rnoKcvi2FQYEln6uWZRYSglIZHYrIxYC0G+H9DQI7X4dhqUj/KKaFZy2Z4n2nB91f1O5ti6DIk0Mw52uK28EpjhcLXAzWNEG1dxZUIIIYQQQgghhBCrR9rNCbHOVGs3txwhkaZpWFqArik0ffmqEa6UOfMq5QVwbrnSek5sZuYic4l8d3lbzhnxdvRI/YL9Tnp9ziXSjdkemfPmEi3zPCchhBBCCCGEEEKI9URCIiHWmXNt5s4PiVy3+kAgy1q8jdL5IZGmQUTz0Vg7IZE18yqlCIMiCFvOCbFZ6dEGND0Mfw2rtrL/qswlqq8yl6g4gr/Mz7USNHM2JFIzbeeAdTljSQghhBBCCCGEEGK5SEgkxDpzNSuJACK6t6Yqiaw5r1LnQiKpJBKbmabpGNGm8APdRJ9pMaf8Msq3l/W5og0LQyIIW86tN5qmoxlRAJRXJoyepZJICCGEEEIIIYQQm5uEREKsM8sZEgVBsOBxo2utksiY3XZnlquUVBOJzc2Y13JutppouSt8IouFROnjy/o8K+VcyzmFIvDLAAReARXIC4oQQgghhBBCCCE2p8XvHgsh1qTlDImqPW50jVUS1UXDuUSWDntaYFsjRAxYQ0sUYsUZsebKth6pg+IoAIGbhXjrMj5PG3qkgcBJz9tvr9O5RJoZh5nPRXklMOKgFIFXwIjUXfhiIYQQQgghhBBCiA1IKomEWGcWm0m0XJVEFj6Op5EpQ255O1ddloQFLQmoj0HUhJgpAZEQuhHFiNTPbMfRjHD2WOAWUGr5qmI0TSPacP2C/X5pFN9OL9vzrBR9zlyiwJudSxS462/GkhBCCCGEEEIIIcRykJBIiHVmsUoi13Wrnm9Z1pIed1y1cKzUwim7iZNZkzNpGCtc+voCdfFzLpe0mBNi1vyWc+eqYBSBm1/W54nUX1d1v5NZfy3nNGM2JFL+nJDIkblEQgghhBBCCCGE2Jyk3ZwQ68zVqiTyMHECAx0wZkp1LhbK9Gfg4DhMlmCqCBNFmCrBX/90WAG03GwJiYSoMOItkD0Vbkfq8MtTAAROtlJltBwiVSqJAJz0MeJtdyzb86wETTfRdAsVuCivXNkfuBISCSGEEEIIIYQQYnOSkEiIdaZaJRFwxTOJorrPuSKgqKHhEYZEgVq8vdvJafhqldEkU0VILN896goJiYSYZVi16GaMwCujW7Vo6CgCAieLUmrBa8RlP0+sBT3aRGBPz9tvZ9bvXCLluCjlowIbTY8SuPll/ZoJIYQQQgghhBBCrBfSbk6IdWbuTcxz20EQXHElUUSfvT46pwrIrv6wQDgrqJrJUvX9V+pCaxFiM5ptOaehR2oAUMqb10rtSmmaRrR+14L9fmkc304t2/OsFH1uyzk3/DopFaC8y+ivKYQQQgghhBBCCLHOSUgkxDpzrt3c+S4nJFJqdoBQVJst04nOueRC1TuLhkTFxa+5EjKTSIj55s0litRVtgMnu6zPE2lYGBJB2HJuvdHM2ReuYE6Y5kvLOSGEEEIIIYQQQmxCEhIJsc7MrSQ6FxhdbiXRvJBI90gaDo1mid3NsL0Brm+Buujia2mOV99/tUKiQIEXXPw8ITYLI9KIphkA6NZsSOSvUEhkZ9ZfSKSbsy9cgTcbEgWOhERCCCGEEEIIIYTYfGQmkRDrTLWZGUopXNeter5lWVX3n7vunKge0BELW0dd1wyFJYQxURPqIpBzoDEWVha1JOCaxotfe7lsD8zI1Xt8IdYTTTcwoo145Uk03UI34wReCeWXUIGLpi/+838pzFgLRrQZ356at39dVhLpFppmhm35vNlEO5BKIiGEEEIIIYQQQmxCEhIJsc7MbTen6zq+H/Zgu9JKornhUzKy9CLDP/0pqI2CeRXrEgsO5B1wA3h8BGJm2AbvJ7rBkHpIsckZ8Ra88iQQtpw7Vx3jO1nMWPOyPU+k4XpKYw/O2+eXJ/DL0xixpmV7npWgmTGUm0cpvxKmBW4OpVTVIF4IIYQQQgghhBBio5Lbq0KsM9VuYC5Hu7m5j2saGrElRsiN8asbEAEUXBjJh23sRguQsaHsXXhekhCbhRFrrWzPbTm3/HOJrqu6fz22nJs7l0jNhGoq8FBzZhQJIYQQQgghhBBCbAYSEgmxzsytJJob7CxnSKTrOvHl6VK1LKw5r1RzZxI5EhIJgW5EMSK14baZQNPDn/nAy6PU8g3xitZXn0u0HlvO6cacuUT+3JZz+dVYjhBCCCGEEEIIIcSqkZBIiHVmbphzblsptawhkaZpJNdQSDS3UmluMCSVREKEjFhLZbtSTaSCZQ09jFjzvKqlc5z00WV7jpWimbMh0blKIoDAkblEQgghhBBCCCGE2FxkJpEQ68ylhES6rmMYxqKPVS0k0jQNTdNIrKGQyJrzKcytJLKr52JCbDpGrBWyZ8LtSD2+PQ1A4GYxInUXunRJ/PIUgZvHTHbhlyfmH7OnKE09hRlpWHCdbtVgLONcpOWi6RHQ9DBIm9NiLnCXt0WfEEIIIYQQQgghxFonIZEQ68xiIZHrugvOvVAVEYSzjM4518bu3GNebkh0eAL+9SD8yo2wZ2HRwWU5V0mkaaABNRGImuF/QgjQrVo0I4LyHXQriYaGQoVziZJX9th+eYrxR94NavFUNn3o76of0Ezabn/fmguKNE1DN+IEXgHluxB4oJv4rlQSCSGEEEIIIYQQYnORW6xCrDPVZhItVkl0sZBornOPde7xLyckUgq+egRG8uH/d7eEwc6VMnW4oTX8f00Untt95Y8pxEaiaRpmrAW3MAyagWbVoNwcKnAJvBL6nPZqlypw8xcMiC5IeQRufs2FRDDTcs4rABD4JXS9FuU7BL6NbkRXeXVCCCGEEEIIIYQQK0NmEgmxzlxqu7kLmVtJdO6xPGUwVYTJAgxl4VQKTqeWtrZDE3A2E26fzYQfLxfLCAMnR+YQCVHV3LlEc1vMSQu16uYGZ8G8uUTy9RJCCCGEEEIIIcTmISGREOtMtZAIqNpuzveXnqice6xRt5YnRuH4NGQdyNmQd8IqoQtRCr52NGwHB+H//+/Ri193qVwfgmV+TCE2AiPahKaFv9b1uSGRhB5VacZsSKTmzSXKr8ZyhBBCCCGEEEIIIVaFtJsTYp05Vx00NTXF8PAwhULYLimTySw417ZtTp06NW9fQ0MDzc1h66dqlUQxY3Zf1ADbC0MZN4CIUX1N3zgOPzgN+Tk5lWK2mujGtkv+NC/I8SEmr15CzKPpJnq0Eb88haZH0IwYyi8TeEVU4KHp8kMzl2ZECeNsNb+SSCqvhBBCCCGEEEIIsYnIHSMh1plzYc5f/uVfcvjw4QueGwQBb3vb2+btu+GGG/jgBz8IhG3qzn/cuDm7L2oCdrhte4uHRI43PyCqPCZhNdENrcszm+gc25OQSIhqzFgLfnkKCFvOeaUyEAYfRrRpNZe25miajm7GCLwSyrdB+aAZBG4OFfho+iIveEIIIYQQQgghhBAbiLSbE2KdOVdJ9NM//dOY5tKTEk3TsCyLl770pZV91UIiUzm4Xpj4ROfcI7Uv0LnOCarvn1tNtJzmrsULIGMv7+MLsV4ZsebKtm7NbTmXW43lrHmakahsB1658v/iyAOUp57GK46igoXz3oQQQgghhBBCCCE2CnkvvhDrzLn2cnfffTemafKZz3yGVCo1L/A5n67rdHZ28kd/9Ef09vZW9lcLiXCLHHzmINdccw2xeD1RExLW/MBoLqXg4Pji670a1USTRWhJgK7ByWkYykJPPexoBEOib7GJ6WYC3UoSuAV0K4mmGSjl47tZzFVqOafU2g1ZNDNeqZZUfgmsZLitfLzSOF5pHE3TMaJNGPE2zFgLmhFZxRULIYQQQgghhBBCLC+5nSrEOpLNZhkcHATA8zySySS/8Ru/wZ49ey543c0338x99903LyACiEajle2TJ0/iui6GpmjRprH7HqbXPsT1zQFb66E2ev6jhg5NwFhh8ee+GtVEwzk4MAQDGRjMhs/Rn4F9gzBduujlQmxoZqy1sq1HG8MNFeDb06uynumDf0uu75v4a7CaSTeTlW23MISTPY1vT6GC2f6ZSgV45Uns1GEKo3spTT6BWxgk8KWEUQghhBBCCCGEEOufhERCrCNHjhypbA8PD+P7PpFIhN27d1/wurNnz1ba1M3V2tpaqSDKZDIcPHiQdDpNi1Wk1nAY6j/N6aNPUypXT16UCquELlYgdK6a6ALFTpcsa8PXj4WBUTDzuGUPHh8JAyMhNisz0TG7HW+pbPvlqQtWHF4tyiuQ7/sG4/vfQfr453ALwyu+hsXoZgw9Mqctn5vDzQ9ipw7jZE/hlyfnBUYohV+ewk4dpTiyl9LEo7j5/kqrOiGEEEIIIYQQQoj1RkIiIdaJiYkJxsfDvm62bTM2NgaEbeKmp6cxjMWHrE9NTfGFL3xhwf6amhquu+46LMsCwHVdjh8/Tn9/P0EQDhoKShkOHTzExMTCUqBDE2GV0MVuO1+NaqKxfBgKjRfg6BTknXC/roWt6ITYrHSrBiPaBICmRzGsWgBU4BC42dVbmPIoje5l8rH3MP3MfdjTh1YltDqfVbMVM9GBps9vIxe4edzCUBgYZU7glSZQgTPvHN9OY6ePUxz9MaXxAzi5swRecSWXL4QQQgghhBBCCHFFJCQSYh1QSnH48OHKx4ODg5Wbqx0dHZw8eRLf99F1vWrFEMDXvva1eY9xTn19PTfeeCMNDQ2VfaOjoxw+fJhSqUTCcAmCgDNnznDixHFcz51Z09KqiM5Z7moiXZ+dceR44WyigQz01oczlITYzKyansq2Ma+aaHI1lrOAnTrE9MH7mHzszyiO7J1frbPCNE3HjLcTbdxNpP5azHgbmjG/v2bgFfGKw9ipI9jpY3ilMdR57eZ8J4uTOUlx9CGKYw/jZE8TuPmV/FSEEEIIIYQQQgghLpmEREKsA0NDQ2SzYQVAPp9namoKANM0aW5urswp6uzs5KMf/Shbt25d8BhBEPDXf/3XFIsL3+VuWRbXXXcdvb29lfZzxWKRgwcPkp8cqpyXSqU5ePAg2Wx2yVVE55xfTVS6wln27UnY1QzJOW/+L3kwnIWJC8xIEmIzMGIt6GYcAN2qq4QegZtfU63RvOIwmROfY3z/H5I7+w18ZxUrnQDdTGAmOok2XE+kfhdmvB3NiM07R/llvOIodvoodvooXnF0QfVQ4OZxsqcpjj1McWwfTubUqn9uQgghhBBCCCGEENVISCTEGuf7PkePHq18PDAwUNnesmULQRDQ29vLi1/8Yu677z527NjBvffei2maCx5rbGyMT3/604s+V0dHBzfccAPxeHhzWSnFSP9JRoaH8Pww1XEdlyNHjvKlp220JUdEoXPVRNky/MUD8NUjV1ZZFDNhZyN01YGhQ08dOAE8NQbPjIPjX/5jC7GeaZqGmeyufGzGmivbvr02qonmCtwc+f5vMr7/D0kf+z+4haGLX3SV6WYMM9FBtGEXkYbrMROdleDtHOXbeKUxnMwJ7PQR3OJwlcCogJM7Q2n8AMXRB7EzJ/CdzJpotSeEEEIIIYQQQgix8C6yEGJNOXPmDKVSCYB0Ok0ulwMgGo3S1taGruvcd99989rMbd++nde97nV89rOfXfB43/ve97j99tt57nOfW/X5EokEe/bsYXBwkLGxMTTAyU3QX7Zp72gnmUgSoJGyddSSm82FFDBdgr99BMYK8J8nw4/fcBOYlxlZaxq0JqApFgZF54zlw8fe1QwdNfOvSZWgITbbrk6IjchKbsHNnkYpHyPahFcYRRHg2ynMeAeavrS/AuhWDWgmqMso/9NMmm78X5QnH6U4tg/Om+mzgPIojT1IaexBIg17SHa/hGjjDWja6r6nRTei6PE2iLehfAffyRA4GQJvtmxR+Q5+aQK/NIGmW+iReoxIffj1mxF4JYJcH26uD82IYsbbMONt6JGGShWnEEIIIYQQQgghxEqSkEiINcxxHE6cOAGEVT39/f2VYz09PZVgqNocole/+tU88sgjVecQfeITn2DXrl00NjZWfV7DMNi6dSt1dXWcOXOGiCqT8xMMDQ3R2NBIc0szr2k6RCkw0XWdzs5OGhuqP9ZcAfC1I3B4TiHDw0OQteG3b4P4FcwSMqrcQ3Z9ODgOo3m4viWsPEqX4bERqI/Bnpb57eqE2Eg03cJMtOMWhkEz0GON+OUpUOeCotYlPY4Ra6bt9vdd1nwd3arBiDUTbbye2m2vpjjyXxSGf0jgZC56rZM+jJM+jJnoJNn1EuJtz0UzVv8HVjMi4dcu3ooK3NnAaM7XRwUufnkSvzyJppvoVj1G9FxgFIZByrdx8wO4+YHwzyreihFvx4g2rnooJoQQQgghhBBCiM1DU9LvZEN4/PHHufXWW3nssce45ZZbVns5YpkcPHiQM2fOADA+Ps7Zs2cBqKmpYc+ePRe9fmxsjLe+9a2VSqS5br/9dt797ndf9N3rjuPw9OkxTpab8bQIOgF1kYDOjg4ikdnh7k1NTWzbvg3TWDx7/udn4Idnqx97Xjf8+s0X/ZQum6HDjkYYyMzOQ9I0uKYBtjaALm/iFxuQ7+Yoje0Hwlk6dvoYAJoeIdJw/apUr6jAozTxCIWh7+Pl+y9+wQzdqiHR+QISW16EEam/iiu8PCrwCJwMvpMlcHNUm9imacZshVGkFqpUY2q6hRFrwYy3YcSaJTASQlwW+beBEEIIIYQQYqnkzoMQa1ShUKiEQr7vMzQ0O6Ojp6dnSY/R3t7OG9/4xqrHHnnkEb773e9e8PpRp4aBoAOj6zZoupai0UhZT2LbNv39/WSys9UA09PTHDx4sNIOr5odjWBUuSfdEod7di/pU7psfgD/dRaeHgd7ZlaRUnAqBY8NX9lsJCHWKsOqxYiGVX6aEUO3agFQgTMTZKw8TTdJtP8ELTe/m6Zn/wHR5udQLSw5X+Dmyff/B+P730n62Gdw8wMXvWYlabqJEWsmUredaOMerJpe9Eg9zAl5lPLx7Wmc3Bns6UO4+f6wqkoFs+cELl5xhPLUUxRHHqA8/QxecQwVyJA1IYQQQgghhBBCLD9pNyfEGnXkyJHKYPORkRFc1wWgsbGR2traJT/O3XffzYEDB9i3b9+CY5/+9Kd51rOexZYtW6peWwwsir6FqUNdTYJINEJ6ehrlQ6AUY2NjFPIF2tvbMQwDx3Y4evQInVu20LWla0GVwk90Q30UPvEolGeqeWoseNtzw/ZvV1PJhfFiGAYdnQznFLUlwmqitqTMJxIbl1XTg2+nADBjLTgz4ZBfnsSI1K3aujRNI9qwi2jDLrzSGIWhH1AafRC1pLlF+yiN7SPScD3JrpcSbbpxTVXcaLqJEW3EiDaiVEDgZMMqIzdbCYTCwCiFb6fQ0NEjNRiRBvRIHWhGeE7g4RXH8IpjaJqOEWvGiLdhxlrQ9CvozymEEEIIIYQQQggxY+3cURFCVExPTzMyMgKE7d5GR0eB8KbqUquIztE0jbe85S00NDQsOFYul7nvvvvw/ervUE/obmU7qntYVoSW1jZq6poq+/OFPH19fRSLRSAMYYaHhjly5Ai2bS94zD2t8IfPC8MiS4ffvSMMbK42X4XPd26NIzk4Ph1WNvWuvc5VQiwbI9aKboYprB6pq8z1CdwcgV9ezaVVmPF26nf+Cm13foTa7a9BjzQs6TonfZTUob9l4tH3UBj+Ecpf+Jqz2jRNx4g2YNVuJdp4A1bt9rC6ayYIAlAE+E4WJ98fVhhlT+PbUxB4s+eoAK80gT19iOLIXsqTT+AWhlD+RUI1IYQQQgghhBBCiAuQkEiINejw4cOV7aGhIYIgfOd5W1sbsdill9zU1dXx1re+teqxo0eP8tWvfrXqsbkhUUQPgyRN16lv6WRL5xZ0PXwJ8XyPwaFBJqcmCWbeJZ/P5zl48CBTU1MLHre3Hv74J+F3boedTQsOXxU1Ebi+BVqTs/vKHhScsOVcIO3mxAalaRpmoqvysRFtqWz75YU/n6tJt5LU9Lyctjs+SMP1v4FVs3VJ1/mlUbIn/4Wx/X9I9sz/xbfTV3ehl0nTdIxIHVZNb9iSrvYajGgzmjZb2K1Q+G4ONz9IOXUIJ3sKvzyFCmZfj5UK8MpT2KkjFEb3Upp4HDc/SLAGQzIhhBBCCCGEEEKsbRISCbHGjIyMkEqFraFKpRKTk5MAGIaxaFu4pbjtttt42cteVvXYF77wBU6ePLlgf3xuJZE2W23kKYOamhq2bd1GIp6o7J+enmZwYBDHDd/Z7vs+p06d4tTpUwuqlZoTcGPbZX86l0XXoKsWrm2CmBm2m4tZcDYNDw9Cem0UVQix7KxkV6UdmxlrQpv59e/b0yi19mbdaLpJvO1Omm/+Y5qf83aizTexlLlFyitQGPhPxg+8k/TRT+Pm+6/6Wi9XGBjVYtV0E2ncQ6RuB0aVNnKBm8ctDGKnDuNkT+KXJ+YFRiiFb09jp49SHNlLaeLRcNaRJy9oQgghhBBCCCGEuDgJiYRYQ4Ig4MiRI5WPBwYGKnOJOjs7sawrm0Hxa7/2a3R2di7Y7/s+H/vYxxa0h7P0gLjuUmeU6YlmaLfy9EQyNJjhzUfTNOnq7qKluQVt5gZu2S7T399PNputPM7U5BQHDx4kn89f1roHMuAu433sZASua4b2OW3uii48OgzHJsEL5p+fd8BZe/fRhVgyzYhgJjrOfYAebQi3VYBfnl61dV2MpmlE6q+j6Ya30Hr7+0hsuRtNj178QuVTGn+Yycf/gqmn/ory1JMoFVz8ulWiaRq6VYOV7CLSsJtI3U6MWCuaHpl3XuAWcAvDYWCUOYFXGkcF81+3fTuNnT5OcfTHlMYP4OTOEnjFlfx0hBBCCCGEEEIIsY5ISCTEGtLX10ehUAAgm82STqcBsCyL9vb2K378WCzGvffeW2kTN9fg4CCf+9znFuzfGZ9mayxDZyRPg1nG0Ob3ZdPQaGpqorunG8sMQ6wgCBgdG2VkdKRSQWTbNkeOHGZ4eLgSfC3FYBY+/BD89f4wyFkuuhb+d76BbFhVNDVzTzVQ8PQY7BuE0cvLuIRYE8xkd2XbiM9pOWdPXdLP5Gox423U7/xl2p77EWq334MeXVqvSidzjNShTzDx6J9QGP7hmm/JFgZGSazkFqKNu4nUX4cZb0Mz5odjgVfEK45gp45ip4/hlUZR582Y8p0sTuYkxdGHKI49jJM9TeDKC5kQQgghhBBCCCFmSUgkxBrhui7Hjx8HQClFf/9sm6Tu7m4Mw1js0kuya9cuXvva11Y99s1vfpMnnnhi0Wvnzig6XzwWZ+vWrdTX1Vf25XI5+vr7KJVKACgVhlFHjh7Bdi5+o3a6BPfth5IHx6bggw+G+662sgdPjMLBcTgxFYZTrh9+/ORoeFyI9caI1GHMVBDpRhzdCkvplG+vq+BANxPU9PwMbbe/n4brfxOrdtuSrvNL42RP/ivj+99B9sxX8e21W0E1l27GMROdRBuuJ9KwCzPRgWbMn02n/DJecQw7fQw7fRSvOLqgeihw8zjZ0xTHHqY4+hBO5hS+k0UIIYQQQgghhBCbm4REQqwRJ0+exHHCWT7T09MUi+ENvkQiQUtLy4UuvWSvfe1r2blzZ9VjH//4x8nlclWPxS8QEgHouk57ezudHR2VaiXP8xgcHGRyahJFWK2Qz+U5ePAgU9NTiz5W0Q2rh1Jz3hg/nIMP/DisLloJZ1Lw7VPzZxVNFsOqotzaLkYQoior2VPZNmNzqonKk6uxnCsSzi26g+ab3kXzc/6QWMstLG1uUZHCwLcZP/AuUkc+hZM7e9XXulx0I4YZbyfasItIw/WYiU50MzHvHOXbeKUxnMwJ7PQR3OLwwsDIK+LkzlAaP0Bx9EHs9HF8O70uKsqEEEIIIYQQQgixvCQkEmINKJVKnD59GghbtQ0MDFSO9fT0oGkXv/F5KUzT5N577yUSiSw4Nj09zSc/+cmq1yWMpfV7q62tY2vvVuKx8N3uCsX09DSDAwO4bvgYvudz6uQpTp8+XWlJN9ennwhDofOlyvCDM0taxhVRKmw95/pwNh0GRufmEiUsqFn4pRNizTPirZW2ZXqkHs2YaRHpZtd8G7bFhHOLdtK458203v5+kl0vWdCarSrlU544wNQT72fqyY9Qnnx8Tc8tOp9uRDHjbUTqryXasBszsQXdTM47R/kOfmkiDIxSh3ELQwuqxgKvhJvvpzTxKMXRH2Onj+KXpyUwEkIIIYQQQgghNgkJiYRYA44ePUoQhDcnx8bGKhVFdXV11NfXX+jSy9bd3c0b3vCGqsf27t3Lf/3Xfy3YH9U8NG1pNw4ty6K7p4eW5ha0mXf3l8pl+vr7yOVmS4EmJyc5dOgg+cL8G5c/dz00zu+oBMD1zfArNy5pCVfEV2DN6fCXscOWd9Ml2NMCy5zbCbEiNE3HSnZVPjai67ua6HxmvJW6Hb9I250fofaaX8CINi/pOid7gtThf2DikXdTGPoBwXmzfdY6zYhgxluJ1O8k2rgHM9ldaSd4jgpc/PIkTvYU9vRB3PwAgZsFZl/TlW/j5gcpTT5OceQB7NRhvPLkugrPhBBCCCGEEEIIcWkkJBJilWWzWQYHB4FwLtHw8HDlWG9v71V97le84hXcfPPNVY998pOfZGJiYt4+Xbt4y7m5NDSampro7unGMmcqFoKAkdFRRkZHKsFYuWxz5PBhhkeGK+9e766Dd/0kdNXOPl5XLbzl9vnhzdVi6rC9AbY2hNsAfgC2B8enobT0L4MQa4qZ7ELTwm9qM9pUCXF9O4VSC6v61iPdTFDT/dO03vF+Gnb/FlbdjiVd55cnyJ76IuMPv4Ps6S/jlxdviblWabqFGWsmUreDaOMNWMkedKuOua34lPLx7Wmc7Bns6UO4+X4CJwtzwiAVuLiFYcqTT1Ic2Ut5+hBeaQIVbIzvESGEEEIIIYQQQoQkJBJilR0+fLiyPTIyUmm91tLSQiKRWOyyZaFpGm9961upra1dcKxQKPDxj3+8EuSck7iEkOiceCzO1q1b5z1PLpejr6+PUrkEhO3dBgcGOXbsWKWSqikO77wrrB5qjMHv3Rm2eltJjTG4vgUa4xAzob0GUqVwLlF/Jly3EOuJbkQx4u0zH5jo0cZwW/n4dnrV1nU1aJpBvPU2Wm56J803vZNY620saW6RX6Iw+N2ZuUX/Gye7Aj0urwJNNzFiTUTqthNtugGrphc9Ug/a7F//wsAohZM7Fxj1EdhpmBMYqsDFK45QnnqK4sgDlKefwSuOoQJvFT4rIYQQQgghhBBCLCcJiYRYRePj45VqnXK5zNjYGAC6rtPd3b0ia2hubua3f/u3qx57+umn+eY3vzlvX1wPbwoqBZ5aes81Xdfp7Oiks6MDXQ9felzPZXBgkOnpadRMy6NsNsszB58hlUoBYSj0e3fCHz4vDI1Wg6nD1nq4timspgIIFByfgkeHIe/MPz9QYXs6IdYqq6ansm3EZluybYSWc4uJ1O2gcfdv0XrHB0l2/zSasZQXlIDyxCNMPfkBJp/8MKWJx9Zt6zVNMzCijURqt4UVRjVbMSIN8wMjAnw7jZPvCwOj3Bl8OzU/MFI+XnGM8vQzYWA09RRucQQVSHmlEEIIIYQQQgixHpmrvQAhNiul1LwqosHBwUqrtY6ODiKRyIqt5a677uJFL3oRP/zhDxcc+9znPsfNN99Me/d2ioFFxosx4tTgKIOY7tFuFS7puWpr64jF4oyOjlAql1EoJqcmKRQLdLR3YFkWvudz4sQJ2tpa6e3txTIMWpMXf+yrzagSq2ds2D8Utqbb1hCGSGfScCYFvfVwTeNsuzoh1gojUocRqcd3MuhmAt1KErgFlF8mcHPo1sLqwo3CjDVTd80vUNP7SkqjD1IY+j6+ffG2cm72JOnsSYxYC8ktLybecRe6uUrJ9RXSNB0j2oARbcBUAYGbJ3Ay+E6mEggpFL6TxXeyeGjoVg16tB7Dqgc9/OujUgFeaQKvNIGtaRjRJsx4G2asFc1Yud9hQgghhBBCCCGEuHxy61KIVTIwMEAulwMgn88zPT0NgGmadHZ2rvh63vjGN9La2rpgv+u6fPSjH+VsMc6gXU/Oj+IpHYWGE1xezmxZFt09PTQ1zc5DKZVK9PX3kcvnKueNj09w8NAhisXikh/74UGYXPrpy0IpOJ0Kw6KhHJwNi6Doz4TrmVrh9QixFHOricxoS2Xb28DVRHPpZpxk90toveMDNOx+E1bdziVd55cnyZ7+EuP7/5DsqX/DW4dzi+bSNB0jUodV00O08QYidddgxJrRtNnXd4XCd3O4+UHKqUM42VP45an51UNK4ZensFNHKIzupTTxGG5+gMCXskohhBBCCCGEEGItk5BIiFXg+z7Hjh2rfNzf31/Z7urqwjCMFV9TMpnk937v99C0hS3kzpw5ww++/E+Vj6N6+E5zHw1XXd7LiIZGS3ML3d3dmGZ4MzIIAkZGRhgbG6vMQiqXyhw6fIjR0dFKpdViHh+Bf3oCPvDjMKBZaXkbvnEUBnNhyzmAsgdPjIaVRUKsJUa8rVLtoUfr0fRw4FfgZFGb6Ma+punEW2+l5aY/pPmmdxFrvZ2l/PVI+SUKQ99j4sAfkTr8SZzsqau/2KtM0zR0qxYr2U2kcQ+Rup0YsZbK98Y5gZvHLQxipw7jZE/ilydQwZy+m0rh2yns9DGKI3spjT+Ck+sj8Eor/BkJIYQQQgghhBDiYiQkEmIVnD59mnK5DEAqlSKfzwMQjUarVvOslGc961m86lWvqnrsO1//ImePPglARJsdVu4EVxZoxeNxtvZupbZmtr1VJpuhr6+Psh1+jVSg6O/v5/jxY7hu9bkXJ6fhfz8OirAF3IcehEMTV7S0SzZRhIILEwU4Ogm5mXumGtCcWNm1CHExmqZjJbvOfTRvNtF6r465XJG67TTufiNtd3yAZPfPLHFukaI8+RhTT36IySc+SGniUdScGT7rVRgYJbGSXUQb9xCpvzYMFvX5beQCt4BbGMZOHcHJHMcrjaGC+SGj72RwMicojj5IaXw/TvYMgXtprUqFEEIIIYQQQghxdUhIJMQKs22bkydPAmHlzNwqot7eXnR9dX8sf/VXf5WtW7cu2K+CgK/8w3uxS4VKJRGAra58tJlhGHR2dtLe3o4+U8nkei4D/QNMp6ZRhGU5mUyWZ555hnR6flnOaB7+5gC4c+bJ2z58fD88NHDFy1syDThXiOX4cGo6rGjaUgt10ZVbhxBLZSa7K9+0RnS2/aNvT6NUcKFLNzQj1kzdNffQ9tyPULfjlzBiSwvv3dxp0kf+kYkDf0x+8LsE3sbpNambCaxEJ9HG3UTqr8OMt6MZsXnnBF4JrziKnTqKnT6GVxol8OdXD/lODid7iuLYPopjD4et69wcQgghhBBCCCGEWB0SEgmxwo4fP47nhZU4ExMT2Hb4juuamhoaGxtXc2kARCIR7r333koLuLlS48P8x+fvI2k4JHSXRqNEUneqPMrlqa+rp3frVmLR8MajQjE5OcnQ4FDla+Z5HsePn6Cvr48gCMOqrxwJK3jO5ytIr2DXrNYkXN8MyTlvtC+4MF4I/xNirdGNKGa8HQBNt9CjDeEB5RPY0iNRN2Iku15M6+3vo3HPbxOpv25J1/n2FLnTX2Z8/zvInPoiXmmFyxqvMt2MYyY6iDbsItKwCzPRsaDqSvllvOIYTvo4dvooXnFkQWgWuHmc7BlKY/spjj6EkzmJ72RX8lMRQgghhBBCCCE2PQmJhFhB+Xyevr4+IJxLNDQ0VDnW29u7WstaYPv27bzuda+reuyxH36D3NPfpDuaod6051UVLYeIFaG7p5umOYFZsVSkr6+v0pYPYGxsjEOHDlMqFfn1m2BPy8LHunsbvHzHsi7voqIm7GyE7jowNOipCyucnh6DZ8bA9i7+GEKsJCvZXdk2YrM/SF55cjWWsyZpmk6s5Waan/N2Wm5+N7G2O0G7eKtN5dsUh37AxCN/TOrwP+BkTl50ttp6oxsxzHg70YbriDZcj5noRDfn99dUvo1XGsfJnMBOH8YtDC9oNxd4RZzcWUrjByiO/hg7fRzfTm+4r5cQQgghhBBCCLHWSEgkxAo6cuRI5YbXyMhIpTqmqamJmpqa1VzaAq9+9avZs2dP1WOf+MQn8LLjV+25dU2npaWV7q5uTCOsaPIDn+GRYcbGxgiCsA1WqVTi4KFDZKdH+V93wk/M3uvmlg745Rtn27+tJE2DlgTsboWaOVVFYwXYNwgjVTorZcog90LFajCiDRiRcCaYbiYqN/iVXyZw8xe6dFOyarfSeP1vhHOLel6OZi5l4JiiPPk4U099mKknP0Bp/AAq2HiJsWZEMeNtROqvJdq4BzOxBd1MzjtH+S5+eQInexI7dRi3MLjg+yzwyrj5fkoTj1Ic3YudPopfnpbASAghhBBCCCGEuAokJBJihUxPTzM6OgqA4ziVbU3T6OnpWc2lVWUYBm9729uIxxcObs9kMnzxkx++6jfsEokEvVt7qUnOBmiZbIb+/v5Kmz4VKPr6+jl98jj/4waXV+wMK3l+8xbQVyEgmsus8grrBXBoAp4YhfLMPeK8A4+OwKPD4bYQK81Mzr4GmVJNtCRGtIm67a+h7c6PULfzVzBibUu6zs2dJX30U4wfeBf5ge9sqLlFc2m6hRlvJVK/k2jjHqxkN7o1/80QKnDxy1M42VPY0wdx8wMEbhaY/d2ifAc3P0hp8nGKIw9gpw7jlSc39cwsIYQQQgghhBBiOUlIJMQKOXToUGV7cHCwUg3T3t5ONBpdrWVdUHt7O2984xurHnvqsYd59P6vX/U1mIbJli1baGtrQ58pC3Jch/7+flKpFGrmZmI6nebQoYO8ZEuGP/gJiFy8E9SqmiqGVUX9GTg8EVYRZWzYPwSnUxDIG+bFCjITHWi6BYAebUDTwwq+wMmgfEkuL0Q3oiS3vIjW2/+Cxht+h0j9riVdFzgpcme+wvjD7yBz8gt4patXnbnaNN3CiDUTqdtBtPEGrJoe9EgdMJvkK+Xj29M42TPY04dw8/0EThbmhEEqcHELw5Qnn6Q48gDl6YN4pQlUsLxtT4UQQgghhBBCiM1k4WR6IcSyGx4eJp1OA1AsFpmcDN+dbxgGnZ2dq7iyi7v77rs5cOAA+/btW3DsPz9/H9fccCvNHVe/EqqhvoFEPM7I6Ci2baNQTExOUCwWaO/owDRMXNfl2LFjdHS0093Tg66t7RzcD+DBfkjb4eyimBmGRadTMFGE27esfjWU2Bw0TcdKduPkzgAaRqwZrzgGgG9PYSbW9uvUWqBpOrHm5xBrfg5uvp/C4PcoTTwC6sIBhgpsisP3Uxz+IdHm51DT/VKsumvRVqNX5grQdBMj2oQRbUIpn8DJETgZfHc2EAoDoxS+nUJDR4/UYkTqw2BpZhaUCjy84ihecRRNMzBizZjxNoxYSyXkFEIIIYQQQgghxMWt7TuoQmwAQRBw5MiRysf9/f2V7S1btmBZ1mosa8k0TeMtb3kLDQ0NC445domv/P178f2Vma0RiUTp6emhsaGxsq9QLNJ3to9CYXYI+ujoGIcPHaZULi36WErBvx6EZ8au6pIvyPZgJA8FB45NwVh+toKoKS4BkVhZZk13ZYiXEW2u7PfLU9La6xJZNb00XP/rtN3xIZI9r0A7by5PdQp76kmmnvpLpp54P6Wxhzfk3KK5NM3AiDZg1W4NK4xqt2FEGytBEIAiwHcyOPn+sMIoewbfnp4Xvinl45XGKU8fDCuMJp/ELQyjAnc1Pi0hhBBCCCGEEGJdkZBIiKvs7NmzFIvhzIlMJkM2mwUgEonQ3t6+mktbsrq6Ot761rdWPdZ/4hke+MbnV2wtuqbT2tpKV1cXphG+W9wPfIaGhxifGCeYuZldLBY5dPAQ4+PVWzh94zj84Az8zSOwt7/qKVedr8CauReqVBgYnZgKp3Fc07A6axKbl25EMWOtwEx7sGgYxirlE9jpVVzZ+mVEG6jb/nO03/lh6na+DiPesaTr3Hwf6WOfZvzAH5Hv/xaBW7j4ReucpukYkXqsmt5whlHtdoxoE9q8wEjhu1nc/ADl6YM42dP49tS8MEipAK88iZ06TGHkAUqTT+AWBgl8ezU+LSGEEEIIIYQQYs2TkEiIq8h1XY4fPw6AUoqBgYHKsZ6eHnR9/fwI3nbbbbzsZS+reuz+r36KodNHqh67WpKJJL1be0kmZ9+hn06nGRgYwHHCm4FBEHD27FlOnDiO683eRNzbH4ZEEFbu/J+nwo/VCs8BSliwqxnakpUCDkoeFB04nQ7b0Qmxkqya2daRRqylsu2VJ1djORuGZkRJbnkhrbe9l8YbfpdIw+4lXRc4aXJnv8b4/neQOfEveMXRq7zStSEMjOqwanqINN5ApO4ajFhzZW7WOYGbw80PYqcO42RP4Zcn51cPKYVfnsJOHaU4+mNKE4/h5gckMBJCCCGEEEIIIeZYP3eohViHTpw4geuGN6wmJycrFUWJRIKmpqbVXNpl+bVf+7WqM5QC3+eLn3gvrlNe0fWYhknXli7aWtvQZgag27ZNX19/ZQYUQCqV5uDBg2SzWZ4eg889vfCxvn4MvnBohRY+h67Bllq4tgniJjQnIBmBvjQ8PASpxTvmCbHsjGgjulUDgG4m0M0EAMovbYpqlqstnFv0bJqffS8tt/wp8fbngXbx+TkqcCiO/IiJR/+U6YN/h50+hlrpVHuVaJqGbtViJbuJNOwmUrdzZu7Q+YFRHrcwFAZGmRN4pQlU4MyeoBS+ncJOH6M4spfS+CM4uT4CT15khRBCCCGEEEJsbhs2JJqamuKf/umf+Lmf+zl27txJPB6nvr6en/zJn+TTn/40QVD9LfoPPfQQr3jFK2hqaiKRSPDsZz+b++67D99ffPD0Zz/7We644w5qamqor6/nhS98If/v//2/Rc8vlUq85z3vYdeuXcRiMdra2njta187b26NWP+KxSJnzpwBwPd9BgcHK8d6e3vX5VDyWCzGvffeW7UCanr4DN/5widWYVXQ0NBAb28vkUgECFsSjU+MMzQ8hDczL8l1XI4ePcq+07nK3J+5dA1ubF3JVc+XsODaZuiqnd1XcuGxETg6Cd55L1klN5xpJMRyW6yayJdqomVl1fTQsOsNtN35IWp6X4lm1izhKoU9/RTTT/8Vk4//BcWxfRt+btFcYWCUxEp2EW3cQ6T+Wsx4G5oemXde4BXxisPYqSM4meN4pTHUedVDvpPByZygOPogxbGHcbJnJAgVQgghhBBCCLEpaWqDvhX1k5/8JG9+85vp6Ojg7rvvpre3l7GxMb72ta+RyWR4zWtew1e+8pV5N+q//vWv8/M///PEYjF+8Rd/kaamJr75zW9y7Ngx7rnnHr785S8veJ4/+IM/4KMf/Sjd3d3cc889OI7DF7/4Raanp/nbv/1bfud3fmfe+bZt8+IXv5gHH3yQ2267jbvvvpuBgQG+/OUvE4lEuP/++7nzzjsv+fN9/PHHufXWW3nssce45ZZbLv0LJpbd448/ztDQEADDw8OVkKihoYHrrrtuNZd2xf7x81/hP778uarH3vBHf8POZ1/69/ByCFTA5OTkvCoi0zBp72gnmQjb0ikFTzvbeDjdNu/a1z8Hnt+7kqu9NFEDrm+B1mT4OTw6DAU3bFfXWXvx64VYKhX4FEd/PNO2S2FPH0Kp8I0S0cY9Cyo4xPJQvkNp/GEKQ9/HK44s+To9Uk9yy4tIdL6gUgW2GQVemcBJ4zsZlF+9qlUzYhjRevRIPboRr3qObiUxY20YiTYMS15cxfol/zYQQgghhBBCLNWGDYnuv/9+crkcr3zlKzGM2aHHo6Oj3HHHHZVg5p577gEgm82yY8cOstlsJcABKJfL3H333ezbt48vfOEL/NIv/VLlsR566CHuuusuduzYwSOPPEJjYzjk++zZs9x6660UCgWOHj3Ktm3bKtd88IMf5F3vehf33HMPX/rSlyoVGV//+td59atfzZ49e3jmmWcueVaN/ENwbUmn0+zduxcI5xI9/fTT+L6PpmnccMMNJBKJVV7hlZksm/zJO3+/6hyi2sZW3vqRfyFRU78KKwvl83nGxsbwg9kKwMaGRppbmtG18GfraLmNvZmtBGj87HXwql2rtdpL014TtqU7m57d15yA3S0Qu3jXKiGWxMmcxMmdBcArjuKVxgAw4+2YiY5VXNnGp1SAnTpMYfB7OOnDS79Qj5Bo/wmSXS/Z9H9GgW8TOGkCJ7NoOznNiGJEZgIjs/rvZN2MY8TbMONtGJHV+50mxOWQfxsIIYQQQgghlmrDtpu7++67edWrXjUvIALo6OjgTW96EwA/+tGPKvu//OUvMzk5yS//8i9XAiII22u9733vA+Dv//7v5z3WP/zDPwDw7ne/uxIQAWzbto23vOUt2LbNZz7zmcp+pRSf/OQnAfjIRz4yLwh61atexfOf/3wOHz48b11ifTp8ePbG3vDwcKVdYUtLy7oPiABqI4pfeMt7sSLRBcdyqQm++Zm/XIVVzaqpqWHrtq0k4rNf61Q6xcDAAI4Tthy6PjbOzzQc59bGNK/YsX7aNfWn4T9PQGrOG+WnirBvENIrOxJKbGBmshtmKm2NWHNlv1+eQqnq7VrF8tA0nVjTjTQ/+2203Poe4u13LWluEYFDceS/mHj0T5g++DfYqSObZm7R+XQjihlvJ1J/HdGG3ZiJLehmct45yrfxSuM4mRPY6cO4heEF7eYCr4Sb66M0/giFkb3Y6WP4dmrTfl2FEEIIIYQQQmxMGzYkupBzc0ssa7Zlzg9/+EMAXvayly04/6d+6qdIJBLs27cP27aXdM3LX/7yeecAnDp1iv7+fnbt2sX27duXdI1Yf8bGxpiamgLCSrTx8XEAdF2nq6trNZe2bKK6T0dXDy973e9WPf70vu/x1IPfWeFVzWcaJl3dXbS2tKIR3uy2bZv+/n4y2QwAvdEMt0WOc+jQQbK57Goud8kGc+D40JeG06lwGyBiQG3kgpcKsWS6GcOcmUek6RZGtAEApTwCJ716C9tkrGQ3DbteT9udH6am97+hL7H9mT39DNPPfIzJx/+c4uiDM60DNyfNiGDGW4nU7yTauAcz2bWgLZ/yXfzyBE72JHbqEG5+kMDNAWrOOTZufoDSxGMUR/dip47gSWgqhBBCCCGEEGID2HTNiTzP47Of/SwwP9w5duwYANdee+2Ca0zTZPv27Rw6dIjTp0+ze/duCoUCQ0ND1NTU0NGxsK3Lucc5fvz4kp5jsWvONzIywsjIwlkFR44cmff/83V2dtLZ2bno44rloZSaV0U0MDBQecdxR0dHJaDcCJrMEq98xcs5+8QPeebJxxYc/8ZnPsLW62+iobl9FVYX0tBobGwkkUgwMjKC4zoESjE2NkYhX6CtvQ3TMHFsh2NHj9LZuYUtXVsqLenm8gIwVzlWDxQYs2PUyNpwdAq21MBPXwPGpoz9xdViJXvwShMAGNEWfDsNgF+exIg2reLKNh8jUkfttp+lpvfllMbOzS0avuh1XmGQzPH/Q+7M10jMzC0yIpt3zo6mW2H4GWtBBR6Bk8F3MgRunnOBkAo8fHsK355C0wz0SP1MW7pamHnDgfId3MIQbmEofMx4K0asFSPWjFbl94cQQgghhBBCCLGWbbqQ6J3vfCcHDx7k5S9/OT/zMz9T2Z/JhJUF9fXVe86f259Opy/r/Mu95nz/+I//yHvf+95Fj//qr/5q1f3vec97+LM/+7NFrxPLo7+/n3w+D0AulyOVSgFh1dpGC+k6IuHnee//+h3e8rv/i2J+fiVOuZjnq//w57zhXX97yTO2lls0GqW3t5eJiYlKFVG+kKfcV6ajo4NEIoFSYWvAc/PJotHZVnqODx/dB9e3wKt3VbpwrThdg20NYVu5wWwYXAUBlDw4nYaYBQnrYo8ixNIYsSZ0q4bAzaNbSTQjhvLLBF6JwC2gW8mLP4hYVppukeh8PvGOn8RJHaYw9H3s1MGLXhe4WfJ9Xyc/8J/E255LsuslWMktK7DitUvTTYxYM0asOQyM3GwYGDmzFURK+fj2NL49PRMY1YWBkVULM2GQClzcwjBuYXjmMVvCGUbRZjTduMAKhBBCCCGEEEKItWFThUT33XcfH/3oR9m1axef+9znLunac9Ug2iXeHb6U85fyHL/1W7/Fz/7szy7Yf+TIEX71V3+Vf/7nf2b37t0Ljm+0gGIt8jyvUi0GYRXROV1dXQvmY20Uzc3NvP5Nv8ff/9WfLzh2+tCj7Pv2l7jrFb+8CiubT9d12tvbSSaTjI6NEgQBnu8xODRIU2MjTc3N6JpOPp/n4MGDbN26lZaWFgIFn3ocTqbC/6ZL8D+fs7pVRQ0xqInASA6yDnTWhMHRvkHY2Qi99asXZImNxarpxk4dBcCMt+DmB4GwmkhCotWjaRrRphuINt2AWximMPR9SmP7QF1kvlrgUhrdS2l0L9HGG0l2v5RIw+5L/rvNRqPpJka0CSPahFI+gZMLq4zcLMy0kwsDoxS+nUJDR4/UzlQY1YEW/n5XgYdXHMUrjqJpBkasOQyMYi1o+qb6K7cQQgghhBBCiHVk0/yL9eMf/zhve9vb2L17N/fffz8tLS3zjp+r4jlX7XO+bDY777yLnV+tauhSn6Oai7WN2717N7fccsuix8XVc+rUqcrMqunp6UpFUSwWo7W1dTWXdtU9/66f4KH9L+fJvd9acOy7X/x7dj7rTtp7rlmFlS1UU1PDttg2RkdHKZaKAEynUhSLJTo6O4hYEXzf5/Tp06TTGfYVt/P46Gwi9NAgZGx4820QX8VXUFOHnvr5bfCUghPTMFqAPS1QO1sMhVKQc6AuWv3xhKjGjHfiZE6hAhcj0oinjYQ3y50MZuCi6VK6ttqs5BYarvsf1G77OYoj/0Vx+IcE7sVnrNmpg9ipg5iJLpLdLyHedqf8eUIY7kQbMKINmCogcGcCIycLKhwCpwjwZ1rVaWjoVi16tB7DqoOZMEgpH680jlcaR9N0jGgjRrwNM9aKZmyc1rNCCCGEEEIIIda/TdE4/a/+6q/4vd/7PW688UZ+9KMfVZ0htGvXLqD6PCDP8zhz5gymaXLNNeGN7mQySVdXF/l8vuqMoBMnTgBw3XXXLek5FrtGrA/lcplTp04BEATBvCqinp6eDf8u7bju8t9e//s0tCz82fJchy9/4j143toZnG6aJl3dXbS0tKDNzJgo22X6+/oq7egA7h+w+FHfwpfJQxPwmSdWbLkXVK2iKWfDgSE4OR3OMQIYyIb7jk6GwZIQS6HpBmai89wHGLHmmSMKvzy1ausSCxmRWmq3vpK2Oz9E/XWvx0x2Lek6rzhE5vhnGd//h+T6vhGGIQIgDHci9Vg1vUQb92DVXoMRbULTZiuDFQrfzeLmByinDuFkT+PbU6hg9neeUgFeeQo7dYTC6F5KE4/jFgYJfHs1Pi0hhBBCCCGEEGKeDR8SffCDH+Ttb387N910Ez/84Q9pa2uret7dd98NwLe//e0Fxx544AGKxSLPe97z5s0pudA13/rWt+adA7Bjxw56e3s5fvw4Z86cWdI1Yn04duwYvh++w3hiYqJSUVRbW0tjY+NqLm1F6Bo01sT4+Tf/adVAbKTvOPd/5VOrsLLFaWg0NTbR09uDZYbvng+UYmxsjJGREXzfJ6576CxMVJIWvOb6lV7xpVHA2TQ8PAij+TAwgnCW0cODMFlczdWJ9cSq6alsG7HZKlzfnkYpSRzXGk23SHTcRcst76HpWfcSbXrWkq4L3Bz5vm8yvv8PSR//LG5h6CqvdH0JA6NarJoeIo03EKnbMdNGbn71VeDmcPOD2KnDONmT+OWJeYERSuHb09ipoxRH9lKaeBQ330/glVf4MxJCCCGEEEIIIUIbOiT6i7/4C971rndx66238oMf/GBBi7m57rnnHlpaWvjiF7/Io48+WtlfLpd597vfDcCb3/zmede86U1vAuD9738/qVSqsv/s2bN84hOfIBqN8oY3vKGyX9O0yjXveMc7CILZm2tf//rX2bt3L3v27OEFL3jBFXzWYqXlcrlK5ZDneQwNzd5Y6+3tXa1lrbi47nLNnlsXnT/0wDc+z9mjT67sopYgFo2xdetW6utm2zzm8jn6+vvoZYCXNZzA0vzKMUtX/O4d0Fm7Gqu9dEUXvn4M+jPgz1QVlT14cnQ2OBLiQnQzjjkTDmm6hREJf1ZU4BI41dunitWnaRrRxt003fhWWm/7cxKdLwB9CW3OlEdp9MdMPvZnTD3z15SnD1ZmJoqQpmnoVg1WsotIw24idTsxYq1o5319A7eAWxgOA6PMCbzSOCqYXz3k22ns9HGKoz+mNH4AJ3eWwJMUXwghhBBCCCHEytHUBv2X/2c/+1le//rXYxgGv/u7v1t1zs+2bdt4/etfX/n43//937nnnnuIxWL80i/9Ek1NTXzjG9/g2LFj3HPPPfzbv/3bgiqJ3//93+djH/sY3d3d3HPPPTiOw5e+9CWmpqb427/9W37nd35n3vm2bXP33Xfz0EMPcdttt/HiF7+Y/v5+vvzlLxOJRLj//vu58847L/nzffzxx7n11lt57LHHZCbRCjtw4ABjY2MADAwMVNoPNjc3s2PHjtVc2opKeTEG7Xpcx+Yf3v0GxgZOLTinsW0Lv/uhfyYaX5sD73P5HGNjY5UAV0OjsakRVdfDt9O7KAYWL2s6zd27G2huar7Io60N06UwIAKIGNBdNzuX6JZOaIqv3trE+uGVpyhPhj0WAzePkw1/vnUzSaR+52ouTVyCwM1RGHkgnFt0CQGfmegk2fUS4m3PlXk6FxF4xZkZRhnUIu3kNCOGEa3HiDSgGbGq5+hWDWa8DTPehm7VXM0liw1K/m0ghBBCCCGEWKoNGxL92Z/9Ge9973sveM4LXvACfvSjH83b9+CDD/L+97+fffv2US6X2blzJ7/2a7/GW9/6VgzDqPo4n/3sZ/m7v/s7Dh8+jK7r3HLLLbz97W/nla98ZdXzS6USH/rQh/jXf/1X+vv7qaur44UvfCHvfe972bNnz2V9vvIPwdUxOTnJvn37gDAAfPrpp1FKoWkaz372s+e1J9zoyoHB8WILrtIZ7jvJZ/7kv+P73oLzbn3Rz/KaN/7xKqxwaVzXZXRslFKpVNkXj8VItm5jUjVyXTycw9LS0sLWrVsXfV1YKyaLMJybnU0EYTB02xZ4dvvqrUusP8WxfQRuAQA7fQzlh+2xIvXXopuJ1VyauEQqcClNPEJh8Pt4hYGLXzBDt2pIdL6QxJYXVirKxOICr0zgpGcCo+rt5DQjihFpQI/ULfpzpFtJzFgbRrwVI1J3NZcsNhD5t4EQQgghhBBiqTZsSLTZyD8EV55Sir1795LJhO/GPnXqFFNTYYDQ0dGxaVrN5f0IeT9Cwbc4Vm7BVzomAae/8wm+84W/q3rN637/I+y5be22VVQoUtMppqamUIQvkbqu097WRm3t7A26WCzKNTt2UJNc2+/ytj0YyELeCT+2DHhWG9zQBu1rs6hLrEFufhA7fRQA357CzQ8CYEQbsWo2x+vdRqOUwskcpzD4Pezpp5Z+oWYSb7uDZNdLsWq6r94CN5DAtwmcDIGTJvBKVc/RjAh6JKwwWjQwMuMYlQqjuqpzAIUA+beBEEIIIYQQYunM1V6AEOvV8PBwJSAqFAqVgMgwDLZs2bKaS1tRGT/KtBvezLK0AF/peOg89/97Hcee+HHVOUT//qkP0rvzRmoa1mbLNg2NpqYm4ok4oyOjuJ5LEASMjI6SLxRob2tH13XKZZsjhw/T1d1NZ0dn5WbdZBEaYmCukalvURN2NsHUTFVRd21YWfTMGIwl4bpmiMlvA3ERZqIDJ3sSFXgYkUY8bQSlfHw7jZnYgqbLN9F6o2ka0YZdRBt24RVHKQz9gNLYQ6jAufCFyqM09hClsYeINOwm2f1Soo03oGlr5EVvDdKNKHq8DeJtKN/BdzJhaOQVKuco38EvTeCXJtB0ayYwqp/Xbi7wSgS5PtxcH5oRnW1JF2mQwEgIIYQQQgghxGWRf80LcRmCIODIkSOVjwcGZtv1dHV1YZqb52ZpQncr21Fttr2cR5R7fvs9ROML3w1dyKb42qc+sOaHocdjcbZu3UptbW1lXy6Xo6+vj1I5fCe4UjA4MMjRY0dxHIfpEnzoQfjr/VB0F3vk1dGcgN2tUD9nBMZ4AR4eDMOj8+Xs8PMTAkDTTcxE57kP0GNNM0cUvj21ausSy8NMdFB/7etou/Mj1G57DXqkYUnXOekjpA7+DROPvofC8H8tOodHzNKMCGa8lUj9TqKNezCTXQvmDqnAxS9P4mRPYacO4eYHCdwcMPuirHwbNz9AaeIxiiMPYKcO45WnUCpY4c9ICCGEEEIIIcR6JiGREJfhzJkzlZk16XSabDYLQDQapa2tbTWXtuLmh0R+ZdtWBo2tW3jl//yDqtcde/zHPHr/16/6+q6Urut0dnTS2dGBrocvma7nMjgwyPT0dKUdXS6b49GnD/HRhzxSZTg6CR9+CFLVuwqtmmrVTV4Ahyfg8REozfxxlj14dAQeGQ7DIiEArJqeyrYZa6ls++WpNR/6iqXRrSQ1vS+n7Y4P0rDr1zGX2ErQL42SPfnPjO1/J7kz/xffTl/dhW4Qmm5hxlqI1O0g2ngDVrIb3aoDZquCVODh21M42dPY04dw8wMETpZ5gVHg4haGKU8+QXFkL+XpQ3ilCQmMhBBCCCGEEEJclIREQlwix3E4ceIEEM5zmFtF1N3dXQkSNouI5mNo4U2oiD5bSWQHYTXVzT/1Cm6444VVr/3Pz9/H1OjSh6avptraOrb2biUeC8twFIrJqUkGBwZwXRdfaXxrcgejxdkqssEsfODHMFSlSmctmi7BvkHoz4ShkR9A1oYDQ3AqFbaoE5ubbiYwY2GbSE2PYETCGV0qcAmczGouTSwzTTeJtz+XlpvfTdOz3060+SbmBheLUV6e/MB/Mn7gnaSPfgY333/V17pRaLqJEWsmUredaOMerJpe9Eg9zGnjF7Z4nMbJnZkJjPoI7DTMCYNU4OIVRyhPPUVx5AHK08/gFcdQgVflWYUQQgghhBBCbHab6262EMvgxIkTuG5YbjE5OVmpKEomkzQ3r80ZO1eTpkFcdzG0gAazTItZoM3M02oVZo5rvOrX/4ia+qYF1zp2ia/8/Xvx/fVx48qyLLp7emhqakKbuVlaKpfp6+/jR9OdDLt1C66ZLsPXjizYvWYFKmw/t38QSjN/LAo4k4L9Q2HVkdjczDnVRMa8aqLJ1ViOuMrCuUXX0XTDW2i9/X0ktrwITY9e/ELlUxrfx+Tjf8HUU39FeeopqWq5BJpuYkQbidRuCyuMarZiRBqqBEZpnHwf9vRB3NwZfDsFaraqVwUeXnGM8vQzYWA09RRucQQVrLF+qEIIIYQQQgghVo2EREJcgkKhwNmzZwHwfZ/BwcHKsd7epbXk2Yh6oxn2JCbYHkuzJZojYXgY2mzZSbKugdf81rurXtt/4hke+MbnV2qpV0xDo6W5he7u7srsqSAIaEw/SYyFveXa4i5veM76KcFx/bDyqeDC8SkYzc9WENVHq7erE5uLEW1GN8NZY7pVi2aEgUHgFQi8NdZfUSwrM95G/c5foe3OD1O7/efRI41Lus7JHCN16O+YePRPKAz/kEDmFl0STdMxog1YtVvDwKh2O0a0ETSjco5C4TtZ3Hx/WGGUPR3OCptTPaRUgFeawJ4+FLakm3wCtzCE8p3V+LSEEEIIIYQQQqwRcrtPiEtw9OhRgiB8J/TY2FiloqixsZHa2trVXNqqmhsIzZ1RNNeum+/ijpe8puqx+7/6KYZOr6NyGyAej7O1d2vlz70mSHNz7lskg9mWWwnd4aXJQwydPYbjrI+bcF4wGwQpFYZEx6fADeDahcVgYhPSNA2rprvysRlrrWxLNdHmoFtJanpeRtsdH6Dh+t/Eqtm6pOv80jjZk//K+P53kD3ztbDqRVwSTdMxInVYNb1hS7raazCizWjabKtThcJ3c7j5QcqpQzjZU+HcsDnVQ0oFeOUp7NQRCqN7KU08jpsflABPCCGEEEIIITYhCYmEWKJUKsXw8DAArusyMjIChDdMu7u7L3TpphJfJCQCePnr3kpzx8KvVeD7fPkTf4brlK/m0padYRh0dnTS0d6BruvEVJGb89+hwRvDxOXlDUepMRwymSwHDx4knV77N0TjFuxqhvZk2EoQoOxByYEz6XBOkRBmohNtporBiDZUtn07JXNPNhFNN4m33UHzzX9M83PeQazlFpY2t6hIYeBbjB/4I1JH/wk313f1F7sBhYFRLVZNN5HGPUTqdmDEWtB0a955gZvHLQxipw7jZE/ilyfmt5tTCt+exk4fpTiyl9LEo7j5fgJvff1OFkIIIYQQQghxeSQkEmKJDh8+XNkeGhrC98Oe/62trcTj8dVa1poT1z3CKTYLRWJxfuEt70XXjQXHJobP8p0vfOIqr+7qqKuro7e3l1g0hoXDs4s/4Kb8dymPncTzwhvmnudx/PgJzvadJQj8izzi6tI16KwNK4fiFjTEoC4G/RnYNwjT0lFs09N0CzPZOfOBgR49V2YW3mwWm4umaUTqr6Vxz5tpvf39JLpeXGlDeEHKpzy+n8kn3sfUU39JefJJmVt0mTRNQ7dqsJJdRBp2E6nbiRFrRdMj884L3AJuYTgMjDIn8ErjqGB+9ZBvp7HTxymO/pjS+H6c7BkCr7iSn44QQgghhBBCiBUkIZEQSzA6Osr0dHjjs1QqMTExAYSVJF1dXau5tDXH0BQxffEQpGfnjbzg1a+vemzft/+Nk0/vv0oru7oiVoTunm6ampowCKgNUhRLRc72nSWfz1fOGx8b59ChwxSLa/+GW8IKg6Luutl9ZQ8eH4HDE+H8ornKHthSRLJpWMmeyrYZb65s++VJlFo/c7jE8jLjrdTv+CXa7vwItdf8AkZ0aX0qncxxUoc/wcQj76YwdD+BL1UslysMjJJYyS1EG3cTqb8OM962ILgLvCJecQQ7dRQ7fQyvNIo67+vuOzmc7CmKow9RHHs4bF3n5lby0xFCCCGEEEIIcZVJSCTERQRBMK+KaHBwsHIDtLOzE8uyFrt007pQyzmAF/3cr9F1ze6qx77yyb+gmM9UPbbW6ZpOS3ML3V3dmEY4HyIIAoZHhhkbG6vMsyqVShw6fIixsVEOTaztyhxdm51RNNdwDh4ehPHC7L4jk2Gl0bDcP9wUdCuJEQvDIU2PYljhfC4VuARudjWXJtYA3UxQ0/3TtN7xARp2vxGrdvuSrvPLE2RPfYHx/X9I9vRX8MtSmXaldDOOmegk2nA9kYZdmIkONCM27xzll/GKY9jpY9jpo3jF0QXVQ4Gbx8meoTS2n+LoQziZk/iO/KwLIYQQQgghxHonIZEQF9Hf30+hEN4Jz+VypFLhXBnLsmhvb1/Npa1ZCePCIZFhmvzCW96LFVnYjiiXmuAbn/nIuq5ESCQSbN26lZpkTWVfJpuhv78f2w7b+qhAceDEFH+zP+B9exUD6/A+m+3D02PwzBj0pWGqCF4QVhk9PgKlC38biA3ASs7OGDPiLZVtvzy5GssRa5CmGcRbb6fl5nfRfNM7ibXcypLnFg1+J5xbdORTOLkzV3+xm4BuxDDj7UQbdhFpuB4z0YluJuado3wbrzSGkzmBnT6CWxgmcAvzzgm8Ik7uLKXxAxRHf4ydPo5vp9f1724hhBBCCCGE2KwkJBLiAjzP49ixY5WP+/v7K9vd3d0YxsLZOuLilUQArVu28rLX/W7VY8/s+z5PP/Td5V7WijIMgy1bttDe3o6uhTdEHdehv7+fVCpFyovy7fR1eEonY2t86MeKI+v0vvpgFr5xfH5F1HQprCqaWvtd9cQVMGIt6GY4k0236irtrAI3L0PvxQKRuh007nkTrXd8gGTXSxdUs1QXUJ44wNQTH2DyyQ9Tmnxc5hYtE92IYsbbiNRfS7RhN2ZiC7qZnHeO8h388gRO9iR26jBuYZDAzc87J/DKuPl+ShOPzgRGR/HL0xIYCSGEEEIIIcQ6ISGREBdw8uRJHMcBYGpqqlJRlEgkaGlpudClm5YT6Ni+QdqPMerUMOTULnrunS+9h2uf/dyqx77xmY+Qnhq7WstcMfV19fT29hKNhjfPFYqhqRzfnNxJWc22Kiz7Gh97WLFvcP3d/BzOhbOI+jNwKgXOzKwiU4e6JcyuF+uXpmmYc6qJzJhUE4mLM2Mt1O14LW13foS6a34RI9p88YsAN3uS9OF/YOKRP6Yw9H0JIpeRZkQw461E6ncSbdyDmexGt2rmnaMCF788hZM9hT19EDc/MNNacjYMUr6Nmx+kNPk4xZEHsFOH8cqTEuwJIYQQQgghxBomIZEQiyiXy5w+fRoI58oMDg5WjnV3d6NpF2+Xs9mMODUcK7Uy4DRQDkzKysRVBr6q/rXSNI3X/Na7idfULThWLub56j/8eWWOz3oWiUTp6emhsaERgFPRmylpyQXnBUrjwMkUpdL6Kb8J1Nzbg5Cz4egUTBRhVzNYUmy34VnJLWha+AdtRBsr276TQgXeai5NrHG6GSfZ/RJa73g/DbvfhFW3Y0nX+eVJsqe+xPj+d5A9/WW88tRVXunmoukWZqyZSN0Ooo03YCV70K065rYJVMrHt6dxsmewpw/h5vsJnCzMCYNU4OIWhilPPklxZC/l6UN4pQlU4K/CZyWEEEIIIYQQYjESEgmxiKNHj+L74Y2M8fHxyiyZuro6GhoaVnFla1dMn70hHNFmt+1g8aSgrqmVV//GO6seO33oUfZ9+0vLt8BVpGs6ra2tdHV1cb37JA3eyIJztkZT3Bk/xcFDhxgfH1+FVV46XYNtDbC9YTYQCgIoONCfDf8vNjZNtzATHTMfGOjRhnBbBfh2atXWJdaPcG7RrbTc9E6ab/ojYq23s5S/oiq/RGHwu0wceBepI/+Ikz119Re7yWi6iRFrIlK3nWjTDVg1veiRetBm/3zCwCiFkzsXGPUR2GlQs2GQCly84gjlqacojjxAefoZvOKYBMlCCCGEEEIIsQaYq70AIdaibDbLwMAAEM4lGhoaqhzr7e1drWWteXNnEUW12ZtDtjJJsPiNoBvvfDE3Pf/lPLn3WwuOffeLf8/OZ91Je881y7vYVZJMJNmxNUpibD+Puc9hzNoOQH0wyU/Fj6FrFipQnD17lkwmzbbt27FM6yKPuvrqY5CMwEgO0jZ01UKmDA8PwY5G6K0PAyWxMZk13biF8HXSjLXiz1R2+OVJjFiLVF6KJYvUXUOk7o3426coDN9PcWQvyi9d5KqA8sSjlCcexarbQbLrJcRabq5UtYnloWkGRrQRI9qIUgGBkyVwMvjubAWRIsC30/h2Gg0NPVKLHmnAiNTBzJ+HUj5ecQyvOIam6RixZox4G2asBU1f+7/vhBBCCCGEEGKjkUoiIao4fPhwZXt4eLhSUdTc3EwikVitZa15Uc1H18LmY9E5VUXOBSqJzvlvr/8DGlo6Fuz3XIcvf+I9eJ5b5ar1yTRMerZs4QXJE/Tah4j7WW4s/JCh/rOk0+nKealUmoMHD5LNZldvsZfA1KGnHna3zFYVKQUnp+HAEGTthdfkquwT649h1WJEw3aKmhFFt8JZZCpwCNzcai5NrFNGrJm6a34hnFu045cwYq1Lus7NniJ95B+ZOPDH5Ae/R+BdLGASl0PTdIxoA1bt1rAlXe12jGhTJQiCcAaf72Rx8/2Upw/iZE/j21Mwp3pIqQCvNIE9fYjCyAOUJp/ALQyhfClDFUIIIYQQQoiVIiGREOeZmJhgYmICANu2GRsbA8L5Od3d3Re6dNPTtNlqIlNTRDSPuO7Oa0O3mFiihp9/859WrTgY6TvO/V/51LKvd7U1NjZwd/s0d3k/IKJsFIrxiXGGhofw/PBr5jouR48epX+gn2CdDP42q/xmyTvwyBCcmAZ/5tMYzcP+ITgyAa6MqFj3rJqeyrYZa6ls++WJ1ViO2CB0M0ay68W03v4+Gve8mUjdtUu6zrenyJ3+t3Bu0akv4ZXk+/Bq0TQdI1KHVdNDtPEGInXXYESb0bT5DQsCN4ebH6ScOoSTPYVfnkQFc94AohR+eQo7dYTC6F5KE4/h5gcIfHk3gRBCCCGEEEJcTdJuTog5lFLzqogGBwdRKqyM6ejoIBqNrtbS1o0Ws0CTWSKhu9QZZbJ+bMnXXrPnVu56xS/z4//41wXHHvjG57nupuex7fqblnG1qy8ajbK9p5OpySlS6XB+S6FQoL+vn/aOdpKJJACjI6Nks1l27thJLLb0r+laooC+NIwX4LomODYza34oB5NFuL4FWpOruUJxJYxYK7oZI/DK6JE6NCOC8h0CN0/gl9GN9fl9K9YGTdOJtdxCrOUWnNxZCoPfozz52Ly5N9Uov0xh6PsUhn5ArOVmkl0vxarbIS0QrxJN09CsWnSrFqW6UF4R30kTOJl5gVDg5gncPBSG0M1E2JIuWo+mR8ITlMK3U+Fcs/QxjEh92JIu3oZuxlfpsxNCCCGEEEKIjUkqiYSYY3BwsNLaK5/PMzUV3sU2TZPOzs7VXNq6UWc6NJhlIrpP3Lj0gdQvee2baO/ZsWC/UgFf+Yf3YpcKy7HMNUXXdFpbW+na0oVphNm954ezsCYmJioVRPvG6/jWY/2VSrf1quTCN47BmRT4YQaL7cNTY3BscnXXJi6fpmmYydlqy/nVRPIHK5ZPpHYbjbt/k7Y7PkCy52Vo5lLawCrKk48z9dSHmXryg5TGH0FdJGASV0bTNHQriZXsItq4h0j9tRjxttkgaEbgFfGKw9ipIziZ43ilMdR51UO+k8HJnKA4+iCl8f042TME7sb7+4AQQgghhBBCrAYJiYSY4fs+R48erXw8MDBQ2d6yZQumKYV3lyqhX/ocISsS5Rfe8mcYxsKvd2p8mP/4/H3LsLK1KZlM0ru1l+ScuVepdIqBgQEO5ep5ON/Lf07v5NuHc5w4eaLSkm69ydiQKofVQ8cm588qapA3iK9rVmILmhb+1cKINqHN/DXDt1NyQ14sOyPaRN32n6ftzg9Tt/NXMGJtS7rOzZ0hffR/M37gXeQHvkPgFa/ySgWAbiawEp1EG3cTqb8OM96Odl6FYeCV8Iqj2Omj2OljeKVRAn/+XCnfyeFkT1Ec20dx7OGwdZ3MPhNCCCGEEEKIyyYhkRAzTp8+TblcBiCdTpPLhTccotEobW1Lu/Ek5otfRkgE0Ln1Ol7y2jdVPfbYD7/B4Uf/60qWtaaZhsmWri5aW1rRCNshDXtNPFgI53AE6Pwoew0/6I/x9NPPkM1lV3O5l8UPQJ/p9OT4cDoFfRloiEG7tJtb1zQjgpnoOPcBerQx3FYBfnl69RYmNjTdiJHc8iJab/8LGm94C5H665Z0XWBPkzvzFcb3v4PMyS/ilcav8krFOboZx0x0EG3YRaRhF2aiA82Y/y4B5ZfximM46ePY6aN4xZEFgV7g5nGyZyiN7ac4+hBO5iS+s/5+LwohhBBCCCHEapLSCCEAx3E4efIkEM4l6u/vrxzr6elB1yVPvRyGpojqHnZw6S81P/nKX+HYEz/m7NEnFxz79099kN6dN1LT0LwMq1x7NDQaGxtJJBIcGytxKPJTKG3+9+AjhR6KQQTPPcqWLVvY0rUFXVsf36dNcUhaMJiD3EwVUXamumgsD+01q7s+cWXMmh7cwnC4HW/Bt8O2nX55EiPWIrNgxFWjaTqx5puINd+Em+ujMPR9ShOPLGFukU1x+AcUh+8n2nwTNd0vwaq7Vr5XV4huxNDjMcx4O8q38Z0MgZOZFwgp3w5DvNI4mmGhWw0YkXp0a/adBYFXxMmdhdxZdDOGEZuZYRSplz9LIYQQQgghhLiA9XFHUYir7Pjx43he2LprYmKiUlFUU1NDU1PTai5t3buclnMAum5wz2+/h2h84ayJQjbF1z71AZRSV7q8NS0ajZJvuBFfs6oebzLDG2jDw8McOXyk8n27HkRN2NEIvfVg6LClBjTgmXF4ahTK67OTngAMqxYj2gCAZsTQrTD1U4FDIC2hxAqxarfScP2v03bHB0n2vHzJc4vsqSeYeuovmXri/ZTG96MCeTFaSZoRxYy3Eam/lmjjHszEFnRzfomp8l388gRO9iR26hBuYZDAzc87J/DKuPl+ShOPUhzdi506glee2vB/bxBCCCGEEEKIyyEhkdj0CoUCZ8+eBcK5RENDQ5VjPT09q7SqjeNyQyKAxtYtvPJ//kHVY8ce/zGP3v/1y37s9eInage5OTm0YP9W+xnaiocJVACE38eHDh1icnJypZd4RZrisLsFmufcv50owr5BGKrSMSjvgNzjW/us5OxrpxlrrWz75fX1/SnWPyPaSN3219B250eo2/k6jHj7kq5z832kj/7TzNyibxG4hau8UnE+Tbcw461E6ncSbdyDleyuhM7nqMDDL0/hZE9hTx/EzQ8QuFlg9heF8h3cwhDlyScojjyAnTqMV5pAzfz+FEIIIYQQQojNTtrNiU3vyJEjlXeWjoyM4LphqNHY2Ehtbe1qLm1DiBuXHxIB3PxTr+Do4w9w6MCPFhz7z8/fxzU33Epzx8YN8zQN7qgZokZ3+HFuGwqNDucU2+2nmLahUCzS2dlJxIrg+z6nT58mk8mwddtWTGN9vMSbVd6u4AdwZBJGC2GIlLDC+UWPjUDMhD0tUBtd+bWKpTHirWhGFOXb6JE6NMNC+S6BmyPwbXRD/vDEytKNKMktLyTR+VPY089QGPo+TvroRa8LnBS5M18j3/f/iHfcRbLrxZhLDJrE8tF0CyPWjBFrRgUegZudaUuX41wgpJSPb0/j29NomoEeqcOINITB0kw7VhW4uIVh3MIwmm5ixFow420Y0WY03VjFz1AIIYQQQgghVs/6uIMoxFUyPT3NyMgIEM4lGh0dBUDTNKkiWiZRzcNTGnZg4iqDBvPSWqJpmsarfv2P6Dv2NPnM/MH3jl3iK3//Xn7jPZ/EWCeByOXak5ggYbgcK7Vwq3WSVFlDobBtm/6+Plrb2qivqwdgamqKfD7PNddcs+6DzlQJHh4MW9NlbXD98L8DQ7C1Aa5pBF1GTaw5mqZjJbtxsqcAMKIteMXwtdYvT6Inu1ZzeWITC+cWPYdY83Nw8/3h3KLxAxefWxQ4FId/SHH4R0Sbn02y66VE6q+TWTerQNNNjGgTRrQJpXwCJ0fgZPDdLMxUB4WBUQrfTqGho0dqwxlGkTrQwjBIBR5ecRSvOIqmGRix5jAwirWg6Rv77xRCCCGEEEIIMZf8C0hsaocPH65sDw0NEQThzYW2tjZisdhqLWtDyHoRpr0ExcBiwktiB+HLTa1hY2iX1i8sWdfAa37r3XzuI/cuONZ/4hke+MbnedHPvWFZ1r2WbYum2RZNA43UJOOMDI/gei6BUoyNjVEsFGlra8MwDGzb5ujRI2zZ0sWWLVvW9Y3MQIUVRKN56KmDuBW+b/xsGsYLcNsWiMgbwNccM7kFN3cGpQLMaBN+cRSFwrenMRMdaJr8oYnVZdX00rDr16jd9hqKIz+iMPxfKC9/kasU9tRT2FNPYdb0kux6KfHW2wiczIK5OEuhWzUYsebL+wREGO5EGzCiDZgqCKsVnQy+k60Ef4oA38ngOxk0NHSrFj1ajxGpnw2MlI9XGscrjaNpehhCxdsw461oevW5gEIIIYQQQgixUUhIJDatkZERUqkUAKVSqTLLxTAMtmzZsppL2xA8DHJ+2FIqqnnYMy83jjKIa5c+CHzXzXdxx0tew4Hvf23Bsfu/+ilqG5p55P5/5xX//ffYet2zr2zx60AsGmPr1q1MTEyQyWYAyOVzlMolOjs6icXiAOw/nWPfMw6/+myN52yJrOaSL5sfwGA2bDd3fAraaqA9GVYQJS0JiNYq3YhixNvDCiLdRI824tvToAJ8O4UZa1ntJQoBgBFtoHbbq6npeTml8f3kB7+HXxq96HVevp/MsU+TPf1llJsHLmPGjWbSdvv7JChaBpqmY0TC8CcMjPJheOdkUJXASOG7WXw3i8sAulWLEa1Ht+oqYZBSAV55Eq88iZ3WMKJNmPFWjFirtMoUQgghhBBCbEgSEolNKQgCjhw5Uvl4YGCgMpeos7MTy5J3jV6puD47iyiqzbbxsQOTuH7pIRHAy1/3Vk4dPMDU6OC8/YHv85+f+2vscpGHv/PlTRESAei6Tnt7O4lkgrGxMYIgwPM8BgYHOV5/N20xn0G3gWkvyheeLtAVydHSsv5uRHrBbEs5BYzlIV2Gaxpgl+QMa5pV01NpM2fEW8KQiLDlnIREYq3RjCiJzp8i3vGT2KlDFAa/j5M+fNHrlJu9/CdVHoGbl5BomYWBUR1GpA6lulFefmaGURYVzP79JHBzBG4OmKnqitSjR+pnq4eUwi9P4ZengKMY0cawJV28TQIjIYQQQgghxIZRZVy4EBtfX18fhUIBgGw2SzqdBsCyLNrbZSD1cohpHvpMW7moPickUpdf9hGJxfmFt7wXvcpwabtcBODg/h9QyKYv+znWo9qaWrb2biUej6OAE9FbGFKdPFHqZsKrAWDCTfJfRyY5dfoUvn/h2RtrTdSE65rD6qFzXfNsD/IO9GfCEEmsTeFN2nBWlm7EwwHygPJtfCe3mksTYlGaphNrehbNz34bLbe+h3j7XaDJ+6rWK00LW8xZyW4iDbuJ1O2cmTs0/w1BgZvHLQxhpw7jZE7glSZQgTPvHN9OYaePURzZS2n8EZxcH4FXWslPRwghhBBCCCGWnYREYtNxXZfjx48DoJSiv7+/cqy7uxvDkN5Vy0HTZquJTC3AmGnD46kre9np2XkjL3j16xc9HvgBT+z9zyt6jvXIsiy6u7uZbriNwejuBcc1FI/ku5icmOLQoYPkC5c+O2M16Rp01sJ1TeFMopoINCfCkOjhQZgqrvYKxWKsmp7K9tzqIb88uRrLEeKSWMluGna9nrY7P0xN7yvRrdrVXpK4AmFglMRKdhFt3EOk/lqMeBuaPr8da+AV8YrD2Kkj2OljeKUxlG/PO8d3MjiZExRHH6Q49jBO9gyBW1jJT0cIIYQQQgghloW8LVJsOidPnsRxwneGTk9PUyyGd5cTiQQtLdL+aDkldQcFJHQXDYWrdMyZ6qLLlZkeZ9fNd3Fw/w+YGDpb5QzFvm//G9v33DJvb019E/VNbVf03GvdqVIzTwc7qx5TaEx4NQw69fRoGY4cPkxXV/e6m78Vt8KgyJ/zbVT24InRMETqrIGm+OqtTyxkxNvQjAjKdyptnFTgErhZlG+jScsmsQ4YkTpqt72qMreoMPS9SitFsX7pZgLdTECik8ArETgZfCeD8suVc5RfxiuO4hVH0YwoRqQBPVqPbsz+sgncPI6bx8memgmhujGT3Wjnyl+FEEIIIYQQYg2TkEhsKqVSidOnTwPhXKKBgYHKsZ6eHvnH/DJrjxRoJ3xXrY5i3K254sf80t/8CX3HnrzgOenJEf7+Xf9z3r5t19/Eb77nH6/4+dcyDx0NheLc97EC5nxPK8X+XCfdkQwAg4ODaLpGZ0fniq/1SmgamOf9qHoB7B+ErA0v3QE3tK7O2kQ1Gka0Ea84BoARa8YrjgLglaewkusrqBSbm2ZESHQ+n3jHT+KkDlEY+j526tBqL0ssA92Mo5txzEQHgW8TOGkCJzOvnZzybbzSGJTG0IwIeqQ+DI3MROWcwC1gp48RuHmijQsre4UQQgghhBBirZF2c2JTOX36NEEQtj0bGxurVBTV1dVRX1+/mkvb8ExteQbH3H73qzCtyMVPrNAwrQi3vehVy/L8a9n18Ule1nAcnXMzh85LUjSNKb+Ow5NhlAThz8F6lyrD0UmYLoVh0fdPw6np1V6VUIGHmx+gNPZQJSACMKPNaDPfm+cGxgux3miaRrTpRuqu/VUiDRIEbDS6EcWMtxOpv45ow27MxBZ0MznvHOU7+KUJnMwJ7NRh3MIQgTvbytUtDqMCb6WXLoQQQgghhBCXTCqJxKbhui59fX0A+L7PyMhsm5je3t7VWtamkPZijLjLM8fhpue/nPGhMzzwjc9d9FxN02nu6OF1936Itu5rluX517qeSIY6wybtx1kQEgGogKfda9jlHcc0DQJ/ecK71dKfCcOhc3Qd2pNg+4tfI66uwLfx8oO4hUFU4M4/5hXxy5OVkBK1vr//xOakfJvS5BOUxh7ESR9d7eWIq03T0TQdNIPw92qVtrkqAOXP/BeApoNS1c8VQgghhBBCiDVGQiKxafT19eH74Z3jyclJPC98d2dzczOJROJCl4orMOnGGXHqluWxfN/j//2fj3Hg+19d0vk3PvfFvOa33k0kGluW518PBp160v4Fvp81nazRzIjfRI+Zobm5eeUWdxXURGZDovoodNVBxIDhXDifqFHmE62YwM3j5vvxiqOo88KfwM3ilSbmvcsewtZzQqwHSinc3GmKow9SnngU5ZcufpFYt1Tg4ttpAje74HXrHE0zwnZz0Xp0q5bz35hhJtrRdGsFViuEEEIIIYQQV0ZCIrEpBEHAmTNngPBGz+joaOVYZ+f6mseyVgUKRt1aWswiET0M40adGibc5EWuXJpyMc8XPv4uTj69f4lXaGzffcuGDoiUCufzzP34kXzXeXOJFtJQPJLvYntNka7urhVY6dXTFIe8A3VRaJjzR23oUk20UvzyNG6+D688dd4RhW+n8EoT84bAQ3hz1Yi3Y8ZleJRY23w7TWl8H8XRh/BLoxe/QKxb4RyizMwcomLVczTdmplDVI9uVZ+zqOkWVrIbq3bbVVytEEIIIYQQQiwfCYnEpjA0NES5HN6kTKVS2LYNhLOIpIroyvlKo9+uJ+9HyfkRtkdTjLs1pLzlKeOYHh/m8x+5l/GhM0u+Rtd1hs9s3DZApcDkh5lreE5yhK5IONdl0Klnwqt+02ouhcaEV4PTsBPTWN+/BrbUwh1b4NGRMKgEaEnA9S0QW9+f2pqmlMIvjeHm+/Cd8+YKKR+vPBm2lTtvHoemRzDibRjRxrB9kxBrkApcylNPUxp7EHv6INIybOMKvBKBk8F3MgvC7HM0IxqGQpF6dLP63xk1I4oZb8OMt6FHGtC0xd+oIYQQQgghhBBrjdxCE5vCqVOnKttSRbS8PKVxttxIKQhbqpQDkwO5bmoNG30Z7pH0HX+af/noOyhkU4ueo2kahmlx50t/nv3f+yqB7xMEPv0nnrnyBaxBI04N38/spBhEmPQS/HzTIRK6u6QqonM0FN8bqOXObfOrkdaLuAW7W8JKIoCdTXAmDbuaoePiOZm4TCrw8IrDuPl+Aq983jEnbClXnkYxv92cbiYx4q3oVp3cPBVrlpvvpzj6EKXx/Siveosxsb4ppVBeEd/NEthpVOBUPU8zYmEbuUg9ulH9DS+6mcCMt4XBd2R52uoKIYQQQgghxGqQkEhseOPj4+Ry4Tvdc7kc+Xx44yeRSFBfX7+aS1v33EDntN2IE4QvJQEw5tZgByblwKTNKlxRAPHUg9/ha//4Pjy3+k2cc5o7enndvR+irfsabnvRz/IvH/tDJkf6mRg+i+vYWJHo5S9iDVEKnip2cCDfUwmCSkGEH2R28JzEyJKqiCqPhcbZDByagBvbrtaKr4wfgOOHgdA5GtDbANc0hC3lzumpC2cQWcYKL3KTCHwbLz+AWxhCBe78Y14RvzyBb6cXXKdH6jFjrejW8rSdFGK5BW6O0vgBiqMP4hUGLvl6M9FFpHE3xaHvX4XVieUQBkN5fCdL4GQWvIado5sJ9EgDRrQOTa/+9wbdqpmtGFqk3ZwQQgghhBBCrDcSEokNb7Eqoo6OjtVYzoaiawpjpg2PpzTG3BpcFd6lt5WJq3QiWnChh6hKKcX9X/0n7v/qPy16Tk1dE9FEkq27nsN/e8PbK7OH2rqv4S0f+Bzf/D9/ycjZE3ius2FCojN2I/vzvQv2j7h1pHMxwpZIS0/lNOD/HoUbWtdeNVHWhsFs+BntagZTh9poWD1UV+WPU9MkILoafDeHlx/AK46i1Pyf5cDJ4pUnFg5113SMaCNGrBXd2Bg/e2JjUcrHnj5EaexBylNPgbq0AWaamSDeegfxjruwarbi5fslJFpjlAoI3HxlxpBa5M9Yt2owIg3okTo03ap6jhFtwIi1hsGQuTxtdIUQQgghhBBiLZGQSGxomUyGyclJAMrlMqlU2LLMsiyamppWc2kbgqEptsbSHCu2MOrU4RGWdhgEtFkFIvqlB0SuY/O1f3wfTz/03UXP6dx6Hf/97X9FbWMrur5wrkkkFufn3/SnBEFQ9fh6tT2aYmskRZ/TuOBYObC4lIAIwgBmugxesHYCFi+AoSyk5nQyG8vDC7dBb/3aC7M2Kq88hZvvxy9PnXdE4dvTeKUJlG/PO6JpBkasBSPWgqbLXy/E2uMVRyiOPkhp/GECJ3OJV2tEGneTaL+LWMvN8wIF3aoBzQTlXeD6xR7WlIqUZaKUT+DkwhlDbhbUwr+DaGjoVi16tB7DqoNqr1WahhFtwoy1hm0yJewWQgghhBBCbHByF0dsaHOriEZGRirb7e3tGyo8WE1uYOCjVcZ6mwS0R/JYl1FBlM9M8y8ffccFZwldf+vzee3v/DnRWPXh0XNttD9jTYMX1p/mq1M3kg9mb1p1RzLcWdNfaUE3MTFBqVQCwraKLS0tAJiGwc5rd2Iaszc3a6NrJyCyPTgxHQZF59REoSUJ9TEJiK42pQK80hhurm9hdVDg4dlT+OVJVDD/RrhmRMOWctFGNG1j/cyJ9S/wSpQnHqE4+iBu7vQlX2/E2oh3PI9E209gxKq/ucSINdN2+/sW/twsgW7VYMSaL/k6EVKBR+Bm8Z0MgZODyt9GZmno6NE6DKsOPVIH2sJfepqmY0SbMOJtmLEWNCOyAqsXQgghhBBCiLVBQiKxYZVKJYaHhwFwXbdSUWQYBm1ta3QIyzqT8yP02w3oQLuVZ9pL0GoVMLSFN2kuZmzgNJ//y3tJTYwses5P/n+/ws/8yu+g62sk1VgFMd3npQ0n+fr0bhQatyWHuDk5XAlQcvkcZmGEWsDQDba2NWAaRQB27NxBc1P1djprQdQM5w/l7HDe0JZaaJ7p7HN4Ap7bDboERctOBS5uYRg337+gOkgFNl5pgqCcQjE/+NXNJEa8Dd2qRZMET6whSgU46WOUxh6iNPk4BBeea3c+TY8Sa72NRMfzsOquXdL3txFrlrBnhajAnZkvlF40mNM0Az1SjxGpn6n0Whhga7qJEWvGjLVhxJqlAlIIIYQQQgixacm/hsSGdfr0aZQKw4rx8fHKdmtrK6Yp3/pXKuXFGLTrONfiLKIHdEQu/V3UACeeepgvfPxd2KVC1eO6YfCzb3gHt7/41Ze52o2lzSrw/Lqz1Bo2XZFcZb/ne4yPjc+e19aKaYTf641NjTQ3rf0bmN21MKZDZ838CqeIAY4PMfnRXTaBV8YtDOAVhhZUBwVeEb80jl+lJZcRaQhbMJkXr+YTYiV55UlKow9RGnsI3z6/VeLFReqvI97+PGKtt6IbsauwQnG5lG/PBEMZAq/63xU03ZwfDFVpwarpFma8FSPWGgZDUv0ohBBCCCGEEBISiY3JdV36+/sB8H2fsbExADRNo729fTWXtiFMuAlGndpleayHv/sV/uOzHyMIqg+VjiVq+JW3fYgdN96+LM+3likVNspZSrXM9fHJBfsmJibwZ76ONckaamvrADBMg21bty3jSq+OqAHPboeyB8dn7u+aOlzbFFYVSbHK8vCdLG6+H680Fn7TzRE4WbzyOIF73k3YmVZMYRsmmc8h1g7l25QmH6c0+iBO5tglX69HGkm0/wTxjrsw41JlvJYEfjmcL2RnUH6p6jmaEQmDIase3Uouck4UM96KGWubaYspv0yEEEIIIYQQYi4JicSG1N/fj+eF74yfmpqqbDc1NRGNyg3OpQoUDDn1NJolagwHpWDUrWHSrX4j5lL4vse3Pv9x9n3n3xY9p6mti//xjo/R2rXtip9vrXOVzt7sNizN5/l1fZd8fT6fJ5cLq4p0XaetffZm57at27CstdtmDqC7DnY2haGQUjCaD0OjXS1SPbRcvPIkbq4f356ef0AF+E4KrzSxoN2cppkY8RaMqLRiEmuHUgo3d5ri6IOUJx5B+eVLewDNJNZyM4n2u4g07pZqkjUk8IphMORkFrwenaMZsbBaKFK3aEWjbsbD+ULxNnSrToIhIYQQQgghhLgAueMjNpwgCDh9OhxOrZRiZGR2xk1HR8dqLWvd8ZVGn91AwY+Q9aNsi04z7SVIe/ErfuxyMc+X/vbdHH9y36LnbN31HF5370dI1jVc8fOtdSkvxvfSO0n54c2uDivPtfGlt0ryfZ/x8Tlt5lrbKm3mGhoaaG5eG23m8k4Y+Jhz7scmLNjTCg1zOjtpGtzSOf88cXmUCvCKo7j5/oWzOwIPz57EL02i1PxKPs2IYcZa0aMNcgNdrBm+naY0vo/i6EP4pdFLvt6q3Ua8/S7irbcvWnUiVpZSCuUV8Z00gZNBBW7V83QzgR6pw4g0LFrNqFs1YSu5eBuGtTzVzkIIIYQQQgixGUhIJDac4eFhyuXwXcXpdBrbDt+JWldXRzIpN4WWwlU6Z8uNlIPwJcJTGgdy3dSbNpYWXOTqC0tNjPD5v/x9xgZOLXrOzc9/Ba/+zT/CtCJX9FzrwfFSM3uz2/CYHcDzQG4bLVaBRnNp744fnxjH88NquWQySV3dnDZz27Yt+5ovlReElUGTRWhJhFVDGrCtEbY3VG+vJwHRlVGBi1sYws0PLHg3vgpsvOIEgT2NYn67Od2qwYi1olu18s57sSaowKU89TSlsQexpw/Ced+zF6NbtcTbf4J4+/Owkl1XZ5HikigVELiFcL6Qk0Epr+p5ulWDEalDjzSg6dWrYY1I3WzFkMxJE0IIIYQQQojLIiGR2HBOnZoNH6SK6NK5Sud0uQknCEMLHxh3arCVie2adFh5DO3SbtKdM3DyIP/8V28nn5le9JyX/uKbecGr/uemuEFd9C325uYHRACeMvj/27vz+LjKen/gn7POkmUmyWQmbdO9tLQUWtnbCBRQBFxQWQQBWb1cFy6yefWHCiLXq2yiXBdAZF+kKigIggIVbNmXUpC1S9Il+zJLZjvL8/vjpNNMZibJtEkmy+f9evXlzDnPc+aZk5MTeb7n+33+3rMAX6j595BBuYFl5kLBXWtuzZo1C7pe2kBbOAlsiwJGX6JKRxyY5QMOmg5UsPLjiLPNBIzYVpi923Oyg2yjF1ayDVY6ktNP0f1QPLWcZKVxw4g1Id6yFom2lyDM3qE79CcpcFXvC29dA1xVS1kqcRxwAkPRvlJyEUDkrkMoQYKslUN2+ZwScfkCQ5IERfdD9QSdgLbqzm1DREREREREReF/NdOk0t7ejkjEmQCNxWKIxZzySh6PB36/v4QjmzhU2PDKBtK2AlNIaDXKYYi+gJGQYQoZipQ7uTOUDS/8A3/49dUwjfxrDKiaCyd9/Urse+jRezT+icSrGDi8YgueiczP2ddr6+g2PQhqhSdHB5aZq62thao6t3Wf34faQO3ID7oIrb1Ac3TXe1kCplU4aw2VTf4ksTFlpSMwYo0wE23Ook792OkwzEQbbDOe3UmSobiqobprISn8gVDp2UYUibaXEG9ZC7N3W9H9Ve8MeOpWwhM8FIpeOQojpGII24RtRGGlw7CNKCByH3qQIEPWKzJrDEFScttIMhRXlZMxxPsVERERERHRiGOQiCYVZhHtOUkCZuhh9FoatqaqYMGp+6XCRlCLQZeLKzcnhMCah+/AP1bfUrBNua8aZ1x2PWYu2GePxj4R7eXpRLNRgXcTwcy2gNqLT/o+QqWaP6C2U0dHR6bMnNfjha/SBwBQlPFRZs7vAlpjgC2crKGZlYCuAAkT2NQNLKgu9QgnNiEErGQHjFgTrFT3gJ02rFQ3zGQbhJXO2iXJGhR3AIqrmhkWVHJCWEh1vY1E6zokO9fnzTAZjKR64ak9GJ66Bmjls6dEFup4JmwDdjrSFxiKIV95QElS+tYX8kHWKoA8655JkgLFXdOXMVRTsNwcERERERER7TnODtGkEYlE0N7eDgBIJpPo7nYmTTVNQ01NTSmHNuEkbA2mkKBKNiwhQ5MshLQY1CLLzJlGGg/f9mO8+fwTBduEZi7AV759A/yBqRvIW1nRiHajDB1mGZZ4WrGiomnIc90b70U4EgbQV2YulF1mzqWXvpabSwVmOnErVPWrCCRLTrCIdo8QNsx4M4xYE2wjO9NM2AasZCesZEdOuTlJcUP11Drre+SZlCUaS2a8ua+c3Iuw0+Eie0twVS2BJ9QAd2A5AwglJqy0ExRKh2EXKA3oBIZ8UFx9gSHkBvN2BrBVT7AviM0/FERERERERGOBQSKaNPpnEbW0tGReh0IhyDInRIcrYrrQlPZBQEJQ60WX6UG1mih6HaLeSA/uu/HbaHx/fcE2iz7WgC9d+CO4PGV7OuwJTZUEPuH7CO1GGRZ4Cq/XtJNt22htbc28DwQC0DRnktTnq0RtbWnLzO1UVw4cNgtY3wpE+pKiqj3A4gDg4Zxu0YSVhtG7HUbv1pzsIGGlnJJyqW6IAU/uy1o5FHcQil4xlsMlymGbcSTbX0W8ZS2M6Kai+yvuILx1K+EJrYDiYipiKdlWygkKpXtgm4m8bSRFg6z5oeiVkLXyAm10qO5aKJ4gFFcVA9hEREREREQlwCARTQrJZBLbt28HABiGgY6ODgBOhkUwGBysK/XTZXqwPbXrCV9FEqjV4oN3yqN9+xbcfe0l6GrbXrDNymO/hOPOvAjyJH9S2LBlaMMo0edTU/ANUV5up/b2dpjmrjJzfp8fgHO9z5kzd7fHOlLcKrB3AAh4nfeLA8AbLU55uemMUxTNNhMwYk0we3fkZAfZRgxWoh2WEcnpp7iq+hZ294zVUIlyCGEj3fM+4q1rkex4A7DTQ3fqR5JdcNceCG/dSmiVe7GcXAnZZgJ2OgwrHYawknnbSIoLiu6HrFdCVr1528iqG4o7CNUThKz7+DMlIiIiIiIqMQaJaFLYtGkTRN9i7e3t7bBtZ1I+GAxCVXmZD0ebUYbWdP4nfYvx0YaX8cBN30UyHsu7X5YVfObsS3HIJ0/c488az2wBvBKrx8ZUNU6sfgcuubh1NgqJx+O7ysxJUlaZuZmzZsLlGpsyc7YAoinA587ePssHzKsC1H4Pg1e4gI/PcsrM0fBZ6TCMaCPMZDsgsrOD7FQPzGQ7bHNAEFeSobhqoHpqWYKLSspMtCPRug6J1hdgpTqL7q/7FsITWgl37QGQFffQHWjECSEgzHimlJwoEOCTFDcUlw+K7odU4Gcla2VQ3UEonlooeuVoDpuIiIiIiIiKxNlzmvBM00RjYyOA7DJc0oAJdHLYAtia8qFcSaNGS0AIYIdRgS4j/xO/xXj56Yfx6O+ug23nD4i4PGU47aIfY69lh+7xZ41nvZaGp8Pz0Ww4E2HPhufhU/4PsacPS+eWmavNlJmrqKxAsHZssuaiKWBbFEiZTnZQuQ6U6cCSQG7QaCcGiIZHCAEr2QEj1ggr1TNgpwUr1QUz2Q5hGVm7nLU8aqG4qyFJkzs7j8YvYaWQ6HgdiZa1SIffL7q/7KqGN7QCntBKqB5mAZeCEDaE2dsXGIpA2EbedrJWBllz1hiSZD1vG0Wv2JUxpE3tsrJERERERETjGYNENOE1NTVlSm91dnbCMJwJjaqqqjHLqpgoLCFhS8qPuKUjYrkhw0bUdiNs7tlT2rZt4W/3/R/WPn5/wTZVtdNw5uU3IjRz3h591ni3LVWJp8PzkRS7sjga01V4K16HZWUtg/QcWkdnBwzTub49Hg98fh8Ap8zc3DlzR71kj2kDzVGgs9/yE9uiwHHzgblVDATtCWFbMBPNMKJNOdlBwjZgJTtgJTtzys1JirtfySau5UFjTwgBI7IR8dZ1SLa/UrAMWUGSCndgf3jrGqD79+Z1XAJC2LCNGOx0D6x0BBD5H/SQtQooug+yXlkwU1Fx+aF6gix1SURERERENIEwSEQTmm3b2LTJWfxaCIHm5ubMvrq6ulINa1wybBmbU1VI2c6vvQ3gtd4ZqFRS8Mjmbh83lYzjof/7Ad577fmCbWbttS9Ov/RalPsm90LjQgBvxKdlBYh2eik2EyEthjo9fxm+oSQSCfT09ADYVWZO6ls7aubMerjdo1uOyRbAB51Aut/cYZkOzKwEBBgg2l3CSsPo3QYjtjXniX1hJWEm2mGnuiGQXW5O1iqgemoha1zkiUrDSvUg0foC4q3rYCWKD4BrFXPhCa2Ep/YgZpmUgBAW7HTUWWPIiAAid+08CRJkvQKy7oOi+4B8WYqSBMVVDdVT6wSGFD6cQ0RERERENNEwSEQTWnNzMxIJJ60hHA4jmXSeYK6oqEB5+Z6vrzNZWELCxmQ1DOFM8JiQ0J4uQ0qoSNkqQlpst9bMCXe24p7rLkNz4wcF2+y38hh88YLvQdMn/8SRJAFHVW7CH7uWImFnB4okCEQsF+pQfJDItm20tOyahK2pCUDXnPI+5RXlCAZHv6yiLAEBL7AjCsgyML0cqPE437mxBwiVOWsP0fDYZhxGrAlm7w6IAZOzthGDlWiDZUQH9JKguPxQ3EHIKtdoobEnbAPJzvVItKxFqvsdYEDwciiyVgFPXzk5rWzG6AySChK2CTsdcUrJGVHk+/lJkgJZr4SiVULWK/IGhiRJhuKugeIJQnUHuP4ZERERERHRBMcgEU1oGzduzLxmFlFhiiRQo8XRkq6AIWS0GWWZgNHu2rbxXdx7/WWI9nQUbHPUiV/FUSeeN+pl0MaTMsXA0b6P8NfuvSH6Mn0qlCQ+6fsItVp8iN75dXZ27ioz53bDX+UHAEiyhHlz543Z+a31OtlSVR5A73f5VLqYSTRcVqoHRqwRZqJ9wB4BO9UDM9kO20xk75IUqO4aKJyMpRIxYk2It/wLibaXIcze4jpLClzV+8Jb1wBX1VJIMv+v51gSttG3vlAYtpH/IQUnMOTrKyVXASD3hi7JKhR3wCkl56qBJHPtMyIiIiIiosmC/6VOE1ZHRwfC4TAAIBaLIRp1nrp3u93w+/0lHNn4VKvFEbN0vBuvhQVnzQcVNkJaDJqcW2ZmMO+8/CxW//JKGOlU3v2qpuOLF3wPyxo+tcfjnohm6FEcWLYdr/TWY46rC6sqN+9WphYAJJIJdPd0A3BK//QvM1dfP/pl5nbSFWBRAPCqwMvbd5WYW1DtlJybQnHAogkhYCXbYUQbYaXDA3ZasFJdMJPtEFZ2uTlJ1qC4a6G4qyHlK/NENIpsI4pE20uIt6yF2but6P5q2Qx4Qg3wBA+BoleOwgipEGGldgWGzPwPJ0iy5mQM6X7IWv7Ma0nWnDJyniAUVzXXiyIiIiIiIpqkGCSiCat/FlH/UlzTpk2bUpkrwxWzdPRaOtyyiV5bhy5ZCGoxqNLwywUJIfDcX+7GUw/+qmCbssoqnH7ptZi9cL+RGPaE9bGyHfCpCcxzde92AMUWNlpbWjPva2pqoPeV7SsvL0ddaGwy5qZXAHtVA1pfnGK2H4imgcUBwM2/IgUJ24IZb4YRa8qZqBW24WQNJbsgBiwSL6sep6Sc7uO9jMaUEBZSXW8j0boOyc71gCguuC2pXniCh8AbaoBaPovX7xiyzSTsdA+sdBjCSuZtIyl6X8aQH7LqLdDGBdUThOoJQtb9/BkSERERERFNAZzeowkpGo2ira0NAJBKpdDd7WRaaJqGmpqaUg5tXOoxXdiW9kFAQkCNQ7VsVCopKEUEiEzTwJ9/+xO8/s/HCrYJzpiLM799I6qD00di2ONSr6WhTDGGbCdJwHx39x59VldnJ9JGGgDgdrlRVV3lHFuWMHfe3BGdvIv3fSVvv2pmbhVYUgtUe7Lbzq9i5tBgbCsFs3cbjNg2CNsYsC8BK9EOK5V7bchaJVRPbcGn+olGixFvRqJlLRJtL8IemO02JAmuqiXw1DXAXbOcJRHHkG3GnYyhVA+Enc7bRlLcUFw+yLoPsuLJ20ZWvU4ZOU8QslbBwBAREREREdEUwyARTUgDs4iEcIIdoVAIssxyKP11Gh7sSO8q9SNJQJWa/ynjQuLRMO7/2Xew+d3XC7ZZsN8hOO2iH8PtnZwT3EIAbydCeDE6E8f4P8RsV7ETqcVJJBPo7u4B4JSZq6vbVWZuxowZ8LjzT/YVy7KBll6gvdcJCi2sARQJmOUH5vkBJc+vE+cP87ONXme9oXgLhLAH7IvCTLT3LRbfnwTFVQXFUwtZGZvSgUSAE2BItL2CROtaGNHNRfdX3EF461bCE1oBxVU9CiOkgYQQEGZvppTcwCD0TrLqdTKGXD5Isit/G618V8YQA9NERERERERTGoNENOEkk0ls374dAGCaJtrbnQXgZVlGbW1tKYdWUrZwlpruP4Hfki5Hu1G2R8ftaG7C3ddegs6WrQXbHPLJE/Hpsy6BokzOW0rKVvBcZC42pZyJ0GfD83FizduoUPI/ub2nbGGjtbUVAk7ws3+ZubKyMkyrmzYinxNNAVsjQLqvolTSBGJp4BPzgMr884qUh5XqhhFthJnsGLBHwEr1wEy05ZZ/khSo7hoo7gAzL2jMCGEj3fM+4q1rkex4HSgQZChEUlxwBw6Et64BWuUCZpyMASFs2EbMWV8oHc4pT7mTrJVD0Z2MoUL3FEX3QfEEnYzFAuXmiIiIiIiIaOqZnDO6NKlt3rwZtu08pd/W1pZ5XVtbC02bmpOttgCaUn6oko16VwRCANvTleg29yzbZNO/X8P9N34Hid5I3v2SJOPTX7kYK449ZY8+ZzzrMLz4e3gBItauLI+UUPGP8AJ8rurdokr2DVdXVxfSaScA5XK54K/yA3DKzM0boTJzkRSwqV/FM0kC6sqd4BCnfYcmhICVaIMRa4SVHvD7ISyYyU5YyY6cJ/0lWYfiqeUi8DSmzEQ7Eq3rkGh9AVaqs+j+um8hPKEGuGv3Z8bbGBDChp2OwE6HYRkRYEBmIuBkmMpaOWSXD4rmA+Q8/5dekqDoVX2l5GohK4z+ExERERERUS4GiWhCMU0TjY2NAADbdrItAECSJIRCoVIOrWRMIaExVYW45QTIFNhICyUrqLE7Xn32L/jz7T+BbeV/all3e3Hqf12DRR9r2KPPGe9ajfK857LNKMeLsZloqGga0c9LppLo7nKiNxIk1IXqIPcFE6ZPmw6PZ2Se/q7QnfWH4gZQ7gJmVgIuxdn3bgdw0HSWlctH2CbMeDOMWBNsMzFgn+GUlEt15TztL6teKO5a5yl/nlgaA7aVQrLjNSRa1iEdfr/o/rKrGt6QU05O9QRHYYTUn7BN2Eakr5RcFEDuAwgSZMh6RV/GUCUgKbltJBmKq9rJGHIHICn6GIyeiIiIiIiIJjIGiWhCaWpqgmE4T+Z3dnZmXvv9frjdU+/p5rQtY0uqCinb+VW2AWxIhFAmp1G5m6XQbNvGUw/+Cs8/ek/BNv5AHc68/AbUzVqwW58xkSzxtKE5XYGNqZoBewR0yYIQIxdMGVhmrqq6Ci6X8+S31+vFtOkjU2YOcMY81w9E00C1J3t7rdeZnmQoYxfbSsGMbYPRuy0nO8g247CSHbBS3Tn9ZL0SqjsIWduzso9EwyGEgBHZ6JSTa381t8zhUGQN7pqPwVvXAN2/N7PdRpmwDVjpCOx0D2wjlreNJCmQ9Uoout9ZOyjPz0SSFCieAFR3EIq7BlK+rCIiIiIiIiKiAvhfkTRhCCGwadOmzOvm5ubMvmnTRm7yfKIQAticqkK6L0BkCgmtRjkMoSBlq1AgUKYUt95EOpnA6l9dhX+/sqZgm/r5++CMy65DhX9g0GRykiTg8MrN6OjyImw50RS3ZOBI3ybMcoVH9LO6u7qRSqUAOGXmqqurM2OYN29eJqNoJITKgIU1zppEW3qcbX43sDgAlPHB8wzbiMGINcGMt0AMKPlkGxEncyhnclfqe5Kf5Z1obFipHiRaX0C8dS2sRGvR/bWKufCEVsITPJhr1YwyYaX7soXCsM3evG0kWYWs+aC4fE5gKE/IXpI1qJ5aKO6+8pVyblYRERERERER0XAwSEQTRnNzMxIJp7xTOBxGMuk8IV1eXo7y8vJSDq0kJAmYrkexJemHIRS0psthwgkiKBBQpdw1DAYT6WrHPddfhh2b3yvYZt9DP4ETv/Z9aPrUytrSZRuf9H2Eh7v2QUDrxSd8G1G+m5lahaRSKXR1dQFwysyFQqFMUGja9Onwekdm4talAIsCQLAvsWWuH+hKANMrgBkVLDG3k5XsghFrhJkcuH6LgJXqhploz8nSkCQFijsAxR3gk/w06oRtINm5HomWtUh1v4N85ckGI2uV8IQOhSe0ElrZjNEZJAEAbCvprC+UCkNYibxtJEWDrPmdUnIFMg8lRXfWF3LXQnFVMdOLiIiIiIiIRgRnsWjC+OijjzKvW1paMq+nYhbRThVKGjVqHG/2ToPVFyBSYSOkx6AVESTasfl93HP9pYh0tRdss+oL5+Dok/4Dsjw1J6VqtAQ+W/0uAmocilTcZOxQBARaWluyysy5XU4gzuPxYPr06UUdzxZAZxyo8QJyv6DPjApgQTWg9XvgXJGBgzk/DMBZLN5KtMGINcJKRwfstGAmO2AlOyBsM2uXJOtQPEFO2tKoE0LAjDUh3roWibaXIQpkohQkKXBV7wdvXQNcVfswmDmKbDPuBIbSYQgrlbeNpLicMnJ6ZcEMLln19K0vxDXNiIiIiIiIaHRwdoAmhM7OToTDTmmv3t5eRCIRAE5JLr/fX8KRlVbU0tFteVGppNBteaBLFkJarKggxruvPoeH/u8HSKfyP92sqBq+8B//Dx877PiRGva4EjZd8MoGNHnooFpIK3JCdpj6l5nTdT2rzNzceXOLKjMXSwPbIkDSBEwbmFYBeDVgSa1TTo5yCduEGd8BI9YE20wO2Jd2SsoluyCQfY3IaplTUk6r5MQtjSorHUWy7SXEW9fC7N1WdH+1bAY8oQZ4godA0StHYYQkhIAw47DSPbDT4Zy1y3aSVQ9k3QdF90MqUI5S1sqdUnKeIBStYjSHTURERERERMQgEU0MGzduzLwemEU0VSdnu003tqUqAUjwqSnIkoBXNoYdIBJCYO1f78ff7r8ZQuTv4y334fRLf4o5e39sBEc+fmxKVmFNZB7muLpxZOWmkpRaS6VS6Ox0SpoNLDNXVzcN5WXDK6Vo2UBzDOiI79rWFgf2CwH7hrIzishhWymYsa0werfnTOjaZhxWsh1Wqienn6z7nKf6C5SEIhoJQlhIdb2NeMtapLreAoRVVH9J9cITPATeUAPU8llT9m/laBLChm30OusLpcMQwszbTtbKnDJyug+SnH/RN0WvhOKuheoJ8t5CREREREREY4pBIhr3otEoWludhbj7r9uiqipqampKObSS6TC8aE5nP11cUcQaOZZp4i93XItXn/lzwTa10+fgzG/fgJpQ/W6Pc7yyhIQXozPxdqIOAPBhMoBpWhSLvYXL7Y0GAYHW1tZMmTm/3w+P2wMAcHvcmFE//DpwTREg3C8JxqsBMyuBlJVvyfOpzTKiMKJNMBMtwIAAqZ2OwEy2wzZi2Z0kGYqrCoq7FnKBp/+JRoIRb0aiZS0SbS/CToeL7C3BVbUPPHUr4a5ZDknWRmWMU5kTGIr2lZKLFAzeyVoFFJfPyTQs8HNQXFVOxpA7CFllqicRERERERGVBoNENO5t2rQp87q1tTWT9RIKhaAoSqFuk4ItAAEpKzuoOV2ODmP3nzJOxCJ44Of/DxvffqVgm/lLD8JpF/0YnvLJV5Yoaun4R88CtJnZGTpro7NRq/UioMUL9Bx53d3dSKacyI6mapmgpyQB8+bOK6rMXF0ZEEk5AaFpFUDA4xwnkgK2RoBZvtH4BhOLmeyEEWuClewcsEfASnXBTLTnrB0iSSoUTwCKq4brt9Cosc04Em2vING6FkZ0c9H9FU8Q3lADPKEVUFxVozDCqU0IC3Y6Aisdhm1EAZFbnlSCBFmvgKz7nZJ+Uu7/P5F2Bps9QSjuAAPORERERERENC5wxovGtVQqhW3bnPUXTNNEe7uT6SFJEoLBYCmHNuosIaEx5YcAMNfVDQDYnq5Ej+nZ7WN2tm7D3ddego4djQXbHHT05/HZsy+Hok7O24MA0GPlPrFtQcbfwwtwYvXb0IexPtGeSqdT6OzYFayoq6uDLDtBoVBdHcrLh1dmbiePBuxVDSgy4Oo3N1nhmtprEQlhw0y0wog25mYH2SbMVAesZCeEnV0mSlJcTkk5VxWkIoJ1RMMlhI10z3uIt6xFsvMNoMAaNoVIigvuwIHw1n0cWuV8lpMbYcI2+7KFwn33jtyyrJKkQNYrnVJyWgWQ514hSQoUdw1UTxCKu4bZXURERERERDTuTM5ZYJo0Nm/eDNt2Juzb2tpgWU5Zl9raWmja5J1oMYSMxqQfCdv5jo0pPyCAmL37Tx1vee8N3HfDfyMey1++SJIkHHv6f6Hh+NMm9WRjpZLGkZWb8GR4Yc6+aVp0TNYlGlhmrspfBY+nr8yc24X6GcMvMwcAmgIsrAaCZcCL24GE4axBNL/KySCaxD/OgoRtwOjdASPWlJMdJOwUzEQ77GQ3BLIDgrJaBsUThKxVTOrfAyodM9GOROs6JFrXwUp1Fd1f9y2EJ9QAd+0BzEQZYcI2YKV6nDWGzN68bZzAkK+vlFwF8hX0lGQNijvgBIZc1ZDkyZ31TERERERERBMbg0Q0blmWhS1btgAAbNvOrEsEOFkXk1XaVrA55Ufadn49LQAfJmugwd7tUmhvPPc4Hr71f2BZ+RfV1l0enPLNq7H4wMN3d9gTyhx3D/YzmvFWfBoAQIWFj1c2YpGnY0w+v6e7B4lkbpk5AJg7dx7kIiYUQ+XAohpA7+uyJABs7gH2DjjrEk01tpmEEWuCGd+Rkx1km3FYiTZYedZ5UXQ/FE8tZNU7VkOlKcS2Uki2v4ZE6zqkw+8X3V9xVcMTWglPaAVUz+TOoh1rtpVygkLpHthmIm8bSdacwJDug6zlz/KUZM1ZX2hnYIgZiERERERERDRBMEhE41ZTUxMMwym/09nZmXldVVUFt3vy1s/amvZlAkSmkNBqlMMQClIAVNOGX00O+1i2bePp1bdizSN3FGxTWV2LMy+7AdPnLtrToU8oB5dvQ6tRjpSt4pP+j1Ct5p8cHGlpI43Ozl3BqFAotKvMXCiEioqKnD4JA4gbQE2/+IVbdQJBgQExjSqP82+qsdIRJziUaAVEdlkoOx2BmWyDbQzIDJBkKK5qqO4AJGZk0AgTQsCIbES8dS2S7a/kZLQNSdbgrvkYvHUN0P17M+gwgmwzkSklJ6z8f1MlxeUEhXRfweCxrLqhuINQPbWQdT+zD4mIiIiIiGhCYpCIxiUhBDZt2pR539LSknk9mbOIAKBeD2NjshoJW0VruhwWnIlBBTa8cnrYxzHSSfzhV1fj7ZeeLthm+ty9ceZl16OyunaPxz3RKJLAMb6PoEkWtDFYgwjYVWbO7gti+H0+eL3O5KPL5cLMmfVZ7W0BtMSA9r4EMq/mrD00sxKYXw2onDOGmeyAEW3KLdslbFjpbpiJ9pzJ+Z2loJwyUPwzSCPLSnUj0foC4q3rYCVah+4wgFYxF55QAzzBg5jZNkKEEBBm3FlfKB2GsPP/LZUUNxSXD4ruh6TkfxhFVr1QPSEonlooeuVoDpuIiIiIiIhoTHB2jMallpYWxOPOzHg4HEYi4WR5lJeX5820mExcsoWgFsMrsfpMgEiTLAS1XmjS8IIZ0Z5O3Hv95di28Z2CbZYctAonf/0q6O7JlXYSt1T02jpqh1Gaz6sUt1D8ngr37LqWNVVDILArODd33tysMnPRFLAtCqT6VUzrSABfmAX4J9ePrGhC2DDjLTBiTX0LyvfbZxuwUp2wEh0QwsraJyluqO5ayC4/szJoRAnbQLLzTSRa1iHV/Q4AMWSf/mStEp7QofCEGqCVTR+dQU4xTmAo1hcYikDY+e/3suqFrPuhuCohyfkzChW9YlfGUIFyc0REREREREQTFYNENC599NFHmdfNzc2Z19OmTSvFcMZUxNTRYlSgRo2jzSiHLpkIar1QpOFNOrY0foh7rr8MPR0tBdsc/rmv4JNf+lqmzNlksSNdgafD8wEAJ9W8DY+cfw2mUjAMAx0d7Zn3/cvMBUNBVFbseiLdsIBNPbuqpkkSECoDgmVAJD11g0TCNmDEtsHo3QphpQfsS8GMt8NOdUEMmKCXtXIobj71TyNLCAEz1oR461ok2l6CMItcM05S4KreD966Briq9mFW2wgQwoZtxJz1hdKRnEDxTrJWDkX3Q9YrIcn5F29TXH4o7lqoniBkdYredImIiIiIiGhK4IwEjTtdXV3o6ekBAMTjcUQiEQBOOS6/31+6gY2BLtOD7akKABI8somgFoNLMiEPc5mD999Yiwd/8T2kk/knK2VFwQnnfQcHHvm5kRv0OCAEsD4+DS/H6iHgnKynw/NxvP/9YZ+70da/zJyvcleZOd2lY2b9zKy2mgIEvUBrL1CmO+Xl3H1364+6nGCRewrdvW0z4aw31LsjZ9LXNnphJdtgpSM5/RTdD8VTy5JdNKKsdBTJtpcQb/0XzN7tRfdXy+rhDTXAHTwEij65M2PHghAW7HTUWWPIiAAiN+NWggRZq4Ds8kHRKoF8ATlJ6lujrNa5b3CdMiIiIiIiIpoiptA0I00UGzduzLzun0VUV1c3qReFbjPK0JrOLmMz3EwYIQReePIhPH73TRB5JsgAwFNWiS9f8hPMW3LAHo91PDGEjH/0zEdTuipr+/a0D6/3zsCB5cVP4o60nnAP4gkncKeqKmpr+5WZmzMXiqLk9JleCVS4gDLNySQCAAnAbD+g5zaflKx0BEasEWaibVdaVR87HYaZaIM9MHtDkqG4aqC6A5AUfQxHS5OZEBZSXW8j3rIWqa63gAIZKoVIqhee4CHwhhqgls+a1H/LxoKwTdjpCCwjDDsdRb7yfhJkyK5KKJoPsl4BSLk3TkmSobhr+jKGagtmFRERERERERFNZgwS0bgSi8XQ0uKUSUulUujqchajV1UVgUCglEMbMbYATKFAl51JRiGAZqMCncbuZTtYlom/3nUjXvr7Hwu2qambia98+0YEps3arc8Yz1TYmeyhgV7rnY46LYp6V26WyVhxysx1ZN73LzNXW1sLn8+X0yfgBfYOAAkDeK0vTupzOdsqJvnD7UIIWMkOGLEmWKnuATttWKkumMn2nHJzkqxBcQeguKpZtotGjNG7A4nWtUi0vgjbKPY+IsFVtQ88dSvhrlnOAMQeErbRt75QOGctsp0kSYGs+6DoPmftoDxrj0myCsUdcDKG3DW8XxAREREREdGUx/8ypnFl06ZNmdetra0QfdkDwWAwb7bFRGMJCY0pP1K2gvnuLqiSje1pH3pM924dLxmP4cGfX4EP33qxYJu5i/fHly/5CbzlucGIyUCSgKN8m/DHzn0Qs7MjKDP1MAJakeuEjLDW1lbYtpPdVVlZiTJvGQBA0zXMnJVdZk5XgEU1QKgvocytArN8zv/OrNyVUTQZCWHDjDfDiDXBNnqz99kGrGQnrGRHTrk5SXE7i8nrfkh5JoSJimWbcSTaXkaidR2M6Oai+yueILyhBnhCK6C4qobuQAUJK9UXGIrANnvztpFkDbJe6awxpJUBeR4akGQNqqfWWZvMXcN7BREREREREVE/DBLRuJFKpbB161YAgGmaaG9vBwBIkoRQKFTKoY0Iw5axJVWFpO382m1KVkOVLCTs3SuJ1dW2A/dcewnatheexNz/iM/ghPO/A1Wd3E+wu2UTR/s24tHuvWFDhgSBg8q3Ybm3uaSBlXAkvKvMnKKiNlALIYCI5cK+82dDVXbdgqdVAAurnfWI+ltYM5YjHnvCSsPo3Q6jd2tOdpCwUk5JuVQ3xIByUrJWDsUd5JouNCKEsJHueQ/xlrVIdr4B2EZR/SXFBXftQfCGGqBVzmc5uT1gm0nY6R5Y6TCElczbRlJ0J2NI8/UFhvK1cUH11EJ1ByG7qvgzISIiIiIiIiqAQSIaN7Zs2ZLJuGhvb4dlORkDgUAAmjaxgxwpW8GWVBXSthMBMCGhOeVk9oS0GOQi564aP3gL993wbfRGugu2+dRp38Bhnz1zykyM1ekxHFK+Fevj03C0byOm69GSjqd/oBNwysyZko5Owwt3RRUi8CMkAI8GLA4ANbtXbXDCss04jFgTzN7mnOwg24jBSrQ7i9APoLiqoLhrIauesRoqTWJmoh2J1nVItK6Dleoqur/uW+SUkwscAFmZ5LUgR5FtxmGnw32BoVTeNpLihuLyQdZ9kJX8v/+y6oHiCUL1BCFrlVPm7x8RERERERHRnmCQiMYFy7KwZcsWAIBt25l1iQCgrq6uRKMaOS1G+a4AkZDRapTBEM77TtOL2iJKoq1f+yT+dMs1MI103v2a7sLJ3/gh9jn4yD0f+ASzr7cVCz2dcMtmqYeC1rZdZebKKyqQcgXQYbigqApqa2uRMJzycivqAWUKVT6y0mEY0UaYibacfXaqB2ayHbY54PdBkvvWEAlwXRfaY7aVQrL9NSRa1yId/qDo/oqrGp7QSnhCK6F6akdhhJOfEALC7M2sMSQKZG7JqjezxpBUIAgna+VOKTlPEIrGzEIiIiIiIiKiYjFIROPC1q1bkU47QY+uri4YhjNhVFVVBY9n4mcM1OsRbLJVRCwXWtNlsOBEBVTY8Cn5y+kMJITAM3/8LZ75428LtqnwB3DGZdejfv7iERn3eGDYMjanqrDQ0zlkW0kC3FLpA0SRSAS9vc76Gaqiwl09CxHLmeAMBUMo1xXM9AGWANIW4JnkQSIhBKxkB4xYI6xUz4CdFqxUF8xkO4SVPVEsyVrfGiLVkKSJvyYZlY4QAkbkI6ecXMerBbNVCpI1uGs+Bm9dA3T/3lzTZjcIYcM2YrB3BoYGZBDuJGvlUHQnY6hQUFjRfVA8tU7GkDrF0jCJiIiIiIiIRhiDRFRyQghs2rQp836yZREBgCIJBLQYNiWrMgEiTbIQ0mJQJTFEb8BIp/CnW67BW+ueKthm2uyFOPPy6+GrmfjrN+3UZXrw954F6LE8UCQb892Fy+uNF6Zloq19V5ZMMBiEVzOQMCx4KnxYUFeOWi8gS4AtgPc6gY9Njss8h7AtmIlmGNGmnOwgYRuwkh2wkp05k8WS4oHqqXUmiTkZT3vASnUh0foC4q3rYOXJXhuKVjEXnlADPMGDGIzYDULYsNMRp5ScEQXyBIYkSJC1csgun1MiLl9gSJKg6H6onmBfuUn3GIyeiIiIiIiIaGpgkIhKrqWlJZN1EQ6HEY87k8nl5eWoqJgcpWPCpgvb0z7Uar1oSVdAlSwEtV4owwgQxcJduO+Gb6Ppww0F2+y9/2E45cKr4XJPnknMDxI1eD4yByacDJJ/RuahRn0HfnV4mVel0tbalikzV1FegfLycgDAvLI45i9agPJ+c5tlOjDPX4JBjjJhpWH0boUR25ZTRkpYSZiJdtipbghkX/+yVuEEh1gyivaAsA0kO99EomUdUt3vABj6PtufrFXCE1oBT2gltLLpozPISUzYJmwj4pSSM2KAsHPaSJAh6xV9GUOVQJ5MQUmSnTXIPEGo7lpIij4WwyciIiIiIiKachgkopLbuHFj5nVzc3Pm9WTJIuoyPNiergQAaJKNkBaFKtmQh7GeduvWTbjnukvQ3d5csE3D8V/Gsad/E7I8ecpxrY3MwtuJ7J+/IRT8PbwAX6h+Z1jZV6UQjUYQ640BABRZQW2wFopko06P4ZhD90G3qmFH1CmLN88PzPZjWNfBRGGbcWe9oXgzxICJYduIwUq0OdkEWSRnIpjZAbQHhBAwY02It65Fou0liIHrWg1FUuCq3g/euga4qvaBJPP/HhVD2AbsdL/AUJ7AnCQpkPVKKLofslYO5MkSlCQFirumL2OohmuQEREREREREY0BzoJQSXV1daG72ykhFo/HEYlEAAAulwtVVVWlHNqIaE2Xoc0oz9qmy7lPVefz4foX8cDP/x9Sid68+2VZwWfPvRwHH/2FPR7neBPQ4kAid3uX6cVL0ZloqGwa+0ENwbRMtLW1Z94Hg7WodpmYrkUxu74O06ZNQ8ACTBuYX+VkEU0WVqoHRqwRZqJ9wB4BO9UDI9EGYQ3IAJMUqO4aKO4AJ4Jpt1npKBJtLyLRuhZm7/ai+6tl9fCGGuAOHgJFZwZbMYSVdoJC6TBsM//fKUlWIWs+KC6fExhCblTcWXss4ASGXNWQJtEDD0REREREREQTAYNEVFL9s4j6r0UUCoUgSRMnxcIWQMLWUKY4pbWEAHakK9Bl7l75txef+gP+eteNsO38C3u7veU47Vv/iwX7HrzbYx7PFnk60JIux3vJYNb2WjWGfctaCvQqjbQtI2q5kOrYBKvv5+Urc2NpwEalGoau69h3330BAJoC7DdJlowSQsBKtsOINsJKhwfstGAmu2Al23PKzUmyDsUdgOKuhpSnxBTRUIRtItX9NuIta5Hq2pB3nZvBSKoXnuAh8IYaoJbPmlB/a0rNtpJOUCgdhm3mieQDkBQNsuZ3SslpZQXa6FDdtVA8QSiuKq49RkRERERERFRCDBJRyfT29mYCQ+l0Gp2dnQAARVFQW1tbyqEVxRQSGlNVSNgq5rq64ZENbE37EDGLL51l2xYev+cmvPC3hwq2qQ7OwJnfvgHBGXP3ZNjjXkNlI9rM8kygbR9PK1ZUNA1rHaexIAQQttwIWy7EE0mkewU8ACoRxcdnl8GtpgAA++67L3R98qQNCduCGW+GEWvMmSQWtgEz2Q472QUxYOJeVj1Q3EHIuo+T8rRbjN4dSLSuRaL1RdhGpMjeElxV+8BT1wB3zTJmrxXBNuOw02FY6UhuRmAfSXE5ZeT0Sshq/ocjZNUNxR2E6uF9gIiIiIiIiGg8YZCISmbTpk2Z162trRDCmfwPhUJQlImRYZC2ZWxJVSFlO79Km5NVUCUbhih+/KlELx78xffwwZvrCraZvWgZTr/kWpRV+nd3yBOGKgl80vcRHu3eGysrmjDf3VXqIWWkbAWdphdpocC2LETCYUD2YnryAyybF4Rbd66Huro6TJ8+ORa+t60UzNg2GL3bcrKDbCsBK9EOK9Wd00/WKp1J4QIZBUSDsc04Em0vI9G6DkZ0c9H9FU8Q3lADPKEVUFwTv4TpWBBCQJhxWOke2OkIhJ3O205WPZB1HxTdB0nJ/1CErJVBdQeheGqh6JWjOWwiIiIiIiIi2k0MElFJpNNpNDU568pYloW2tjYAgCRJCIUmRj2upK1gc7IKZl9AyBQS2owK2EJCnR6FWkTGS09HC+6+9lK0bv2oYJvlHz8WX/iPK6BqkycrZSh+NYkvB9aPm+whwMkg6jC9mUBgJBKGy+yBx45C8dWjpsZZ10TTNOy3336lHOqIsI1eZ72heAuEsAfsi8JMtMM2ogN6SVBcVVA8tZALTB4TFSKEjXTPe4i3rEWy8w1gQFByKJLigrv2IHhDDdAq5zNjZRiEsGEbvbCNMOxUGEKYedvJWplTRk73QZLz/y1S9IpdGUMMDhMRERERERGNewwSUUls2bIFtu1MOLe3t8OynNJUgUAAmjYxygB1m55MgMgQMtqMchjCWVehwyhDnR4b1nG2fvQO7r3+MsTChTNlPnHyBVj1hXMmxWSnJSSsj9dhH08bXPLQa4mMpwARAEgSUKMm0GKUw05GoUcbocKALMuoDM1BjxmDX01h6dKlcLlcpR7ubrNS3TCijTCTHQP2CFipHpiJttzSU5IC1R2A4q5hOS8qmploQ6J1HeKtL8BOFZ85qPsWwVO3Eu7AAZCVifu7N1acwFA0U0qu0NpOslYBxeWDrFUW/L1WXH6oniAUdy1k1TOawyYiIiIiIiKiEcYgEY05y7KwebNTNsi27cy6RIBTnmuiqNNiSAsF7ekytBllsOAEiFTYqNHiwzrGhhefxh9+9UOYRirvflVz4aSv/QD7rvjEiI27lGKWhqfDC9BiVKDdKMMxvo8wEeNeXsXALHRg8/YmqHCeuA/W1mKaJ4VKJYVQKIT6+voSj7J4QghYiTYYsUZn0jhrpwUz2Qkr2ZFTbk6SdaeclKuaC9BTUWwrhWT7a0i0rkU6/EHR/RVXNTyhlfCEVkL1TJy17EpFCAt2OgI7HYFlRIAB2YEAIEGCrFdkSslBylM+VZKguKqhemqdwBCDckREREREREQTFoNENOa2bduGdNpZ46C7uzvz2u/3w+OZOE8gSxLgVxL4yKrJBIh0yUJQiw1Zak4IgTWP3Il/PPSbgm3KfdU447LrMHPB0hEdd6lsTVXimfB8JIXzJPqWVDU2xEPYr6y1xCMrTrmSwgw9isYtGwGzApBUVHlV7B8y4ZGTE7LMnLBNmPEdMGJNsM3kgH2GU1Iu1QUxINNAVr3OBDEXoaciCCFgRD5yysl1vAph5Q+SFyRrcAf2hzfUAN2/iIHJIQjbzGQLOaUhc/8+SZICWa+EolVC1ivyBoYkSYbiroHiCUJ1B5gtSERERERERDRJMEhEY0oIgY0bN2beNzc3Z15PpCwiAOgx3diWrkSNGodplEOGQK3WO2R5NNNI4+Hbfow3n3+iYJvQzAU48/LrUVU7baSHXRLvJwJYE5kLIDuQ8FJsJkJaDCG9tzQDK4Ii2ZimR1GlJtHT04PujjZUSXHYqhsrZs2AW3YyivbZZx+43RNjHR7bSsGMbYXRuz0nO8g247CSHbBS3Tn9ZL0SqpvrjVBxrFQXEq0vIN66Dlairej+WsU8eOsa4K49ELLqHYURTh7CNmClemAbEdhG/tKnTmDI17fGUAUG3p8BQJJVKO6AU0rOVQNJzpNVREREREREREQTGoNENKZaW1vR2+sEBCKRCOJxpyxbWVkZKisrSzm0onQYXjSnKwA4a+aEtBhkiCFLp/VGenDfjd9G4/vrC7ZZuHwlvnThj+D2lo/kkEuqXg/DLZmZLKKdbMh4NjIfp9S8BXkcJKIIAUQsF2RJoEJJZ7b71STq9Cg0yYZpmplyiR4Rw9z6WrjdTqml2tpazJw5syRjL4ZtxGDEmmDGWyAGlJuyjYiTOZQzsSxBcVeztBQVRdgGkh1vItG6FqnufyNfFstgZN0HT/BQeOoaoHknR9B8tNhWCnY67Pwz85c8lWRtV2BIy/83RpI1p4ycJ8gSkkRERERERERTAINENKYmQxZRS7oc7UZ2BsVQ2UMA0L59C+6+9hJ0tW0v2GbFsafguDMugqJMrl/NMsXAUb6NeLxnEfo/rV6pJHG076NxESBK2zI6TS9SQoUMAbdswisbmK5HUKnuChht3boVhuFk3VRWVqK21lkHRVVVLFu2rCRjHy4r2QUj1ggz2Tlgj4CV6oKZ6ICwssvNSZICxR2A4g5AkifXdUmjQwgBM9aEeOtaJNpegigQsChIUuCuWQZPaCVc1Ush5VsThwAAtpnoKyUXzvnd3UlSXE4pOd1fMANLUlxQPUGoniBk3c/ykURERERERERTCGf8aMx0d3ejq6sLAJBIJBAOhwEAuq6jurq6lEPLyxISopYLftWZeBMC2J6uRLdZ/LpJH214GQ/c9F0k4/nL/siygk+fdQkOPeakPRrzeDbTFcH+ZTvweu8MAMBcVxeOqNwMl2wN0XN02QIIW25ELHcmx8GGBEvI2MvTmRUADIfDaG9vBwAoioK5c+dm9i1ZsmRcrqklhA0r0YZ0dEtudpCwYCY7YCU7IGwza5ck632ZBFXMJKBhsdJRJNpeRKJ1LczewsHwQtSyenjrGuAJHgJZqxiFEU58QggIMw7LiMBO9UDY6bztJMUNxeWDrPsgK/nvS7LqdcrIeYKQtQoGhoiIiIiIiIimKAaJaMwMlkU03ianTCFhS7IKCVuDDQl+JYGmlB9Rq/gyWy8//TAe/d11sO38wRCXpwynXfRj7LXs0D0d9rh3QNl2tBtlmOkKY6mndcjyfGMhLRSErV1rCGmShYAah0u2soKElmVlyswBQH19PVwu53oIBAKYPXv22A58CMI2YfRuhxFrgrBSA/alnZJyyS4IZJebk9UyKJ5ayFrluPu9pPFH2CZS3W8j3rIWqa4NgCgu6CupZfAED4G3rgFa+axRGuXE5gSGYrDSEdjpcM76YTvJqtcpJefyQZLz/62StfJdGUMFys0RERERERER0dTCIBGNid7eXrS0tAAA0uk0OjudcleKomTKdY0XaVvB5pQfadv59diaqsQ2VEDKs6j3YGzbwt/u+z+sffz+gm2qaqfhzMtvRGjmvD0a80QhS8Bx/g/GRXBoJ7dsoUJOIWbr8ClJVKop7Myb2ZGuQKWShCw5ZebSaeep/YqKCgSDQQDONTyeyszZVspZb6h3e052kG3GYSXbYaV6cvopuh+KOwBZK8vZRzSQ0bsdidZ1SLS+ANuIFtlbgqtqH3jqGuCuWQZJ1obuMsUIYcM2Ypk1hkSB4JuslTvrC+m+gudR0X1QPEGontqC5eaIiIiIiIiIaOpikIjGxObNmyGEU7arra0t8zoYDEJRxs96EwlbxZakH6ZwxmQKCa1GOUwhI6TF4B5mabRUMo6H/u8HeO+15wu2mbXXvjj90mtR7ht/pfaKIQSwIR5ClZrETFd4yPbjKUC003RXFElbzQoDumQTM/QIZAmIRCJoa2sDAMiyjHnz5mWybJYsWQKvt/QTr5YRhRFtgplocX4o/djpCMxkG2yjN7uTJENxVUN1ByApxWfJ0dRim3Ek2l5GonUtjOiWovsrnhC8oQZ4QodCcVWN/AAnOCEs2Omos8aQEQGEndNGggRZK4fs8kHRfEC+dcIkCYpe1VdKrhYyf7eJiIiIiIiIaBAMEtGoS6fTaGpqAuCU7GptbQUASJKEUChUyqHlSNhaJkBkCBkt6XJYfXklnaYX07XokEGOcGcr7rnuMjQ3flCwzX4rj8EXL/geNH1iT96lbAVrInOxJVUNt2TgxJq3Ua7kL4U0HsmSQJ0WRbWaQNRyoTHlByBQq8UR1GKQpdwyczNnzsyUmaupqSl5mTkz2Qkj1gQr2Tlgj4CV6oKZaM8pNydJKhRPAIqrBlK+SWaiPkLYSHe/i3jrWiQ73gCEOXSnfiTFDXftQfCGVkKrnM8ShgMI24RtRGClw7DTUQAip40EGbJe0ZcxVAlIuQ9WSH0BX8UT7Av66mMweiIiIiIiIiKaDDg7SKOusbERluVk4HR0dGRe19TUQNfH10RWtZqAYcvYmvKhzSjLBIg0yUJQ6x0yQLR907u457rLEO3pKNjmqBPPx1Ennj/hJ0vbDS/+EV6ASN96Pkmh4R/hBfhs1XtQpNyJzvGmQklhuh6BLjtP61eqKdTavfCpSXjkXRPh27dvRyrlBFnKy8tzysyV4ucohA0z0Qoj2gjbiGXvtE2YqQ5Yyc6ccnOS4oLqroXsqoIkySAqxEy0IdG6DvHWF2Cnuorur/sWOeXkAvszk2UAYRt96wv15P7+9pEkBbJeCUX3O2sH5fl9lSQFiicA1R2E4mbAl4iIiIiIiIh2D2cUaFTZtp3JwhBCZNYlAoC6urpSDWtQHtlA3NYyASJdshDSYkMGPt55+Vms/uWVMNKpvPsVVcOJ//l9LGv41IiPeax1mR78uWtJ5hzt1GpU4OVYPVZUbC3RyLIZQkaX6UGNGofa9/NTJBvT9Sj8ajKnfZ2ePWEbjUYz16wkSVll5vbee2+UlY3t+j3CNmD0bocR25qTHSTsFMxEO+xkNwSyy1TJahkUTxCyVjHhg5M0emwriWT7a0i0rkM6XDgTshDFVQNPaAU8oZVQPeNrrblSE1aqLzAUhm325m0jySpkzQfF5XMCQ3nWwZNkDaqnFoq7FoqrGpI8fsq1EhEREREREdHExCARjapt27ZlsjC6uroyr30+37hYx2WgbtONbalK+JUkTCHDFhJqtV7Ig8yrCyHw/KP34MkHflmwTVllFU6/9FrMXrjfKIx67FUpCcxy9WBzKnc9pQ3xOiz2tOcNwowVIYCI5UKP5YaAhE7Ti5DWiyo1gTo9mgkYDcayLGzatCnzvr6+Hm63kzVVXV2NuXPnjtr4B7LNJIxYE8z4jpzsINuMw0q0wUrnrgel6H5nTRIuVk8FCCFgRD5EvGUdku2vQtj5g9wFyRrcgf3hDTVA9y9ihlo/tpmEbYRhpcIQViJvG0nRIGt+p5Sclj/oLCkuqJ5aqO4gZJef55iIiIiIiIiIRhSDRDRqhBDYuHFj5n3/LKJp06aVYkiDaje8aElXAAAkCQio8czrQkzTwF9u/yleW/NowTbBGXNx5rdvRHVw+oiOt5QkCTiicjM6u7yZcnMA4JYMHOXbWNIAUcpW0Gl6kRa7nrA3hYIqNY56V3TYxxlYZm5n5pssy2NWZs5KR5zgUKLViXz1Y6cjMJNtsI0BWQl9a5M465KwzBflZ6W6EG99AYmWdbCSbUX31yrmwVvXAHftgQxC9mObcdjpMKx0OCfbbydJcTll5PTKgudOVj196wvVQtZ9zAAkIiIiIiIiolHDIBGNmra2NsRiTvmuSCSC3l5nMtvr9aKysrKUQ8siBNBilKPDyH6Ke6g5uXgsjPt/9h1s/vfrBdss2O8QnHbRj+H2lo/EUMcVl2zhk76P8Ehf2bk6LYqjfR+hXDFKOq6YpfcLEAlUKin41SQilhumiA0riygWi6G1tRWAU2Zu7ty5WWXmystH7+cphICV6oQRbYI1cC0YYcNKdcNMtudMQEuyBsUd6CtBxVs75RK2gWTHm4i3/gvp7ncBFLd2mKz74AkeCk9dAzTv+Av0l4IQAsKMw0r3wE6HIez89z9Z9UDWfVB0f8HgrayVO6XkPEEoWsVoDpuIiIiIiIiIKIMziTRqxmMWkSWc0mO1ai8kCbAFsD3tQ4/pHrpzPx3NTbj72kvQ2VJ47Z2DP3EiPnP2JVCUyftrFtDiaKhoRNhy46DybUOu2zQW/GoS8bQGRRKoUeNwyRYAwBIy2oxyTNcHzyaybRubNm2C6MvcmTFjBjwej3Nsvx/z5s0blXELYcOMN8OIbc1ZzF7YBqxUJ6xEB4SwsvZJitvJNmAZqknJSnbmXA/DIWvlUNw1Tjm5WCMSLWuRaH8ZwowXdyBJgbtmGTyhBriq94EkcQ0cIWzYRq+zvlA6DCHMvO1krcwpI6f7Icla3jaKXrkrY6hAuTkiIiIiIiIiotE0eWevqaR6enrQ2dkJAEgkEujp6QEA6LqOqqqqkozJsGVsSVUhaaswhIw6LYamlA8xa+iSXI0fvIXH77kJx5/5LVimgftv/A4SvZG8bSVJxvFnXoQVx35pwpUI2paqxNrobDRUNKLelf/7DbTY2z7KoyqOKttY5O1AzNLRP2RSo8UR0oaebN++fTuSSadcXllZWSaoKcsyli9fPuI/U2EbMGLbYPRuhbDS2fusFMxEO+xUF8SArA8nCBCEojPjYLKykp1oe+V7QIEgxKAkFWUzP4VUx5sw49uL7q6W1cNb1wBP8BDIzGrpCwxF+0rJRYABwdqdZK0CissHWavMHxiSJCi6H6onCMVdC1kt7gEFIiIiIiIiIqKRxiARjYpCWUR1dXWQ5bHPdkjZCrakqpC2nafg2w0vdqQq4JbzT/QN9MLfHsK2j97B43f/DDu2vA/byt9Pd3vxpQt/hL33//iIjX2sCAG8HKtHj+XBc9E5mJXswcd9TaUeVlHKlDRm6BG4ZAuNSR8ilhsu2US9HoF3GGXwYrFY5nqVJAnz5s3LBIUWLlyIioqRmyy3zYSz3lDvjpzsINvohZVscyajB1BcVX2Ty54RGwuNT7YR270AEQAIE71Nfy2qi6SWwRM8BN66Bmjls3bvcycRYZuwjSisdBi2EQWEndNGggxZL4es+6HolUCeTCtJkp3fW08QijsAmWuFEREREREREdE4wiARjbh4PI7m5mYAgGEY6OjoAAAoioLa2toxH0/CVrE5WQVLOMEpU8hoNcpgCAU1ahwVSnrQ/r2RHrzz8jMAgG0b/12wna8mhK9cfgPqZu81coMfQ9vSPrSbzlo7UcuNd6w61OpxLPJ0lHhkQ1MkG3V6DFVKIrOW1HQ9Co9lIqD2Qh5G8o9t29i8eXOmzNz06dMzZeZ8Ph/mz58/ImO10hEYsUaYiTYnMtd/DOkwzEQb7IElwSQZiqsGqjsASdFHZBxEDgmu6qXwhBrgrtmvYFm0qULYBux0pC8wFEO+dZskSYGsVzql5LQKIE+ZR0lSoLhr+jKGaqb8eSUiIiIiIiKi8YtBIhpx/SfaW1tbM6+DwSAUZezXs7CFBBtOlCAtFLSmy2D1FSLrMr1wSSb6VxCTIKD2W1vnlWceKZg5tNOM+fvg1Euvh89fg6EWg7cFMp/fnwJ7yGCG1e+79KdJuU+4D2QKCWJA353fVQjgxejMvrHvavN8ZDYCai8q1VTO8WSIIdcgKjReFTaGqtqWb7wxS4cpZNRqu4IolUoS0/UoNDn7HGiyjaDcO/iH9LNjxw4kEgkAgNfrzSkztycZcEIIWMkOGLFGWKmeATttWKkumMn2nHJzkqxBcQeguKohybxd08hRPKG+cnIroLj8pR5OSQkr7QSF0mHYZv57hhMY8vWVkqsA8tzXdv6+qp5g3+8s128iIiIiIiIiovGPs440ogzDQGNjIwDAsiy0trZm9vX29maVoRtLNrzYinp0owo2nLJjKiwIAF3YNZGX6GmDEW2HH2HnfSyCp/9w26DHDu51EPY9+XI0pvzwtkZRieig7VPQ0Y3cdZmq0A0XBs9qiqACcXhzttehNU/rbB0IwET2pKWONKrRjRYE0SXlHteCgic652Jv/BsKsoMwFYiiDPGcPv3F4UEElTnbA+iAisEDbz3wI4mBZZmc0ltRhFGBXtSgAybiGImieF1dXQB2lZnbGRTaa6+9UFmZ+x2Gy4y3IB3dDNvInnwWtgEr2Qkr2ZFTbs4ZiAxZLYMwEzDN4teUoYnPjDeP6PEkWYdetQTu6mVQy+ohSZITGEmHR/RzJhJhp2Cbibz7JFlzAkO6D7JWnr+NokN11zql5FxVkPJkFRERERERERERjWcMEtGIamxshNWXddPR0ZF5DQCRSO76KmMlIaUQ1mrQ27eOiyrS8FidiCrVMKRdgYh1d30P3Vs2FHXstg9fwcv3X4MV/3ETYPdCsgcPEqUlFxJK7mLlmhVDWuRm7PQXl2Uk8qQbRc3BPxMA4ooXlpT9K2+KFFQrine9DYAikC+9p1cqR0uqEtVW9oS1bPXCFrFBPzMpWUgouWWWomYMKgZfa6VX1pCWC2RIWSkEUm8jBQODn7HiTZs2DV6vEzCrrKzEggULdvtY6cgmpCObsrYJKwkz0Q471Q0xWNaZsGGle3b7s2nis4yhf6+HQy2bAd2/GHrl/EzZM9uYuoGhwUiKywkK6T7Iam7gHABk1Q3FHYTqCULWfZl1y4iIiIiIiIiIJiIGiWhE7VyLSAiBlpaWEo/GYUJDXK5AldUKXSSRllzwW+2QIGDABVneFciad8An8Ma292CbxjCPLkFWVcw94Gi47DjcVgxee/BgmCJ5kMqTteOxonCJ5KB9LaHAzlOqzmsNHYCLS+WwpOyAjW4nEZd8iKqBgv3mJN9EIE8mi8ce+rtKkp0VhOs/3qGCRGm4IOUJorjtXmhII6IEUGONbKaFx+PB9OnTATgZRXtSZk4IG0ZsV46TbcRgJdphGaULltLUovuXwF17IBR99zPhpgJJcUNx+aDofkh5AvgAIGtlUN1BKJ5ank8iIiIiIiIimlQYJKIRZRhOcEUIgUWLFpV4NPkJISBJTlCkMe1HzN4VxNh31hfx8YP2w0M//39oaWnJrKeUjyTJqK6rx5f+6xrUzpgLAKhRVNRpg/9aRS0XmgxfzvbZmolyZfBycy1GJTqtspzt+7hrB+0HAB+l/EiJ7LGVSW78OfIxSIYNkSf4JMGGUTELS8tjOUlGdaqEGjU3ANRft+nBDjP3uy7QU3DJg5eb25quQsTOnrDVJAsVsoquvnMwX58Gtzx4sKkYqqpmgkILFiyAz5c79mETol8ZOQFJ0aCWT4eK6Xs+UJoSZC33d70YFXM+C6185giNZrKSM9lVAyl6RV/GUG3BcnNERERERERERBMdg0Q0ombMmIEPPvgAsizD7c7/RPZ4okOHbulZ22bOXYif//znuPnmm/H8888X7Lv00KPxxQu+B92163u6NANuffDvbVg6dOg5211uN9zK4FkrLlmHbuT2Hc651oUOYWf/yjcbPmw1qgv2EZCx3ahGm6jFTD27PJVLd8GtDR7ocZlu6Kn84x0qSKRLOnQzu68mWZjliUKkgKDWi3JFxWjcxnw+HxYuXLhHx5BkBao7ADPRDkCCJA8eUCMaSJLyBy+K6c/rrjiKyw/VE4TiroXcV56UiIiIiIiIiGgyY5CIRtTChQshSRJ27NiBVGqkV4sZeXWyCcPOXvdGkQQqtUosW7YM//rXv/JmE0mShAOXL8Ve1QLArkXPPYqAruQGRfqrsGXMVnIXSq9QZejy4H0DikCZnttX1wfvBwAzpDQssauMnhDA4zv2hoT8WUQ7SbCxPj4NDVUtWdlEZcP4rn4FUNXc8Xo0FaqkDNo3JFuosrP7yhLg0TTs7ert2zL09y6GoigIBALYZ599drvMXH+uqqWQlA9hJbsg7OGWMCTqI+/hn2hZLZglQ30kGbJWDtVT6wSGFAbViIiIiIiIiGhqYZCIRpQkSVi4cOEeZ2GMB6tXr4aiKDDN3HJmiqJAMaI4/bNHlGBkI+OfjcDWzUO3E5CxPV2JmcuOwBGzR39ck4kkK3D59y71MGiCUrpq9qi/p/YAuKuXjtBoiIiIiIiIiIhoMtrzR+WJJqkXX3wRpmlCVVW43W5cfPHFcLvdmcDRCy+8UOoh7jYhgOtfABRp6LaA0+76F5x+RERERERERERERDQ5MEhElEcymcR7770HAJg/fz5ee+013HjjjXjttdcwf/58AMB7772HZDJZymHutueagLdaAWuYQR9LOO2faxrdcRERERERERERERHR2GGQiCiPRCKBpUuX4pxzzsHrr7+OJUuWAACWLFmC119/HWeffTb23XffCRkk2plFNMwkogwJzCYiIiIiIiIiIiIimky4JhFRHlVVVXj99dchy7lx1LKyMtxxxx2wbTvv/vEubQE7okCxsR4BoDnq9HfxzkE06hRXFSTZBWGniu4ryS4orqpRGBUREREREREREU0mnOolKmCoANBEDBABToDn0VOBzkTxfQMeBoiIxopWNgOzP/s0rFR30X0VVxW0shmjMCoiIiIiIiIiIppMON1LNAVNr3D+EdH4ppXNYLCHiIiIiIiIiIhGzcRMhSAiIiIiIiIiIiIiIqI9wiARERERERERERERERHRFMQgERERERERERERERER0RTEIBEREREREREREREREdEUxCARERERERERERERERHRFMQgERERERERERERERER0RTEIBEREREREREREREREdEUxCARERERERERERERERHRFMQgERERERERERERERER0RTEIBEREREREREREREREdEUxCARERERERERERERERHRFMQgERERERERERERERER0RTEIBEREREREREREREREdEUxCARERERERERERERERHRFMQgERERERERERERERER0RTEIBEREREREREREREREdEUxCARERERERERERERERHRFMQgERERERERERERERER0RTEIBEREREREREREREREdEUxCARERERERERERERERHRFMQgERERERERERERERER0RTEIBEREREREREREREREdEUxCARERERERERERERERHRFMQgERERERERERERERER0RTEIBEREREREREREREREdEUxCARERERERERERERERHRFMQgERERERERERERERER0RTEIBEREREREREREREREdEUxCBRiWzbtg3nnnsupk+fDpfLhTlz5uBb3/oWuru7Sz00IiIiIiIiIiIiIiKaAtRSD2Aq2rhxI1auXIm2tjaccMIJ2HvvvfHyyy/j5z//Of72t79h7dq1qKmpKfUwiYiIiIiIiIiIiIhoEmMmUQl8/etfR1tbG37xi1/gkUcewU9+8hM888wzuPjii/H+++/jiiuuKPUQiYiIiIiIiIiIiIhokmOQaIxt3LgRTz31FObOnYtvfOMbWft++MMfoqysDHfffTdisViJRkhERERERERERERERFMBg0Rj7NlnnwUAHHPMMZDl7NNfUVGBhoYGJBIJvPTSS6UYHg2hubkZV111FZqbm0s9lEmP53ps8DyPDZ7nscNzPTZ4nscGz/PY4bkmIiIiIqKpikGiMfb+++8DAPbaa6+8+3du/+CDD/Lub25uxuuvv57z79133wUAvPvuu3n38z94R0ZzczN++MMf8nyOAZ7rscHzPDZ4nscOz/XY4HkeGzzPY4fnmoiIiIiIpiq11AOYasLhMADA5/Pl3b9ze09PT979t9xyC374wx8WPP4ZZ5yRd/uVV16Jq666avgDJSIiIiIiIiIiIiKiSY1BonFGCAEAkCQp7/4LLrgAn/vc53K2v/vuuzjjjDNw7733YvHixTn7p02bNrIDJSIiIiIiIiIiIiKiCY1BojG2M1NoZ0bRQJFIJKvdQNOmTRs04LN48WLsv//+ezhKIiIiIiIiIiIiIiKa7Lgm0RhbtGgRgMJrDn344YcAgIULF47ZmIiIiIiIiIiIiIiIaOphJtEYO/LIIwEATz31FGzbhizvitNFo1GsXbsWHo8Hhx56aFHHTSQSAJyyczR6dp5fnufRx3M9NniexwbP89jhuR4bPM9jg+d57Ey2c73ze+z8bwQiIiIiIqJCJLFzERwaM5/61Kfw1FNP4Re/+AUuvPDCzPZLLrkEP/vZz3DBBRfgN7/5TVHHvO+++3DGGWeM9FCJiIiIiGiCuvfee3H66aeXehhERERERDSOMUhUAhs3bsTKlSvR1taGE044AYsXL8ZLL72EZ599FgsXLsS6detQU1NT1DE7Ojrw5JNPYs6cOfB4PKM0cnr33Xdxxhln4N5778XixYtLPZxJjed6bPA8jw2e57HDcz02eJ7HBs/z2Jls5zqRSGDLli341Kc+hUAgUOrhEBERERHROMZycyUwf/58vPrqq/jBD36Av/3tb3j88ccxbdo0/Nd//ReuvPJKVFdXF33MQCDApwTH0OLFi7H//vuXehhTAs/12OB5Hhs8z2OH53ps8DyPDZ7nsTOZznVDQ0Oph0BERERERBMAg0QlMnPmTNxxxx2lHgYREREREREREREREU1RcqkHQERERERERERERERERGOPQSIiIiIiIiIiIiIiIqIpiEEiIiIiIiIiIiIiIiKiKYhBIqIiTJs2DVdeeSWmTZtW6qFMejzXY4PneWzwPI8dnuuxwfM8Nniexw7PNRERERERTVWSEEKUehBEREREREREREREREQ0tphJRERERERERERERERENAUxSERERERERERERERERDQFMUhEREREREREREREREQ0BTFIRERERERERERERERENAUxSETUZ86cOZAkKe+/urq6vH3WrVuH448/HtXV1fB6vdhvv/1w0003wbKsMR79xHHnnXcWPM87/ymKkmm/ZcuWQdueeuqpJfw2pfeHP/wBF154IQ477DBUVlZCkiScccYZg/bZnev2rrvuwsEHH4zy8nL4fD6sWrUKjz322Eh/nXGrmPP84Ycf4qc//SmOOuoozJw5E7quIxQK4XOf+xyeffbZvH2G+r34zW9+M5pfb1wp5lzvyf2B1/Twz/PZZ5895H376KOPzurDa9rR2dmJ3/72t/jCF76ABQsWwOPxwOfz4eMf/zhuv/122Ladtx/v08Up9jzzPk1ERERERLSLWuoBEI0nPp8P3/rWt3K2l5eX52z785//jBNPPBFutxtf+tKXUF1djUcffRQXX3wx1q5di9WrV4/BiCee5cuX48orr8y77/nnn8czzzyD4447LmffsmXL8PnPfz5n+9KlS0d6iBPKNddcg/Xr16O8vBz19fV47733Bm2/O9ftZZddhhtuuAH19fX46le/inQ6jQcffBCf/exncfPNN+Ob3/zmaH29caOY8/z9738fv//977F48eLMJO/777+Pv/zlL3j00Udx00034aKLLsrb94QTTsDy5ctzth944IEj9VXGvWKvaaD4+wOv6eLO8+c//3nMmTMn77577rkHmzZtynvfBnhNr169Gl/72tdQV1eHo446CrNmzUJrayv+9Kc/4fzzz8fjjz+OP/zhD5AkKdOH9+niFXueeZ8mIiIiIiLqRxCREEKI2bNni9mzZw+rbTgcFoFAQOi6Ll555ZXM9kQiIVasWCEAiAceeGCURjp5HXrooQKA+POf/5zZtnnzZgFAnHXWWaUb2Dj2zDPPiA8++EDYti2effZZAUCcfvrpedvuznW7du1aAUDMnz9fdHV1ZbZv3rxZVFdXC5fLJTZv3jwq3208KeY8/+53vxOvvvpqzvY1a9YITdOEpmlix44dWfvuuOMOAUDccccdozH8CaWYc7079wde045iznMh3d3dwuPxCF3XRXt7e9Y+XtOOp59+WjzyyCPCNM2s7c3NzWLmzJkCgFi9enVmO+/Tu6fY88z7NBERERER0S4sN0e0G1avXo2Ojg6cdtppWU+Out1uXHPNNQCAX/3qV6Ua3oT09ttv48UXX8SMGTPw6U9/utTDmTCOPPJI7LXXXllPoReyO9ftr3/9awDA9773PVRVVWW2z5kzB9/4xjeQSqXwu9/9biS+yrhWzHk+55xzcMABB+RsP+KII7Bq1SoYhoG1a9eOxjAnhWLO9e7gNe0YifN8zz33IJFI4Itf/CICgcAIjm7yOOqoo3DCCSdklVEFgLq6Ovznf/4nAGDNmjWZ7bxP755izzPv00RERERERLuw3BxRP6lUCvfeey+amppQVlaG/fbbD4cffnjOpMPOevXHHntszjEOP/xweL1evPDCC0ilUnC5XGMy9onulltuAQCcd955OecbAHbs2IFbbrkFnZ2dqKmpwYoVK7DffvuN9TAntN25bgfrc9xxx+FHP/pRwfUbKJeu6wAATdPy7n/zzTdx0003IZlMYsaMGTjyyCNRX18/lkOckIq5P/CaHjm33XYbAOA//uM/CrbhNV1YvvsB79Mjb6j7brHteU0TEREREdFkwyARUT8tLS0488wzs7bNnTsXd9xxB4444ojMtvfffx8AsNdee+UcQ1VVzJ07F++88w42bdqExYsXj+6gJ4FEIoF7770Xsizj/PPPz9vm73//O/7+979nbVu1ahXuuusuzJo1ayyGOeEVe9329vZi+/btKC8vR11dXU6fncf54IMPRnfgk0RjYyP+8Y9/wOv14vDDD8/b5uc//3nWe0VRcP755+Omm26C2+0ei2FOSMO9P/CaHjkvvPACNmzYgIULF+LII48s2I7XdH6maeKuu+4CkB3c4X16ZBU6z4XwPk1ERERERFMRy80R9TnnnHPw9NNPo6WlBb29vdiwYQMuuOACbNmyBccddxzWr1+faRsOhwEAPp8v77F2bu/p6Rn1cU8GDz30EHp6enDcccdh5syZWfu8Xi++//3v47XXXkN3dze6u7vxz3/+E0ceeSTWrFmDo48+Gr29vSUa+cRS7HXL63zkpFIpnH766UilUrjyyiuzSkIBTjD65ptvxvvvv4/e3l7s2LEDDz30EObMmYNbbrkF5557bolGPr4Ve3/gNT1ybr31VgDAV7/61bz7eU0P7jvf+Q7efvttHHfccfjUpz6V2c779MgqdJ7z4X2aiIiIiIimKgaJiPpceeWVOOqooxAKheD1erF06VL85je/wSWXXIJEIoGrrrpq2McSQgDAqK2pMdnsnGy84IILcvYFg0FcffXV2H///eH3++H3+3H44YfjqaeewiGHHIKPPvoIv/3tb8d6yJPS7l63vM4HZ5omTj/9dKxduxYnnXQSLr/88pw2RxxxBL75zW9i4cKF8Hq9mDZtGk4++WQ8++yz8Pv9eOCBB7IC1eQYrfsDr+nBhcNhPPTQQ9B1HWeffXbeNrymC7vppptwww03YNGiRbj77ruL6sv79PAVc555nyYiIiIioqmMQSKiIexc8Pi5557LbNv5ZO7OJ3gHikQiWe2osH//+99Yt24d6uvrcfzxxw+7n6qqmdJ0/X82VFix1+1Q7Yd6gp2ciccvf/nL+OMf/4iTTz4ZDzzwQFGTtTNnzsSnP/1pALzOi1Ho/sBremTce++9iMfj+OIXv4hAIFBU36l+Tf/85z/HxRdfjMWLF2PNmjU554/36ZEx1Hnuj/dpIiIiIiKa6hgkIhpCMBgEgKySRYsWLQKQv8a/aZrYvHkzVFXFvHnzxmaQE9gtt9wCADjvvPOgKEpRffP9bKiwYq/bsrIyzJgxA7FYDM3NzTl9PvzwQwDAwoULR3HUE5dhGDjllFOwevVqfPnLX8YDDzwAVS1+KUBe57sn33njNT0ybrvtNgD5sz+HY6pe09dffz2+9a1vYenSpVizZk3eNYR4n95zwznPO/E+TURERERExCAR0ZBeeuklAMgK+Bx11FEAgL/97W857Z977jnE43GsXLkSLpdrbAY5QSWTSdxzzz2QZRnnnXde0f3z/WyosN25bgfr88QTT2S1oV3S6TROPPFEPPzww/jKV76Ce+65p+gg6E68zndPofPGa3rPvPTSS1i/fj0WLlyIVatW7fYxgKl1Tf/v//4vLr/8cixfvhzPPvtsJqgwEO/Te2a45xngfZqIiIiIiChDEJF4++23RWdnZ872pqYmsXDhQgFA/M///E9mezgcFoFAQOi6Ll555ZXM9kQiIVasWCEAiAceeGBMxj6R3X333QKA+MxnPlOwzYsvvihSqVTO9jVr1gi32y0AiLVr147mMCeMZ599VgAQp59+et79u3Pdrl27VgAQ8+fPF11dXZntmzdvFtXV1cLlconNmzePyvcZr4Y6z8lkUhx//PECgDjvvPOEZVlDHvO5557L2WbbtvjpT38qAIhAICDC4fAej32iGepc7879gdd0rqHOc3/nnnuuACCuv/76Qdvxmt7l6quvFgDEAQcckPf/a/TH+/TuK+Y88z5NRERERES0iyRE3wq4RFPYVVddhZ/85Cc48sgjMXfuXFRUVGDTpk147LHHkEwmcfzxx+Phhx+GruuZPo888ghOOukkuN1unHrqqaiursZf/vIXvP/++zjppJPw0EMPTcmFootx2GGH4V//+hf+8pe/4LOf/WzeNqtWrcI777yDVatWob6+HgCwYcMGPP300wCAH/3oR/je9743ZmMebx555BE88sgjAICWlhY8+eSTmDdvHg477DAAQCAQwPXXX5/Vvtjr9tJLL8WNN96I+vp6nHTSSUin0/j973+Pzs5O3HzzzfjmN785Zt+3VIo5z+eccw7uvPNOBAIBfP3rX897H1i1alVWFoYkSVi4cCEOOuggzJgxA+FwGOvWrcOGDRvg9Xrx8MMP45hjjhn17zkeFHOud/f+wGu6+HsH4KyHM336dBiGge3btw+6zguvacddd92Fs88+G4qi4MILL8y7NtCcOXNw9tlnZ97zPl28Ys8z79NERERERET9lDpKRTQerFmzRpx66qli0aJFwufzCVVVRSAQEJ/4xCfEXXfdJWzbztvvX//6lzjuuOOE3+8XbrdbLF26VNx4443CNM0x/gYTz7///W8BQNTX1w96vn7729+KT3/602L27NmirKxM6LouZs6cKU455ZS8T/VONVdeeaUAUPDf7Nmzc/rsznV75513igMPPFB4vV5RXl4uDj/8cPHoo4+O4jcbX4o5z0ccccSgbQGIK6+8Muv4l112mTj88MPFtGnThMvlEh6PRyxatEh84xvfEBs3bhzbL1tixZzrPbk/8Jou/t7xq1/9SgAQp5566pDH5zXtGOo8AxBHHHFETj/ep4tT7HnmfZqIiIiIiGgXZhIRERERERERERERERFNQXKpB0BERERERERERERERERjj0EiIiIiIiIiIiIiIiKiKYhBIiIiIiIiIiIiIiIioimIQSIiIiIiIiIiIiIiIqIpiEEiIiIiIiIiIiIiIiKiKYhBIiIiIiIiIiIiIiIioimIQSIiIiIiIiIiIiIiIqIpiEEiIiIiIiIiIiIiIiKiKYhBIiIiIiIiIiIiIiIioimIQSIiIqIpZOXKlZAkCZIkYd68eTBNs9RDGtTOse78d+edd5ZkHIcffnhmDHPnzkUqlSrJOIiIiIiIiIiIRhKDRERENGaEEHj88cfxta99DcuWLUMwGISu66iqqsLChQtx2mmn4Xe/+x0SiUSphzoprV69Gi+88ELm/Xe+8x2oqlrCEU0cV1xxReb1li1bcPPNN5dwNEREREREREREI0MSQohSD4KIiCa/V155Beeeey7efvvtIdsGg0Fce+21OOuss8ZgZFODYRhYvHgxNm7cCACYMWMGNm3aBF3XSzyywUmSlPX+jjvuwNlnn12SsRx88MF45ZVXAAB+vx8bN25EdXV1ScZCRERERERERDQSmElERESj7g9/+AM+/vGPDytABABtbW04++yzcemll47yyKaO1atXZwJEAHDWWWeN+wDReHP++ednXvf09OCWW24p4WiIiIiIiIiIiPYcg0RERDSq3njjDZx55plIp9NZ20855RQ8+eSTeP/997Fu3TpcfvnlOUGLG2+8Eb/5zW/GcriT1q9//eus96effnqJRjJxnXzyyVnX6K233grbtks4IiIiIiIiIiKiPcMgERERjapLLrkEyWQya9s111yD3//+9zjmmGOwcOFCrFixAtdeey0ef/xxKIqS1fa73/0uwuFw5v2aNWsgSdKw/xUqTfbhhx/i8ssvx0EHHYSamhpomobq6mp87GMfw0UXXYR33nmn4HdatWpV3s946KGHcPTRR6O6uhputxtLlizBj370o5zvP1BbWxuuueYaHHHEEVnrNO2///747//+b2zbtm3Q/kN577338K9//SvzfunSpViyZElR3+2BBx7AqlWrUF1djbKyMixfvhw33HADDMPIe5w5c+ZkHeeqq66CZVn41a9+hUMOOQSVlZWoqKjAihUr8Lvf/Q7FVL9Np9O47rrrsHz5cpSXl8Pv9+Ooo47CI488ktP2C1/4QtY4TjrppLzHFELkjPnqq6/OalNVVYVjjjkm837Lli34+9//PuxxExERERERERGNNwwSERHRqHnzzTexZs2arG3Lli3Dd7/73bztjz76aFxwwQVZ23p6enDnnXeO2Jhs28b3v/997L333rj++uvx6quvoqurC6Zporu7G2+++SZ+8YtfYN9998Ull1wC0zSHPGYqlcJJJ52EL33pS3jmmWfQ3d2NVCqFd999Fz/4wQ/w6U9/GpZl5e37u9/9DnPnzsX3v/99PPfcc2hvb4dhGOjp6cEbb7yBa6+9FgsWLMDtt9++29/5iSeeyHp/+OGHD7uvaZo49dRT8eUvfxn//Oc/0d3djXg8jvXr1+Oyyy7DkUceiWg0OuRxYrEYjj76aHzjG9/Ayy+/jGg0ilgshhdffBHnnXceTj755IIBp/56enrQ0NCAb3/721i/fj16e3sRDofx7LPP4gtf+AIuuuiirPbnnntu1vu//vWvWUHHndatW4fGxsbMe1mW8wYYDzvssKz3A88tEREREREREdFEwiARERGNmqeeeipn21lnnQVZLvznZ+CkfqHj7K5vf/vbuOaaa4YsEyaEwM9+9jN8/etfH/KYv//97/HHP/6x4P5nnnkmb6Dr1ltvxXnnnYd4PD7o8VOpFM4//3zcc889Q44ln4GBukMOOWTYfR966CH8/ve/L7h/7dq1+OpXvzrkcX7xi1/gn//8Z8H9f/zjH/H9739/yONcccUVePXVVwf9nP4lCo8//nhMmzYt8z6ZTOJPf/pTTr/7778/6/0nPvEJzJo1K6fdwHM38NwSEREREREREU0kDBIREdGoyVey7aCDDhq0z7Jly3LWJnr77bczrw899FBs3rw559+HH36Igw8+OKuf2+3OCjq9+uqruOGGG7La1NfX4/7778eGDRvwhz/8AfPmzcvaf9tttw0ZCBBCIBgM4t5778U777yDX/7yl9A0LavNwCBEc3MzvvWtb2VtO/bYY/HEE0/gvffew5o1a/D5z38+a/+FF16I7u7uQceSz8svv5z1fr/99ht2X8MwMG3aNNx333146623cP/992cFXQAnSDbwM/IdZ9GiRXj44Yfx1ltv4dZbb0VlZWVWmxtuuAHbt28f9DjxeBwrVqzA3/72t0ym1cDr5YorrkAikQAAKIqCr3zlK1n7B/4sTNPE6tWrs7add955eT9/2bJlWe/feuutzGcREREREREREU00aqkHQEREk1d7e3vOtmAwOGgfVVVRXV2NlpaWzLaOjo7Ma7fbjTlz5mT1EULgzDPPzApUKIqCBx98MKu02q9//eusfrIs4+mnn8bChQsBOGv1HHTQQViwYEFW6bNf//rXWLVq1aDjvvvuu/GpT30KALBkyRL8+9//xi9/+cvM/rfeeiur/e23354VXNh3333x17/+NZNltWjRInz84x/H/PnzM2XQwuEw7rvvPnzzm98cdCz92baNtra2rG21tbXD7g8Ajz32GPbff//MOBctWoQDDjggq80999yTE6Trz+Vy4dlnn80EmPbdd1/U1NTgxBNPzLQxTRMPPvggLr300oLHCYVCePrpp+HxeAAAy5cvh6IoWX26urrw+OOPZ4597rnn4qc//Wlm/7PPPouWlhbU1dUBAP7xj39kXavV1dU44YQT8n6+3++HqqqZMoRCCLS1tWH27NkFx0xERERERERENF4xk4iIiMYdIURR7S+66CLcd999Wdtuu+22nIn+geXOVq1alQkQ7TRr1iwcd9xxWduee+65QT9/r732ygSIdtp7772z3g/MABo4lg0bNkBRFEiSlPmnqmrWOjnDGctAnZ2dOaX1qqurh91/+fLlmQDRTvvvvz+WL1+ete3FF18c9DjHHXdcTgbS5z//+ZyxDHWc0047LRMg2ilf1k//4yxcuBANDQ2Z95ZlZZXQG5hZdMYZZ8DlchUcw8AxDwzCERERERERERFNFAwSERHRqMmXsTLUhLppmjkBlUAgULD9VVddhZtvvjlr27XXXotzzjknp+2OHTuy3s+fPz/vMQeWnGttbYVlWQXHsGjRopxtAwMZA/sPVVatkObm5qLaFxtwG2ju3LnD2t4/82u4x5FlOScDZ3eO4/P5UFVVNehxBq51tTMwlEgk8MgjjwzadqCB51SSpEHbExERERERERGNVwwSERHRqNlnn31ytr3yyiuD9lm/fj3S6XTWtqVLl+Zte/PNN+OHP/xh1rbLLrsMl19+eZEj3TM1NTU52xRFGZXPKnb9m0AgkClht1NXV9ew+xcKgBQbKCn1cU455RSUl5dn3r/88sv46KOP8NhjjyEajWa2H3DAATnrDg00MIhZbPk+IiIiIiIiIqLxgkEiIiIaNcccc0zOtnvuuWfQ7JY777xzWMe57777cNFFF2VtO/vss3HttdcWPPb06dOz3m/cuDFvu02bNmW9DwaDIx70GTiWT37yk9i8efOQ/x599NGiPkeW5ZwgRv81noYy8FzstGXLlqz3oVCo6OPYto2mpqY9Pk44HEZPT8+gxykvL8cpp5ySte3+++/PKTWXr3Rdf93d3Zn1iAAnGDXUOltEREREREREROMVg0RERDRqli9fjiOOOCJr2xtvvIGf/vSneduvWbMGv/nNb7K2+f1+nHXWWVnbHnvsMZx99tlZwabPfvazuO222wbNRBk4ljVr1uCDDz7I2tbU1IQnnngia9vhhx9e8Ji7a9WqVVnv161bB8MwMGfOnLz/Zs6ciddee23QtXIKOeigg7Lev/XWW8Pu++abb+L111/P2vb666/jzTffzNp2yCGHDHqcJ554IqdU3iOPPJKT1TTUcR544IGcbKrbb789p12+4wwsI3fnnXdm/azdbjdOO+20QT9//fr1We/322+/nNKCREREREREREQTBYNEREQ0qm688Ua43e6sbd/97ndx2mmn4e9//zs+/PBDvPjii/jOd76DY489NitLAwB+/OMfw+/3Z94///zzOOWUU7LaLV68GD/96U+xbds2bNmyJetf/6yZr33ta1nHtm0bRx99NB544AG8/fbb+NOf/oQjjzwShmFktfv617++p6chxznnnJMVXOjt7cWqVavws5/9DC+99BI+/PBDvPrqq7j33ntxwQUXoL6+HieddBIikUjRnzUwOPbyyy8X1f8zn/lM5hw9+OCD+MxnPpPT5swzzxz0GKlUCkceeST+/Oc/Y8OGDbjtttty1o1SVRWnnnrqoMdpbW3F0UcfjSeffBLr16/Hddddh+9+97tZbaqqqvDpT386p29DQwP23nvvzPvNmzcjlUpl3p944olZ11o+L730Utb7gcE+IiIiIiIiIqKJRC31AIiIaHLbf//NelGqAAAEcklEQVT9cffdd+OMM87IWmvowQcfxIMPPjho34svvjgnsHP77bfnZJK8++67WLJkSd5jnHXWWZkSdgceeCAuueQS3HjjjZn927Ztw5e//OWCYzj//PNHJRAwY8YM3HjjjVnfb8eOHbjkkktG/LOOPfbYrHWann/++WH39Xq9aG5uHvQcnXzyyUNmAHm9Xrz//vv4/Oc/X7DNxRdfjPr6+kGPo6oqXnjhBRx77LEF21xzzTUFs3vOOecc/Pd//3fefQMzjfIZeO6OO+64IfsQEREREREREY1XzCQiIqJRd/LJJ+P555/HPvvsM6z2tbW1uPPOO7OCOSPluuuuwxVXXAFZHvpP4EUXXYRf//rXIz6Gnf7zP/8Tt99+O8rKyobVPhAI7FZps6VLl2LlypWZ9+vXr8d77703rL4nnXQSvvrVrxbcf+ihh+K2224b8jgXXXQRjj/++IL7TzjhBFxzzTVDHufqq6/OygYa6Otf/3pOYLG/r3zlK1DV3Gdk5s6diyOPPHLQz+7q6sJTTz2VeT9nzhx88pOfHHLMRERERERERETjFYNEREQ0Jg4++GBs2LABf/3rX3HBBRdg3333RU1NDVRVhc/nw4IFC/ClL30Jv/3tb9HY2JizDtFIkWUZ11xzDd577z1ceumlOOCAA1BVVZUZx7Jly3DhhRdiw4YNuOmmm/IGFEbSueeeiy1btuAnP/kJjj76aNTV1cHlckHXddTV1eGwww7DJZdcgieeeAI7duxAKBTarc8ZGDi5//77h9VPkiTceuutWL16NVatWgW/3w+Px4P99tsP1113Hf75z3/C5/MNeRxd1/HYY4/h1ltvxSGHHIKKigqUlZXh4IMPxm233YaHH34Yuq4PeZxp06bhtddew9VXX42lS5fC6/WisrISq1atwh//+Ef88pe/HHRdqrq6urzBqnPOOWfQfgCwevXqrFKEX/3qV4cVbCQiIiIiIiIiGq8k0X/VbyIiIpqU0uk0Fi9ejE2bNgEA6uvrsXHjxpzAzKpVq/DPf/4z875/ub5izJkzB42NjZn3V155Ja666qrdGvt4cdBBB+HVV18FAPj9fnz00Ueoqakp8aiIiIiIiIiIiHYfH38lIiKaAnRdx//+7/9m3m/btg133XVXCUc0sTz55JOZABEAXHHFFQwQEREREREREdGExyARERHRFHHKKadgxYoVmfc/+clPYJpmCUc0cfzP//xP5vWcOXNw4YUXlnA0REREREREREQjY3QXWiAiIqJxZd26daUewoT03HPPlXoIREREREREREQjjplEREREREREREREREREU5AkhBClHgQRERERERERERERERGNLWYSERERERERERERERERTUEMEhEREREREREREREREU1BDBIRERERERERERERERFNQQwSERERERERERERERERTUEMEhEREREREREREREREU1BDBIRERERERERERERERFNQQwSERERERERERERERERTUEMEhEREREREREREREREU1B/x9PkMxErcl5UQAAAABJRU5ErkJggg==",
+      "text/plain": [
+       "<Figure size 1000x1400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
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",
+      "text/plain": [
+       "<Figure size 1000x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Saving scatter density plot to /wrk/qrasool/output_testaircraft_PR189_uptoviolin_multiplemodels/plot_grp4.scatter_density.NO2_CL_RYERSON.2019-09-05_12.2019-09-06_00.all.CONUS_firexaq_vs_wrfchem_v4.2.png...\n",
+      "Value of fill after reading from scatter_density_config: True\n",
+      "Processing scatter density plot for model 'wrfchem_v4.2_test' and observation 'firexaq'...\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Saving scatter density plot to /wrk/qrasool/output_testaircraft_PR189_uptoviolin_multiplemodels/plot_grp4.scatter_density.NO2_CL_RYERSON.2019-09-05_12.2019-09-06_00.all.CONUS_firexaq_vs_wrfchem_v4.2_test.png...\n",
+      "Value of fill after reading from scatter_density_config: True\n",
+      "Processing scatter density plot for model 'wrfchem_v4.2' and observation 'firexaq'...\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Saving scatter density plot to /wrk/qrasool/output_testaircraft_PR189_uptoviolin_multiplemodels/plot_grp4.scatter_density.NO_CL_RYERSON.2019-09-05_12.2019-09-06_00.all.CONUS_firexaq_vs_wrfchem_v4.2.png...\n",
+      "Value of fill after reading from scatter_density_config: True\n",
+      "Processing scatter density plot for model 'wrfchem_v4.2_test' and observation 'firexaq'...\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Saving scatter density plot to /wrk/qrasool/output_testaircraft_PR189_uptoviolin_multiplemodels/plot_grp4.scatter_density.NO_CL_RYERSON.2019-09-05_12.2019-09-06_00.all.CONUS_firexaq_vs_wrfchem_v4.2_test.png...\n",
+      "Value of fill after reading from scatter_density_config: True\n",
+      "Processing scatter density plot for model 'wrfchem_v4.2' and observation 'firexaq'...\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Saving scatter density plot to /wrk/qrasool/output_testaircraft_PR189_uptoviolin_multiplemodels/plot_grp4.scatter_density.O3_CL_RYERSON.2019-09-05_12.2019-09-06_00.all.CONUS_firexaq_vs_wrfchem_v4.2.png...\n",
+      "Value of fill after reading from scatter_density_config: True\n",
+      "Processing scatter density plot for model 'wrfchem_v4.2_test' and observation 'firexaq'...\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Saving scatter density plot to /wrk/qrasool/output_testaircraft_PR189_uptoviolin_multiplemodels/plot_grp4.scatter_density.O3_CL_RYERSON.2019-09-05_12.2019-09-06_00.all.CONUS_firexaq_vs_wrfchem_v4.2_test.png...\n",
+      "Warning: ty_scale not specified for NO2_CL_RYERSON, so default used.\n",
+      "Reference std: 1.6687157922450515\n",
+      "Warning: ty_scale not specified for NO2_CL_RYERSON, so default used.\n",
+      "Warning: ty_scale not specified for NO_CL_RYERSON, so default used.\n",
+      "Reference std: 0.2823536302739215\n",
+      "Warning: ty_scale not specified for NO_CL_RYERSON, so default used.\n",
+      "Warning: ty_scale not specified for O3_CL_RYERSON, so default used.\n",
+      "Reference std: 24.787977643616014\n",
+      "Warning: ty_scale not specified for O3_CL_RYERSON, so default used.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/qrasool/mm_developaircraftPR189_scatterviolin/MELODIES-MONET/melodies_monet/plots/surfplots.py:920: FutureWarning: \n",
+      "\n",
+      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
+      "\n",
+      "  sns.boxplot(ax=ax,x=\"variable\", y=\"value\",data=pd.melt(comb_bx), **boxplot_kwargs)\n",
+      "/home/qrasool/mm_developaircraftPR189_scatterviolin/MELODIES-MONET/melodies_monet/plots/surfplots.py:920: FutureWarning: \n",
+      "\n",
+      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
+      "\n",
+      "  sns.boxplot(ax=ax,x=\"variable\", y=\"value\",data=pd.melt(comb_bx), **boxplot_kwargs)\n",
+      "/home/qrasool/mm_developaircraftPR189_scatterviolin/MELODIES-MONET/melodies_monet/plots/surfplots.py:920: FutureWarning: \n",
+      "\n",
+      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
+      "\n",
+      "  sns.boxplot(ax=ax,x=\"variable\", y=\"value\",data=pd.melt(comb_bx), **boxplot_kwargs)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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uvfVWp/MmT56sKVOmXPO5ly1bpjp16rjsi4iI0KeffqotW7YoLi5OoaGh6ty5s4YPH65y5cq55bUBAAAARU2RDBWbN2/WwIEDJUk+Pj6qVauWAgMDdezYMa1atUqrVq3S8OHDNWrUKJfnV61aVVWrVnXZV6pUqWyvOWzYMCUnJ6tixYqqV6+eIiMjNXv2bK1evVrz5s1T5cqV3fHyAAAAvMLGjVK7dp6uAtdDkQwVhmGodu3aGjhwoLp166by5ctLklJTUzVlyhR99tlnmjp1qpo1a6Y777zT6fwHHnhAzzzzTK6vFx8fr+eee07Jycnq37+/xo4dKz8/P8XExGjEiBHasWOHXn75ZX322Wdue40AAABF3V13ScnJnq4C10ORXFPRtGlTLVu2TH379rUHCkny9/fX6NGj1bFjR0nSggUL3HK9efPm6dKlS6pTp47GjRsnPz8/SVKFChX03nvvydfXV+vWrdO+ffvccj0AAICibvJkKSVFymHmObxEkQwVZcqUka9v9oMs7f4aZzt27Jhbrrd69WpJUs+ePVWiRAmHvmrVqqlt27aSpJUrV7rlegAAAEXR7t1SWJh0ww3Sc89Z20aNsj4OC7P2wzsVyelPOUlJSZEklSxZ0mX/li1bdPjwYcXGxiooKEhhYWHq0aOHgoODnY5NT0+3j0CEh4e7fL7w8HCtX79eu3btctMrAAAAKJqSkqSoqL8fZ2RYH2dzHxx4Ca8LFYZhaMWKFZKyDwHbtm1zeLxy5UpNmTJFr776qnr16uXQd/LkSaWlpUmSatas6fL5bO1RWd9BVzl37pzOnz/v1B4REZHtOQAAAEVJ+fJSzZqSq483NWta++GdvC5ULFiwQPv375efn58ee+wxh77g4GA9+eSTuvvuu1WzZk2VLFlS+/fv19SpU/Xrr7/qpZdeUlBQkDp16mQ/Jy4uzv5z+WzeCbbbyWY99mrz58/P8Xa2AAAARVn58lKHDtK6dc59HToQKryZV4WKffv26T//+Y8kadSoUapVq5ZD/8MPP+x0Tnh4uKZPn65nnnlGq1ev1oQJE3TnnXfKYrFIst5Rysa2QPtq/v7+kv6eduVKnz59HMKKTUREhMaMGZPDKwMAACgasrk7f7bt8A5eEyqio6M1bNgwpaSkqHv37hoyZEiuz7VYLHr++ee1evVqHT9+XAcPHlTDhg0l/R0YJCktLU0BAQFO59uCh6s+m5CQEIWEhOS6JgAAgKImKEgaPlx65RUpPf3vdl9fa3tQkKcqQ0Erknd/utr58+c1ePBgnT9/XnfccYfefvtt+0hDbt14440K+utveta1EVmnPGU3veny5ctOxwIAABRHQUFSvXqObfXqESi8XZEPFbGxsRo8eLCOHz+u1q1b66OPPsp2mlJObLepzcjIsLdVr17d/nzR0dEuz7O1165dO1/XBQAA8CYdO0rlykklSli//7WFGLxYkQ4VCQkJeuKJJ3To0CGFhYVp6tSp2d5GNieXLl3SxYsXJUmhoaH2dl9fX918882SpB07drg819berFmzfF0bAADAmzz5pPTSS9bbyb78svUxvFuRDRWpqakaMWKEdu3apXr16mnmzJkqU6ZMvp9vzpw5MgxDZcuWVVhYmENf586dJUmLFy92GMWQpFOnTmnTpk2SpC5duuT7+gAAAEWdbfO7Hj2s6yokafx462M2v/NuRTJUZGRk6LnnntPmzZtVq1YtzZ49274eIjuHDx/Wa6+9psOHDzu0p6SkaNq0aZoxY4YkaejQoQ6LsyXpkUceUYUKFRQREaEJEybY962IiYnR888/r/T0dHXs2FFNmjRx34sEAAAoYpo2lb7+WjpzRrLdQDM11fr466+t/fBORfLuT8uXL9eaNWskST4+Pho5cqTL44KDg/Xxxx9Lsu6MPXfuXM2dO1cVK1ZU1apVJUmRkZFKSkqSJPXu3VtPPPGE0/OUKVNGH3zwgYYNG6avvvpKS5cuVdWqVe3nVq9eXW+99VZBvFQAAIAipWlTqUoVx121q1QhUHi7Ihkqsu4dcezYMR07dszlcdWrV3f4eeTIkdq5c6ciIyN19OhRpaWlqVKlSurYsaMefPBBdejQIdtrtm3bVgsXLtTUqVO1efNmHTp0SKGhoercubOGDx/OnZ8AAECxFxsrzZlj/X51+4cfSgMHchcob2UxDMPwdBHF2b59+9SrVy8tWrRIjRs39nQ5AAAA+bZ8ufTQQ1J8vHNfmTLSggXSPfdc/7qQf7n9rFok11QAAACg8Dl7VkpMdN2XmGjth3cqktOfAAAAUPgMHGj9PmiQc9+sWX/3w/swUgEAAAC3iI11Xk+Rmz4UfYQKAAAAuM1fN9XMdTu8A6ECAAAAbuXre+3H8D6ECgAAALhFUJA0fLh09Z32y5e3tnM7We9FqAAAAIBb2Pap8Pd3bPf3d71/BbwHoQIAAABuERcnrVkjXbrk2H7pkrU9Ls4zdaHgESoAAADgFtHR0pYtUkqKY3tKirU9OtozdaHgESoAAADgFh9/LF244LrvwgVrP7wToQIAAABuMWmSVLWq676qVa398E6ECgAAALhF+fLS44+77nv8cee7QsF7ECoAAADgFkFB0ujRrvtGj+aWst6MUAEAAAC3+PZbqUoV131Vqlj74Z0IFQAAAHCb9PS8tcM7ECoAAADgFp07S48+6rrv0Uet/fBOhAoAAAC4RVCQ9OGHrvs+/JA1Fd6MUAEAAAC3yS44ECi8G6ECAAAAbhEVJfXsKZUs6dhesqS1PSrKM3Wh4BEqAAAA4BY//yz9+KOUnOzYnpxsbf/5Z8/UhYJHqAAAAIBb9OghPfSQ676HHrL2wzsRKgAAAOAWcXHS5cuu+y5ftvbDOxEqAAAA4Ba1a0uffOK675NPrP3wToQKAAAAuEVUlDRqlOu+UaNYqO3NCBUAAABwi+hoaeNG130bN1r74Z0IFQAAAHCL9u2lRYtc9y1aZO2HdyJUAAAAwC1Gj5Y6dHDd16GDtR/eiVABAAAAt8jp7k7c/cl7ESoAAADgFoMGSQEBrvsCAqz98E6ECgAAALhF+/bSmjWu+9asYU2FNyNUAAAAwG2yCw4ECu9GqAAAAIBbvPuuZLG47rNYrP3wToQKAAAAuEXjxpK/v+s+f39rP7wToQIAAABucfSolJbmui8tzdoP70SoAAAAgFu0by9VqeK6r0oV1lV4M0IFAAAA3KJ8ealhQ9d9DRta++GdCBUAAABwGz+/vLXDOxAqAAAA4BZxcVJUlOu+qCh21PZmhAoAAAC4RdOm0oIFrvsWLLD2wzsRKgAAAOAW334rtW7tuq91a2s/vBOhAgAAAG7RoIEUEuK6LyTE2g/vRKgAAACAW+zYIUVHu+6Ljrb2wzsRKgAAAOAWPXpIjzziuu+RR6z98E6ECgAAALhFUJD06aeu+z791NoP70SoAAAAgFvExkpz5rjumzPH2g/vRKgAAACAWwQFSQMHSgEBju0BAdZ2Riq8F6ECAAAAbmEbqWjSxLG9SRNGKrydr6cLAAAAgHf4/nvpX/+SMjIc27dvl/744++RDHgfRioAAADgFqGhkm82v7L29bX2wzsRKgAAAOAW8fFSWprrvrQ0az+8E9OfAAAA4BYPPmj9/tBDzn3z5v3dD+/DSAUAAADcJrvgQKDwboQKAAAAAKYQKgAAAOAWsbHShx9KN90kNWtmbWvWzPr4ww+5paw3I1QAAADALWy3jA0Lk3btsrbt2mV9zOZ33o1QAQAAALeIipIGDbLuSZHVH39Y26OiPFEVrgdCBQAAANzi55+lH390Dg9RUdb2n3/2TF0oeIQKAAAAuMWdd0pNm7rua9rU2g/vRKgAAACAW9SuLS1e7Lpv8WJrP7wToQIAAABuk11wIFB4N0IFAAAA3KpsWev3OnUcH8N7+Xq6AAAAAHiXGTOkW2+1jk5ERUmbN3u6IhQ0QgUAAADcqk+fv3+uXZupT8UB058AAAAAmEKoAAAAAGAKoQIAAACAKYQKAAAAAKYQKgAAAACYQqgAAABAgTh/3tMV4HohVAAAAKBA9O/v6QpwvRAqAAAA4Hb79kkrV0r793u6ElwPbH4HAAAAt4iNlebMsX7/8Udr24ABUvfuUlCQNHCg9Tu8D6ECAAAAbhEXJ61ZI23eLF28aG3bvl06dky69VapZ09Chbdi+hMAAADconZt6ZNPpJQUx/aUFGt77dqeqQsFj1ABAAAAt1i+XAoLk+LjHdvj463ty5d7pi4UPEIFAAAA3OLmm6UmTVz3NWli7Yd3IlQAAADALaKjpSNHXPcdOWLth3ciVAAAAMAtdu+WLlxw3XfhgrUf3qlI3v3JMAxt375da9eu1fbt2xUZGank5GQFBQWpefPm6tevn2699dZsz9+5c6emT5+unTt3KjExUTVq1FC3bt30+OOPKyAgINvzIiIi9Omnn2rLli2Ki4tTaGioOnfurOHDh6tcuXIF8VIBAACKjBEjrN+fesq5b8qUv/vhfYrkSMXmzZvVr18/zZ49W3v27FGlSpVUr149JSQkaNWqVXrsscf04Ycfujz3hx9+UL9+/fTTTz/J399fderU0fHjx/Xxxx+rX79+SkpKyvaavXr10pIlS5SRkaF69erpwoULmj17tnr16qUL2cVyAACAYiS74ECg8G5FMlQYhqHatWvr1Vdf1ebNm7Vy5UotXrxYW7Zs0bBhwyRJU6dO1c8//+xw3okTJ/Tyyy8rIyNDY8aM0S+//KLFixdr5cqVuvHGG7Vnzx5NmjTJ6Xrx8fF67rnnlJycrP79++vXX3/VokWL9PPPPys8PFzR0dF6+eWXr8trBwAAAAobt4eKlJQUnT9/XilX36DYjZo2baply5apb9++Kl++vL3d399fo0ePVseOHSVJCxYscDhv1qxZSk1NVfv27fX444/LYrFIkqpXr6633nrLfs7Vow7z5s3TpUuXVKdOHY0bN05+fn6SpAoVKui9996Tr6+v1q1bp3379hXYawYAACjsoqKsG9wFBjq2BwZa26OiPFMXCp6pNRUnT57Uli1btG3bNu3cuVPnzp1zmD5UsmRJhYSEqHnz5mrVqpXatGmjGjVqmC66TJky1+xv166dfv31Vx07dszeZhiGVq9eLUl64IEHnM4JDw/XTTfdpMjISK1du1Z9+vSx99nO69mzp0qUKOFwXrVq1dS2bVutX79eK1euVOPGjfP7sgAAAIq0zz6Tvv/euT0x0dreqJH01+9x4WXyHCpSU1P1448/6ttvv9WuXbvs7YZhOB2blJSkqKgoHT9+XP/73/8kWUcZHnzwQd13333y9/c3UXr2bKMkJUuWtLedOnVK58+flyS1aNHC5Xnh4eGKjIzUrl277KEiPT3dPgIRHh6e7Xnr1693+PMAAAAobl54Qdq6VVq71rnvrrus/fBOuQ4Vqamp+vrrrzVz5kxdunRJkmOQsE0lciXrcbt379bu3bv1/vvva+jQoerbt+8177iUV4ZhaMWKFZIcQ0DUX+Nt/v7+CgkJcXluzZo1HY6VrKMxaWlpDv25OQ8AAKC4CQqSvvtOqlDBue+776z98E65ChXLli3TpEmTdObMGXtAsFgsDkHC1UiFzdWBwzAMXbp0SRMnTtQXX3yhF154QV27ds1P/U4WLFig/fv3y8/PT4899pi9PS4uTpJUrly5bAOQ7bawly9fdjpPksP6DVfnZT32aufOnbOPlGQVERGR7TkAAABFTXbBgUDh3XIVKkaPHi2LxSLDMOwfyLOGiIoVK6pRo0aqUKGCgoKCVKZMGcXHxys2NlaXLl3SgQMHFBMTYz8+63OcOXNGzz//vFtCxb59+/Sf//xHkjRq1CjVqlXL3mebEmVbZO2KbTpWcnKyvS01NdX+c3bn2s671uL0+fPna8qUKTm9BAAAgCIvMFBKTZUqVZIuXpQKaMY7CpE8r6kwDEMlS5bU7bffri5duqhZs2a5WnwdHR2tXbt2adWqVfr111+VnJxsDyruEB0drWHDhiklJUXdu3fXkCFDHPptU6xsU5lcsQWIrGsxsq77SEtLczlVy3betaZx9enTR506dXJqj4iI0JgxY7I9DwAAoKjZuFFKSpJuu03atEnK8tEKXirXocIwDDVt2lQDBgxQp06dFHj1vcJyULNmTdWsWVPdu3dXYmKiVq9erf/+97/as2dPnou+2vnz5zV48GCdP39ed9xxh95++22nKU62qUuXL192GHHJyjbtKevu2FmnPMXFxblcj2E7L7vpUZIUEhKS7VoOAAAAbxAbK82ZY/1uu7P/kCHSgw9K69ZJAwcyDcpb5SpUtG3bVsOGDdOtt97qlosGBgbq/vvv1/33369NmzZp+vTp+X6u2NhYDR48WMePH1fr1q310UcfuZymVLt2bUnWUYVz584pNDTU6Zjo6GiHYyXrHhZ+fn5KS0tTdHS0y2Dg6jwAAIDi5vhxacYM6ehR60iFJO3fL02cKN14o9SpE6HCW+Vq87vPP//cbYHiam3bttXnn3+er3MTEhL0xBNP6NChQwoLC9PUqVMdpi5lVa1aNQUHB0uStm/f7vKYHTt2SJKaNWtmb/P19dXNN9/s0J+b8wAAAIqj1NS/A4VNUpK1Hd7L1OZ3npSamqoRI0Zo165dqlevnmbOnHnNTfEsFovuvvtuzZ07VwsXLnRaGL5jxw5FRkbKz8/Pae1D586dtWvXLi1evFiDBw922ADv1KlT2rRpkySpS5cubnyFAAAAjgzDUGJioqfLyFalSlK3br766CN/SVmnmhvq1i1VlSqlKyHBU9VdW2Bg4DW3SMC1mQoV0dHR2e7dUJAyMjL03HPPafPmzapVq5Zmz56toFyMpQ0ZMkTfffedNmzYoJkzZ2rIkCGyWCw6efKkXnrpJUlS79697SMaNo888ohmzZqliIgITZgwQWPHjpWfn59iYmL0/PPPKz09XR07dlSTJk0K4uUCAADIMAy1b99ev/32m6dLuYZakj6R1M2p56OPVuujj56SdPx6F5Ur7dq10/r16wkW+WQqVHTp0kUtWrRQz5499c9//lOlS5d2V13XtHz5cq1Zs0aS5OPjo5EjR7o8Ljg4WB9//LH9cc2aNfXmm29q3LhxmjRpkr788ktVqlRJhw8fVlpamho3bqwXXGz1WKZMGX3wwQcaNmyYvvrqKy1dulRVq1ZVZGSkkpKSVL16db3FnvMAAKCAFf4PvMclPSVXocLaXjgDBcwzFSoMw9D27du1fft2vfnmm+rSpYt69Oihtm3buqs+l7LuHXHs2DEdO3bM5XHVq1d3auvRo4dq1aql6dOna+fOnTpy5Ihq1Kih7t27a+jQodneFrZt27ZauHChpk6dqs2bN+vQoUMKDQ1V586dNXz48Gve+QkAAMAsi8Wi9evXF+rpTzbVqhm6fPnvAFS+vHTy5H4PVpQzpj+ZYzFMbBTRsGFDh70mbP8hqlatqvvvv189evTgjkg52Ldvn3r16qVFixapcePGni4HAADAtObNM/THHz6SIiTVUYsWFv3+u6erQn7k9rNqru7+lBOLxWIPF4Zh6NSpU5o2bZr++c9/6pFHHtG3336r+Ph4d1wKAAAAhdyoUWmSbpBUT/v2JYp9fr2fqVDRrl07lShRwh4mbOEia8D4448/9Morr6h9+/YaM2aMNm7c6K7aAQAAUAj17p0h2/qJ2rWlPn08Ww8Knqk1FbNmzVJsbKxWrVqlZcuWadu2bcrIyJDkuJDIMAwlJydryZIlWrJkiUJDQ3X//ffrueeeM1c9AAAAAI8zPf0pKChIDz30kObMmaNff/1V48ePV8uWLSXJaQTD9vjMmTOmdtEGAAAAUHi4dfO7SpUqqV+/furXr5/Onj2r5cuXa/ny5dq1a5c9WEiSibXhAAAAAAoZtyzUdiU0NFQDBw7U22+/rV69ehEkAAAAAC/l1pEKm5MnT2rZsmVavny5Dhw4YG+3TYUCAAAA4D3cFirOnTun5cuXa9myZdq9e7ckx2lOhAkAAADAO5kKFZcuXdKKFSu0fPlybd++3R4irt4ML2tb5cqVde+996pXr15mLg0AAACgkDAVKjp06KDMzExJjkHi6gXZ/v7+6tSpk3r27KkOHTrIx6fAlnIAAAAAuM5MhYqMjAz7rWJdjUo0bdpUPXv2VLdu3VSuXDlzlQIAAAAolNyypsIWLCTrXZ/uu+8+9ezZUzfddJM7nh4AAABAIWY6VBiGoZIlS+quu+5Sz5491a5dOxZlAwAAAMWIqVDRvHlz9erVS/fcc4/KlCnjrpoAAAAAFCGmQsXcuXPdVQcAAACAIsrtm99FR0frzz//VExMjCwWi4KCgtSwYUPVrFnT3ZcCAAAAUAi4LVTMmzdPX3zxhY4dO+ayv3bt2nrsscf08MMPs+YCAAAA8CKmQ8Xly5c1fPhw7dixw2EH7asdO3ZMr7/+un744QdNnTpVQUFBZi8NAAAAoBAwtQtdenq6Bg0aZN9N27bxXXZfhmFo586dGjJkiDIyMtz1GgAAAAB4kKlQ8c0332jfvn0Ou2hL1tvMZv2ysR2zf/9+ff3112YuDQAAAKCQMDX96YcffnB4bBiG/P391bRpU4WGhkqSzp49q927dys1NdUeKgzD0P/+9z8NGDDAzOUBAAAAFAKmQsXRo0ft05osFovuu+8+/fvf/1a5cuUcjrty5Yr+85//6Pvvv7cfn92CbgAAAABFi6npT1mnPN1000165513nAKFJJUtW1ZvvfWW6tSpY+ZyAAAAAAohU6Gidu3a9lGKli1bXvNWsT4+PmrZsqX9+Nq1a5u5NAAAAIBCwlSo6Nq1q/3nK1eu5Hh81mP+8Y9/mLk0AAAAgELCVKjo37+/6tatK8Mw9Msvv+jkyZPZHhsdHa1169ZJkmrUqKHHHnvMzKUBAAAAFBKmQoW/v79mzZqlunXrKiEhQX369NE333yj6OhopaenKz09XdHR0frmm2/0yCOPKDExUdWqVdOsWbNUsmRJd70GAAAAAB6Uq7s/NWrUKMdjLBaLLly4oDfeeMNlv20txenTp/WPf/xDFotF+/fvz1u1AAAAAAqdXIWKrBvYZSfrrtnZ9efl+QAAAAAUDbnep+Jad3bKz3EAAAAAvIOpNRUAAAAAkKuRimrVqhV0HQAAAACKqFyFip9++qmg6wAAAABQRDH9CQAAAIAphAoAAAAApuT67k+5kZKSop07d+rPP/9UTEyMJKlChQpq2LChmjdvroCAAHdeDgAAAEAh4JZQkZycrE8++UQLFizQ5cuXXR5TtmxZPfTQQ3rqqadUqlQpd1wWAAAAQCFgevrTiRMndP/992vmzJmKi4uTYRguvy5fvqxZs2apR48eOnHihDtqBwAAAFAImAoVSUlJGjRokKKiomQYhn1X7ey+DMNQVFSUBg0apKSkJHe9BgAAAAAeZCpUzJ49W9HR0fbQYHP1KIWN7ZgTJ05o9uzZZi4NAAAAoJAwtaZixYoVDo8Nw1BISIjatm2rKlWqyDAMnT17Vps3b9bZs2cdRixWrFihp556ylTxAAAAADzPVKg4ceKEPSRYLBYNGzZMzz77rEqUKOFwXEZGhiZPnqxp06Y5jFYAAAAAKPpMTX/y9/e3/9y4cWM999xzToFCkkqUKKFRo0apSZMm9ulQWc8FAAAAUHSZChU33nijfZQiLCwsx+Ntx1gsFt10001mLg0AAACgkDAVKrp3727/+fz58zken/WY+++/38ylAQAAABQSpkLFI488optvvlmGYejXX3/Vvn37sj127969+uWXXyRJLVq0UJ8+fcxcGgAAAEAhYWqh9tmzZ/V///d/GjlypE6dOqVHH31Uffv2VYcOHVS1alVZLBadOnVK69ev1zfffKO0tDTVq1dP48eP1+nTp7N93mrVqpkpCwAAAMB1ZCpUdOrUyX43J4vFoqSkJM2ePdvlHhS2tRdHjhxRjx49sn1Oi8Wi/fv3mykLAAAAwHVkKlRIst/NKeseFK7Ywkd2/QAAAACKJtOhIutO2q4e53R8VgQOAAAAoOgxHSokwgAAAABQnJkKFa1atXJXHQAAAACKKFOh4quvvnJXHQAAAACKKFP7VAAAAAAAoQIAAACAKW5ZqG1z9uxZbdiwQQcOHFBMTIwsFouCgoLUqFEjtWvXTlWqVHHn5QAAAAAUAm4JFefPn9eECRO0atUqZWRkuDymRIkS6ty5s1588UWFhoa647IAAAAACgHT05/27dune++9V8uXL1d6eroMw3D5lZ6erhUrVuj+++/X3r173VE7AAAAgELAVKiIiYnR448/rtjYWBmGYd9VO7svwzAUGxurJ554QjExMe56DQAAAAA8yFSomDFjhn3thG2n7OxGKqS/d9OOiYnRjBkzTJYOAAAAoDAwtaZi7dq19qAgWQNF06ZN1b59e1WpUkWGYejs2bPauHGjdu3a5TBisXbtWr3wwgumXwAAAAAAzzIVKs6cOSNJ9qlPr7/+uh566CGn45599ll9++23Gj9+vD2E2M4FAAAAULSZmv4UGBgoyTqtqVWrVi4Dhc2DDz6o1q1b26dClS5d2sylAQAAABQSpkJF/fr17SGhbt26OR5fp04dSdYQ0rBhQzOXBgAAAFBImAoVPXv2tP8cHR2d4/EnTpyw/9y7d28zlwYAAABQSJgKFT169FC7du1kGIY2btyoX375Jdtj161bpw0bNshisahLly7q2rWrmUsDAAAAKCRMLdTetm2bBgwYoKNHj+rUqVMaPny4OnfurI4dO6pq1aqyWCw6deqU1q9fr1WrVkmyTpN6+OGHtW3btmyft1WrVmbKAgAAAHAdmQoV/fv3t9/NyWKxKDMzU6tWrbIHiKxsd4g6cuSIBg8enO1zWiwW7d+/30xZAAAAAK4jU6FCksPGdrY9KFzJujkeAAAAAO9hOlRk3fzO1eOcjs+KwAEAAAAUPW4bqQAAAABQPJkKFVlvKQsAAACgeDIVKiZMmOCuOgAAAAAUUab2qQAAAAAAQgUAAAAAUwgVAAAAAEzJ1ZqK6dOnq2/fvipTpozbC4iPj9fXX3+tYcOGuf25AQAAcmIYhhITEz1dhldJSEhw+TPcIzAwMMdtHK63XIWK999/XzNmzFDfvn3Vr18/hYSEmL7w+fPn9d///lfffPON4uPjCRUAAMAjEhMTC+QXp7AKDQ31dAleJz4+XqVLl/Z0GQ5yffen+Ph4TZ8+XTNnzlTLli3VvXt33XXXXapYsWKuL3bp0iWtWbNGS5cu1e+//67MzEwZhpGvpBUdHa1NmzZp9+7d2r17t44cOaKMjAyNHDlSI0aMcHnO5MmTNWXKlGs+77Jly1SnTh2XfREREfr000+1ZcsWxcXFKTQ0VJ07d9bw4cNVrly5PL8GAAAAwBvk6ZayhmEoIyNDW7du1datW/XKK6+oZs2aCgsLU8OGDVWxYkWVL19epUuXVkJCgmJjY3Xp0iX9+eef2rNnj06cOOHwXGaGbb788kt9+eWX+Tq3atWqqlq1qsu+UqVKuWzfvHmzhg0bpuTkZFWsWFH16tVTZGSkZs+erdWrV2vevHmqXLlyvuoBAACFww/vhatkAEtOUfgkp2Tqvud3eLqMbOUqVPTu3VuLFi1yCAK2nbSPHz+u6OhoLVu27JrPkXXnbYvFIovFIsMw5OPjo969e+e58AoVKujOO+9UWFiYwsLC9N1332nlypW5OveBBx7QM888k+trxcfH67nnnlNycrL69++vsWPHys/PTzExMRoxYoR27Nihl19+WZ999lmeXwcAACg8Sgb4qFRACU+XARQ5uQoVb775pvr166cPPvhAv/76qyQ5jDJkDQzZcXV8hw4dNHr0aDVq1ChPRUtymuKUU6gxY968ebp06ZLq1KmjcePGqUQJ6/9sKlSooPfee0+dO3fWunXrtG/fPjVu3LjA6gAAAAAKo1yP7zVq1EjTp0/XwoULde+998rPz0+GYdhHL3L6sh1bokQJde3aVQsWLNCMGTPyFSiut9WrV0uSevbsaQ8UNtWqVVPbtm0lKdcjJQAAAIA3ydOaCklq3LixJk2apFdeeUWrV6/W5s2btW3bNp0+fTrbc0JDQ9WyZUu1adNGXbp0UVBQkJmaTduyZYsOHz6s2NhYBQUFKSwsTD169FBwcLDTsenp6dq3b58kKTw83OXzhYeHa/369dq1a1eB1g0AAAAURnkOFTZly5ZVr1691KtXL0nS2bNnde7cOV26dEmXL19WuXLlVKFCBYWEhKhKlSpuK9gdtm3b5vB45cqVmjJlil599VX767E5efKk0tLSJEk1a9Z0+Xy29qioqAKoFgAAACjc8h0qrhYaGlro70McHBysJ598Unfffbdq1qypkiVLav/+/Zo6dap+/fVXvfTSSwoKClKnTp3s58TFxdl/Ll++vMvntd1ONuuxVzt37pzOnz/v1B4REZHflwMAAAAUCm4LFUXBww8/7NQWHh6u6dOn65lnntHq1as1YcIE3XnnnfaF5ampqfZj/fz8XD6vv7+/JCklJSXba8+fPz/HPTIAAAC8gWEYiotPV1JKpkoF+Kh8Gd9CtwM03KtYhYrsWCwWPf/881q9erWOHz+ugwcPqmHDhpL+DgySlJaWpoCAAKfzbcHDVZ9Nnz59HEZAbCIiIjRmzBizLwEAAMDjriSma8VvF7TwpzM6ef7vX7ZWDw7QA52q6J+3VVbZQD5+eiP+q/7lxhtvVFBQkGJjYxUVFWUPFVmnPMXFxSkkJMTp3MuXLzsde7WQkBCX5wIAAHiDLXtjNX7aYSWnZEpXDUqcupCiyfOjNOP7aL3xZD21aRLkkRpRcNgyMgtfX2vGysjIsLdVr17dPu0pOjra5Xm29tq1axdwhQAAAIXPlr2xemHyQSWnZsqQdPUWZoYhGZKSUzP1wuSD2rI31gNVoiARKv5y6dIlXbx4UZIcFpz7+vrq5ptvliTt2OF6a3Rbe7NmzQq4SgAAgMLlSmK6xk87bA0OOeyHbDtm/LTDupKYfn0KxHVBqPjLnDlzZBiGypYtq7CwMIe+zp07S5IWL17sMIohSadOndKmTZskSV26dLk+xQIAABQSK367oOSUzBwDhY1hSMkpmVq56ULBFobrqtiEisOHD+u1117T4cOHHdpTUlI0bdo0zZgxQ5I0dOhQh8XZkvTII4+oQoUKioiI0IQJE+z7VsTExOj5559Xenq6OnbsqCZNmlyfFwMAAFAIGIahhT+dyfuJFum7tWdk5DaJoNArsgu1t2/frhEjRtgfJyYmSpKmT5+uL774wt7+/fffq2rVqkpPT9fcuXM1d+5cVaxYUVWrVpUkRUZGKikpSZLUu3dvPfHEE07XKlOmjD744AMNGzZMX331lZYuXaqqVavaz61evbreeuutgny5AAAAhU5cfLrDXZ5yyzCkk+dTdDkhXeXLuL5lP4qWIhsq0tPTFRsb69SelJRkDwnS34uuq1evrpEjR2rnzp2KjIzU0aNHlZaWpkqVKqljx4568MEH1aFDh2yv17ZtWy1cuFBTp07V5s2bdejQIYWGhqpz584aPnz4Ne/8BAAA4I2SUjJNnZ+YnKnyZdxUDDyqyIaKNm3a6ODBg7k+vly5cg4jG/lRr149vf/++6aeAwAAwFuUCjA3kz6wZLGZie/1+C8JAACAfClfxlfVgwOU182yLRbrhnjlShfZ32/jKgUSKs6ePav9+/fr999/z3ZvBwAAABRtFotFD3SqYt2EIi8MqfddVWTJaxpBoeW2eHju3DnNnj1bK1eu1Jkzf98FYMCAARo7dqz+7//+T6mpqZKs+zk8/PDD7ro0AAAAPOSft1XWjO+jrRvf5SJcWCxSSX8f/aNt5YIvDteNW0LF6tWrNW7cOCUkJDjcGsyWPn18fBQfH69ly5ZJkn766Sc98MAD9p2qAQAAUDSVDfTVG0/W0wuTrWtdrxUsLBbr15vD66lsIFOfvInp6U/r1q3TyJEjFR8fL8MwZLFYXA5l3XvvvTIMQ4Zh6PLly9q8ebPZSwMAAKAQaNMkSBOfaaCS/j6ySE5rLCwWySLrCMWkZxuodeMgD1SJgmQqVMTHx+vFF19UZmZmtmHCpm3btgoICLAf89tvv5m5NAAAAAqRNk2CtHBicz37cG1Vqxzg0FetcoCefbi2Fk1sTqDwUqbGnRYsWKDY2Fh7UDAMQ5UqVdLFixedjg0ICFC9evW0d+9eWSwW7d+/38ylAQAAUMiUDfRV77uq6IFOobqckK7E5EwFlvRRudK+LMr2cqZGKn755RdJsq+jePnll7Vx40ZJcvkXp3bt2vbjo6KizFwaAAAAhZTFYlH5Mn6qWjlA5cv4ESiKAVMjFREREfa/JGFhYerfv/81j8+663RcXJyZSwMAAAAoJEyNVMTGxtp/btiwYY7HJyUl2X9OS0szc2kAAAAAhYSpkYrSpUvr8uXLkqyLtnOSdSO8smXLmrk0AACA2yWlZHi6BMClwv5301SoCA4O1uXLl2UYhn777TelpKQoICDA5bHHjx/Xjh07ZLFYZBiGqlataubSAAAAbnf/8zs9XQJQJJma/nTLLbfY96aIi4vT008/rRMnTjgdt3fvXg0bNkyZmZn245s3b27m0gAAAAAKCVMjFffcc4++++47SdY7Om3YsEGdO3e2j0ZYLBZ9/fXX+vLLL+2PbXeKuueee8xXDwAA4Eb/e6+5SgWU8HQZgJOklIxCPZJmKlS0a9dOzZo10+7dux0Cg41hGEpPT5f09y1mLRaLWrRooZYtW5q5NAAAgNuVCihBqADywdT0J0l677337LeKte2q7epLsoaMoKAgTZw40exlAQAAABQSpkNFjRo1NH/+fNWtW1eGYTiNVkiyt9erV0/z5s1TtWrVzF4WAIBsDR/u6QoAoHgxNf3Jpnbt2vrhhx+0fPlyrVq1Srt379alS5ckSRUrVlRYWJi6dOmirl27sqMiAKDATZsmTZ3q6SoAoPhwS6iQrFOfunbtqq5du7rrKQEAyDPbXqyNGkkHDni2FgAoLkxPfwIAwNPeeEOyWKxfBw9a2/788++2N97wbH0A4O0IFQCAIm/8eOn11133vf66tR8AUHDcNv3pwIED2rZtm06ePKn4+HhlZmZe83iLxaK33nrLXZcHABRz48dLr7ziuh0AULBMh4pjx45p3Lhx+uOPP3J9jm0jPEIFAMAd3njDdaCQrNOfGK0AgIJlKlScO3dOjz76qC5evOjyVrIAAFwPtsDgKlgQKACg4JlaUzFt2jRduHBB0rU3vnO1ER4AAO6UXXAgUABAwTM1UvHLL784hARGKwAAAIDix/T0J+nvNRLh4eHq2bOnQkJC5O/vrxIlSrilSAAAcqNWLenxx62jE2+8Ic2c6emKAKB4MBUqypYtq5iYGElSvXr1NGfOHPn7+7ulMAAA8ioq6u+fx49n6hMAXC+m1lQ0atTIPkrRokULAgUAAABQDJkKFQ888ID958jISNPFAAAAACh6TIWKrl27qn379jIMQ1u3btV3333nrroAAAAAFBGm1lRs27ZNjz76qA4cOKCLFy9q/Pjxmjdvnrp3767q1asrKCjomue3atXKzOUBAAAAFAKmQkX//v3tt5S1WCwyDEN79+7Vvn37cjzXYrFo//79Zi4PAAAAoBAwFSokx70pbMGC/SoAAJ40caL0wguergJFUXJKpqdLAFwq7H83TYeKq3fIzs2O2YQOAEBBGjuWUIH8ue/5HZ4uASiSTC3UlmQfmcjLFwAABaVLF+v3f/zDs3UAQHFiaqSiZ8+e7qoDAIB8mzPHupN2ZqZk+93VqlWSj4/1a+ZMaeBAT1aIwiwwMFDx8fGeLsOrJCQkKDQ0VJJ09uxZlS5d2sMVeZfAwEBPl+DEVKiYMGGCu+oAACDfwsOlkBDp9GnHdsOwtoeHe6YuFA0Wi4UPvQWodOnS/PkWA6bXVAAFyTAMJSYmeroMrxMYGJir9U9AUdG0qbRihdSsmXPfihXWfgBAwSFUoNAyDEPt27fXb7/95ulSvE67du20fv16ggW8SnbBgUABAAXPraHiyJEj+umnn7Rnzx5dvHhRklSpUiWFhYWpU6dOqlu3rjsvh2KAD70AcmP3bqlfP9d9YWHS118TLgCgILklVMTHx+uVV17RihUrXN7dac2aNfrwww91zz336P/+7/9UpkwZd1wWXs5isWj9+vWFfvpTUVyMxvQneJtataR77pH27nXuu+ceaz8AoOCYDhWxsbF65JFHdOzYsWveLtYwDC1btkwHDhzQ3LlzVb58ebOXRjFQ1BbPsRgN8IzJk6VJk1z3TZoklS0rjR9/fWsCgOLE9D4VL774oo4ePSrDMGSxWK75ZRiGjh49qhdffNEdtQMAIEkaMEBq2NB1X8OG1n4AQMExFSr++OMPrVu3zh4apOw3w5NkDxbr1q3Trl27zFcPAMBfspvixNQnACh4pqY//fDDD/afbSMVd999t26//XZVrVpVknT69Gn9+uuvWrNmjdO5zVzd+w8AAABAkWIqVGzfvt0++uDj46OPP/5Yd999t9NxDz74oFavXq1nn33Wfvz27dvNXBoAALu4OCkqynVfVJS1HwBQcExNfzpz5owk67Smtm3bugwUNp07d9Ztt91mnwp1+uptTwEAyKcRI6SDB133HTxo7QcAFBxToSIhIcH+c+3atXM8PusxWc8FAMCMJUuk7P4Zql3b2g8AKDimQkXWW2eeOHEix+Ojo6NdngsAgBmTJ197+tPkyde3HgAobkyFCtuGX4ZhaOPGjdq0aVO2x27atEkbN2603yXKdi4AAGbdf78UHOy6LzjY2g8AKDimFmqHh4fr0KFDslgsysjI0NChQ9WjRw/dfvvtqlKliiwWi06fPq1ffvlF33//vf32shaLReHh4e56DQCAYq5pU2nNGsnVTQXXrLH2AwAKjqlQ0b17d82bN0+SdbF2enq6Fi5cqIULFzodawsTWc8FAMAd3nhDeuUV133Nmkmvv86O2gBQkExNf2rZsqXDHZ1st4t19WULFBaLRbfddptatmxpvnoAAMSO2gDgaaZChSRNmjRJ1apVcwgWrr4k62hFtWrVNHHiRLOXBQDAbutWKTLSdV9kpLUfAFBwTIeKSpUq6dtvv1W7du0cRiZssra1a9dOCxYsUKVKlcxeFgAAB2lpeWsHALiPqTUVNpUqVdKsWbO0c+dOrVq1Snv37tWlS5dkGIYqVaqkJk2aqEuXLmrevLk7LgcAgIN33pGy/D7LgWFY+x988PrWBADFiVtChU3z5s0JDgCA627NGqlJE+nkSee+6tWt/QCAgmN6+hMAAJ42ebLrQCFZ29n8DgAKlqmRiilTpth/rl69unr27HnN4zds2KA//vjD/vjpp582c3kAACRJx46Z6wcAmGM6VGTde2LPnj0aP368Q1tWv/76q7766iv7Y0IFAMAdBg2SvvlGSk527itZ0toPACg4bpn+ZLu709y5czVy5EilpqbmeCwAAO5UunTe2gEA7uOWUGHbi8IwDK1evVqDBg3S5cuX3fHUAADkaPNm6eJF130XL1r7AQAFx20jFdLfO2rv2LFDffv21ZkzZ9zx9AAAXFPlyub6AQDmuO3uT1cHiyNHjujhhx/W4cOH3XUJAABcuvNOqVkz133Nmln7AQAFx23Tn+666y7VqlVLhmHYp0OdOXNGffv21bZt29xxGQAAXKpdW/rf/1z3/e9/1n4AQMFx20hFjRo1NHfuXIWFhTmMWly5ckVDhgzR8uXL3XUpAAAcvPGGdMMNrvtuuMHaDwAoOG7d/K5ixYr68ssv1bFjR4dgkZqaqueff17r1q1z5+UAAJAklSplrh8AYI7bd9QuVaqUpk6dqp49ezoEi8zMTEVHR2e7hwUAAPn1r39Jkya57ps0ydoPACg4bg8VklSiRAlNmDBBTzzxhNMCbgAA3C02VvLNZjtXX19rPwCg4BRIqLAZPXq0ww7bjFIAAArC6tXS2LGu+8aOtfYDAApOgYYKSerXr58++OAD+fn5FfSlAADFVJkykk82/6L5+Fj7AQAFJ5vB4txp1aqV/edatWple9w//vEPVaxYUU899RQ7bQMA3O6ee6RFi6SuXZ37Fi2y9gMACo6pUPHVV1/l+thWrVppzZo1unLliplLAgDgUnbBgUABAAXPVKjIq3LlyqlcuXLX85IAgGLEYpEMw/E7AKDguS1UXLx4UTExMbpy5YrKli2rChUqqFKlSu56egAAcvTww1L//lK5ctLly1IeBtQBACaYChXbtm3TggULtGXLFp0/f96pPzg4WG3atNFDDz3ksP4CAICC8M031u/+/lJqKlOfAOB6ydfdn86ePasBAwZowIABWrJkic6dOyfDMJy+zp07pyVLlmjAgAF67LHHdPbsWXfXDwCAg8mTpbQ0acoUT1cCAMVHnkPFvn379MADD2jbtm328GCxWLL9sh2zZcsWPfDAAzpw4IBbCo+OjtaCBQv073//W/fdd59uvvlmNWjQQJ9++mmO5+7cuVPDhw/XrbfeqqZNm6pr16765JNPlJKScs3zIiIi9Pzzz6t9+/YKCwvT3XffrXfeeYc7WgGAh+3eLYWFSTfcII0aZW0bOdL6OCzM2g8AKDh5ChUXL17UU089pQsXLjiEiWvJesyFCxc0YsQIXbx4Mf8V/+XLL7/U+PHj9e233+rgwYPKyMjI1Xk//PCD+vXrp59++kn+/v6qU6eOjh8/ro8//lj9+vVTUlKSy/M2b96sXr16acmSJcrIyFC9evV04cIFzZ49W7169dKFCxdMvyYAQP6cPClFRkpRUVJmprUtM9P6ODLS2g8AKDh5ChUTJkzQmTNnnMKEq6lPti8b2/FnzpzR22+/bbrwChUq6M4779Szzz6rGTNm6B//+EeO55w4cUIvv/yyMjIyNGbMGP3yyy9avHixVq5cqRtvvFF79uzRpEmTnM6Lj4/Xc889p+TkZPXv31+//vqrFi1apJ9//lnh4eGKjo7Wyy+/bPo1AQDyp3p1KTjYdV9wsLUfAFBwcr1QOyoqSsuXL3cKEzfeeKO6deumsLAwhYaGqnTp0kpMTNSZM2e0Z88eLVu2TJGRkQ7ToZYtW6Znnnnmmhvm5WTEiBEOj5ctW5bjObNmzVJqaqrat2+vxx9/3N5evXp1vfXWW3rkkUe0YMECjRgxQpUrV7b3z5s3T5cuXVKdOnU0btw4lShRQpI12Lz33nvq3Lmz1q1bp3379qlx48b5fk0AgPyZN886KuFKVJS1v2nT61sTABQnuR6pWLlypX2KkWEYKlGihF555RUtW7ZMTz/9tG6//XY1bNhQNWvWVIMGDXT77bfr6aef1rJly/Taa6/ZP4hLUmZmplasWOH+V3MNhmFo9erVkqQHHnjAqT88PFw33XST0tLStHbtWoc+23k9e/Z0eB2SVK1aNbVt21aS9c8IAHD9vfWWNG6c675x46z9AICCk+tQsWXLFkmyr6V47bXX1Ldv3xzXVEjSww8/rNdee81+btbnu15OnTplv+1tixYtXB4THh4uSdq1a5e9LT09Xfv27XPoz815AIDrZ8QIacIE130TJlj7AQAFJ9ehIioqyh4Iatasqd69e+fpQr1797ZPdzIMQ8eOHcvT+WZF/TUu7u/vr5CQEJfH1KxZ0+FYSTp58qTS0tIc+nNzHgDg+nnrLem221z33XYbIxUAUNByvaYiJiZGknXBdXa/sc9JeHi4jh8/LkmKjY3N13PkV1xcnCSpXLly2Y6ulCtXTpIcbhFrO0+Sypcvf83zsh57tXPnzrncIDAiIiKHygEAOQkKkpYulSpUcO5butTaDwAoOLkOFampqfafAwIC8nWxrOfZfvt/vdj2oPDz88v2GH9/f0lScnKyvS3r687uXNt519rnYv78+ZrCTkwAUCBiY6U5c1z3zZkjDRxIsACAgpTrUBEUFGTfi+Ho0aP5uljW87L7rX9BsQWaa4UZW4AoWbKkvc0WGGznugpUtvOuFbb69OmjTp06ObVHRERozJgxOVQPALiWTZuk8eNd940fLzVoIN1zz/WtCQCKk1yHipCQEPumdzt27FBkZKRuuummXF8oMjJS27dvt99WNji7G4oXEFuIuXz5ssOC8axs055s05mynidZpze5Wo9hO+9aQSkkJCTbtRwAUNgZhqHExERPl5GtChWkihVLKj7eR1LW/78bqlgxUxUqJCshwVPVZS8wMDBXNzwBgMIu16GiRYsW2rdvnywWi9LT0zVy5Eh9/vnnDvs5ZOfChQsaOXKk/Za0Fosl2zswFZTatWtLso4qnDt3TqGhoU7HREdHOxwrWfew8PPzU1pamqKjo10GA1fnAYC3MAxD7du312+//ebpUq6hvKRxkl5w6jl+/F21bTtBUvbr3jylXbt2Wr9+PcECQJGX67s/tW/f3v6zxWLR4cOH1a1bN82YMUOnT592ec6ZM2c0Y8YMdevWTUeOHHH4n2bHjh1NlJ131apVs4+ObN++3eUxO3bskCQ1a9bM3ubr66ubb77ZoT835wGANyn8H3rjJGVzT1kVzkABAN4k1yMVHTt2VL169XTkyBF7W1xcnN5//329//77qlixoqpUqaJSpUopKSlJZ8+e1cWLFyVZf8tlY7FYVK9ePXXo0MGNLyNnFotFd999t+bOnauFCxeqa9euDv22KV1+fn5Oax86d+6sXbt2afHixRo8eLDDBninTp3Spk2bJEldunQp+BcCANeZxWLR+vXrC/X0J5ugICk9/e/Hvr5SbOxJj9WTE6Y/AfAWuQ4VkjR27Fg98cQTDmsSbIHh4sWLunjxon3NRFZZj/Xx8dHYsWPdUXueDRkyRN999502bNigmTNnasiQIbJYLDp58qReeuklSdb9NK5e7/HII49o1qxZioiI0IQJEzR27Fj5+fkpJiZGzz//vNLT09WxY0c1adLEEy8LAAqcxWJR6dKlPV1Gjtq3T9e6dYmSFqlMmcfUpk3RqBsAijqLcXUCyMFnn32mDz74wOVvVq4ekXDVP3r0aD3xxBP5KNXR9u3bNSLLFqmJiYlKTU1VqVKlHO7C9P3336tq1aoOj8eNG6fMzEyFhoaqUqVKOnz4sNLS0tS4cWP997//VWBgoNP1Nm3apGHDhiklJUUVK1ZU1apVFRkZqaSkJFWvXl3z58/P1+Lzffv2qVevXlq0aJEaN26c5/PheQkJCSpTpowkKT4+ng8wgAdt2pSk226rKilOJ07E6/z50rrlFk9XBRQ//NvoPXL7WTVPIxWSNGzYMJUrV05vvfWW0tLSHMJDdkO4hmHIz89PL7/8sh5++OG8XtKl9PR0lxvoJSUlKSkpyf7YtjjcpkePHqpVq5amT5+unTt36siRI6pRo4a6d++uoUOHZntb2LZt22rhwoWaOnWqNm/erEOHDik0NFSdO3fW8OHDr/stcgEAzpo2zZRt/URQkFS9ukfLAYBiI8+hQrJOB7r11ls1depULVu2TOlZJ7BefQFfX3Xr1k1PPvmkbrzxxnwXerU2bdro4MGD+To3PDxc06ZNy/N59erV0/vvv5+vawIAAADeKl+hQpJuvPFGTZw4Ua+99pq2b9+uAwcOKCYmRvHx8SpTpowqVKigRo0aqUWLFi6nEwEAAADwDvkOFTaBgYHq0KHDdb+bEwAAAIDCwXSoQNFS2HfFLYoSsmzTm1AYt+wt4rjlJgAAhR+hophJTEy0340B7udqp3aYw11DAAAo/HK9ozYAAAAAuMJIRTH2r3/9S/7+/p4uA3CSmpqqd99919NlAACAXCJUFGP+/v6ECgAAAJjG9CcAAAAAphAqAAAAAJhCqAAAAABgCqECAAAAgCmECgAAAACmECoAAAAAmEKoAAAAAGAKoQIAAACAKYQKAAAAAKYQKgAAAFBA/unpAnCd+Hq6AAAAAOSOYRhKTEz0dBk5SkhI+OunpUpIuODRWnIrMDBQFovF02UUWYQKAACAIsAwDLVv316//fabp0vJpTck+Sg0dJqkVz1dTI7atWun9evXEyzyielPAAAARUTh/8DbVtJJSTGSXv6rbfxfj0/+1Q9vxEgFAABAEWCxWLR+/fpCPf1pwABp0aJSkix/femv7+UllVOvXqv15ZceK++amP5kDqECAACgiLBYLCpdurSny8jWrFnSkSPS7t1X91jUtKlFs2aVViEuHyYw/QkAAABu8/DDeWuHdyBUAAAAwC2CgqThw133DR9u7Yd3IlQAAADALWJjpTlzXPfNmWPth3ciVAAAAMBtkpKk8uUd28qXt7bDexEqAAAA4BYzZ0ovvSTFxTm2x8VZ22fO9ExdKHiECgAAALjFgw9KjRu77mvc2NoP70SoAAAAgNtUr563dngHQgUAAADconx5qU0b131t2jivtYD3IFQAAADAbUqVyls7vAOhAgAAAG7l43Ptx/A+vp4uAJ6Tmprq6RIAl4rD303DMJSYmOjpMrxOQkKCy5/hHoGBgbJYLJ4uA4WYbfO7t96S4uP/bg8MZPM7b0eoKMbeffddT5cAFFuJiYkqU6aMp8vwaqGhoZ4uwevEx8erdOnSni4DhVhUlDRqlOu+QYOkDz+Uate+nhXhemEwCgAAAG5Ru7Y1OGRkOLZnZBAovB0jFcXYv/71L/n7+3u6DMBJampqsRpJa/nGTpXwD/R0GUVaetJlXdi+WGc2/lcpl47b2wMq1lKVdo+qcoue8i1VzoMVFl0ZqYn6fXxzT5eBIiI2Vlq82DrNKesO2kFB1vaBA5kC5a0IFcWYv78/oQIoBEr4B6pEAKEiv2IOrNPBz4cpMzXJqS/lUrSifpyg6JUfqsGgz1Sh0R3Xv0CgGAkKsgaHN990bE9NJVB4O6Y/ASYZhqGEhATFxMQoISFBhmF4uiSg2Ig5sE4Hpj+mzLRkScZfX1lZ2zLTknVg+kDFHFh33WsEipugIOmOOxzb7riDQOHtGKkA8ikpKUm7du3Sli1bFBMTY2+vUKGC2rRpo2bNmqkUN+UGCkx6YpwOfj7M+sDIvPbBRqZk8dHBz4ep5Wtb5RvIDlxAQWrSRFq1SrpyRSpb1voY3o2RCiAfjhw5ovfff18rVqxwCBSSFBMToxUrVuj999/XkSNHPFQh4P3ObfvOOuUpp0BhY2QqMzVJ57ctLNjCgGIsNta6IPvMGenWW61tt95qffzhh9Z+eCdCBZBHR44c0ddff620tLRrHpeWlqavv/6aYAEUAMMwdPrXz/N17qlfZzNNESggtjUVZ85Iq1db21avtj5mTYV3I1QAeZCUlKT58+fn+gOJYRiaP3++kpKcF5ACyL/0hBilXIyS8xqKnBhKuRil9MTYAqgKgGQNDrfc4th2yy0ECm9HqADyYNeuXTmOUFwtLS1Nu3btKqCKgOIpI8XcbtkZyfE5HwTAlPLlpcces36H9yNUALlkGIa2bNmSr3O3bNnCdAvAjUoEmNvVuURJdjMHClKPHtKxY9KcOdbvPXp4tBxcB4QKIJcSExOdFmXnVkxMDFOgADfyLV1BAZVqS7Lk8UyLAirVlm9gUAFUBcAm63QnV9Oh4H0IFUAupaammjo/JSXFTZUAsFgsqtpxUL7OrdZxsCyWvIYRAMC1ECqAXDK7+3hAQICbKgEgSSGtesvHv5RkyeU/ZRYf+fiXUnCrBwq2MAAohtj8DsilwMBAVahQIV9ToCpUqMBGeMhWRmqip0sokiwl/FTv0Y918PMnJItFuta6pb9GJur1nyxLCT9lpPBnnlv8/QSQG4QKIJcsFovatGmjFStW5PncNm3aMN0C2fp9fHNPl+D9DEOSoYOzhni6EgDwSkx/AvKgWbNm8vPzy/XxFotFfn5+atasWQFWBQAA4FmMVAB5UKpUKfXp00dff/11rm8R26dPH6Y+4ZpavrFTJfwDPV2GVzAMQ+mJscpMSZBPQGn5BgYxSmhSRmoio2kAckSoAPKobt266tevn+bPn3/NjfD8/PzUp08f1a1b9zpWh6KohH+gSgQQKtzFt6S5PSwAAHlHqADyoW7duho9erR27dqlLVu2OCzerlChgtq0aaNbbrlFJUuW9GCVAAAA1wehAsinUqVK6dZbb1WbNm2UlJSklJQUBQQEqFSpUky3AAAAxQqhAjDJYrEoMDBQgYFMXwEAAMUTd38CAAAAYAqhAgAAAIAphAoAAAAAphAqAAAAAJjCQm0A8LCM1ERPlwBki7+fAHKDUAEAHsZuxQCAoo7pTwAAAABMYaQCADwgMDBQ8fHxni7D6yQkJCg0NFSSdPbsWZUuXdrDFXkX9uMBkB1CBQB4gMVi4QNvAStdujR/xgBwnTD9CQAAAIAphAoAAAAAphAqAAAAAJhCqAAAAABgCqECAAAAgCmECgAAAACmECoAAAAAmEKoAAAAAGAKoQIAAACAKYQKAAAAAKYQKgAAAACYQqgAAAAAYAqhAgAAAIAphAoAAAAApvh6uoDr7cUXX9TixYuveczu3bsVEBDg1L5z505Nnz5dO3fuVGJiomrUqKFu3brp8ccfd3k8AAAAUBwUu1Bhc8MNN6hixYou+ywWi1PbDz/8oBdffFEZGRkKDQ1V1apVdfjwYX388cf6+eef9dVXX6lUqVIFXTYAAABQ6BTbUDFs2DD16tUrV8eeOHFCL7/8sjIyMjRmzBgNGTJEFotFJ0+e1JAhQ7Rnzx5NmjRJr7zySgFXDQAAABQ+rKnIhVmzZik1NVXt27fX448/bh/JqF69ut566y1J0oIFC3ThwgVPlgkAAAB4BKEiB4ZhaPXq1ZKkBx54wKk/PDxcN910k9LS0rR27drrXR4AAADgccV2+tPKlSu1Zs0axcfHq1KlSgoPD1ePHj1UtmxZh+NOnTql8+fPS5JatGjh8rnCw8MVGRmpXbt2qU+fPgVeOwAAAFCYFNtQsW7dOofHy5Yt0+TJk/Xuu++qY8eO9vaoqChJkr+/v0JCQlw+V82aNR2OBQAAAIqTYhcqatasqdGjR+v2229XjRo1ZLFY9Mcff+ijjz7Srl279NRTT+mbb75RWFiYJCkuLk6SVK5cOZd3hbL1SdLly5ezve65c+fsIx5ZRUREmH1JAAAAgEcVu1Dx1FNPObW1a9dOrVq1Ur9+/bR79269++67+uKLLyRJKSkpkiQ/P79sn9Pf31+SlJycnO0x8+fP15QpU8yUDgAAABRKxS5UZMff318jR47UkCFDtHXrVsXFxal8+fL2Te3S0tKyPTc1NVWSVLJkyWyP6dOnjzp16uTUHhERoTFjxpisHgAAAPAcQkUWt9xyiyQpMzNT0dHRKl++vMqXLy/JOrXJMAyXU6Bs055s06BcCQkJyXZNBgAAAFCUESqyyDrFKSMjQ5JUu3ZtSdbRiHPnzik0NNTpvOjoaIdjiwrbCAtQ2PB3EwCAooVQkcXhw4ftP1epUkWSVK1aNQUHB+v8+fPavn27unbt6nTejh07JEnNmjW7PoW6ybvvvuvpEgAAAOAF2Pwui88//1ySdNNNN9lHJCwWi+6++25J0sKFC53O2bFjhyIjI+Xn5+dyzQQAAADg7YrVSMXGjRu1efNmPfTQQ/a9JSTpypUr+uijj7RkyRJJzneIGjJkiL777jtt2LBBM2fO1JAhQ2SxWHTy5Em99NJLkqTevXsrODj4+r2YfAoMDFR8fLyny/AqCQkJ9hB69uxZlS5d2sMVeZfAwEBPlwAAAHJQrEJFUlKSpk+frunTpys0NFQhISFKT0/XkSNHlJaWJovFoqeeekrdu3d3OK9mzZp68803NW7cOE2aNElffvmlKlWqpMOHDystLU2NGzfWCy+84KFXlTcWi4UPvQWodOnS/PkCAIBip1iFisaNG+vJJ5/UH3/8oePHj+vw4cMyDEOhoaFq2bKl+vbtm+26iB49eqhWrVqaPn26du7cqSNHjqhGjRrq3r27hg4dar/1LAAAAFDcFKtQUbVqVT333HP5Pj88PFzTpk1zY0UAAABA0cdCbQAAAACmECoAAF7oZ08XAADFCqECAOCFbvd0AQBQrBSrNRUAgPwxDEOJiYmeLiNHCQkJki5LsqhyZT9duJDg6ZKuKTAwUBaLxdNlAIBphAoAwDUZhqH27dvrt99+83Qp1/C1pIcl/b2vSXKyn8qU8ZNkSJonqZ9nSruGdu3aaf369QQLAEUe058AADkq/B96p0iyjUpYrvqe8Fc/AKCgMFIBALgmi8Wi9evXF+rpT7Gx0ptv+srVXb+ffNJf//73agUFXe+qcsb0JwDeglABAMiRxWIp1LvFf/GF9Nlnrnos+uyzAIWFBWjEiOtdFQAUH0x/AgAUecHBkk82/6L5+Fj7AQAFh1ABACjyWreWbrnFdd8tt1j7AQAFh1ABAPAKlSrlrR0A4D6ECgAAAACmECoAAEVe+fJSmzau+9q0sfYDAAoOoQIAUOQFBUmjRzsv1vbxsbYXxtvJAoA3IVQAAIq82FhpzhwpIMCxPSDA2h4be/1rAoDihFABACjygoKkgQOdRySyawcAuBehAgDgFYKCpPvuc2y77z4CBQBcD4QKAIDXqFLFuij7sces36tU8XRFAFA8+Hq6AAAA3KVHD2nUKOvoRGysdOyYR8sBgGKDUAEA8BpZd9UOCsp+l20AgHsx/QkAAACAKYQKAAAAAKYQKgAAAACYQqgAAAAAYAqhAgAAAIAphAoAAAAAphAqAAAAAJjCPhUo1AzDUGJioqfLuKaEhASXPxdmgYGBslgsni4DAAB4CUIFCi3DMNS+fXv99ttvni4l10JDQz1dQq60a9dO69evJ1gAAAC3YPoTCjU+9AIAABR+jFSg0LJYLFq/fn2hn/5UFDH9CQAAuBOhAoWaxWJR6dKlPV0GAAAAroHpTwAAAABMIVQAAAAAMIVQAQAAAMAUQgUAAAAAUwgVAAAAAEwhVAAAAAAwhVABAAAAwBRCBQAAAABTCBUAAAAATCFUAAAAADCFUAEAAADAFEIFAAAAAFMIFQAAAABMIVQAAAAAMIVQAQAAAMAUQgUAAAAAUwgVAAAAAEwhVAAAAAAwhVABAAAAwBRfTxdQ3KWkpEiSIiIiPFwJAAAA4Mj2GdX2mTU7hAoPO3HihCRpzJgxHq4EAAAAcO3EiRMKDw/Ptt9iGIZxHevBVS5duqQNGzaoRo0aCggI8HQ5yKeIiAiNGTNGkyZNUp06dTxdDlCs8X4ECgfei94hJSVFJ06cUPv27VWxYsVsj2OkwsMqVqyo++67z9NlwE3q1Kmjxo0be7oMAOL9CBQWvBeLvmuNUNiwUBsAAACAKYQKAAAAAKYQKgAAAACYQqgAAAAAYAqhAnCD4OBgPf300woODvZ0KUCxx/sRKBx4LxYv3FIWAAAAgCmMVAAAAAAwhVABAAAAwBRCBQAAAABTCBUo0v78808NGzZMrVu3VsOGDdWgQQNt2bJFDRo0UIMGDTxdHlAkJSUl6Z133lGnTp3UuHFjNWjQQC+++GK+nmvy5Mlq0KCBJk+e7OYqAc/hPQI48/V0AUB+Xbx4UQMGDFBcXJxCQ0N10003yWKxqGzZsp4uDSjS/v3vf2vJkiUqVaqUGjZsKH9/f91www2eLqvY+de//qUff/xRkjRx4kTdf//9uT7XMAxt375da9eu1fbt2xUZGank5GQFBQWpefPm6tevn2699daCKt3r8R4pHIrCe2TRokU6efKkevbsqRo1aph+vsJcB6ECRdbSpUsVFxenu+66S1OmTJGPz98DbzfeeKMHKwOKrri4OC1btkylSpXS8uXLVbVqVU+XVCz99ttv9g9L+bF582YNHDhQkuTj46NatWopMDBQx44d06pVq7Rq1SoNHz5co0aNck/BxQjvkcKhqLxHFi9erK1bt6p169YeDRXXow5CBYqsyMhISVL79u0dAoUkrVixwhMlAUVeVFSUMjMzVa9ePT4seUhKSopee+01hYSEKDg4WPv27cvzcxiGodq1a2vgwIHq1q2bypcvL0lKTU3VlClT9Nlnn2nq1Klq1qyZ7rzzTne/BK/Ge8TzeI8UTqypQJGVkpIiSSpZsqSHKwG8R3JysiTeV5706aefKioqSuPGjVPp0qXz9RxNmzbVsmXL1LdvX/uHJUny9/fX6NGj1bFjR0nSggUL3FJzccJ7xPN4jxROhAoUObZFbYsWLZIkjRs3zr4wu3///pKU7ULtTp06qUGDBjpx4oQ2b96sxx9/XG3atLEv8LZJSkrS9OnT1atXL4WHh6tZs2a6//77NXPmTKWmpjo856effqoGDRqoe/fu9qCT1XfffacGDRqoffv2iomJsbefP39eX331lYYMGaJOnTopLCxMrVq10qOPPqrvv//+mn8Gf/75p4YPH65WrVqpefPmevDBB7V06dJrvnYUTZmZmWrdurUaNWqkuLg4h74//vjD/t/722+/dTo369/3qx9f/fd/0aJFDu+hrVu32p8763PYbNy4UU8//bTat2+vJk2aqH379urfv7++/vprp/eIzZUrV/Sf//xHd9xxh5o0aaLOnTvrk08+UXp6eravPyIiQuPGjVOnTp3UpEkTtWnTRk888YQ2bdrk8visr3Hr1q0aOHCgWrZsqdatW+upp57SsWPH7MeuXbtWffv2VXh4uFq1aqXRo0fr7Nmz2daSk//+979q0KCBhg0blu0xsbGxatKkiRo3buzw/4Osr3fWrFlq166dunbtmu9aypQpI1/f7CcjtGvXTpIc/jyKKt4jvEfyo6DfI7abxmzdulWSNGDAAIe/L7bPMDZ5+dwhWUdavv/+e/Xr108tW7ZUkyZN1K5dO/Xq1UsTJ07UmTNn8lWHGYQKFDlVq1ZVeHi4KlWqJEm64YYbFB4ervDwcNWvXz9Xz7F06VINGjRIu3fvVs2aNVWlShV739mzZ9W7d2+99957OnjwoCpXrqzq1avryJEjmjRpkgYOHGj/TZUkDRs2TM2bN9fhw4f17rvvOlznxIkTeuuttyRJ//nPf1ShQgV737fffqs333xTv//+u0qUKKH69eurTJky2rZtm8aOHatXX33VZe3btm1Tnz599NNPPykzM1M33XSTTp8+rdGjR2vmzJm5+0NEkeHj46Pw8HBlZmZq+/btDn3btm1z+bMknTp1SidPnlS1atWc5s+6+vsfEBDg8B4qU6aM/X0VHh6ugIAA+/mvv/66Bg8erNWrVystLU0NGjSQv7+/fv/9d73++us6d+6c0+u4cuWK+vTpo2+++UZBQUEKCQnR8ePH9fHHH+u1115z+dqXLVum+++/X4sWLVJsbKzq1q0rPz8//fLLLxo0aJC++uqrbP/c1qxZo4EDB+rQoUOqVauW0tLStGbNGj366KM6f/685syZoxEjRujkyZOqWbOmkpOTtXTpUj322GMufzmQG127dpWvr682btyo2NhYl8esXLlSaWlpateuncP/DyTrh4RXXnlFFotFr7zySr5qyC1vGunlPcJ7pCCYfY+ULVtW4eHhKlOmjCSpfv36Dn9fbJ9hpLx/7pCsC9PHjh2r33//XWXLllXDhg1VsmRJHTp0SLNmzdLevXvzXIdpBlBEjR071qhfv76xcOFCp7769esb9evXd2q/8847jfr16xuNGjUyJk+ebKSlpRmGYRiZmZlGSkqKkZGRYfTp08eoX7++8dxzzxnnz5+3n3v69Gmjb9++Rv369Y23337b4XmjoqKMW265xWjQoIGxceNGwzAMIyMjw378q6++6lTLtm3bjE2bNhnp6ekO7QcOHDDuueceo379+saWLVsc+hISEoyOHTsa9evXN1544QUjMTHRfq3Zs2cbjRs3zva1o+iaOXOmy793Q4cONRo2bGi0a9fOuOOOOxz6Fi9ebNSvX98YM2aMvS2nv/+GYRibN2826tevbzz66KMua5kzZ45Rv359o1mzZsb3339vZGRk2PtiYmKM2bNnGxcvXrS3ffzxx0b9+vWNxo0bG/369TPOnDlj71u7dq3RqFEjo379+saRI0ccrnPgwAGjSZMmRlhYmDF//nyH66xdu9YIDw83GjVqZBw4cMDhPNtrbNy4sTF79mz7eXFxccZDDz1k1K9f33jiiSeMZs2aGT/88IP9vFOnThl33XWXUb9+fePrr792+dpzY/DgwUb9+vWNefPmuex/9NFHjfr16xv/+9//nPoWLFhg1K9f3/jggw+cjv/+++/zXdPVMjMzjR49ehj169c3Xn/9dbc9ryfxHuE9UljfI7b6Nm/e7LI/P587Ll68aDRs2NBo0aKF8fvvvzs8X3JysrFkyRKn/+451eEOjFSgWOrYsaOefvpp+9CnxWKRv7+/1q1bp507dyosLEwTJ05U5cqV7edUqVJFH3zwgQIDAzVv3jyH3xrUqlVLL774ogzD0Isvvqi4uDjNnDlTv//+u2644QaNHTvWqYaWLVvq1ltvVYkSJRzaGzZsqPHjx0uS050tli5dqjNnzig0NFRvvvmmSpUqJcn6m7pBgwapQ4cO7vkDQqHSqlUrSbIPX0vWKR87duxQw4YN1b59e506dcph+oXtt7K2c7PK7u9/TpKTk/Xpp59Kkl577TXdf//9DjdJCAoK0qBBg1SxYkWnc0uUKKF3331XoaGh9rZOnTrprrvukiStX7/e4fhPPvlEqamp+te//qWHHnrI4TqdOnXSc889p4yMDH355Zcua+3YsaMGDRpkP69cuXJ65plnJEnr1q3Tgw8+qHvvvdd+fNWqVfX444+7rCUvbM+5ZMkSp76zZ8/q999/V6lSpeyv2+bSpUt69913VaNGDT355JP5vn5uLFiwQPv375efn58ee+yxAr3W9cJ7hPeIO13P90h+PnccP35cmZmZuvXWW9WiRQuH5wsICFC3bt3UsGHDAq3bFUIFiqUePXq4bF+9erUkqWfPni7nWoaEhCgsLEyJiYn2oUWbPn366M4779TZs2f19NNP6+OPP5avr68mTZpk//B/tfj4eC1YsEBjx47V4MGD1bdvXz3yyCP2aVR//vmnw/EbNmyQJPXu3Vt+fn5Oz9e3b99rv3AUSTfffLMCAwN14MABxcfHS5IOHDigK1euqFWrVvYPRVmnd/z++++SXH9gyu7vf0527Nih2NhYhYSE6L777svTuR06dHCYZmgTFhYmSYqOjra3paam6pdfflGJEiXUq1cvl8/XqVMnSc5TWmx69+7t1NaoUaNr9t98882S5DQ3Pi/uvvtulSxZUr///rvT3PPly5crMzNTd955p9Pi0rfeekuxsbEaP358gU5J2rdvn/7zn/9IkkaNGqVatWoV2LWuJ94jzniP5M/1fo/k53OH7a5ju3bt0qlTpwq0vrzglrIolurUqeOy/eDBg5KkefPmufwtivT3oi1Xc2LffPNN3Xvvvfbflj3zzDNq2rSpy+fZv3+/hg0b5vJ5bK5edGi7dnb1Z9eOos3X11fh4eHasGGDduzYoY4dO9o/KLRu3dq+MH/r1q3q2bOnzp07p2PHjik4ONjlhlz5/XsSEREhyXrXlKtv45yTmjVrumy3/cY2MTHR3nbs2DGlpKTIz89PQ4cOdXmeYRiSlO2iUVcfBLL+dthVv23+dkJCgsvnzI0yZcrojjvu0IoVK7R8+XL7ffClv38z261bN4dzNm3apB9//FF33XWX7rjjjnxfOyfR0dEaNmyYUlJS1L17dw0ZMqTArnW98R5xxnsk7zzxHsnP547Q0FD985//1IoVK9SlSxe1adNGrVu3VosWLXTLLbdccwF6QSJUoFi61siBJB06dCjH57h60ZQkVa5cWXXr1tXWrVvl4+Ojnj17ujw3IyNDo0aN0rlz53T77bdr6NChqlu3rsqVK6cSJUooKipKXbp0cbrjh+0fFVdD57brwzu1atVKGzZs0LZt29SxY0dt3bpVFotFLVq0UIUKFVSlShX7h6isH6Zcye7vf05s749y5crl+dzAwECX7bYPXrYPQJJ1waokpaWlaceOHdd83uwWjLr6TabFYrH/7OrPIGu/Gffee69WrFihJUuW2D8wHT9+XHv27FG5cuXst6qUpPT0dL366qsqVaqUXn75Zbdc35Xz589r8ODBOn/+vO644w69/fbbbnu9hQXvEdd4j+SOp94j+f3cMXHiRNWtW1fffvutNmzYYJ/JULFiRT3++OMOU9uuF0IFkIXtf+qff/65brvttjyf//XXX9sDRWZmpsaPH69Zs2Y5/Y9p9+7dioqKUvXq1TVlyhSnubqnT5++Zn2XLl1y2X/x4sU814yioWXLlpKsH4YMw9D27dtVr149+28OW7ZsqSVLlujMmTP2kTJX0zrMsE1HuHz5slufN7vrhIaG6tdffy3QaxWEjh07qly5ctqzZ4+ioqJUu3Zt+28gu3Tp4vB+T0xMVFRUlPz8/PTQQw85PZdttPKNN97QxIkT1bx5c02ZMiVP9cTGxmrw4ME6fvy4WrdurY8++sjl9MmijvdI0cF75G/5/dwREBCgZ555Rs8884wiIiL0+++/6+eff9Yvv/yiiRMnStJ1H41kTQWQhW3IOze/Mbja0aNHNWnSJPn4+Gjq1KmqUaOGNm7cqP/+979Ox548eVKS1LhxY5eL/65eS2FjG6a37SZ+NdvQO7xP06ZNVbJkSe3du1e7d+9WbGysw29ZbT9v2bLlmnPFzahXr54kac+ePcrMzHTrc2dVu3Zt+fn56fz589nedrIw8/f3V+fOnSX9PZ3Dto9M9+7dXZ6TlpamCxcuOH2lpaVJsv5m+sKFC05TInOSkJCgJ554QocOHVJYWJimTp3qFbeRdYX3SNHBe+RvZj53ZH2OPn36aNq0afbb0Xti0z5CBZBFly5dJEnz58/P032409PT9cILLygpKUmDBg3SHXfcoXfeeUc+Pj569913nUKA7X9YFy5ccHqutLS0bO/W0b59e0nWDfVs/yPN6ptvvsl1zSha/P391bRpU6Wlpemzzz6T5PiByPZb2pUrVyoiIkIVK1ZU3bp13VpDeHi4KlSooLNnz2Y799cdSpUqpfbt2yszM/Oa99kvzGx3uFm6dKn+/PNPHTlyRMHBwWrTpo3DceXKldPBgwez/bJ9EJ44caIOHjyYpz+P1NRUjRgxQrt27VK9evU0c+ZM+73qvRHvkaKluLxHbP/eu5oyLeX/c0d2brnlFknO6z5zqsMdCBVAFp07d9Ytt9yiyMhIPfnkk4qKinLoT01N1bp16zRu3DiH9qlTp2r37t2qX7++Ro0aJcn6D9jgwYOVnJysMWPGOKyPaNasmXx9fbVjxw6H3bOvXLmif/3rXy7DhmRdvBYaGqozZ87olVdesf/PwTAMffHFF0VyGBy5Z/vH86effpLk+IGpTp06qly5sn766ScZhuH238BK1uH2ESNGSJJeffVVLVmyxGGed1xcnObMmZPt9Ly8GDlypPz9/TV16lRNnz7d6R/Cc+fO6YsvvtDcuXNNX6sgtGnTRsHBwYqIiLDfza1r165un+P8zjvvqFOnTnrnnXcc2jMyMvTcc89p8+bNqlWrlmbPnq2goCC3Xrsw4j3yN94jVp5+j9gW4Gd3F678fO7YtGmT3nnnHR05csTh2ISEBPsmuI0bN85THe7AmgogCx8fH02ePFnDhg3Tb7/9pi5duqh27doKCgpSQkKCoqKilJaW5rAgevfu3Zo2bZr8/Pw0adIkh+lMI0eO1IYNG7R37159+umnevbZZyVJwcHBGjBggGbPnq2xY8fqo48+UoUKFRQREaGMjAy9/PLLLndQDQwM1MSJEzV06FAtWrRIq1at0o033qgzZ87o/PnzGjNmjCZNmlTgf07wDNtvWg3DUJ06dZx2Qm3ZsqVWrFghyf3TOmz69++vyMhIzZ07V88//7zefPNN1ahRQ5cuXdKZM2eUkZGhu+++O9ubCeRWo0aN9P7772vMmDF67733NGXKFN100032KR+2dUfZ3fnG03x8fNS1a1d98cUX9nv6Zzetw4yYmBidPHlSMTExDu3Lly/XmjVr7LWMHDnS5fnBwcH6+OOP3V6Xp/Ae4T1yNU+/R7p27aqvv/5aM2bM0OrVqxUcHCyLxaKhQ4eqY8eO+frckZCQoNmzZ2v27NmqWLGiqlWrpvT0dEVFRSkpKUlly5Z1+uVnTnW4A6ECuEpISIjmz5+v7777TsuWLdOhQ4d06tQpVa5cWU2bNtVtt92me+65R5KUlJRkH4V4/vnnnTab8ff316RJk/TAAw/os88+0x133GG/xewLL7ygKlWqaN68eYqOjlZSUpLatm2r4cOHO/1DmNWtt96qBQsW6KOPPtLvv/+uiIgI1alTR+PGjVO3bt0IFV6sefPm8vPzU1pamssPRK1bty7wD0wWi0Wvvfaa7rzzTs2dO1e7du3Sn3/+qYoVK6pVq1b6xz/+oZCQELdcq3Pnzlq6dKnmzJmjDRs26OjRo/Lx8VFoaKg6d+6su+++234v/sKoe/fu+uKLLyRZb8+Z3e2lC0Jqaqr952PHjtlvSXm16tWrX6eKrg/eI7xHcut6vUdatmyp9957T1988YWOHDliv07Wu0Pm5XOHJLVo0UL//ve/tXHjRh0+fFgRERHy9fVVrVq11KFDBw0cOFDBwcF5rsMsi5F1XA5AkWe7H7vt3tcAAAAFjTUVAAAAAEwhVAAAAAAwhTUVAAC48N1332nhwoW5Pr6w3mUHKCjF6T1y/vx5+81WcuPJJ5/U7bffXoAVFT6ECgAAXDh9+rR27Njh6TKAQqs4vUdSUlLy9FovXrxYgNUUTizUBgAAAGAKayoAAAAAmEKoAAAAAGAKoQIAAACAKYQKAAAAAKYQKgAAAACYQqgAAAAAYAqhAgAAAIAphAoAAAAAphAqAAAAAJjy/22dcZ4KqXY7AAAAAElFTkSuQmCC",
+      "text/plain": [
+       "<Figure size 800x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#And this generates all the plots.\n",
+    "an.plotting()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "7631704a",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "#Calculate stats\n",
+    "an.stats()                                         "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4fa579be",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3af8b1c3",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ecc919b7",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6fe7f117",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a3d073b6",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "04544882",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8caab88a",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "dc80edd7",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9be2e87a",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ccc8e63c",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1768d84d",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ae2f74e2",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e5277261",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "491e21a1",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3cbc4900",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b0fe3ce6",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "81bf1c7f",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ff002563",
+   "metadata": {
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+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1d343040",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "06ff16fd",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "fc2aea7d",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3d14cafa",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "403f9e53",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1e840bba",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a7bd6c77",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "693ea701",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ec3e42cd",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4da3f10c",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f17280bb",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "49c4065e",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5903640f",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7d587f4e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1e2160b0",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e59c79df",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ec499981",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "553f501b",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7d114d0e",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5836c6d4",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "54c41ab2",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "98bf1187",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1f1a4f05",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "17a5eb19",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e678ce81",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7a11236c",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "da3753bc",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "47c84dd0",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "555b7b73",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.18"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/examples/jupyter_notebooks/Monet-analysis-example-plots-wrfChemexample_develop_aircraft_Latest.py b/examples/jupyter_notebooks/Monet-analysis-example-plots-wrfChemexample_develop_aircraft_Latest.py
new file mode 100644
index 00000000..cdb59fa1
--- /dev/null
+++ b/examples/jupyter_notebooks/Monet-analysis-example-plots-wrfChemexample_develop_aircraft_Latest.py
@@ -0,0 +1,18 @@
+from melodies_monet import driver
+
+an = driver.analysis()
+
+an.control = '../examples/yaml/control_wrfchem_aircraft_Latestfor_develop_aircraft.yaml'
+
+an.read_control() 
+
+an.control_dict   
+
+an.open_models()
+
+an.open_obs()
+
+#This just pairs the data
+an.pair_data()
+
+an.plotting()
diff --git a/examples/jupyter_notebooks/Monet-example_aircraft_pairing_loop.ipynb b/examples/jupyter_notebooks/Monet-example_aircraft_pairing_loop.ipynb
new file mode 100755
index 00000000..d9093c4e
--- /dev/null
+++ b/examples/jupyter_notebooks/Monet-example_aircraft_pairing_loop.ipynb
@@ -0,0 +1,1532 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "fa641328-fd14-4d05-a2f6-99aa3b0bcdbd",
+   "metadata": {},
+   "source": [
+    "# Looping over aircraft observations, saving out a netcdf with paired data for each set"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "90856e9f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from melodies_monet.util.tools import loop_pairing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "dc80edd7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "file_pairs = {'0722':{'model':{'wrfchem_v4.2':'/wrk/users/charkins/melodies-monet_data/wrfchem/run_CONUS_fv19_BEIS_1.0xISO_RACM_v4.2.2_racm_berk_vcp_noI_phot/0722/*'},\n",
+    "                      'obs':{'firexaq':'/wrk/d2/rschwantes/obs/firex-aq/R1/10s_merge/firexaq-mrg10-dc8_merge_20190722_R1.ict'}},\n",
+    "            '0905':{'model':{'wrfchem_v4.2':'/wrk/users/charkins/melodies-monet_data/wrfchem/run_CONUS_fv19_BEIS_1.0xISO_RACM_v4.2.2_racm_berk_vcp_noI_phot_soa/0905/*'},\n",
+    "                    'obs':{'firexaq':'/wrk/d2/rschwantes/obs/firex-aq/R1/10s_merge/firexaq-mrg10-dc8_merge_20190905_R1.ict'}}\n",
+    "            }"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "9be2e87a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "control_fn='../yaml/control_aircraft_looping.yaml'"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5a4b72b9-d3b7-4b4f-b3b4-95b9172e602e",
+   "metadata": {},
+   "source": [
+    "## Looping over aircraft pairing using info from a separate control yaml"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "cd0d569b-80f1-4345-84cc-6ba93780cb73",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/charkins/miniconda3/envs/melodies-monet_aircraft/lib/python3.9/site-packages/dask/dataframe/_pyarrow_compat.py:17: FutureWarning: Minimal version of pyarrow will soon be increased to 14.0.1. You are using 11.0.0. Please consider upgrading.\n",
+      "  warnings.warn(\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "wrfchem\n",
+      "/wrk/users/charkins/melodies-monet_data/wrfchem/run_CONUS_fv19_BEIS_1.0xISO_RACM_v4.2.2_racm_berk_vcp_noI_phot/0722/*\n",
+      "**** Reading WRF-Chem model output...\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/charkins/miniconda3/envs/melodies-monet_aircraft/lib/python3.9/site-packages/xarray/core/groupby.py:534: FutureWarning: 'S' is deprecated and will be removed in a future version, please use 's' instead.\n",
+      "  index_grouper = pd.Grouper(\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "After pairing:      Time_Stop  Day_Of_Year_YANG   latitude                time   longitude  \\\n",
+      "0     65905.0             203.0  34.636072 2019-07-22 18:10:00 -118.139775   \n",
+      "1     66310.0             203.0  34.520597 2019-07-22 18:20:00 -117.717356   \n",
+      "2     66910.0             203.0  34.174384 2019-07-22 18:30:00 -117.603158   \n",
+      "3     67510.0             203.0  34.102602 2019-07-22 18:40:00 -118.361519   \n",
+      "4     68110.0             203.0  33.866911 2019-07-22 18:50:00 -118.895332   \n",
+      "5     68710.0             203.0  33.600202 2019-07-22 19:00:00 -118.564034   \n",
+      "6     69310.0             203.0  33.753515 2019-07-22 19:10:00 -117.968233   \n",
+      "7     69910.0             203.0  33.985567 2019-07-22 19:20:00 -117.437606   \n",
+      "8     70510.0             203.0  34.163247 2019-07-22 19:30:00 -117.851272   \n",
+      "9     71110.0             203.0  34.537180 2019-07-22 19:40:00 -118.526429   \n",
+      "10    71710.0             203.0  35.309810 2019-07-22 19:50:00 -119.123868   \n",
+      "11    72310.0             203.0  36.226741 2019-07-22 20:00:00 -119.547113   \n",
+      "12    72910.0             203.0  37.134482 2019-07-22 20:10:00 -120.143756   \n",
+      "13    73510.0             203.0  37.975441 2019-07-22 20:20:00 -120.700291   \n",
+      "14    74110.0             203.0  37.901537 2019-07-22 20:30:00 -121.364430   \n",
+      "15    74710.0             203.0  37.717381 2019-07-22 20:40:00 -121.011395   \n",
+      "16    75310.0             203.0  37.546843 2019-07-22 20:50:00 -120.598869   \n",
+      "17    75910.0             203.0  37.173246 2019-07-22 21:00:00 -121.024890   \n",
+      "18    76510.0             203.0  37.121143 2019-07-22 21:10:00 -120.487622   \n",
+      "19    77110.0             203.0  37.108647 2019-07-22 21:20:00 -119.899767   \n",
+      "20    77710.0             203.0  36.747118 2019-07-22 21:30:00 -120.375273   \n",
+      "21    78310.0             203.0  36.487591 2019-07-22 21:40:00 -120.188678   \n",
+      "22    78910.0             203.0  36.556247 2019-07-22 21:50:00 -119.430301   \n",
+      "23    79510.0             203.0  36.162445 2019-07-22 22:00:00 -119.532292   \n",
+      "24    80110.0             203.0  35.842443 2019-07-22 22:10:00 -119.840327   \n",
+      "25    80710.0             203.0  35.957125 2019-07-22 22:20:00 -119.187474   \n",
+      "26    81310.0             203.0  35.654423 2019-07-22 22:30:00 -119.351302   \n",
+      "27    81910.0             203.0  35.426144 2019-07-22 22:40:00 -119.632331   \n",
+      "28    82510.0             203.0  35.459973 2019-07-22 22:50:00 -118.959830   \n",
+      "29    83110.0             203.0  35.192984 2019-07-22 23:00:00 -119.260506   \n",
+      "30    83710.0             203.0  34.905976 2019-07-22 23:10:00 -118.578383   \n",
+      "31    84310.0             203.0  34.394222 2019-07-22 23:20:00 -117.566666   \n",
+      "32    84910.0             203.0  34.166601 2019-07-22 23:30:00 -117.824551   \n",
+      "33    85510.0             203.0  34.637761 2019-07-22 23:40:00 -118.568665   \n",
+      "34    86110.0             203.0  35.544457 2019-07-22 23:50:00 -119.230834   \n",
+      "35    86710.0             203.0  36.613801 2019-07-23 00:00:00 -119.551456   \n",
+      "36    87310.0             203.0  37.909203 2019-07-23 00:10:00 -119.420821   \n",
+      "37    87910.0             203.0  39.279940 2019-07-23 00:20:00 -119.388695   \n",
+      "38    88510.0             203.0  40.586553 2019-07-23 00:30:00 -118.930815   \n",
+      "39    89110.0             203.0  41.865071 2019-07-23 00:40:00 -118.169258   \n",
+      "40    89710.0             203.0  42.869333 2019-07-23 00:50:00 -117.109481   \n",
+      "41    90250.0             203.0  43.409062 2019-07-23 01:00:00 -116.256079   \n",
+      "\n",
+      "        altitude  HAE_GPS_Altitude_YANG  Pressure_Altitude_YANG  \\\n",
+      "0    1330.171429            1300.748095             4134.495238   \n",
+      "1    2891.590000            2861.474167             8878.721667   \n",
+      "2    1329.585000            1296.738500             4100.635000   \n",
+      "3     789.731667             755.256333             2454.616667   \n",
+      "4     456.455000             420.872833             1414.905000   \n",
+      "5     388.110000             352.063667             1195.108333   \n",
+      "6     884.305000             850.087167             2745.273333   \n",
+      "7     692.220000             658.430500             2146.456667   \n",
+      "8     978.838333             944.772667             3020.430000   \n",
+      "9    4448.583333            4416.236167            13672.116667   \n",
+      "10   4699.603333            4666.808000            14453.471667   \n",
+      "11   4702.930000            4671.746167            14470.700000   \n",
+      "12   4651.821667            4621.899500            14338.598333   \n",
+      "13   2057.683333            2027.691167             6363.271667   \n",
+      "14    347.575000             317.914500             1097.440000   \n",
+      "15    401.340000             372.076833             1270.806667   \n",
+      "16    415.476667             386.477500             1320.788333   \n",
+      "17    486.568333             455.656500             1542.610000   \n",
+      "18    383.860000             353.190667             1230.475000   \n",
+      "19    566.430000             535.867833             1794.350000   \n",
+      "20    413.650000             382.798000             1326.226667   \n",
+      "21    456.285000             424.915000             1458.981667   \n",
+      "22    441.401667             411.150667             1409.630000   \n",
+      "23    391.538333             360.022500             1269.263333   \n",
+      "24    443.633333             410.852000             1432.801667   \n",
+      "25    433.648333             401.712000             1398.123333   \n",
+      "26    450.413333             417.380500             1454.841667   \n",
+      "27    584.306667             551.021000             1866.391667   \n",
+      "28    621.223333             589.189333             1988.930000   \n",
+      "29   1103.690000            1071.349833             3446.908333   \n",
+      "30   4886.990000            4852.221333            15033.178333   \n",
+      "31   3227.766667            3191.527000             9930.980000   \n",
+      "32    980.678333             944.656833             3037.476667   \n",
+      "33   4916.175000            4882.097500            15126.913333   \n",
+      "34   5366.841667            5333.401667            16546.148333   \n",
+      "35   6374.786667            6344.491500            19679.323333   \n",
+      "36  10469.588333           10442.075500            32493.161667   \n",
+      "37  12483.868333           12457.703333            38920.385000   \n",
+      "38  12473.943333           12450.180000            38950.370000   \n",
+      "39  12025.688333           12002.561333            37548.035000   \n",
+      "40   6028.668333            6006.139500            18660.910000   \n",
+      "41   2020.721527            1999.906390             6318.911042   \n",
+      "\n",
+      "    Radar_Altitude_YANG  Ground_Speed_YANG  ...  smoke_age_HOLMES  \\\n",
+      "0           1810.085714         107.236905  ...               NaN   \n",
+      "1           6264.286667         135.144100  ...               NaN   \n",
+      "2           2319.345833         136.029600  ...               NaN   \n",
+      "3           1801.628333         112.417467  ...               NaN   \n",
+      "4           1459.666667         108.933183  ...               NaN   \n",
+      "5           1260.395000         104.355950  ...               NaN   \n",
+      "6           2749.386667         105.992217  ...               NaN   \n",
+      "7           1263.733333         111.095683  ...               NaN   \n",
+      "8           1649.393333         114.995967  ...               NaN   \n",
+      "9          11609.339167         158.400283  ...               NaN   \n",
+      "10         14722.710000         182.714333  ...               NaN   \n",
+      "11         15188.196667         180.931333  ...               NaN   \n",
+      "12         14943.548333         205.462900  ...               NaN   \n",
+      "13          5830.063333         152.469367  ...               NaN   \n",
+      "14          1106.500000         128.836283  ...               NaN   \n",
+      "15          1157.649167         127.694483  ...               NaN   \n",
+      "16          1112.593333         123.989783  ...               NaN   \n",
+      "17          1258.561667         125.426017  ...               NaN   \n",
+      "18          1087.955000         123.996183  ...               NaN   \n",
+      "19          1162.829167         124.919000  ...               NaN   \n",
+      "20          1061.278333         127.847450  ...               NaN   \n",
+      "21          1104.408333         127.579550  ...               NaN   \n",
+      "22          1085.115833         126.351033  ...               NaN   \n",
+      "23          1048.204167         124.213800  ...               NaN   \n",
+      "24          1101.781667         126.204933  ...               NaN   \n",
+      "25          1035.869167         124.252350  ...               NaN   \n",
+      "26          1054.296667         130.615483  ...               NaN   \n",
+      "27          1163.598333         131.728217  ...               NaN   \n",
+      "28          1246.755000         124.834083  ...               NaN   \n",
+      "29          3160.055833         131.548783  ...               NaN   \n",
+      "30         13703.975000         194.748700  ...               NaN   \n",
+      "31          7213.434167         162.101050  ...               NaN   \n",
+      "32          1591.854167         133.545617  ...               NaN   \n",
+      "33         12880.261667         194.177217  ...               NaN   \n",
+      "34         17214.746667         204.192533  ...               NaN   \n",
+      "35         20204.583333         220.150867  ...               NaN   \n",
+      "36         25932.503333         257.683217  ...               NaN   \n",
+      "37         35274.855000         255.261500  ...               NaN   \n",
+      "38         35591.463333         259.636117  ...               NaN   \n",
+      "39         33669.345000         258.961817  ...               NaN   \n",
+      "40         14888.741667         214.276550  ...               NaN   \n",
+      "41          3605.892708         125.354083  ...               NaN   \n",
+      "\n",
+      "    smoke_age_corr_HOLMES  smoke_age_rise_HOLMES  smoke_rise_HOLMES  \\\n",
+      "0                     NaN                    NaN                NaN   \n",
+      "1                     NaN                    NaN                NaN   \n",
+      "2                     NaN                    NaN                NaN   \n",
+      "3                     NaN                    NaN                NaN   \n",
+      "4                     NaN                    NaN                NaN   \n",
+      "5                     NaN                    NaN                NaN   \n",
+      "6                     NaN                    NaN                NaN   \n",
+      "7                     NaN                    NaN                NaN   \n",
+      "8                     NaN                    NaN                NaN   \n",
+      "9                     NaN                    NaN                NaN   \n",
+      "10                    NaN                    NaN                NaN   \n",
+      "11                    NaN                    NaN                NaN   \n",
+      "12                    NaN                    NaN                NaN   \n",
+      "13                    NaN                    NaN                NaN   \n",
+      "14                    NaN                    NaN                NaN   \n",
+      "15                    NaN                    NaN                NaN   \n",
+      "16                    NaN                    NaN                NaN   \n",
+      "17                    NaN                    NaN                NaN   \n",
+      "18                    NaN                    NaN                NaN   \n",
+      "19                    NaN                    NaN                NaN   \n",
+      "20                    NaN                    NaN                NaN   \n",
+      "21                    NaN                    NaN                NaN   \n",
+      "22                    NaN                    NaN                NaN   \n",
+      "23                    NaN                    NaN                NaN   \n",
+      "24                    NaN                    NaN                NaN   \n",
+      "25                    NaN                    NaN                NaN   \n",
+      "26                    NaN                    NaN                NaN   \n",
+      "27                    NaN                    NaN                NaN   \n",
+      "28                    NaN                    NaN                NaN   \n",
+      "29                    NaN                    NaN                NaN   \n",
+      "30                    NaN                    NaN                NaN   \n",
+      "31                    NaN                    NaN                NaN   \n",
+      "32                    NaN                    NaN                NaN   \n",
+      "33                    NaN                    NaN                NaN   \n",
+      "34                    NaN                    NaN                NaN   \n",
+      "35                    NaN                    NaN                NaN   \n",
+      "36                    NaN                    NaN                NaN   \n",
+      "37                    NaN                    NaN                NaN   \n",
+      "38                    NaN                    NaN                NaN   \n",
+      "39                    NaN                    NaN                NaN   \n",
+      "40                    NaN                    NaN                NaN   \n",
+      "41                    NaN                    NaN                NaN   \n",
+      "\n",
+      "    fire_distance_HOLMES  smoke_agemethod_HOLMES       no2        no  \\\n",
+      "0                    NaN                     NaN  0.122522  0.019905   \n",
+      "1                    NaN                     NaN  0.053957  0.018913   \n",
+      "2                    NaN                     NaN  7.627246  2.115838   \n",
+      "3                    NaN                     NaN  2.175637  0.476912   \n",
+      "4                    NaN                     NaN  0.583338  0.173662   \n",
+      "5                    NaN                     NaN  0.228939  0.082676   \n",
+      "6                    NaN                     NaN  0.802599  0.224332   \n",
+      "7                    NaN                     NaN  4.432410  1.082180   \n",
+      "8                    NaN                     NaN  6.916218  2.025461   \n",
+      "9                    NaN                     NaN  0.024518  0.013080   \n",
+      "10                   NaN                     NaN  0.013201  0.007279   \n",
+      "11                   NaN                     NaN  0.013664  0.006940   \n",
+      "12                   NaN                     NaN  0.016320  0.008900   \n",
+      "13                   NaN                     NaN  0.022961  0.008513   \n",
+      "14                   NaN                     NaN  1.026490  0.215797   \n",
+      "15                   NaN                     NaN  0.842013  0.169011   \n",
+      "16                   NaN                     NaN  0.699509  0.141229   \n",
+      "17                   NaN                     NaN  0.388654  0.081787   \n",
+      "18                   NaN                     NaN  0.533184  0.110072   \n",
+      "19                   NaN                     NaN  0.640762  0.122460   \n",
+      "20                   NaN                     NaN  0.469143  0.096359   \n",
+      "21                   NaN                     NaN  0.450651  0.090687   \n",
+      "22                   NaN                     NaN  0.871470  0.145382   \n",
+      "23                   NaN                     NaN  0.504581  0.094897   \n",
+      "24                   NaN                     NaN  0.470249  0.090558   \n",
+      "25                   NaN                     NaN  0.653810  0.120993   \n",
+      "26                   NaN                     NaN  0.575991  0.109725   \n",
+      "27                   NaN                     NaN  0.821052  0.147723   \n",
+      "28                   NaN                     NaN  1.089419  0.203690   \n",
+      "29                   NaN                     NaN  0.532588  0.112997   \n",
+      "30                   NaN                     NaN  0.015762  0.008777   \n",
+      "31                   NaN                     NaN  0.064315  0.023181   \n",
+      "32                   NaN                     NaN  6.333918  0.784311   \n",
+      "33                   NaN                     NaN  0.015495  0.008541   \n",
+      "34                   NaN                     NaN  0.011213  0.006946   \n",
+      "35                   NaN                     NaN  0.013553  0.010971   \n",
+      "36                   NaN                     NaN  0.021208  0.051385   \n",
+      "37                   NaN                     NaN  0.035450  0.138139   \n",
+      "38                   NaN                     NaN  0.034754  0.114122   \n",
+      "39                   NaN                     NaN  0.037999  0.093451   \n",
+      "40                   NaN                     NaN  0.011679  0.007715   \n",
+      "41                   NaN                     NaN  0.058921  0.012355   \n",
+      "\n",
+      "            o3  temp_model  \n",
+      "0    51.305995  300.371623  \n",
+      "1    52.421507  288.820422  \n",
+      "2    60.100534  299.822678  \n",
+      "3    47.583521  298.518989  \n",
+      "4    47.162077  295.905053  \n",
+      "5    37.774421  293.187716  \n",
+      "6    59.828919  299.835180  \n",
+      "7    72.034705  300.110961  \n",
+      "8    67.743776  299.104228  \n",
+      "9    53.653065  276.060637  \n",
+      "10   53.147322  273.531236  \n",
+      "11   54.822424  273.216146  \n",
+      "12   54.930731  274.352880  \n",
+      "13   44.690583  293.234401  \n",
+      "14   58.176093  303.677049  \n",
+      "15   61.010512  304.256941  \n",
+      "16   58.111635  305.812981  \n",
+      "17   53.329552  304.858109  \n",
+      "18   55.867485  306.275578  \n",
+      "19   60.565171  306.391196  \n",
+      "20   54.214828  306.485789  \n",
+      "21   54.165336  307.066782  \n",
+      "22   69.127629  307.176335  \n",
+      "23   57.297145  307.717143  \n",
+      "24   56.936562  308.032527  \n",
+      "25   59.102308  307.637274  \n",
+      "26   57.119073  307.627132  \n",
+      "27   63.302212  307.094842  \n",
+      "28   61.251840  307.975101  \n",
+      "29   59.252297  303.453705  \n",
+      "30   53.972373  272.912668  \n",
+      "31   51.288907  287.152925  \n",
+      "32  103.192044  301.856393  \n",
+      "33   54.167179  273.000949  \n",
+      "34   55.493833  269.622581  \n",
+      "35   58.168320  262.686412  \n",
+      "36   70.167588  232.388259  \n",
+      "37  119.675101  219.682454  \n",
+      "38   94.363613  217.760078  \n",
+      "39  122.660361  222.184711  \n",
+      "40   57.430789  266.217350  \n",
+      "41   44.094105  301.142818  \n",
+      "\n",
+      "[42 rows x 647 columns]\n",
+      "Writing: /wrk/charkins/melodies_monet/aircraft/develop_aircraft_looping/output/0722_firexaq_wrfchem_v4.2.nc4\n",
+      "wrfchem\n",
+      "/wrk/users/charkins/melodies-monet_data/wrfchem/run_CONUS_fv19_BEIS_1.0xISO_RACM_v4.2.2_racm_berk_vcp_noI_phot_soa/0905/*\n",
+      "**** Reading WRF-Chem model output...\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/charkins/miniconda3/envs/melodies-monet_aircraft/lib/python3.9/site-packages/xarray/core/groupby.py:534: FutureWarning: 'S' is deprecated and will be removed in a future version, please use 's' instead.\n",
+      "  index_grouper = pd.Grouper(\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "After pairing:      Time_Stop  Day_Of_Year_YANG   latitude                time   longitude  \\\n",
+      "0     63500.0             248.0  38.734977 2019-09-05 17:30:00  -97.653676   \n",
+      "1     63910.0             248.0  38.677687 2019-09-05 17:40:00  -98.239499   \n",
+      "2     64510.0             248.0  38.499000 2019-09-05 17:50:00  -99.550963   \n",
+      "3     65110.0             248.0  38.250739 2019-09-05 18:00:00 -101.083832   \n",
+      "4     65710.0             248.0  37.963158 2019-09-05 18:10:00 -102.715195   \n",
+      "5     66310.0             248.0  37.645989 2019-09-05 18:20:00 -104.370251   \n",
+      "6     66910.0             248.0  37.418731 2019-09-05 18:30:00 -105.996288   \n",
+      "7     67510.0             248.0  37.601763 2019-09-05 18:40:00 -107.633907   \n",
+      "8     68110.0             248.0  37.807663 2019-09-05 18:50:00 -109.295016   \n",
+      "9     68710.0             248.0  37.989196 2019-09-05 19:00:00 -110.938352   \n",
+      "10    69310.0             248.0  38.123925 2019-09-05 19:10:00 -112.295670   \n",
+      "11    70510.0             248.0  38.368578 2019-09-05 19:30:00 -116.226834   \n",
+      "12    71110.0             248.0  38.030544 2019-09-05 19:40:00 -117.588246   \n",
+      "13    71710.0             248.0  37.424994 2019-09-05 19:50:00 -118.953838   \n",
+      "14    72310.0             248.0  36.787872 2019-09-05 20:00:00 -119.541030   \n",
+      "15    72910.0             248.0  36.577204 2019-09-05 20:10:00 -119.389426   \n",
+      "16    73510.0             248.0  35.944105 2019-09-05 20:20:00 -119.262761   \n",
+      "17    74110.0             248.0  35.368064 2019-09-05 20:30:00 -118.874691   \n",
+      "18    74710.0             248.0  34.845105 2019-09-05 20:40:00 -118.187151   \n",
+      "19    75310.0             248.0  34.360774 2019-09-05 20:50:00 -117.478716   \n",
+      "20    75910.0             248.0  34.154338 2019-09-05 21:00:00 -117.842208   \n",
+      "21    76510.0             248.0  34.063278 2019-09-05 21:10:00 -118.575703   \n",
+      "22    77110.0             248.0  33.717972 2019-09-05 21:20:00 -118.868338   \n",
+      "23    77710.0             248.0  33.635185 2019-09-05 21:30:00 -118.266848   \n",
+      "24    78310.0             248.0  33.869226 2019-09-05 21:40:00 -117.637406   \n",
+      "25    78910.0             248.0  34.127806 2019-09-05 21:50:00 -117.554224   \n",
+      "26    79510.0             248.0  34.117361 2019-09-05 22:00:00 -118.273340   \n",
+      "27    80110.0             248.0  33.915614 2019-09-05 22:10:00 -118.860136   \n",
+      "28    80710.0             248.0  33.601620 2019-09-05 22:20:00 -118.616768   \n",
+      "29    81310.0             248.0  33.753054 2019-09-05 22:30:00 -117.968083   \n",
+      "30    81910.0             248.0  33.993472 2019-09-05 22:40:00 -117.426485   \n",
+      "31    82510.0             248.0  34.168588 2019-09-05 22:50:00 -117.883018   \n",
+      "32    83110.0             248.0  34.548364 2019-09-05 23:00:00 -118.133860   \n",
+      "33    83435.0             248.0  34.627215 2019-09-05 23:10:00 -118.075917   \n",
+      "\n",
+      "        altitude  HAE_GPS_Altitude_YANG  Pressure_Altitude_YANG  \\\n",
+      "0     894.690909             868.942273             2723.631818   \n",
+      "1    3604.428333            3581.033167            11012.364667   \n",
+      "2    7319.502833            7295.814667            22461.166667   \n",
+      "3    9786.676667            9762.397000            30081.718333   \n",
+      "4   10407.810000           10383.433333            32011.196667   \n",
+      "5   10414.333333           10389.993333            32021.300000   \n",
+      "6   10411.490000           10388.208333            32011.770000   \n",
+      "7   10404.180000           10381.626667            32007.816667   \n",
+      "8   10979.271667           10958.295000            33824.063333   \n",
+      "9   11672.405000           11650.991667            36009.871667   \n",
+      "10  11666.662162           11643.972973            36009.876667   \n",
+      "11  11631.415556           11605.715556            36022.105000   \n",
+      "12  11615.803333           11588.305000            36024.730000   \n",
+      "13  10504.813333           10474.243167            32599.155000   \n",
+      "14   4241.425000            4207.823000            13122.673333   \n",
+      "15    637.723333             606.008667             1998.695000   \n",
+      "16    421.666667             388.597500             1339.843333   \n",
+      "17   1440.125000            1405.962833             4446.410000   \n",
+      "18   3059.091667            3024.490667             9395.545000   \n",
+      "19   2320.718333            2285.024333             7140.183333   \n",
+      "20   1230.903333            1195.037833             3800.290000   \n",
+      "21    864.623333             829.587000             2691.010000   \n",
+      "22    348.911667             311.499000             1082.768333   \n",
+      "23    534.426667             499.543333             1657.283333   \n",
+      "24    850.476667             816.171167             2655.686667   \n",
+      "25   1097.641667            1063.743833             3409.431667   \n",
+      "26   1119.500000            1085.065000             3479.891667   \n",
+      "27    348.151667             312.048667             1098.271667   \n",
+      "28    164.778333             129.355000              527.185000   \n",
+      "29    972.900000             938.972333             3032.373333   \n",
+      "30    825.286667             791.459167             2587.446667   \n",
+      "31   1328.658333            1295.573167             4115.413333   \n",
+      "32   1832.190000            1798.128167             5680.118333   \n",
+      "33    770.100000             736.106000             2429.620000   \n",
+      "\n",
+      "    Radar_Altitude_YANG  Ground_Speed_YANG  ...  smoke_age_HOLMES  \\\n",
+      "0           3624.733333          97.101455  ...               NaN   \n",
+      "1          10158.393333         164.819317  ...               NaN   \n",
+      "2          21757.255000         215.161400  ...               NaN   \n",
+      "3          28922.423333         238.651867  ...               NaN   \n",
+      "4          30188.393333         249.379167  ...               NaN   \n",
+      "5          28189.871667         249.595700  ...               NaN   \n",
+      "6          24977.645000         245.304950  ...               NaN   \n",
+      "7          23327.355000         246.791267  ...               NaN   \n",
+      "8          28174.040000         244.818833  ...               NaN   \n",
+      "9          30877.383333         246.004950  ...               NaN   \n",
+      "10         31376.451667         250.340305  ...               NaN   \n",
+      "11         31929.470000         244.688762  ...               NaN   \n",
+      "12         32019.820000         237.545700  ...               NaN   \n",
+      "13         26933.873333         218.816950  ...               NaN   \n",
+      "14         13267.180000         177.255317  ...               NaN   \n",
+      "15          1714.861667         126.960767  ...               NaN   \n",
+      "16          1074.213333         123.811933  ...               NaN   \n",
+      "17          3323.102500         136.835350  ...               NaN   \n",
+      "18          6640.450833         147.673917  ...               NaN   \n",
+      "19          4366.171667         136.331083  ...               NaN   \n",
+      "20          2529.547500         120.674683  ...               NaN   \n",
+      "21          2272.865833         111.110267  ...               NaN   \n",
+      "22          1139.750833         118.355017  ...               NaN   \n",
+      "23          1744.688333         115.952117  ...               NaN   \n",
+      "24          2061.186667         118.996167  ...               NaN   \n",
+      "25          1971.540833         118.255883  ...               NaN   \n",
+      "26          2816.974167         110.606150  ...               NaN   \n",
+      "27          1061.895000         110.472350  ...               NaN   \n",
+      "28           535.490833         114.044033  ...               NaN   \n",
+      "29          3018.250000         113.971633  ...               NaN   \n",
+      "30          1509.157500         116.837750  ...               NaN   \n",
+      "31          2645.973333         117.974083  ...               NaN   \n",
+      "32          2993.435833         116.279983  ...               NaN   \n",
+      "33             3.910000          17.564200  ...               NaN   \n",
+      "\n",
+      "    smoke_age_corr_HOLMES  smoke_age_rise_HOLMES  smoke_rise_HOLMES  \\\n",
+      "0                     NaN                    NaN                NaN   \n",
+      "1                     NaN                    NaN                NaN   \n",
+      "2                     NaN                    NaN                NaN   \n",
+      "3                     NaN                    NaN                NaN   \n",
+      "4                     NaN                    NaN                NaN   \n",
+      "5                     NaN                    NaN                NaN   \n",
+      "6                     NaN                    NaN                NaN   \n",
+      "7                     NaN                    NaN                NaN   \n",
+      "8                     NaN                    NaN                NaN   \n",
+      "9                     NaN                    NaN                NaN   \n",
+      "10                    NaN                    NaN                NaN   \n",
+      "11                    NaN                    NaN                NaN   \n",
+      "12                    NaN                    NaN                NaN   \n",
+      "13                    NaN                    NaN                NaN   \n",
+      "14                    NaN                    NaN                NaN   \n",
+      "15                    NaN                    NaN                NaN   \n",
+      "16                    NaN                    NaN                NaN   \n",
+      "17                    NaN                    NaN                NaN   \n",
+      "18                    NaN                    NaN                NaN   \n",
+      "19                    NaN                    NaN                NaN   \n",
+      "20                    NaN                    NaN                NaN   \n",
+      "21                    NaN                    NaN                NaN   \n",
+      "22                    NaN                    NaN                NaN   \n",
+      "23                    NaN                    NaN                NaN   \n",
+      "24                    NaN                    NaN                NaN   \n",
+      "25                    NaN                    NaN                NaN   \n",
+      "26                    NaN                    NaN                NaN   \n",
+      "27                    NaN                    NaN                NaN   \n",
+      "28                    NaN                    NaN                NaN   \n",
+      "29                    NaN                    NaN                NaN   \n",
+      "30                    NaN                    NaN                NaN   \n",
+      "31                    NaN                    NaN                NaN   \n",
+      "32                    NaN                    NaN                NaN   \n",
+      "33                    NaN                    NaN                NaN   \n",
+      "\n",
+      "    fire_distance_HOLMES  smoke_agemethod_HOLMES       no2        no  \\\n",
+      "0                    NaN                     NaN  0.369187  0.080655   \n",
+      "1                    NaN                     NaN  0.066953  0.026467   \n",
+      "2                    NaN                     NaN  0.024407  0.023548   \n",
+      "3                    NaN                     NaN  0.014954  0.023697   \n",
+      "4                    NaN                     NaN  0.011589  0.020452   \n",
+      "5                    NaN                     NaN  0.012446  0.025369   \n",
+      "6                    NaN                     NaN  0.011575  0.020669   \n",
+      "7                    NaN                     NaN  0.011834  0.022708   \n",
+      "8                    NaN                     NaN  0.014187  0.023868   \n",
+      "9                    NaN                     NaN  0.009450  0.018363   \n",
+      "10                   NaN                     NaN  0.012301  0.025155   \n",
+      "11                   NaN                     NaN  0.026284  0.092669   \n",
+      "12                   NaN                     NaN  0.017747  0.081770   \n",
+      "13                   NaN                     NaN  0.012366  0.042793   \n",
+      "14                   NaN                     NaN  0.038027  0.017216   \n",
+      "15                   NaN                     NaN  1.090161  0.186698   \n",
+      "16                   NaN                     NaN  0.963027  0.146033   \n",
+      "17                   NaN                     NaN  0.209307  0.048873   \n",
+      "18                   NaN                     NaN  0.079565  0.027141   \n",
+      "19                   NaN                     NaN  0.159230  0.043906   \n",
+      "20                   NaN                     NaN  3.907354  0.526845   \n",
+      "21                   NaN                     NaN  0.251779  0.059314   \n",
+      "22                   NaN                     NaN  0.089886  0.028595   \n",
+      "23                   NaN                     NaN  0.038612  0.012282   \n",
+      "24                   NaN                     NaN  1.728503  0.309476   \n",
+      "25                   NaN                     NaN  2.828000  0.373965   \n",
+      "26                   NaN                     NaN  0.622667  0.112616   \n",
+      "27                   NaN                     NaN  0.093071  0.028471   \n",
+      "28                   NaN                     NaN  0.157249  0.044961   \n",
+      "29                   NaN                     NaN  0.294662  0.060520   \n",
+      "30                   NaN                     NaN  2.441050  0.319217   \n",
+      "31                   NaN                     NaN  3.053191  0.463047   \n",
+      "32                   NaN                     NaN  1.714251  0.220931   \n",
+      "33                   NaN                     NaN  1.572429  0.167168   \n",
+      "\n",
+      "            o3  temp_model  \n",
+      "0    67.755870  300.721478  \n",
+      "1    62.362977  283.845681  \n",
+      "2    69.232232  258.860673  \n",
+      "3    67.767709  239.699705  \n",
+      "4    65.097720  234.926779  \n",
+      "5    68.705167  235.180141  \n",
+      "6    67.452322  235.925135  \n",
+      "7    67.417338  235.901365  \n",
+      "8    70.691808  232.455918  \n",
+      "9    72.781808  228.101094  \n",
+      "10   70.139320  227.247372  \n",
+      "11   79.127530  226.714925  \n",
+      "12   51.499168  226.418541  \n",
+      "13   49.536412  233.064741  \n",
+      "14   66.294145  276.549419  \n",
+      "15   77.489692  301.898289  \n",
+      "16   70.638313  304.550366  \n",
+      "17   67.949148  298.821680  \n",
+      "18   64.754358  285.585491  \n",
+      "19   67.563417  292.122093  \n",
+      "20  129.504251  298.813400  \n",
+      "21   61.347351  301.015340  \n",
+      "22   41.255299  301.130530  \n",
+      "23   39.264672  301.368937  \n",
+      "24   84.396089  300.913017  \n",
+      "25  119.959903  301.410482  \n",
+      "26   86.935897  299.853776  \n",
+      "27   41.624443  301.148777  \n",
+      "28   44.158677  295.023443  \n",
+      "29   70.425271  301.152392  \n",
+      "30  107.698509  303.321913  \n",
+      "31  105.909291  298.115557  \n",
+      "32  125.464884  296.451659  \n",
+      "33  105.248910  306.475800  \n",
+      "\n",
+      "[34 rows x 647 columns]\n",
+      "Writing: /wrk/charkins/melodies_monet/aircraft/develop_aircraft_looping/output/0905_firexaq_wrfchem_v4.2.nc4\n"
+     ]
+    }
+   ],
+   "source": [
+    "loop_pairing(control=control_fn,file_pairs_yaml='../yaml/supplementary_yaml/aircraft_looping_file_pairs.yaml')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b5c161f7-2eaa-432b-a299-2caa184fd27a",
+   "metadata": {},
+   "source": [
+    "## Looping over aircraft pairing using info from a dictionary"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "ccc8e63c",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "wrfchem\n",
+      "/wrk/users/charkins/melodies-monet_data/wrfchem/run_CONUS_fv19_BEIS_1.0xISO_RACM_v4.2.2_racm_berk_vcp_noI_phot/0722/*\n",
+      "**** Reading WRF-Chem model output...\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/charkins/miniconda3/envs/melodies-monet_aircraft/lib/python3.9/site-packages/xarray/core/groupby.py:534: FutureWarning: 'S' is deprecated and will be removed in a future version, please use 's' instead.\n",
+      "  index_grouper = pd.Grouper(\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "After pairing:      Time_Stop  Day_Of_Year_YANG   latitude                time   longitude  \\\n",
+      "0     65905.0             203.0  34.636072 2019-07-22 18:10:00 -118.139775   \n",
+      "1     66310.0             203.0  34.520597 2019-07-22 18:20:00 -117.717356   \n",
+      "2     66910.0             203.0  34.174384 2019-07-22 18:30:00 -117.603158   \n",
+      "3     67510.0             203.0  34.102602 2019-07-22 18:40:00 -118.361519   \n",
+      "4     68110.0             203.0  33.866911 2019-07-22 18:50:00 -118.895332   \n",
+      "5     68710.0             203.0  33.600202 2019-07-22 19:00:00 -118.564034   \n",
+      "6     69310.0             203.0  33.753515 2019-07-22 19:10:00 -117.968233   \n",
+      "7     69910.0             203.0  33.985567 2019-07-22 19:20:00 -117.437606   \n",
+      "8     70510.0             203.0  34.163247 2019-07-22 19:30:00 -117.851272   \n",
+      "9     71110.0             203.0  34.537180 2019-07-22 19:40:00 -118.526429   \n",
+      "10    71710.0             203.0  35.309810 2019-07-22 19:50:00 -119.123868   \n",
+      "11    72310.0             203.0  36.226741 2019-07-22 20:00:00 -119.547113   \n",
+      "12    72910.0             203.0  37.134482 2019-07-22 20:10:00 -120.143756   \n",
+      "13    73510.0             203.0  37.975441 2019-07-22 20:20:00 -120.700291   \n",
+      "14    74110.0             203.0  37.901537 2019-07-22 20:30:00 -121.364430   \n",
+      "15    74710.0             203.0  37.717381 2019-07-22 20:40:00 -121.011395   \n",
+      "16    75310.0             203.0  37.546843 2019-07-22 20:50:00 -120.598869   \n",
+      "17    75910.0             203.0  37.173246 2019-07-22 21:00:00 -121.024890   \n",
+      "18    76510.0             203.0  37.121143 2019-07-22 21:10:00 -120.487622   \n",
+      "19    77110.0             203.0  37.108647 2019-07-22 21:20:00 -119.899767   \n",
+      "20    77710.0             203.0  36.747118 2019-07-22 21:30:00 -120.375273   \n",
+      "21    78310.0             203.0  36.487591 2019-07-22 21:40:00 -120.188678   \n",
+      "22    78910.0             203.0  36.556247 2019-07-22 21:50:00 -119.430301   \n",
+      "23    79510.0             203.0  36.162445 2019-07-22 22:00:00 -119.532292   \n",
+      "24    80110.0             203.0  35.842443 2019-07-22 22:10:00 -119.840327   \n",
+      "25    80710.0             203.0  35.957125 2019-07-22 22:20:00 -119.187474   \n",
+      "26    81310.0             203.0  35.654423 2019-07-22 22:30:00 -119.351302   \n",
+      "27    81910.0             203.0  35.426144 2019-07-22 22:40:00 -119.632331   \n",
+      "28    82510.0             203.0  35.459973 2019-07-22 22:50:00 -118.959830   \n",
+      "29    83110.0             203.0  35.192984 2019-07-22 23:00:00 -119.260506   \n",
+      "30    83710.0             203.0  34.905976 2019-07-22 23:10:00 -118.578383   \n",
+      "31    84310.0             203.0  34.394222 2019-07-22 23:20:00 -117.566666   \n",
+      "32    84910.0             203.0  34.166601 2019-07-22 23:30:00 -117.824551   \n",
+      "33    85510.0             203.0  34.637761 2019-07-22 23:40:00 -118.568665   \n",
+      "34    86110.0             203.0  35.544457 2019-07-22 23:50:00 -119.230834   \n",
+      "35    86710.0             203.0  36.613801 2019-07-23 00:00:00 -119.551456   \n",
+      "36    87310.0             203.0  37.909203 2019-07-23 00:10:00 -119.420821   \n",
+      "37    87910.0             203.0  39.279940 2019-07-23 00:20:00 -119.388695   \n",
+      "38    88510.0             203.0  40.586553 2019-07-23 00:30:00 -118.930815   \n",
+      "39    89110.0             203.0  41.865071 2019-07-23 00:40:00 -118.169258   \n",
+      "40    89710.0             203.0  42.869333 2019-07-23 00:50:00 -117.109481   \n",
+      "41    90250.0             203.0  43.409062 2019-07-23 01:00:00 -116.256079   \n",
+      "\n",
+      "        altitude  HAE_GPS_Altitude_YANG  Pressure_Altitude_YANG  \\\n",
+      "0    1330.171429            1300.748095             4134.495238   \n",
+      "1    2891.590000            2861.474167             8878.721667   \n",
+      "2    1329.585000            1296.738500             4100.635000   \n",
+      "3     789.731667             755.256333             2454.616667   \n",
+      "4     456.455000             420.872833             1414.905000   \n",
+      "5     388.110000             352.063667             1195.108333   \n",
+      "6     884.305000             850.087167             2745.273333   \n",
+      "7     692.220000             658.430500             2146.456667   \n",
+      "8     978.838333             944.772667             3020.430000   \n",
+      "9    4448.583333            4416.236167            13672.116667   \n",
+      "10   4699.603333            4666.808000            14453.471667   \n",
+      "11   4702.930000            4671.746167            14470.700000   \n",
+      "12   4651.821667            4621.899500            14338.598333   \n",
+      "13   2057.683333            2027.691167             6363.271667   \n",
+      "14    347.575000             317.914500             1097.440000   \n",
+      "15    401.340000             372.076833             1270.806667   \n",
+      "16    415.476667             386.477500             1320.788333   \n",
+      "17    486.568333             455.656500             1542.610000   \n",
+      "18    383.860000             353.190667             1230.475000   \n",
+      "19    566.430000             535.867833             1794.350000   \n",
+      "20    413.650000             382.798000             1326.226667   \n",
+      "21    456.285000             424.915000             1458.981667   \n",
+      "22    441.401667             411.150667             1409.630000   \n",
+      "23    391.538333             360.022500             1269.263333   \n",
+      "24    443.633333             410.852000             1432.801667   \n",
+      "25    433.648333             401.712000             1398.123333   \n",
+      "26    450.413333             417.380500             1454.841667   \n",
+      "27    584.306667             551.021000             1866.391667   \n",
+      "28    621.223333             589.189333             1988.930000   \n",
+      "29   1103.690000            1071.349833             3446.908333   \n",
+      "30   4886.990000            4852.221333            15033.178333   \n",
+      "31   3227.766667            3191.527000             9930.980000   \n",
+      "32    980.678333             944.656833             3037.476667   \n",
+      "33   4916.175000            4882.097500            15126.913333   \n",
+      "34   5366.841667            5333.401667            16546.148333   \n",
+      "35   6374.786667            6344.491500            19679.323333   \n",
+      "36  10469.588333           10442.075500            32493.161667   \n",
+      "37  12483.868333           12457.703333            38920.385000   \n",
+      "38  12473.943333           12450.180000            38950.370000   \n",
+      "39  12025.688333           12002.561333            37548.035000   \n",
+      "40   6028.668333            6006.139500            18660.910000   \n",
+      "41   2020.721527            1999.906390             6318.911042   \n",
+      "\n",
+      "    Radar_Altitude_YANG  Ground_Speed_YANG  ...  smoke_age_HOLMES  \\\n",
+      "0           1810.085714         107.236905  ...               NaN   \n",
+      "1           6264.286667         135.144100  ...               NaN   \n",
+      "2           2319.345833         136.029600  ...               NaN   \n",
+      "3           1801.628333         112.417467  ...               NaN   \n",
+      "4           1459.666667         108.933183  ...               NaN   \n",
+      "5           1260.395000         104.355950  ...               NaN   \n",
+      "6           2749.386667         105.992217  ...               NaN   \n",
+      "7           1263.733333         111.095683  ...               NaN   \n",
+      "8           1649.393333         114.995967  ...               NaN   \n",
+      "9          11609.339167         158.400283  ...               NaN   \n",
+      "10         14722.710000         182.714333  ...               NaN   \n",
+      "11         15188.196667         180.931333  ...               NaN   \n",
+      "12         14943.548333         205.462900  ...               NaN   \n",
+      "13          5830.063333         152.469367  ...               NaN   \n",
+      "14          1106.500000         128.836283  ...               NaN   \n",
+      "15          1157.649167         127.694483  ...               NaN   \n",
+      "16          1112.593333         123.989783  ...               NaN   \n",
+      "17          1258.561667         125.426017  ...               NaN   \n",
+      "18          1087.955000         123.996183  ...               NaN   \n",
+      "19          1162.829167         124.919000  ...               NaN   \n",
+      "20          1061.278333         127.847450  ...               NaN   \n",
+      "21          1104.408333         127.579550  ...               NaN   \n",
+      "22          1085.115833         126.351033  ...               NaN   \n",
+      "23          1048.204167         124.213800  ...               NaN   \n",
+      "24          1101.781667         126.204933  ...               NaN   \n",
+      "25          1035.869167         124.252350  ...               NaN   \n",
+      "26          1054.296667         130.615483  ...               NaN   \n",
+      "27          1163.598333         131.728217  ...               NaN   \n",
+      "28          1246.755000         124.834083  ...               NaN   \n",
+      "29          3160.055833         131.548783  ...               NaN   \n",
+      "30         13703.975000         194.748700  ...               NaN   \n",
+      "31          7213.434167         162.101050  ...               NaN   \n",
+      "32          1591.854167         133.545617  ...               NaN   \n",
+      "33         12880.261667         194.177217  ...               NaN   \n",
+      "34         17214.746667         204.192533  ...               NaN   \n",
+      "35         20204.583333         220.150867  ...               NaN   \n",
+      "36         25932.503333         257.683217  ...               NaN   \n",
+      "37         35274.855000         255.261500  ...               NaN   \n",
+      "38         35591.463333         259.636117  ...               NaN   \n",
+      "39         33669.345000         258.961817  ...               NaN   \n",
+      "40         14888.741667         214.276550  ...               NaN   \n",
+      "41          3605.892708         125.354083  ...               NaN   \n",
+      "\n",
+      "    smoke_age_corr_HOLMES  smoke_age_rise_HOLMES  smoke_rise_HOLMES  \\\n",
+      "0                     NaN                    NaN                NaN   \n",
+      "1                     NaN                    NaN                NaN   \n",
+      "2                     NaN                    NaN                NaN   \n",
+      "3                     NaN                    NaN                NaN   \n",
+      "4                     NaN                    NaN                NaN   \n",
+      "5                     NaN                    NaN                NaN   \n",
+      "6                     NaN                    NaN                NaN   \n",
+      "7                     NaN                    NaN                NaN   \n",
+      "8                     NaN                    NaN                NaN   \n",
+      "9                     NaN                    NaN                NaN   \n",
+      "10                    NaN                    NaN                NaN   \n",
+      "11                    NaN                    NaN                NaN   \n",
+      "12                    NaN                    NaN                NaN   \n",
+      "13                    NaN                    NaN                NaN   \n",
+      "14                    NaN                    NaN                NaN   \n",
+      "15                    NaN                    NaN                NaN   \n",
+      "16                    NaN                    NaN                NaN   \n",
+      "17                    NaN                    NaN                NaN   \n",
+      "18                    NaN                    NaN                NaN   \n",
+      "19                    NaN                    NaN                NaN   \n",
+      "20                    NaN                    NaN                NaN   \n",
+      "21                    NaN                    NaN                NaN   \n",
+      "22                    NaN                    NaN                NaN   \n",
+      "23                    NaN                    NaN                NaN   \n",
+      "24                    NaN                    NaN                NaN   \n",
+      "25                    NaN                    NaN                NaN   \n",
+      "26                    NaN                    NaN                NaN   \n",
+      "27                    NaN                    NaN                NaN   \n",
+      "28                    NaN                    NaN                NaN   \n",
+      "29                    NaN                    NaN                NaN   \n",
+      "30                    NaN                    NaN                NaN   \n",
+      "31                    NaN                    NaN                NaN   \n",
+      "32                    NaN                    NaN                NaN   \n",
+      "33                    NaN                    NaN                NaN   \n",
+      "34                    NaN                    NaN                NaN   \n",
+      "35                    NaN                    NaN                NaN   \n",
+      "36                    NaN                    NaN                NaN   \n",
+      "37                    NaN                    NaN                NaN   \n",
+      "38                    NaN                    NaN                NaN   \n",
+      "39                    NaN                    NaN                NaN   \n",
+      "40                    NaN                    NaN                NaN   \n",
+      "41                    NaN                    NaN                NaN   \n",
+      "\n",
+      "    fire_distance_HOLMES  smoke_agemethod_HOLMES       no2        no  \\\n",
+      "0                    NaN                     NaN  0.122522  0.019905   \n",
+      "1                    NaN                     NaN  0.053957  0.018913   \n",
+      "2                    NaN                     NaN  7.627246  2.115838   \n",
+      "3                    NaN                     NaN  2.175637  0.476912   \n",
+      "4                    NaN                     NaN  0.583338  0.173662   \n",
+      "5                    NaN                     NaN  0.228939  0.082676   \n",
+      "6                    NaN                     NaN  0.802599  0.224332   \n",
+      "7                    NaN                     NaN  4.432410  1.082180   \n",
+      "8                    NaN                     NaN  6.916218  2.025461   \n",
+      "9                    NaN                     NaN  0.024518  0.013080   \n",
+      "10                   NaN                     NaN  0.013201  0.007279   \n",
+      "11                   NaN                     NaN  0.013664  0.006940   \n",
+      "12                   NaN                     NaN  0.016320  0.008900   \n",
+      "13                   NaN                     NaN  0.022961  0.008513   \n",
+      "14                   NaN                     NaN  1.026490  0.215797   \n",
+      "15                   NaN                     NaN  0.842013  0.169011   \n",
+      "16                   NaN                     NaN  0.699509  0.141229   \n",
+      "17                   NaN                     NaN  0.388654  0.081787   \n",
+      "18                   NaN                     NaN  0.533184  0.110072   \n",
+      "19                   NaN                     NaN  0.640762  0.122460   \n",
+      "20                   NaN                     NaN  0.469143  0.096359   \n",
+      "21                   NaN                     NaN  0.450651  0.090687   \n",
+      "22                   NaN                     NaN  0.871470  0.145382   \n",
+      "23                   NaN                     NaN  0.504581  0.094897   \n",
+      "24                   NaN                     NaN  0.470249  0.090558   \n",
+      "25                   NaN                     NaN  0.653810  0.120993   \n",
+      "26                   NaN                     NaN  0.575991  0.109725   \n",
+      "27                   NaN                     NaN  0.821052  0.147723   \n",
+      "28                   NaN                     NaN  1.089419  0.203690   \n",
+      "29                   NaN                     NaN  0.532588  0.112997   \n",
+      "30                   NaN                     NaN  0.015762  0.008777   \n",
+      "31                   NaN                     NaN  0.064315  0.023181   \n",
+      "32                   NaN                     NaN  6.333918  0.784311   \n",
+      "33                   NaN                     NaN  0.015495  0.008541   \n",
+      "34                   NaN                     NaN  0.011213  0.006946   \n",
+      "35                   NaN                     NaN  0.013553  0.010971   \n",
+      "36                   NaN                     NaN  0.021208  0.051385   \n",
+      "37                   NaN                     NaN  0.035450  0.138139   \n",
+      "38                   NaN                     NaN  0.034754  0.114122   \n",
+      "39                   NaN                     NaN  0.037999  0.093451   \n",
+      "40                   NaN                     NaN  0.011679  0.007715   \n",
+      "41                   NaN                     NaN  0.058921  0.012355   \n",
+      "\n",
+      "            o3  temp_model  \n",
+      "0    51.305995  300.371623  \n",
+      "1    52.421507  288.820422  \n",
+      "2    60.100534  299.822678  \n",
+      "3    47.583521  298.518989  \n",
+      "4    47.162077  295.905053  \n",
+      "5    37.774421  293.187716  \n",
+      "6    59.828919  299.835180  \n",
+      "7    72.034705  300.110961  \n",
+      "8    67.743776  299.104228  \n",
+      "9    53.653065  276.060637  \n",
+      "10   53.147322  273.531236  \n",
+      "11   54.822424  273.216146  \n",
+      "12   54.930731  274.352880  \n",
+      "13   44.690583  293.234401  \n",
+      "14   58.176093  303.677049  \n",
+      "15   61.010512  304.256941  \n",
+      "16   58.111635  305.812981  \n",
+      "17   53.329552  304.858109  \n",
+      "18   55.867485  306.275578  \n",
+      "19   60.565171  306.391196  \n",
+      "20   54.214828  306.485789  \n",
+      "21   54.165336  307.066782  \n",
+      "22   69.127629  307.176335  \n",
+      "23   57.297145  307.717143  \n",
+      "24   56.936562  308.032527  \n",
+      "25   59.102308  307.637274  \n",
+      "26   57.119073  307.627132  \n",
+      "27   63.302212  307.094842  \n",
+      "28   61.251840  307.975101  \n",
+      "29   59.252297  303.453705  \n",
+      "30   53.972373  272.912668  \n",
+      "31   51.288907  287.152925  \n",
+      "32  103.192044  301.856393  \n",
+      "33   54.167179  273.000949  \n",
+      "34   55.493833  269.622581  \n",
+      "35   58.168320  262.686412  \n",
+      "36   70.167588  232.388259  \n",
+      "37  119.675101  219.682454  \n",
+      "38   94.363613  217.760078  \n",
+      "39  122.660361  222.184711  \n",
+      "40   57.430789  266.217350  \n",
+      "41   44.094105  301.142818  \n",
+      "\n",
+      "[42 rows x 647 columns]\n",
+      "Writing: /wrk/charkins/melodies_monet/aircraft/develop_aircraft_looping/output/0722_firexaq_wrfchem_v4.2.nc4\n",
+      "wrfchem\n",
+      "/wrk/users/charkins/melodies-monet_data/wrfchem/run_CONUS_fv19_BEIS_1.0xISO_RACM_v4.2.2_racm_berk_vcp_noI_phot_soa/0905/*\n",
+      "**** Reading WRF-Chem model output...\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/charkins/miniconda3/envs/melodies-monet_aircraft/lib/python3.9/site-packages/xarray/core/groupby.py:534: FutureWarning: 'S' is deprecated and will be removed in a future version, please use 's' instead.\n",
+      "  index_grouper = pd.Grouper(\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "After pairing:      Time_Stop  Day_Of_Year_YANG   latitude                time   longitude  \\\n",
+      "0     63500.0             248.0  38.734977 2019-09-05 17:30:00  -97.653676   \n",
+      "1     63910.0             248.0  38.677687 2019-09-05 17:40:00  -98.239499   \n",
+      "2     64510.0             248.0  38.499000 2019-09-05 17:50:00  -99.550963   \n",
+      "3     65110.0             248.0  38.250739 2019-09-05 18:00:00 -101.083832   \n",
+      "4     65710.0             248.0  37.963158 2019-09-05 18:10:00 -102.715195   \n",
+      "5     66310.0             248.0  37.645989 2019-09-05 18:20:00 -104.370251   \n",
+      "6     66910.0             248.0  37.418731 2019-09-05 18:30:00 -105.996288   \n",
+      "7     67510.0             248.0  37.601763 2019-09-05 18:40:00 -107.633907   \n",
+      "8     68110.0             248.0  37.807663 2019-09-05 18:50:00 -109.295016   \n",
+      "9     68710.0             248.0  37.989196 2019-09-05 19:00:00 -110.938352   \n",
+      "10    69310.0             248.0  38.123925 2019-09-05 19:10:00 -112.295670   \n",
+      "11    70510.0             248.0  38.368578 2019-09-05 19:30:00 -116.226834   \n",
+      "12    71110.0             248.0  38.030544 2019-09-05 19:40:00 -117.588246   \n",
+      "13    71710.0             248.0  37.424994 2019-09-05 19:50:00 -118.953838   \n",
+      "14    72310.0             248.0  36.787872 2019-09-05 20:00:00 -119.541030   \n",
+      "15    72910.0             248.0  36.577204 2019-09-05 20:10:00 -119.389426   \n",
+      "16    73510.0             248.0  35.944105 2019-09-05 20:20:00 -119.262761   \n",
+      "17    74110.0             248.0  35.368064 2019-09-05 20:30:00 -118.874691   \n",
+      "18    74710.0             248.0  34.845105 2019-09-05 20:40:00 -118.187151   \n",
+      "19    75310.0             248.0  34.360774 2019-09-05 20:50:00 -117.478716   \n",
+      "20    75910.0             248.0  34.154338 2019-09-05 21:00:00 -117.842208   \n",
+      "21    76510.0             248.0  34.063278 2019-09-05 21:10:00 -118.575703   \n",
+      "22    77110.0             248.0  33.717972 2019-09-05 21:20:00 -118.868338   \n",
+      "23    77710.0             248.0  33.635185 2019-09-05 21:30:00 -118.266848   \n",
+      "24    78310.0             248.0  33.869226 2019-09-05 21:40:00 -117.637406   \n",
+      "25    78910.0             248.0  34.127806 2019-09-05 21:50:00 -117.554224   \n",
+      "26    79510.0             248.0  34.117361 2019-09-05 22:00:00 -118.273340   \n",
+      "27    80110.0             248.0  33.915614 2019-09-05 22:10:00 -118.860136   \n",
+      "28    80710.0             248.0  33.601620 2019-09-05 22:20:00 -118.616768   \n",
+      "29    81310.0             248.0  33.753054 2019-09-05 22:30:00 -117.968083   \n",
+      "30    81910.0             248.0  33.993472 2019-09-05 22:40:00 -117.426485   \n",
+      "31    82510.0             248.0  34.168588 2019-09-05 22:50:00 -117.883018   \n",
+      "32    83110.0             248.0  34.548364 2019-09-05 23:00:00 -118.133860   \n",
+      "33    83435.0             248.0  34.627215 2019-09-05 23:10:00 -118.075917   \n",
+      "\n",
+      "        altitude  HAE_GPS_Altitude_YANG  Pressure_Altitude_YANG  \\\n",
+      "0     894.690909             868.942273             2723.631818   \n",
+      "1    3604.428333            3581.033167            11012.364667   \n",
+      "2    7319.502833            7295.814667            22461.166667   \n",
+      "3    9786.676667            9762.397000            30081.718333   \n",
+      "4   10407.810000           10383.433333            32011.196667   \n",
+      "5   10414.333333           10389.993333            32021.300000   \n",
+      "6   10411.490000           10388.208333            32011.770000   \n",
+      "7   10404.180000           10381.626667            32007.816667   \n",
+      "8   10979.271667           10958.295000            33824.063333   \n",
+      "9   11672.405000           11650.991667            36009.871667   \n",
+      "10  11666.662162           11643.972973            36009.876667   \n",
+      "11  11631.415556           11605.715556            36022.105000   \n",
+      "12  11615.803333           11588.305000            36024.730000   \n",
+      "13  10504.813333           10474.243167            32599.155000   \n",
+      "14   4241.425000            4207.823000            13122.673333   \n",
+      "15    637.723333             606.008667             1998.695000   \n",
+      "16    421.666667             388.597500             1339.843333   \n",
+      "17   1440.125000            1405.962833             4446.410000   \n",
+      "18   3059.091667            3024.490667             9395.545000   \n",
+      "19   2320.718333            2285.024333             7140.183333   \n",
+      "20   1230.903333            1195.037833             3800.290000   \n",
+      "21    864.623333             829.587000             2691.010000   \n",
+      "22    348.911667             311.499000             1082.768333   \n",
+      "23    534.426667             499.543333             1657.283333   \n",
+      "24    850.476667             816.171167             2655.686667   \n",
+      "25   1097.641667            1063.743833             3409.431667   \n",
+      "26   1119.500000            1085.065000             3479.891667   \n",
+      "27    348.151667             312.048667             1098.271667   \n",
+      "28    164.778333             129.355000              527.185000   \n",
+      "29    972.900000             938.972333             3032.373333   \n",
+      "30    825.286667             791.459167             2587.446667   \n",
+      "31   1328.658333            1295.573167             4115.413333   \n",
+      "32   1832.190000            1798.128167             5680.118333   \n",
+      "33    770.100000             736.106000             2429.620000   \n",
+      "\n",
+      "    Radar_Altitude_YANG  Ground_Speed_YANG  ...  smoke_age_HOLMES  \\\n",
+      "0           3624.733333          97.101455  ...               NaN   \n",
+      "1          10158.393333         164.819317  ...               NaN   \n",
+      "2          21757.255000         215.161400  ...               NaN   \n",
+      "3          28922.423333         238.651867  ...               NaN   \n",
+      "4          30188.393333         249.379167  ...               NaN   \n",
+      "5          28189.871667         249.595700  ...               NaN   \n",
+      "6          24977.645000         245.304950  ...               NaN   \n",
+      "7          23327.355000         246.791267  ...               NaN   \n",
+      "8          28174.040000         244.818833  ...               NaN   \n",
+      "9          30877.383333         246.004950  ...               NaN   \n",
+      "10         31376.451667         250.340305  ...               NaN   \n",
+      "11         31929.470000         244.688762  ...               NaN   \n",
+      "12         32019.820000         237.545700  ...               NaN   \n",
+      "13         26933.873333         218.816950  ...               NaN   \n",
+      "14         13267.180000         177.255317  ...               NaN   \n",
+      "15          1714.861667         126.960767  ...               NaN   \n",
+      "16          1074.213333         123.811933  ...               NaN   \n",
+      "17          3323.102500         136.835350  ...               NaN   \n",
+      "18          6640.450833         147.673917  ...               NaN   \n",
+      "19          4366.171667         136.331083  ...               NaN   \n",
+      "20          2529.547500         120.674683  ...               NaN   \n",
+      "21          2272.865833         111.110267  ...               NaN   \n",
+      "22          1139.750833         118.355017  ...               NaN   \n",
+      "23          1744.688333         115.952117  ...               NaN   \n",
+      "24          2061.186667         118.996167  ...               NaN   \n",
+      "25          1971.540833         118.255883  ...               NaN   \n",
+      "26          2816.974167         110.606150  ...               NaN   \n",
+      "27          1061.895000         110.472350  ...               NaN   \n",
+      "28           535.490833         114.044033  ...               NaN   \n",
+      "29          3018.250000         113.971633  ...               NaN   \n",
+      "30          1509.157500         116.837750  ...               NaN   \n",
+      "31          2645.973333         117.974083  ...               NaN   \n",
+      "32          2993.435833         116.279983  ...               NaN   \n",
+      "33             3.910000          17.564200  ...               NaN   \n",
+      "\n",
+      "    smoke_age_corr_HOLMES  smoke_age_rise_HOLMES  smoke_rise_HOLMES  \\\n",
+      "0                     NaN                    NaN                NaN   \n",
+      "1                     NaN                    NaN                NaN   \n",
+      "2                     NaN                    NaN                NaN   \n",
+      "3                     NaN                    NaN                NaN   \n",
+      "4                     NaN                    NaN                NaN   \n",
+      "5                     NaN                    NaN                NaN   \n",
+      "6                     NaN                    NaN                NaN   \n",
+      "7                     NaN                    NaN                NaN   \n",
+      "8                     NaN                    NaN                NaN   \n",
+      "9                     NaN                    NaN                NaN   \n",
+      "10                    NaN                    NaN                NaN   \n",
+      "11                    NaN                    NaN                NaN   \n",
+      "12                    NaN                    NaN                NaN   \n",
+      "13                    NaN                    NaN                NaN   \n",
+      "14                    NaN                    NaN                NaN   \n",
+      "15                    NaN                    NaN                NaN   \n",
+      "16                    NaN                    NaN                NaN   \n",
+      "17                    NaN                    NaN                NaN   \n",
+      "18                    NaN                    NaN                NaN   \n",
+      "19                    NaN                    NaN                NaN   \n",
+      "20                    NaN                    NaN                NaN   \n",
+      "21                    NaN                    NaN                NaN   \n",
+      "22                    NaN                    NaN                NaN   \n",
+      "23                    NaN                    NaN                NaN   \n",
+      "24                    NaN                    NaN                NaN   \n",
+      "25                    NaN                    NaN                NaN   \n",
+      "26                    NaN                    NaN                NaN   \n",
+      "27                    NaN                    NaN                NaN   \n",
+      "28                    NaN                    NaN                NaN   \n",
+      "29                    NaN                    NaN                NaN   \n",
+      "30                    NaN                    NaN                NaN   \n",
+      "31                    NaN                    NaN                NaN   \n",
+      "32                    NaN                    NaN                NaN   \n",
+      "33                    NaN                    NaN                NaN   \n",
+      "\n",
+      "    fire_distance_HOLMES  smoke_agemethod_HOLMES       no2        no  \\\n",
+      "0                    NaN                     NaN  0.369187  0.080655   \n",
+      "1                    NaN                     NaN  0.066953  0.026467   \n",
+      "2                    NaN                     NaN  0.024407  0.023548   \n",
+      "3                    NaN                     NaN  0.014954  0.023697   \n",
+      "4                    NaN                     NaN  0.011589  0.020452   \n",
+      "5                    NaN                     NaN  0.012446  0.025369   \n",
+      "6                    NaN                     NaN  0.011575  0.020669   \n",
+      "7                    NaN                     NaN  0.011834  0.022708   \n",
+      "8                    NaN                     NaN  0.014187  0.023868   \n",
+      "9                    NaN                     NaN  0.009450  0.018363   \n",
+      "10                   NaN                     NaN  0.012301  0.025155   \n",
+      "11                   NaN                     NaN  0.026284  0.092669   \n",
+      "12                   NaN                     NaN  0.017747  0.081770   \n",
+      "13                   NaN                     NaN  0.012366  0.042793   \n",
+      "14                   NaN                     NaN  0.038027  0.017216   \n",
+      "15                   NaN                     NaN  1.090161  0.186698   \n",
+      "16                   NaN                     NaN  0.963027  0.146033   \n",
+      "17                   NaN                     NaN  0.209307  0.048873   \n",
+      "18                   NaN                     NaN  0.079565  0.027141   \n",
+      "19                   NaN                     NaN  0.159230  0.043906   \n",
+      "20                   NaN                     NaN  3.907354  0.526845   \n",
+      "21                   NaN                     NaN  0.251779  0.059314   \n",
+      "22                   NaN                     NaN  0.089886  0.028595   \n",
+      "23                   NaN                     NaN  0.038612  0.012282   \n",
+      "24                   NaN                     NaN  1.728503  0.309476   \n",
+      "25                   NaN                     NaN  2.828000  0.373965   \n",
+      "26                   NaN                     NaN  0.622667  0.112616   \n",
+      "27                   NaN                     NaN  0.093071  0.028471   \n",
+      "28                   NaN                     NaN  0.157249  0.044961   \n",
+      "29                   NaN                     NaN  0.294662  0.060520   \n",
+      "30                   NaN                     NaN  2.441050  0.319217   \n",
+      "31                   NaN                     NaN  3.053191  0.463047   \n",
+      "32                   NaN                     NaN  1.714251  0.220931   \n",
+      "33                   NaN                     NaN  1.572429  0.167168   \n",
+      "\n",
+      "            o3  temp_model  \n",
+      "0    67.755870  300.721478  \n",
+      "1    62.362977  283.845681  \n",
+      "2    69.232232  258.860673  \n",
+      "3    67.767709  239.699705  \n",
+      "4    65.097720  234.926779  \n",
+      "5    68.705167  235.180141  \n",
+      "6    67.452322  235.925135  \n",
+      "7    67.417338  235.901365  \n",
+      "8    70.691808  232.455918  \n",
+      "9    72.781808  228.101094  \n",
+      "10   70.139320  227.247372  \n",
+      "11   79.127530  226.714925  \n",
+      "12   51.499168  226.418541  \n",
+      "13   49.536412  233.064741  \n",
+      "14   66.294145  276.549419  \n",
+      "15   77.489692  301.898289  \n",
+      "16   70.638313  304.550366  \n",
+      "17   67.949148  298.821680  \n",
+      "18   64.754358  285.585491  \n",
+      "19   67.563417  292.122093  \n",
+      "20  129.504251  298.813400  \n",
+      "21   61.347351  301.015340  \n",
+      "22   41.255299  301.130530  \n",
+      "23   39.264672  301.368937  \n",
+      "24   84.396089  300.913017  \n",
+      "25  119.959903  301.410482  \n",
+      "26   86.935897  299.853776  \n",
+      "27   41.624443  301.148777  \n",
+      "28   44.158677  295.023443  \n",
+      "29   70.425271  301.152392  \n",
+      "30  107.698509  303.321913  \n",
+      "31  105.909291  298.115557  \n",
+      "32  125.464884  296.451659  \n",
+      "33  105.248910  306.475800  \n",
+      "\n",
+      "[34 rows x 647 columns]\n",
+      "Writing: /wrk/charkins/melodies_monet/aircraft/develop_aircraft_looping/output/0905_firexaq_wrfchem_v4.2.nc4\n"
+     ]
+    }
+   ],
+   "source": [
+    "loop_pairing(control=control_fn,file_pairs=file_pairs)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6b5b7fbf-332f-4cd5-aaea-a98f0b40c4f5",
+   "metadata": {},
+   "source": [
+    "## Finding time bounds of observation files so that it's easier to make the pairing dict/yaml"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "1768d84d",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "For /wrk/d2/rschwantes/obs/firex-aq/R1/10s_merge/firexaq-mrg10-dc8_merge_20190722_R1.ict, time bounds are, Min: <xarray.DataArray 'time' ()>\n",
+      "array('2019-07-22T18:16:35.000000000', dtype='datetime64[ns]'), Max: <xarray.DataArray 'time' ()>\n",
+      "array('2019-07-23T01:07:55.000000000', dtype='datetime64[ns]')\n",
+      "For /wrk/d2/rschwantes/obs/firex-aq/R1/10s_merge/firexaq-mrg10-dc8_merge_20190905_R1.ict, time bounds are, Min: <xarray.DataArray 'time' ()>\n",
+      "array('2019-09-05T17:36:25.000000000', dtype='datetime64[ns]'), Max: <xarray.DataArray 'time' ()>\n",
+      "array('2019-09-05T23:10:45.000000000', dtype='datetime64[ns]')\n"
+     ]
+    }
+   ],
+   "source": [
+    "from melodies_monet.util.tools import find_obs_time_bounds\n",
+    "\n",
+    "#files = '/wrk/users/charkins/melodies-monet_data/airnow/AIRNOW_20190901_20190930.nc'\n",
+    "#files = '/wrk/charkins/melodies_monet/aircraft/add_csv_read/SABRE-Merge_20230305_20230306_1719.csv'\n",
+    "#files = '/wrk/charkins/melodies_monet/aircraft/add_csv_read/firexaq-mrg10-dc8_merge_20190905_R1.csv'\n",
+    "#files = ['/wrk/d2/rschwantes/obs/firex-aq/R1/10s_merge/firexaq-mrg10-dc8_merge_20190722_R1.ict']\n",
+    "files = ['/wrk/d2/rschwantes/obs/firex-aq/R1/10s_merge/firexaq-mrg10-dc8_merge_20190722_R1.ict','/wrk/d2/rschwantes/obs/firex-aq/R1/10s_merge/firexaq-mrg10-dc8_merge_20190905_R1.ict']\n",
+    "\n",
+    "bounds = find_obs_time_bounds(files=files)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "ae2f74e2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'/wrk/d2/rschwantes/obs/firex-aq/R1/10s_merge/firexaq-mrg10-dc8_merge_20190722_R1.ict': {'Min': <xarray.DataArray 'time' ()>\n",
+       "  array('2019-07-22T18:16:35.000000000', dtype='datetime64[ns]'),\n",
+       "  'Max': <xarray.DataArray 'time' ()>\n",
+       "  array('2019-07-23T01:07:55.000000000', dtype='datetime64[ns]')},\n",
+       " '/wrk/d2/rschwantes/obs/firex-aq/R1/10s_merge/firexaq-mrg10-dc8_merge_20190905_R1.ict': {'Min': <xarray.DataArray 'time' ()>\n",
+       "  array('2019-09-05T17:36:25.000000000', dtype='datetime64[ns]'),\n",
+       "  'Max': <xarray.DataArray 'time' ()>\n",
+       "  array('2019-09-05T23:10:45.000000000', dtype='datetime64[ns]')}}"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "bounds"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e5277261",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "491e21a1",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3cbc4900",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b0fe3ce6",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "81bf1c7f",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ff002563",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1d343040",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "06ff16fd",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "fc2aea7d",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3d14cafa",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "403f9e53",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1e840bba",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a7bd6c77",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "693ea701",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ec3e42cd",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4da3f10c",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f17280bb",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "49c4065e",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5903640f",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7d587f4e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1e2160b0",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e59c79df",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ec499981",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "553f501b",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7d114d0e",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5836c6d4",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "54c41ab2",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "98bf1187",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1f1a4f05",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "17a5eb19",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e678ce81",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7a11236c",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "da3753bc",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "47c84dd0",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "555b7b73",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "63b0e14c-e39e-468a-8305-b08c0dcd2308",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.18"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/examples/jupyter_notebooks/Monet-example_aircraft_pairing_loop_read.ipynb b/examples/jupyter_notebooks/Monet-example_aircraft_pairing_loop_read.ipynb
new file mode 100644
index 00000000..afd5c349
--- /dev/null
+++ b/examples/jupyter_notebooks/Monet-example_aircraft_pairing_loop_read.ipynb
@@ -0,0 +1,249 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "48080cc2-be7e-4fa2-b34d-329041fccdd7",
+   "metadata": {},
+   "source": [
+    "## Reading files saved out from looping aircraft code"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "d7240c01-7c05-49e7-bfca-01e23dc6bed6",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/charkins/miniconda3/envs/melodies-monet_aircraft/lib/python3.9/site-packages/dask/dataframe/_pyarrow_compat.py:17: FutureWarning: Minimal version of pyarrow will soon be increased to 14.0.1. You are using 11.0.0. Please consider upgrading.\n",
+      "  warnings.warn(\n"
+     ]
+    }
+   ],
+   "source": [
+    "from melodies_monet import driver"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "cf1a865a-ead4-436a-8287-5bb8cbf4d3fe",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'analysis': {'start_time': '2019-07-22-00:00:00',\n",
+       "  'end_time': '2019-09-05-23:59:00',\n",
+       "  'output_dir': '/wrk/charkins/melodies_monet/aircraft/develop_aircraft_looping/output',\n",
+       "  'debug': True,\n",
+       "  'read': {'paired': {'method': 'netcdf',\n",
+       "    'filenames': {'firexaq_wrfchem_v4.2': ['/wrk/charkins/melodies_monet/aircraft/develop_aircraft_looping/output/0722_firexaq_wrfchem_v4.2.nc4',\n",
+       "      '/wrk/charkins/melodies_monet/aircraft/develop_aircraft_looping/output/0905_firexaq_wrfchem_v4.2.nc4']}}}},\n",
+       " 'model': {'wrfchem_v4.2': {'files': '/wrk/charkins/melodies_monet/aircraft/develop_aircraft_looping/all_days_model/*',\n",
+       "   'mod_type': 'wrfchem',\n",
+       "   'mod_kwargs': {'mech': 'racm_esrl_vcp'},\n",
+       "   'radius_of_influence': 12000,\n",
+       "   'mapping': {'firexaq': {'no2': 'NO2_CL_RYERSON',\n",
+       "     'no': 'NO_CL_RYERSON',\n",
+       "     'o3': 'O3_CL_RYERSON'}},\n",
+       "   'variables': {'pres_pa_mid': {'rename': 'pressure_model',\n",
+       "     'unit_scale': 1,\n",
+       "     'unit_scale_method': '*'},\n",
+       "    'temperature_k': {'rename': 'temp_model',\n",
+       "     'unit_scale': 1,\n",
+       "     'unit_scale_method': '*'}},\n",
+       "   'projection': None,\n",
+       "   'plot_kwargs': {'color': 'dodgerblue', 'marker': '^', 'linestyle': ':'}}},\n",
+       " 'obs': {'firexaq': {'filename': '/wrk/d2/rschwantes/obs/firex-aq/R1/10s_merge/firexaq-mrg10-dc8_merge_20190905_R1.ict',\n",
+       "   'obs_type': 'aircraft',\n",
+       "   'resample': '600S',\n",
+       "   'variables': {'O3_CL_RYERSON': {'unit_scale': 1,\n",
+       "     'unit_scale_method': '*',\n",
+       "     'nan_value': -777777,\n",
+       "     'LLOD_value': -888888,\n",
+       "     'LLOD_setvalue': 0.0},\n",
+       "    'NO_CL_RYERSON': {'nan_value': -777777,\n",
+       "     'LLOD_value': -888888,\n",
+       "     'LLOD_setvalue': 0.0},\n",
+       "    'NO2_CL_RYERSON': {'nan_value': -777777,\n",
+       "     'LLOD_value': -888888,\n",
+       "     'LLOD_setvalue': 0.0},\n",
+       "    'Latitude_YANG': {'rename': 'latitude',\n",
+       "     'unit_scale': 1,\n",
+       "     'unit_scale_method': '*'},\n",
+       "    'Longitude_YANG': {'rename': 'longitude',\n",
+       "     'unit_scale': 1,\n",
+       "     'unit_scale_method': '*'},\n",
+       "    'P_BUI': {'rename': 'pressure_obs',\n",
+       "     'unit_scale': 100,\n",
+       "     'unit_scale_method': '*'},\n",
+       "    'MSL_GPS_Altitude_YANG': {'rename': 'altitude',\n",
+       "     'unit_scale': 1,\n",
+       "     'unit_scale_method': '*'}}}},\n",
+       " 'plots': {'plot_grp1': {'type': 'timeseries',\n",
+       "   'fig_kwargs': {'figsize': [12, 6]},\n",
+       "   'default_plot_kwargs': {'linewidth': 2.0, 'markersize': 10.0},\n",
+       "   'text_kwargs': {'fontsize': 18.0},\n",
+       "   'domain_type': ['all'],\n",
+       "   'domain_name': ['CONUS'],\n",
+       "   'data': ['firexaq_wrfchem_v4.2'],\n",
+       "   'data_proc': {'rem_obs_nan': True,\n",
+       "    'ts_select_time': 'time',\n",
+       "    'ts_avg_window': None,\n",
+       "    'set_axis': False,\n",
+       "    'altitude_yax2': {'altitude_variable': 'altitude',\n",
+       "     'altitude_ticks': 1000,\n",
+       "     'ylabel2': 'Altitude (m)',\n",
+       "     'plot_kwargs_y2': {'color': 'g'},\n",
+       "     'altitude_unit': 'm',\n",
+       "     'altitude_scaling_factor': 1}}}}}"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "control_fn='../yaml/control_read_looped_aircraft.yaml'\n",
+    "an = driver.analysis()\n",
+    "an.control=control_fn\n",
+    "an.read_control() \n",
+    "an.control_dict  "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "70b89dc7-5d11-47b6-b53f-ef1a05b2bf59",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "wrfchem\n",
+      "/wrk/charkins/melodies_monet/aircraft/develop_aircraft_looping/all_days_model/*\n",
+      "**** Reading WRF-Chem model output...\n"
+     ]
+    }
+   ],
+   "source": [
+    "an.open_models()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "7f9d4211-42a7-4cd4-9daa-f0724c6d00e1",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/charkins/miniconda3/envs/melodies-monet_aircraft/lib/python3.9/site-packages/xarray/core/groupby.py:534: FutureWarning: 'S' is deprecated and will be removed in a future version, please use 's' instead.\n",
+      "  index_grouper = pd.Grouper(\n"
+     ]
+    }
+   ],
+   "source": [
+    "an.open_obs()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "40aad2ca-fafb-44a4-a101-cc88a0dd2a2c",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Reading: /wrk/charkins/melodies_monet/aircraft/develop_aircraft_looping/output/0722_firexaq_wrfchem_v4.2.nc4\n",
+      "Reading: /wrk/charkins/melodies_monet/aircraft/develop_aircraft_looping/output/0905_firexaq_wrfchem_v4.2.nc4\n"
+     ]
+    }
+   ],
+   "source": [
+    "an.read_analysis()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "686bb88c-adf3-4b87-980c-9e15f3a6cfe4",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1200x600 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1200x600 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1200x600 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#And this generates all the plots.\n",
+    "an.plotting()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0cb5d8e3-2cd9-4dd4-afa4-349f2b9c3e6b",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.18"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/examples/submit_jobs/run_aircraft_pairing_loop.py b/examples/submit_jobs/run_aircraft_pairing_loop.py
new file mode 100644
index 00000000..6600ea8f
--- /dev/null
+++ b/examples/submit_jobs/run_aircraft_pairing_loop.py
@@ -0,0 +1,25 @@
+# This code uses MELODIES-MONET to read in a .yaml file 
+# and produces sets of paired aircraft observations. 
+# For an interactive script see jupyter notebooks in main directory.
+
+from melodies_monet import driver
+from melodies_monet.util.tools import loop_pairing
+import os
+import dask
+an = driver.analysis()
+# -- Update the yaml file below
+control_fn = '../yaml/control_aircraft_looping.yaml'
+file_pairs_yaml='../yaml/supplementary_yaml/aircraft_looping_file_pairs.yaml'
+an.control = control_fn
+an.read_control()
+
+# -- Lines below make a copy of the namelist in the plot directory for reference later
+cmd = 'cp ' + an.control + ' ' + an.control_dict['analysis']['output_dir']
+os.system(cmd)
+
+cmd = 'cp ' + file_pairs_yaml + ' ' + an.control_dict['analysis']['output_dir']
+os.system(cmd)
+
+dask.config.set(**{'array.slicing.split_large_chunks': True})
+loop_pairing(control=control_fn,file_pairs_yaml=file_pairs_yaml)
+
diff --git a/examples/yaml/control_aircraft_looping.yaml b/examples/yaml/control_aircraft_looping.yaml
new file mode 100755
index 00000000..dce85d1a
--- /dev/null
+++ b/examples/yaml/control_aircraft_looping.yaml
@@ -0,0 +1,88 @@
+# General Description:  
+# Any key that is specific for a plot type will begin with ts for timeseries, ty for taylor
+# Opt: Specifying the variable or variable group is optional
+# For now all plots except time series average over the analysis window. 
+# Seting axis values - If set_axis = True in data_proc section of each plot_grp the yaxis for the plot will be set based on the values specified in the obs section for each variable. If set_axis is set to False, then defaults will be used. 'vmin_plot' and 'vmax_plot' are needed for 'timeseries', 'spatial_overlay', and 'boxplot'. 'vdiff_plot' is needed for 'spatial_bias' plots and'ty_scale' is needed for 'taylor' plots. 'nlevels' or the number of levels used in the contour plot can also optionally be provided for spatial_overlay plot. If set_axis = True and the proper limits are not provided in the obs section, a warning will print, and the plot will be created using the default limits.
+analysis:
+  #start_time: '2019-09-05-12:00:00' #UTC
+  #end_time: '2019-09-06-00:00:00' #UTC
+  output_dir:  /wrk/charkins/melodies_monet/aircraft/develop_aircraft_looping/output #/wrk/charkins/melodies_monet/aircraft/analysis #Opt if not specified plots stored in code directory.
+  debug: True
+  
+model:
+  wrfchem_v4.2: # model label
+    mod_type: 'wrfchem'
+    mod_kwargs: 
+      mech: 'racm_esrl_vcp'
+    radius_of_influence: 12000 #meters
+    mapping: #model species name : obs species name
+      firexaq:
+        no2: NO2_CL_RYERSON
+        'no': 'NO_CL_RYERSON'
+        #PM2_5_DRY: "PM2.5"
+        o3: "O3_CL_RYERSON"
+    variables:
+        'pres_pa_mid':
+            rename: pressure_model # name to convert this variable to, use 'pressure_model' for aircraft obs
+            unit_scale: 1 #Opt Scaling factor 
+            unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+        'temperature_k':
+            rename: temp_model # name to convert this variable to
+            unit_scale: 1 #Opt Scaling factor 
+            unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+    projection: null
+    #plot_kwargs: #Opt
+    #  color: 'dodgerblue'
+    #  marker: '^'
+    #  linestyle: ':' 
+obs:
+  firexaq: # obs label
+    obs_type: aircraft
+    resample: '600S' #'600S' #10 min so works on Hera as a test. Can comment this if submitting a job. 
+    variables: #Opt 
+      'O3_CL_RYERSON':
+        unit_scale: 1 #Opt Scaling factor 
+        unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+        nan_value: -777777 # Opt Set this value to NaN
+        LLOD_value: -888888 # Opt Set this value to LLOD_setvalue
+        LLOD_setvalue: 0.0 # Opt Set LLOD_value=LLOD_setvalue, applied AFTER unit_scale and obs_unit
+        #ylabel_plot: 'Ozone (ppbv)'
+        #vmin_plot: 15.0 #Opt Min for y-axis during plotting. To apply to a plot, change restrict_yaxis = True.
+        #vmax_plot: 55.0 #Opt Max for y-axis during plotting. To apply to a plot, change restrict_yaxis = True.
+        #vdiff_plot: 20.0 #Opt +/- range to use in bias plots. To apply to a plot, change restrict_yaxis = True.
+        # nlevels_plot: 21 #Opt number of levels used in colorbar for contourf plot.
+      'NO_CL_RYERSON':
+        nan_value: -777777 # Set this value to NaN
+        LLOD_value: -888888 # Opt Set this value to LLOD_setvalue
+        LLOD_setvalue: 0.0 # Opt Set LLOD_value=LLOD_setvalue, applied AFTER unit_scale and obs_unit
+        #ylabel_plot: 'NO (ppbv)' #Optional to set ylabel so can include units and/or instr etc.
+        #vmin_plot: 0.0 #Opt Min for y-axis during plotting. To apply to a plot, change restrict_yaxis = True.
+        #vmax_plot: 20.0 #Opt Max for y-axis during plotting. To apply to a plot, change restrict_yaxis = True.
+        #vdiff_plot: 15.0 #Opt +/- range to use in bias plots. To apply to a plot, change restrict_yaxis = True.
+        #nlevels_plot: 21 #Opt number of levels used in colorbar for contourf plot.
+      'NO2_CL_RYERSON':
+        nan_value: -777777 # Set this value to NaN
+        LLOD_value: -888888 # Opt Set this value to LLOD_setvalue
+        LLOD_setvalue: 0.0 # Opt Set LLOD_value=LLOD_setvalue, applied AFTER unit_scale and obs_unit
+        #ylabel_plot: 'NO2 (ppbv)' #Optional to set ylabel so can include units and/or instr etc.
+        #vmin_plot: 0.0 #Opt Min for y-axis during plotting. To apply to a plot, change restrict_yaxis = True.
+        #vmax_plot: 20.0 #Opt Max for y-axis during plotting. To apply to a plot, change restrict_yaxis = True.
+        #vdiff_plot: 15.0 #Opt +/- range to use in bias plots. To apply to a plot, change restrict_yaxis = True.
+        #nlevels_plot: 21 #Opt number of levels used in colorbar for contourf plot.
+      'Latitude_YANG':
+            rename: latitude # name to convert this variable to
+            unit_scale: 1 #Opt Scaling factor 
+            unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+      'Longitude_YANG':
+            rename: longitude # name to convert this variable to
+            unit_scale: 1 #Opt Scaling factor 
+            unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+      'P_BUI':
+            rename: pressure_obs # name to convert this variable to
+            unit_scale: 100 #Opt Scaling factor 
+            unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+      'MSL_GPS_Altitude_YANG':
+          rename: altitude # name to convert this variable to
+          unit_scale: 1 #Opt Scaling factor 
+          unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+   
diff --git a/examples/yaml/control_hrrr-smoke_mobile.yaml b/examples/yaml/control_hrrr-smoke_mobile.yaml
new file mode 100644
index 00000000..e8310d3e
--- /dev/null
+++ b/examples/yaml/control_hrrr-smoke_mobile.yaml
@@ -0,0 +1,109 @@
+# General Description:  
+# Any key that is specific for a plot type will begin with ts for timeseries, ty for taylor
+# Opt: Specifying the variable or variable group is optional
+# For now all plots except time series average over the analysis window. 
+# Seting axis values - If set_axis = True in data_proc section of each plot_grp the yaxis for the plot will be set based on the values specified in the obs section for each variable. If set_axis is set to False, then defaults will be used. 'vmin_plot' and 'vmax_plot' are needed for 'timeseries', 'spatial_overlay', and 'boxplot'. 'vdiff_plot' is needed for 'spatial_bias' plots and'ty_scale' is needed for 'taylor' plots. 'nlevels' or the number of levels used in the contour plot can also optionally be provided for spatial_overlay plot. If set_axis = True and the proper limits are not provided in the obs section, a warning will print, and the plot will be created using the default limits.
+analysis:
+  start_time: '2022-09-11-06:00:00' #UTC
+  end_time: '2022-09-12-06:00:00' #UTC
+  output_dir: /wrk/charkins/melodies_monet/aircraft/develop_aircraft_mobile/Output_hrrr-smoke #Opt if not specified plots stored in code directory.
+  debug: True
+model:
+  hrrr-smoke: # model label
+    files: /wrk/users/charkins/megan_mobile_data/HRRR/aqm_HRRR-Smoke_2022091106.nc.subset.nc
+    mod_type: random
+    mapping: #model species name : obs species name
+      mobile_fire:
+        PM2_5_DRY: 'PM2.5_5min'
+        'TMP_2maboveground': 'Temperature_5min'
+    plot_kwargs: #Opt
+      color: 'dodgerblue'
+      marker: '^'
+      linestyle: ':' 
+obs:
+  mobile_fire: # obs label
+    filename: '/wrk/users/charkins/megan_mobile_data/Fire_obs_all/treated_final_modtime.csv'
+    obs_type: mobile
+    resample: '600S' 
+    time_var: 'time_5min'
+    variables: #Opt 
+      'PM2.5_5min':
+        unit_scale: 1 #Opt Scaling factor 
+        unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+
+        ylabel_plot: 'PM2.5 (units?)'
+      'Temperature_5min':
+        unit_scale: 273.15 #Opt Scaling factor 
+        unit_scale_method: '+' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+        ylabel_plot: 'Temperature (K)' #Optional to set ylabel so can include units and/or instr etc.
+      'Latitude_5min':
+            rename: latitude # name to convert this variable to
+            unit_scale: 1 #Opt Scaling factor 
+            unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+      'Longitude_5min':
+            rename: longitude # name to convert this variable to
+            unit_scale: 1 #Opt Scaling factor 
+            unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+plots:
+  plot_grp1:
+    type: 'timeseries' # plot type
+    fig_kwargs: #Opt to define figure options
+      figsize: [12,6] # figure size if multiple plots
+    default_plot_kwargs: # Opt to define defaults for all plots. Model kwargs overwrite these.
+      linewidth: 2.0
+      markersize: 10.
+    text_kwargs: #Opt
+      fontsize: 18.
+    domain_type: ['all'] #List of domain types: 'all' or any domain in obs file. (e.g., airnow: epa_region, state_name, siteid, etc.) 
+    domain_name: ['CONUS'] #List of domain names. If domain_type = all domain_name is used in plot title.
+    data: ['mobile_fire_hrrr-smoke'] # make this a list of pairs in obs_model where the obs is the obs label and model is the model_label
+    data_proc:
+      rem_obs_nan: True # True: Remove all points where model or obs variable is NaN. False: Remove only points where model variable is NaN.
+      ts_select_time: 'time' #Time used for avg and plotting: Options: 'time' for UTC or 'time_local'
+      ts_avg_window: null # Options: None for no averaging or list pandas resample rule (e.g., 'H', 'D')
+      set_axis: False #If select True, add vmin_plot and vmax_plot for each variable in obs.
+  plot_grp2:
+    type: 'taylor' # plot type
+    fig_kwargs: #Opt to define figure options
+      figsize: [8,8] # figure size if multiple plots
+    default_plot_kwargs: # Opt to define defaults for all plots. Model kwargs overwrite these.
+      linewidth: 2.0
+      markersize: 10.
+    text_kwargs: #Opt
+      fontsize: 16.
+    domain_type: ['all'] #List of domain types: 'all' or any domain in obs file. (e.g., airnow: epa_region, state_name, siteid, etc.) 
+    domain_name: ['CONUS'] #List of domain names. If domain_type = all domain_name is used in plot title.
+    data: ['mobile_fire_hrrr-smoke'] # make this a list of pairs in obs_model where the obs is the obs label and model is the model_label
+    data_proc:
+      rem_obs_nan: True # True: Remove all points where model or obs variable is NaN. False: Remove only points where model variable is NaN.
+      set_axis: True #If select True, add ty_scale for each variable in obs.
+  plot_grp3:
+    type: 'boxplot' # plot type
+    fig_kwargs: #Opt to define figure options
+      figsize: [8, 6] # figure size 
+    text_kwargs: #Opt
+      fontsize: 20.
+    domain_type: ['all'] #List of domain types: 'all' or any domain in obs file. (e.g., airnow: epa_region, state_name, siteid, etc.) 
+    domain_name: ['CONUS'] #List of domain names. If domain_type = all domain_name is used in plot title.
+    data: ['mobile_fire_hrrr-smoke'] # make this a list of pairs in obs_model where the obs is the obs label and model is the model_label
+    data_proc:
+      rem_obs_nan: True # True: Remove all points where model or obs variable is NaN. False: Remove only points where model variable is NaN.
+      set_axis: False #If select True, add vmin_plot and vmax_plot for each variable in obs.
+
+stats:
+  #Stats require positive numbers, so if you want to calculate temperature use Kelvin!
+  #Wind direction has special calculations for AirNow if obs name is 'WD'
+  stat_list: ['MB', 'MdnB','R2', 'RMSE'] #List stats to calculate. Dictionary of definitions included in plots/proc_stats.py Only stats listed below are currently working.
+  #Full calc list ['STDO', 'STDP', 'MdnNB','MdnNE','NMdnGE', 'NO','NOP','NP','MO','MP', 'MdnO', 'MdnP', 'RM', 'RMdn', 'MB', 'MdnB', 'NMB', 'NMdnB', 'FB', 'ME','MdnE','NME', 'NMdnE', 'FE', 'R2', 'RMSE','d1','E1', 'IOA', 'AC']
+  round_output: 2 #Opt, defaults to rounding to 3rd decimal place.
+  output_table: False #Always outputs a .txt file. Optional to also output as a table.
+  output_table_kwargs: #Opt 
+    figsize: [7, 3] # figure size 
+    fontsize: 12.
+    xscale: 1.4
+    yscale: 1.4
+    edges: 'horizontal'
+  domain_type: ['all'] #List of domain types: 'all' or any domain in obs file. (e.g., airnow: epa_region, state_name, siteid, etc.) 
+  domain_name: ['CONUS'] #List of domain names. If domain_type = all domain_name is used in plot title.
+  data: ['mobile_fire_hrrr-smoke'] # make this a list of pairs in obs_model where the obs is the obs label and model is the model_label
+  
diff --git a/examples/yaml/control_read_looped_aircraft.yaml b/examples/yaml/control_read_looped_aircraft.yaml
new file mode 100644
index 00000000..9c4fe41e
--- /dev/null
+++ b/examples/yaml/control_read_looped_aircraft.yaml
@@ -0,0 +1,136 @@
+# General Description:  
+# Any key that is specific for a plot type will begin with ts for timeseries, ty for taylor
+# Opt: Specifying the variable or variable group is optional
+# For now all plots except time series average over the analysis window. 
+# Seting axis values - If set_axis = True in data_proc section of each plot_grp the yaxis for the plot will be set based on the values specified in the obs section for each variable. If set_axis is set to False, then defaults will be used. 'vmin_plot' and 'vmax_plot' are needed for 'timeseries', 'spatial_overlay', and 'boxplot'. 'vdiff_plot' is needed for 'spatial_bias' plots and'ty_scale' is needed for 'taylor' plots. 'nlevels' or the number of levels used in the contour plot can also optionally be provided for spatial_overlay plot. If set_axis = True and the proper limits are not provided in the obs section, a warning will print, and the plot will be created using the default limits.
+analysis:
+  start_time: '2019-07-22-00:00:00' #UTC
+  end_time: '2019-09-05-23:59:00' #UTC
+  output_dir: /wrk/charkins/melodies_monet/aircraft/develop_aircraft_looping/output # relative to the program using this control file
+  debug: True
+  read:
+      paired:
+          method: 'netcdf' # 'netcdf' or 'pkl'
+          filenames: {'firexaq_wrfchem_v4.2':['/wrk/charkins/melodies_monet/aircraft/develop_aircraft_looping/output/0722_firexaq_wrfchem_v4.2.nc4',
+          '/wrk/charkins/melodies_monet/aircraft/develop_aircraft_looping/output/0905_firexaq_wrfchem_v4.2.nc4']} # example for netcdf method. Uses dict of form {group1: str or iterable of filenames, group2:...}  Any wildcards will be expanded
+          # filenames: {'airnow_wrfchem_v4.2':['0904_airnow_wrfchem_v4.2.nc4','0905_airnow_wrfchem_v4.2.nc4']} # example for netcdf method. Uses dict of form {group1: str or iterable of filenames, group2:...}
+          # filenames: ['0904.pkl','0905.pkl'] # example for pkl method, uses str or iterable of filenames
+      # models:
+      # obs:
+model:
+  wrfchem_v4.2: # model label
+    # files: /wrk/d2/rschwantes/wrf/firex_mech/qzhu/run_CONUS_fv19_BEIS_1.0xISO_RACM_v4.2.2_racm_berk_vcp_noI_phot_soa/0905/*
+    #files: /wrk/qrasool/firex_mech_qzhu/run_CONUS_fv19_BEIS_1.0xISO_RACM_v4.2.2_racm_berk_vcp_noI_phot_soa/0905/* #/wrk/d2/rschwantes/wrf/firex_mech/qzhu/run_CONUS_fv19_BEIS_1.0xISO_RACM_v4.2.2_racm_berk_vcp_noI_phot_soa/0905/*
+    files: '/wrk/charkins/melodies_monet/aircraft/develop_aircraft_looping/all_days_model/*'
+    mod_type: 'wrfchem'
+    mod_kwargs: 
+      mech: 'racm_esrl_vcp'
+    radius_of_influence: 12000 #meters
+    mapping: #model species name : obs species name
+      firexaq:
+        no2: NO2_CL_RYERSON
+        'no': 'NO_CL_RYERSON'
+        #PM2_5_DRY: "PM2.5"
+        o3: "O3_CL_RYERSON"
+    variables:
+        'pres_pa_mid':
+            rename: pressure_model # name to convert this variable to, use 'pressure_model' for aircraft obs
+            unit_scale: 1 #Opt Scaling factor 
+            unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+        'temperature_k':
+            rename: temp_model # name to convert this variable to
+            unit_scale: 1 #Opt Scaling factor 
+            unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+    projection: null
+    plot_kwargs: #Opt
+      color: 'dodgerblue'
+      marker: '^'
+      linestyle: ':' 
+obs:
+  firexaq: # obs label
+    filename: '/wrk/d2/rschwantes/obs/firex-aq/R1/10s_merge/firexaq-mrg10-dc8_merge_20190905_R1.ict'
+    obs_type: aircraft
+    resample: '600S' #'600S' #10 min so works on Hera as a test. Can comment this if submitting a job. 
+    variables: #Opt 
+      'O3_CL_RYERSON':
+        unit_scale: 1 #Opt Scaling factor 
+        unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+        nan_value: -777777 # Opt Set this value to NaN
+        LLOD_value: -888888 # Opt Set this value to LLOD_setvalue
+        LLOD_setvalue: 0.0 # Opt Set LLOD_value=LLOD_setvalue, applied AFTER unit_scale and obs_unit
+        #ylabel_plot: 'Ozone (ppbv)'
+        #vmin_plot: 15.0 #Opt Min for y-axis during plotting. To apply to a plot, change restrict_yaxis = True.
+        #vmax_plot: 55.0 #Opt Max for y-axis during plotting. To apply to a plot, change restrict_yaxis = True.
+        #vdiff_plot: 20.0 #Opt +/- range to use in bias plots. To apply to a plot, change restrict_yaxis = True.
+        # nlevels_plot: 21 #Opt number of levels used in colorbar for contourf plot.
+      'NO_CL_RYERSON':
+        nan_value: -777777 # Set this value to NaN
+        LLOD_value: -888888 # Opt Set this value to LLOD_setvalue
+        LLOD_setvalue: 0.0 # Opt Set LLOD_value=LLOD_setvalue, applied AFTER unit_scale and obs_unit
+        #ylabel_plot: 'NO (ppbv)' #Optional to set ylabel so can include units and/or instr etc.
+        #vmin_plot: 0.0 #Opt Min for y-axis during plotting. To apply to a plot, change restrict_yaxis = True.
+        #vmax_plot: 20.0 #Opt Max for y-axis during plotting. To apply to a plot, change restrict_yaxis = True.
+        #vdiff_plot: 15.0 #Opt +/- range to use in bias plots. To apply to a plot, change restrict_yaxis = True.
+        #nlevels_plot: 21 #Opt number of levels used in colorbar for contourf plot.
+      'NO2_CL_RYERSON':
+        nan_value: -777777 # Set this value to NaN
+        LLOD_value: -888888 # Opt Set this value to LLOD_setvalue
+        LLOD_setvalue: 0.0 # Opt Set LLOD_value=LLOD_setvalue, applied AFTER unit_scale and obs_unit
+        #ylabel_plot: 'NO2 (ppbv)' #Optional to set ylabel so can include units and/or instr etc.
+        #vmin_plot: 0.0 #Opt Min for y-axis during plotting. To apply to a plot, change restrict_yaxis = True.
+        #vmax_plot: 20.0 #Opt Max for y-axis during plotting. To apply to a plot, change restrict_yaxis = True.
+        #vdiff_plot: 15.0 #Opt +/- range to use in bias plots. To apply to a plot, change restrict_yaxis = True.
+        #nlevels_plot: 21 #Opt number of levels used in colorbar for contourf plot.
+      'Latitude_YANG':
+            rename: latitude # name to convert this variable to
+            unit_scale: 1 #Opt Scaling factor 
+            unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+      'Longitude_YANG':
+            rename: longitude # name to convert this variable to
+            unit_scale: 1 #Opt Scaling factor 
+            unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+      'P_BUI':
+            rename: pressure_obs # name to convert this variable to
+            unit_scale: 100 #Opt Scaling factor 
+            unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+      'MSL_GPS_Altitude_YANG':
+          rename: altitude # name to convert this variable to
+          unit_scale: 1 #Opt Scaling factor 
+          unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+
+plots:
+  plot_grp1:
+    type: 'timeseries' # plot type
+    fig_kwargs: #Opt to define figure options
+      figsize: [12,6] # figure size if multiple plots
+    default_plot_kwargs: # Opt to define defaults for all plots. Model kwargs overwrite these.
+      linewidth: 2.0
+      markersize: 10.
+    text_kwargs: #Opt
+      fontsize: 18.
+    domain_type: ['all'] #List of domain types: 'all' or any domain in obs file. (e.g., airnow: epa_region, state_name, siteid, etc.) 
+    domain_name: ['CONUS'] #List of domain names. If domain_type = all domain_name is used in plot title.
+    data: ['firexaq_wrfchem_v4.2'] # make this a list of pairs in obs_model where the obs is the obs label and model is the model_label
+    data_proc:
+      #See 'altitde_yax2' list below for secondary y-axis options
+      #altitude_variable: altitude  
+      #altitude_ticks: 1000  # Altitude tick interval in meters (for secondary y-axis for altitude (m))
+      rem_obs_nan: True # True: Remove all points where model or obs variable is NaN. False: Remove only points where model variable is NaN.
+      ts_select_time: 'time' #Time used for avg and plotting: Options: 'time' for UTC or 'time_local'
+      ts_avg_window: #'H' # pandas resample rule (e.g., 'H', 'D'). No averaging is done if ts_avg_window is null or not specified.
+      set_axis: False #If select True, add vmin_plot and vmax_plot for each variable in obs.
+      #vmin2, vmax2 filter not needed as filter_dict option added in 'altitude_yax2' to subset the paireddf as per altitude secondary-axis limits
+      #vmin2: #0  #Optional
+      #vmax2: #5000 #12000 #Optional #Subset limits for secondary y-axis (altitude_variable) 
+      altitude_yax2:
+        altitude_variable: altitude
+        altitude_ticks: 1000
+        ylabel2: Altitude (m)
+        plot_kwargs_y2:
+          color: g
+        altitude_unit: m
+        altitude_scaling_factor: 1
+        #filter_dict: #Default is min and max if filter_dict doesn't define the options below (or if they are commented out)
+        #  altitude:
+        #    oper: "between"
+        #    value: [2000,8000] # values are [vmin_y2, vmax_y2] 
\ No newline at end of file
diff --git a/examples/yaml/control_wrfchem_aircraft.yaml b/examples/yaml/control_wrfchem_aircraft.yaml
new file mode 100644
index 00000000..569070c0
--- /dev/null
+++ b/examples/yaml/control_wrfchem_aircraft.yaml
@@ -0,0 +1,147 @@
+# General Description:  
+# Any key that is specific for a plot type will begin with ts for timeseries, ty for taylor
+# Opt: Specifying the variable or variable group is optional
+# For now all plots except time series average over the analysis window. 
+# Seting axis values - If set_axis = True in data_proc section of each plot_grp the yaxis for the plot will be set based on the values specified in the obs section for each variable. If set_axis is set to False, then defaults will be used. 'vmin_plot' and 'vmax_plot' are needed for 'timeseries', 'spatial_overlay', and 'boxplot'. 'vdiff_plot' is needed for 'spatial_bias' plots and'ty_scale' is needed for 'taylor' plots. 'nlevels' or the number of levels used in the contour plot can also optionally be provided for spatial_overlay plot. If set_axis = True and the proper limits are not provided in the obs section, a warning will print, and the plot will be created using the default limits.
+analysis:
+  start_time: '2019-09-05-12:00:00' #UTC
+  end_time: '2019-09-06-00:00:00' #UTC
+  output_dir: /wrk/charkins/melodies_monet/aircraft/analysis #Opt if not specified plots stored in code directory.
+  debug: True
+model:
+  wrfchem_v4.2: # model label
+    # files: /wrk/d2/rschwantes/wrf/firex_mech/qzhu/run_CONUS_fv19_BEIS_1.0xISO_RACM_v4.2.2_racm_berk_vcp_noI_phot_soa/0905/*
+    files: /wrk/d2/rschwantes/wrf/firex_mech/qzhu/run_CONUS_fv19_BEIS_1.0xISO_RACM_v4.2.2_racm_berk_vcp_noI_phot_soa/0905/*
+    mod_type: 'wrfchem'
+    mod_kwargs: 
+      mech: 'racm_esrl_vcp'
+    radius_of_influence: 12000 #meters
+    mapping: #model species name : obs species name
+      firexaq:
+        no2: NO2_CL_RYERSON
+        'no': 'NO_CL_RYERSON'
+        #PM2_5_DRY: "PM2.5"
+        o3: "O3_CL_RYERSON"
+    variables:
+        'pres_pa_mid':
+            rename: pressure_model # name to convert this variable to, use 'pressure_model' for aircraft obs
+            unit_scale: 1 #Opt Scaling factor 
+            unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+        'temperature_k':
+            rename: temp_model # name to convert this variable to
+            unit_scale: 1 #Opt Scaling factor 
+            unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+    projection: None
+    plot_kwargs: #Opt
+      color: 'dodgerblue'
+      marker: '^'
+      linestyle: ':' 
+obs:
+  firexaq: # obs label
+    filename: '/wrk/d2/rschwantes/obs/firex-aq/R1/10s_merge/firexaq-mrg10-dc8_merge_20190905_R1.ict'
+    obs_type: aircraft
+    resample: '600S' #10 min so works on Hera as a test. Can comment this if submitting a job. 
+    variables: #Opt 
+      'O3_CL_RYERSON':
+        unit_scale: 1 #Opt Scaling factor 
+        unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+        nan_value: -777777 # Opt Set this value to NaN
+        LLOD_value: -888888 # Opt Set this value to LLOD_setvalue
+        LLOD_setvalue: 0.0 # Opt Set LLOD_value=LLOD_setvalue, applied AFTER unit_scale and obs_unit
+        ylabel_plot: 'Ozone (ppbv)'
+        vmin_plot: 15.0 #Opt Min for y-axis during plotting. To apply to a plot, change restrict_yaxis = True.
+        vmax_plot: 55.0 #Opt Max for y-axis during plotting. To apply to a plot, change restrict_yaxis = True.
+        vdiff_plot: 20.0 #Opt +/- range to use in bias plots. To apply to a plot, change restrict_yaxis = True.
+        # nlevels_plot: 21 #Opt number of levels used in colorbar for contourf plot.
+      'NO_CL_RYERSON':
+        nan_value: -777777 # Set this value to NaN
+        LLOD_value: -888888 # Opt Set this value to LLOD_setvalue
+        LLOD_setvalue: 0.0 # Opt Set LLOD_value=LLOD_setvalue, applied AFTER unit_scale and obs_unit
+        ylabel_plot: 'NO (ppbv)' #Optional to set ylabel so can include units and/or instr etc.
+        vmin_plot: 0.0 #Opt Min for y-axis during plotting. To apply to a plot, change restrict_yaxis = True.
+        vmax_plot: 20.0 #Opt Max for y-axis during plotting. To apply to a plot, change restrict_yaxis = True.
+        vdiff_plot: 15.0 #Opt +/- range to use in bias plots. To apply to a plot, change restrict_yaxis = True.
+        nlevels_plot: 21 #Opt number of levels used in colorbar for contourf plot.
+      'NO2_CL_RYERSON':
+        nan_value: -777777 # Set this value to NaN
+        LLOD_value: -888888 # Opt Set this value to LLOD_setvalue
+        LLOD_setvalue: 0.0 # Opt Set LLOD_value=LLOD_setvalue, applied AFTER unit_scale and obs_unit
+        ylabel_plot: 'NO2 (ppbv)' #Optional to set ylabel so can include units and/or instr etc.
+        vmin_plot: 0.0 #Opt Min for y-axis during plotting. To apply to a plot, change restrict_yaxis = True.
+        vmax_plot: 20.0 #Opt Max for y-axis during plotting. To apply to a plot, change restrict_yaxis = True.
+        vdiff_plot: 15.0 #Opt +/- range to use in bias plots. To apply to a plot, change restrict_yaxis = True.
+        nlevels_plot: 21 #Opt number of levels used in colorbar for contourf plot.
+      'Latitude_YANG':
+            rename: latitude # name to convert this variable to
+            unit_scale: 1 #Opt Scaling factor 
+            unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+      'Longitude_YANG':
+            rename: longitude # name to convert this variable to
+            unit_scale: 1 #Opt Scaling factor 
+            unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+      'P_BUI':
+            rename: pressure_obs # name to convert this variable to
+            unit_scale: 100 #Opt Scaling factor 
+            unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+plots:
+  plot_grp1:
+    type: 'timeseries' # plot type
+    fig_kwargs: #Opt to define figure options
+      figsize: [12,6] # figure size if multiple plots
+    default_plot_kwargs: # Opt to define defaults for all plots. Model kwargs overwrite these.
+      linewidth: 2.0
+      markersize: 10.
+    text_kwargs: #Opt
+      fontsize: 18.
+    domain_type: ['all'] #List of domain types: 'all' or any domain in obs file. (e.g., airnow: epa_region, state_name, siteid, etc.) 
+    domain_name: ['CONUS'] #List of domain names. If domain_type = all domain_name is used in plot title.
+    data: ['firexaq_wrfchem_v4.2'] # make this a list of pairs in obs_model where the obs is the obs label and model is the model_label
+    data_proc:
+      rem_obs_nan: True # True: Remove all points where model or obs variable is NaN. False: Remove only points where model variable is NaN.
+      ts_select_time: 'time' #Time used for avg and plotting: Options: 'time' for UTC or 'time_local'
+      ts_avg_window: 'H' # Options: None for no averaging or list pandas resample rule (e.g., 'H', 'D')
+      set_axis: False #If select True, add vmin_plot and vmax_plot for each variable in obs.
+  plot_grp2:
+    type: 'taylor' # plot type
+    fig_kwargs: #Opt to define figure options
+      figsize: [8,8] # figure size if multiple plots
+    default_plot_kwargs: # Opt to define defaults for all plots. Model kwargs overwrite these.
+      linewidth: 2.0
+      markersize: 10.
+    text_kwargs: #Opt
+      fontsize: 16.
+    domain_type: ['all'] #List of domain types: 'all' or any domain in obs file. (e.g., airnow: epa_region, state_name, siteid, etc.) 
+    domain_name: ['CONUS'] #List of domain names. If domain_type = all domain_name is used in plot title.
+    data: ['firexaq_wrfchem_v4.2'] # make this a list of pairs in obs_model where the obs is the obs label and model is the model_label
+    data_proc:
+      rem_obs_nan: True # True: Remove all points where model or obs variable is NaN. False: Remove only points where model variable is NaN.
+      set_axis: True #If select True, add ty_scale for each variable in obs.
+  plot_grp3:
+    type: 'boxplot' # plot type
+    fig_kwargs: #Opt to define figure options
+      figsize: [8, 6] # figure size 
+    text_kwargs: #Opt
+      fontsize: 20.
+    domain_type: ['all'] #List of domain types: 'all' or any domain in obs file. (e.g., airnow: epa_region, state_name, siteid, etc.) 
+    domain_name: ['CONUS'] #List of domain names. If domain_type = all domain_name is used in plot title.
+    data: ['firexaq_wrfchem_v4.2'] # make this a list of pairs in obs_model where the obs is the obs label and model is the model_label
+    data_proc:
+      rem_obs_nan: True # True: Remove all points where model or obs variable is NaN. False: Remove only points where model variable is NaN.
+      set_axis: False #If select True, add vmin_plot and vmax_plot for each variable in obs.
+stats:
+  #Stats require positive numbers, so if you want to calculate temperature use Kelvin!
+  #Wind direction has special calculations for AirNow if obs name is 'WD'
+  stat_list: ['MB', 'MdnB','R2', 'RMSE'] #List stats to calculate. Dictionary of definitions included in plots/proc_stats.py Only stats listed below are currently working.
+  #Full calc list ['STDO', 'STDP', 'MdnNB','MdnNE','NMdnGE', 'NO','NOP','NP','MO','MP', 'MdnO', 'MdnP', 'RM', 'RMdn', 'MB', 'MdnB', 'NMB', 'NMdnB', 'FB', 'ME','MdnE','NME', 'NMdnE', 'FE', 'R2', 'RMSE','d1','E1', 'IOA', 'AC']
+  round_output: 2 #Opt, defaults to rounding to 3rd decimal place.
+  output_table: False #Always outputs a .txt file. Optional to also output as a table.
+  output_table_kwargs: #Opt 
+    figsize: [7, 3] # figure size 
+    fontsize: 12.
+    xscale: 1.4
+    yscale: 1.4
+    edges: 'horizontal'
+  domain_type: ['all'] #List of domain types: 'all' or any domain in obs file. (e.g., airnow: epa_region, state_name, siteid, etc.) 
+  domain_name: ['CONUS'] #List of domain names. If domain_type = all domain_name is used in plot title.
+  data: ['firexaq_wrfchem_v4.2'] # make this a list of pairs in obs_model where the obs is the obs label and model is the model_label
+
diff --git a/examples/yaml/control_wrfchem_aircraft_Latestfor_develop_aircraft.yaml b/examples/yaml/control_wrfchem_aircraft_Latestfor_develop_aircraft.yaml
new file mode 100644
index 00000000..0c22109d
--- /dev/null
+++ b/examples/yaml/control_wrfchem_aircraft_Latestfor_develop_aircraft.yaml
@@ -0,0 +1,245 @@
+# General Description:  
+# Any key that is specific for a plot type will begin with ts for timeseries, ty for taylor
+# Opt: Specifying the variable or variable group is optional
+# For now all plots except time series average over the analysis window. 
+# Seting axis values - If set_axis = True in data_proc section of each plot_grp the yaxis for the plot will be set based on the values specified in the obs section for each variable. If set_axis is set to False, then defaults will be used. 'vmin_plot' and 'vmax_plot' are needed for 'timeseries', 'spatial_overlay', and 'boxplot'. 'vdiff_plot' is needed for 'spatial_bias' plots and'ty_scale' is needed for 'taylor' plots. 'nlevels' or the number of levels used in the contour plot can also optionally be provided for spatial_overlay plot. If set_axis = True and the proper limits are not provided in the obs section, a warning will print, and the plot will be created using the default limits.
+analysis:
+  start_time: '2019-09-05-12:00:00' #UTC
+  end_time: '2019-09-06-00:00:00' #UTC
+  output_dir: /wrk/qrasool/output_testaircraftrhs #/wrk/charkins/melodies_monet/aircraft/analysis #Opt if not specified plots stored in code directory.
+  debug: True
+model:
+  wrfchem_v4.2: # model label
+    # files: /wrk/d2/rschwantes/wrf/firex_mech/qzhu/run_CONUS_fv19_BEIS_1.0xISO_RACM_v4.2.2_racm_berk_vcp_noI_phot_soa/0905/*
+    files: /wrk/qrasool/firex_mech_qzhu/run_CONUS_fv19_BEIS_1.0xISO_RACM_v4.2.2_racm_berk_vcp_noI_phot_soa/0905/* #/wrk/d2/rschwantes/wrf/firex_mech/qzhu/run_CONUS_fv19_BEIS_1.0xISO_RACM_v4.2.2_racm_berk_vcp_noI_phot_soa/0905/*
+    mod_type: 'wrfchem'
+    mod_kwargs: 
+      mech: 'racm_esrl_vcp'
+    radius_of_influence: 12000 #meters
+    mapping: #model species name : obs species name
+      firexaq:
+        no2: NO2_CL_RYERSON
+        'no': 'NO_CL_RYERSON'
+        #PM2_5_DRY: "PM2.5"
+        o3: "O3_CL_RYERSON"
+    variables:
+        'pres_pa_mid':
+            rename: pressure_model # name to convert this variable to, use 'pressure_model' for aircraft obs
+            unit_scale: 1 #Opt Scaling factor 
+            unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+        'temperature_k':
+            rename: temp_model # name to convert this variable to
+            unit_scale: 1 #Opt Scaling factor 
+            unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+    projection: None
+    plot_kwargs: #Opt
+      color: 'dodgerblue'
+      marker: '^'
+      linestyle: ':' 
+obs:
+  firexaq: # obs label
+    filename: '/wrk/d2/rschwantes/obs/firex-aq/R1/10s_merge/firexaq-mrg10-dc8_merge_20190905_R1.ict'
+    obs_type: aircraft
+    #resample: '60S' #'600S' #10 min so works on Hera as a test. Can comment this if submitting a job. 
+    variables: #Opt 
+      'O3_CL_RYERSON':
+        unit_scale: 1 #Opt Scaling factor 
+        unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+        nan_value: -777777 # Opt Set this value to NaN
+        LLOD_value: -888888 # Opt Set this value to LLOD_setvalue
+        LLOD_setvalue: 0.0 # Opt Set LLOD_value=LLOD_setvalue, applied AFTER unit_scale and obs_unit
+        ylabel_plot: 'Ozone (ppbv)'
+        vmin_plot: 15.0 #Opt Min for y-axis during plotting. To apply to a plot, change restrict_yaxis = True.
+        vmax_plot: 55.0 #Opt Max for y-axis during plotting. To apply to a plot, change restrict_yaxis = True.
+        vdiff_plot: 20.0 #Opt +/- range to use in bias plots. To apply to a plot, change restrict_yaxis = True.
+        # nlevels_plot: 21 #Opt number of levels used in colorbar for contourf plot.
+      'NO_CL_RYERSON':
+        nan_value: -777777 # Set this value to NaN
+        LLOD_value: -888888 # Opt Set this value to LLOD_setvalue
+        LLOD_setvalue: 0.0 # Opt Set LLOD_value=LLOD_setvalue, applied AFTER unit_scale and obs_unit
+        ylabel_plot: 'NO (ppbv)' #Optional to set ylabel so can include units and/or instr etc.
+        vmin_plot: 0.0 #Opt Min for y-axis during plotting. To apply to a plot, change restrict_yaxis = True.
+        vmax_plot: 20.0 #Opt Max for y-axis during plotting. To apply to a plot, change restrict_yaxis = True.
+        vdiff_plot: 15.0 #Opt +/- range to use in bias plots. To apply to a plot, change restrict_yaxis = True.
+        nlevels_plot: 21 #Opt number of levels used in colorbar for contourf plot.
+      'NO2_CL_RYERSON':
+        nan_value: -777777 # Set this value to NaN
+        LLOD_value: -888888 # Opt Set this value to LLOD_setvalue
+        LLOD_setvalue: 0.0 # Opt Set LLOD_value=LLOD_setvalue, applied AFTER unit_scale and obs_unit
+        ylabel_plot: 'NO2 (ppbv)' #Optional to set ylabel so can include units and/or instr etc.
+        vmin_plot: 0.0 #Opt Min for y-axis during plotting. To apply to a plot, change restrict_yaxis = True.
+        vmax_plot: 20.0 #Opt Max for y-axis during plotting. To apply to a plot, change restrict_yaxis = True.
+        vdiff_plot: 15.0 #Opt +/- range to use in bias plots. To apply to a plot, change restrict_yaxis = True.
+        nlevels_plot: 21 #Opt number of levels used in colorbar for contourf plot.
+      'Latitude_YANG':
+            rename: latitude # name to convert this variable to
+            unit_scale: 1 #Opt Scaling factor 
+            unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+      'Longitude_YANG':
+            rename: longitude # name to convert this variable to
+            unit_scale: 1 #Opt Scaling factor 
+            unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+      'P_BUI':
+            rename: pressure_obs # name to convert this variable to
+            unit_scale: 100 #Opt Scaling factor 
+            unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+      'MSL_GPS_Altitude_YANG':
+          rename: altitude # name to convert this variable to
+          unit_scale: 1 #Opt Scaling factor 
+          unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+   
+plots:
+  plot_grp1:
+    type: 'timeseries' # plot type
+    fig_kwargs: #Opt to define figure options
+      figsize: [12,6] # figure size if multiple plots
+    default_plot_kwargs: # Opt to define defaults for all plots. Model kwargs overwrite these.
+      linewidth: 2.0
+      markersize: 10.
+    text_kwargs: #Opt
+      fontsize: 18.
+    domain_type: ['all'] #List of domain types: 'all' or any domain in obs file. (e.g., airnow: epa_region, state_name, siteid, etc.) 
+    domain_name: ['CONUS'] #List of domain names. If domain_type = all domain_name is used in plot title.
+    data: ['firexaq_wrfchem_v4.2'] # make this a list of pairs in obs_model where the obs is the obs label and model is the model_label
+    data_proc:
+      #See 'altitde_yax2' list below for secondary y-axis options
+      #altitude_variable: altitude  
+      #altitude_ticks: 1000  # Altitude tick interval in meters (for secondary y-axis for altitude (m))
+      rem_obs_nan: True # True: Remove all points where model or obs variable is NaN. False: Remove only points where model variable is NaN.
+      ts_select_time: 'time' #Time used for avg and plotting: Options: 'time' for UTC or 'time_local'
+      ts_avg_window: #'H' # pandas resample rule (e.g., 'H', 'D'). No averaging is done if ts_avg_window is null or not specified.
+      set_axis: False #If select True, add vmin_plot and vmax_plot for each variable in obs.
+      #vmin2, vmax2 filter not needed as filter_dict option added in 'altitude_yax2' to subset the paireddf as per altitude secondary-axis limits
+      #vmin2: #0  #Optional
+      #vmax2: #5000 #12000 #Optional #Subset limits for secondary y-axis (altitude_variable) 
+      altitude_yax2:
+        altitude_variable: altitude
+        altitude_ticks: 1000
+        ylabel2: Altitude (m)
+        plot_kwargs_y2:
+          color: g
+        altitude_unit: m
+        altitude_scaling_factor: 1
+        filter_dict: #Default is min and max if filter_dict doesn't define the options below (or if they are commented out)
+          altitude:
+            oper: "between"
+            value: [2000,8000] # values are [vmin_y2, vmax_y2] 
+  plot_grp2:
+    type: 'vertprofile'  # plot type
+    fig_kwargs:  # Opt to define figure options
+      figsize: [10, 14]  # figure size
+    default_plot_kwargs:  # Opt to define defaults for all plots. Model kwargs overwrite these.
+      linewidth: 4.0
+      markersize: 10.
+    text_kwargs:  # Opt
+      fontsize: 18.
+    domain_type: ['all']  # List of domain types: 'all' or any domain in obs file. (e.g., airnow: epa_region, state_name, siteid, etc.)
+    domain_name: ['CONUS']  # List of domain names. If domain_type = all, domain_name is used in plot title.
+    data: ['firexaq_wrfchem_v4.2']  # make this a list of pairs in obs_model where the obs is the obs label and model is the model_label
+    data_proc:
+      rem_obs_nan: True  # True: Remove all points where model or obs variable is NaN. False: Remove only points where model variable is NaN.
+      set_axis: False  # If set to True, add vmin_plot and vmax_plot for each variable in obs.
+      interquartile_style: 'shading' # or 'box'
+    #TO DO: altitude_variable: 'Static_Pressure_YANG' or 'pressure_obs' (=P_BUI(hPa)*100) (pressure in Pa)  # ISSUE created: Add capability of the altitude variable to take pressure as an option to MSL height
+    altitude_variable: altitude #'MSL_GPS_Altitude_YANG' #'ALTITUDE' in m or desired unit
+    #vertprofile_bins: [0, 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, 10000]   # Specify the Pressure altitude bin size in hPa    
+    vertprofile_bins: [0, 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, 10000, 11000, 12000] # meters
+    #vertprofile_bins: [0, 1000, 2000, 3000, 4000, 5000] # meters # Needs to be specified as per min and max altitude (vmin, vmax)
+    vmin: #0  #Optional
+    vmax: #5000 # Optional #'vertprofile bins' need to be edited as per min and max altitude (i.e., vmin and vmax, if specified)
+
+  plot_grp3:
+    type: 'violin'
+    fig_kwargs:
+      figsize: [10, 8]
+    text_kwargs:
+      fontsize: 25.
+    domain_type: ['all']
+    domain_name: ['CONUS']
+    data: ['firexaq_wrfchem_v4.2']
+    data_proc:
+      rem_obs_nan: True 
+      set_axis: False
+
+    
+  plot_grp4:
+    type: 'scatter_density'
+    fig_kwargs:
+      figsize: [10, 10]
+    default_plot_kwargs:
+      linewidth: 4.0
+      markersize: 10.
+    text_kwargs:
+      fontsize: 18.
+    domain_type: ['all']
+    domain_name: ['CONUS']
+    data: ['firexaq_wrfchem_v4.2']
+    data_proc:
+      rem_obs_nan: True
+      set_axis: False #True
+      vmin_x: #0
+      vmax_x: #100
+      vmin_y: #0
+      vmax_y: #100
+    color_map: #'RdBu_r' # Default Colormap for the density plot can be used. Options include:
+                        # 'viridis', 'plasma', 'inferno', 'magma', 'cividis',
+                        # 'jet', 'hot', 'cool', 'spring', 'summer', 'autumn', 'winter',
+                        # 'RdBu_r', 'seismic', 'coolwarm',
+                        # 'Blues', 'BuGn', 'YlOrRd', 'Greys'
+        #To use a custom colormap: Use the following options otherwise use the above default color_map(s) AND COMMENT THESE
+        colors: ['royalblue', 'cyan', 'yellow', 'orange']
+        over: 'red'
+        under: 'blue'
+    xlabel: 'Model'
+    ylabel: 'Observation'
+    title: 'Scatter Density Plot'
+    fill: False #True #False              # Set to True if you want to fill the area under the density curve (for kde plot), False for sactterplot
+    shade_lowest: True #False      # Set to True if you want to shade the lowest contour (if fill=TRUE for KDE plots)
+    # Add other seaborn.kdeplot keyword arguments here as needed
+    vcenter: #0  # Central value for TwoSlopeNorm
+    extensions: ['min', 'max']  # Extensions for the colorbar  
+  plot_grp5:
+    type: 'taylor' # plot type
+    fig_kwargs: #Opt to define figure options
+      figsize: [8,8] # figure size if multiple plots
+    default_plot_kwargs: # Opt to define defaults for all plots. Model kwargs overwrite these.
+      linewidth: 2.0
+      markersize: 10.
+    text_kwargs: #Opt
+      fontsize: 16.
+    domain_type: ['all'] #List of domain types: 'all' or any domain in obs file. (e.g., airnow: epa_region, state_name, siteid, etc.) 
+    domain_name: ['CONUS'] #List of domain names. If domain_type = all domain_name is used in plot title.
+    data: ['firexaq_wrfchem_v4.2'] # make this a list of pairs in obs_model where the obs is the obs label and model is the model_label
+    data_proc:
+      rem_obs_nan: True # True: Remove all points where model or obs variable is NaN. False: Remove only points where model variable is NaN.
+      set_axis: True #If select True, add ty_scale for each variable in obs.
+  plot_grp6:
+    type: 'boxplot' # plot type
+    fig_kwargs: #Opt to define figure options
+      figsize: [8, 6] # figure size 
+    text_kwargs: #Opt
+      fontsize: 20.
+    domain_type: ['all'] #List of domain types: 'all' or any domain in obs file. (e.g., airnow: epa_region, state_name, siteid, etc.) 
+    domain_name: ['CONUS'] #List of domain names. If domain_type = all domain_name is used in plot title.
+    data: ['firexaq_wrfchem_v4.2'] # make this a list of pairs in obs_model where the obs is the obs label and model is the model_label
+    data_proc:
+      rem_obs_nan: True # True: Remove all points where model or obs variable is NaN. False: Remove only points where model variable is NaN.
+      set_axis: False #If select True, add vmin_plot and vmax_plot for each variable in obs.
+stats:
+  #Stats require positive numbers, so if you want to calculate temperature use Kelvin!
+  #Wind direction has special calculations for AirNow if obs name is 'WD'
+  stat_list: ['MB', 'MdnB','R2', 'RMSE'] #List stats to calculate. Dictionary of definitions included in plots/proc_stats.py Only stats listed below are currently working.
+  #Full calc list ['STDO', 'STDP', 'MdnNB','MdnNE','NMdnGE', 'NO','NOP','NP','MO','MP', 'MdnO', 'MdnP', 'RM', 'RMdn', 'MB', 'MdnB', 'NMB', 'NMdnB', 'FB', 'ME','MdnE','NME', 'NMdnE', 'FE', 'R2', 'RMSE','d1','E1', 'IOA', 'AC']
+  round_output: 2 #Opt, defaults to rounding to 3rd decimal place.
+  output_table: False #Always outputs a .txt file. Optional to also output as a table.
+  output_table_kwargs: #Opt 
+    figsize: [7, 3] # figure size 
+    fontsize: 12.
+    xscale: 1.4
+    yscale: 1.4
+    edges: 'horizontal'
+  domain_type: ['all'] #List of domain types: 'all' or any domain in obs file. (e.g., airnow: epa_region, state_name, siteid, etc.) 
+  domain_name: ['CONUS'] #List of domain names. If domain_type = all domain_name is used in plot title.
+  data: ['firexaq_wrfchem_v4.2'] # make this a list of pairs in obs_model where the obs is the obs label and model is the model_label
+
+
diff --git a/examples/yaml/control_wrfchem_aircraft_Latestfor_develop_aircraft_testmultiplemodelgroups.yaml b/examples/yaml/control_wrfchem_aircraft_Latestfor_develop_aircraft_testmultiplemodelgroups.yaml
new file mode 100644
index 00000000..01619ffc
--- /dev/null
+++ b/examples/yaml/control_wrfchem_aircraft_Latestfor_develop_aircraft_testmultiplemodelgroups.yaml
@@ -0,0 +1,282 @@
+# General Description:  
+# Any key that is specific for a plot type will begin with ts for timeseries, ty for taylor
+# Opt: Specifying the variable or variable group is optional
+# For now all plots except time series average over the analysis window. 
+# Seting axis values - If set_axis = True in data_proc section of each plot_grp the yaxis for the plot will be set based on the values specified in the obs section for each variable. If set_axis is set to False, then defaults will be used. 'vmin_plot' and 'vmax_plot' are needed for 'timeseries', 'spatial_overlay', and 'boxplot'. 'vdiff_plot' is needed for 'spatial_bias' plots and'ty_scale' is needed for 'taylor' plots. 'nlevels' or the number of levels used in the contour plot can also optionally be provided for spatial_overlay plot. If set_axis = True and the proper limits are not provided in the obs section, a warning will print, and the plot will be created using the default limits.
+analysis:
+  start_time: '2019-09-05-12:00:00' #UTC
+  end_time: '2019-09-06-00:00:00' #UTC
+  output_dir: /wrk/qrasool/output_testaircraft_PR189_uptoviolin_multiplemodels #/wrk/charkins/melodies_monet/NOAA_CSL_main/test_pull_189_aircraft/output #/wrk/charkins/melodies_monet/aircraft/analysis #Opt if not specified plots stored in code directory.
+  debug: True
+model:
+  wrfchem_v4.2: # model label
+    # files: /wrk/d2/rschwantes/wrf/firex_mech/qzhu/run_CONUS_fv19_BEIS_1.0xISO_RACM_v4.2.2_racm_berk_vcp_noI_phot_soa/0905/*
+    files: /wrk/qrasool/firex_mech_qzhu/run_CONUS_fv19_BEIS_1.0xISO_RACM_v4.2.2_racm_berk_vcp_noI_phot_soa/0905/* #/wrk/d2/rschwantes/wrf/firex_mech/qzhu/run_CONUS_fv19_BEIS_1.0xISO_RACM_v4.2.2_racm_berk_vcp_noI_phot_soa/0905/*
+    mod_type: 'wrfchem'
+    mod_kwargs: 
+      mech: 'racm_esrl_vcp'
+    radius_of_influence: 12000 #meters
+    mapping: #model species name : obs species name
+      firexaq:
+        no2: NO2_CL_RYERSON
+        'no': 'NO_CL_RYERSON'
+        #PM2_5_DRY: "PM2.5"
+        o3: "O3_CL_RYERSON"
+    variables:
+        'pres_pa_mid':
+            rename: pressure_model # name to convert this variable to, use 'pressure_model' for aircraft obs
+            unit_scale: 1 #Opt Scaling factor 
+            unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+        'temperature_k':
+            rename: temp_model # name to convert this variable to
+            unit_scale: 1 #Opt Scaling factor 
+            unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+    projection: None
+    plot_kwargs: #Opt
+      color: 'dodgerblue'
+      marker: '^'
+      linestyle: ':' 
+  wrfchem_v4.2_test: # model label
+    # files: /wrk/d2/rschwantes/wrf/firex_mech/qzhu/run_CONUS_fv19_BEIS_1.0xISO_RACM_v4.2.2_racm_berk_vcp_noI_phot_soa/0905/*
+    files: /wrk/qrasool/firex_mech_qzhu/run_CONUS_fv19_BEIS_1.0xISO_RACM_v4.2.2_racm_berk_vcp_noI_phot_soa/0905/* #/wrk/d2/rschwantes/wrf/firex_mech/qzhu/run_CONUS_fv19_BEIS_1.0xISO_RACM_v4.2.2_racm_berk_vcp_noI_phot_soa/0905/*
+    mod_type: 'wrfchem'
+    mod_kwargs: 
+      mech: 'racm_esrl_vcp'
+    radius_of_influence: 12000 #meters
+    mapping: #model species name : obs species name
+      firexaq:
+        no2: NO2_CL_RYERSON
+        'no': 'NO_CL_RYERSON'
+        #PM2_5_DRY: "PM2.5"
+        o3: "O3_CL_RYERSON"
+    variables:
+        'pres_pa_mid':
+            rename: pressure_model # name to convert this variable to, use 'pressure_model' for aircraft obs
+            unit_scale: 1 #Opt Scaling factor 
+            unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+        'temperature_k':
+            rename: temp_model # name to convert this variable to
+            unit_scale: 1 #Opt Scaling factor 
+            unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+        'no2':
+            unit_scale: 2 #Opt Scaling factor 
+            unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+        'no':
+            unit_scale: 2 #Opt Scaling factor 
+            unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+        'o3':
+            unit_scale: 2 #Opt Scaling factor 
+            unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+    projection: None
+    plot_kwargs: #Opt
+      color: 'goldenrod'
+      marker: 's'
+      linestyle: '-'
+
+obs:
+  firexaq: # obs label
+    filename: '/wrk/d2/rschwantes/obs/firex-aq/R1/10s_merge/firexaq-mrg10-dc8_merge_20190905_R1.ict'
+    obs_type: aircraft
+    #resample: '60S' #'600S' #10 min so works on Hera as a test. Can comment this if submitting a job. 
+    variables: #Opt 
+      'O3_CL_RYERSON':
+        unit_scale: 1 #Opt Scaling factor 
+        unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+        nan_value: -777777 # Opt Set this value to NaN
+        LLOD_value: -888888 # Opt Set this value to LLOD_setvalue
+        LLOD_setvalue: 0.0 # Opt Set LLOD_value=LLOD_setvalue, applied AFTER unit_scale and obs_unit
+        ylabel_plot: 'Ozone (ppbv)'
+        vmin_plot: 15.0 #Opt Min for y-axis during plotting. To apply to a plot, change restrict_yaxis = True.
+        vmax_plot: 55.0 #Opt Max for y-axis during plotting. To apply to a plot, change restrict_yaxis = True.
+        vdiff_plot: 20.0 #Opt +/- range to use in bias plots. To apply to a plot, change restrict_yaxis = True.
+        # nlevels_plot: 21 #Opt number of levels used in colorbar for contourf plot.
+      'NO_CL_RYERSON':
+        nan_value: -777777 # Set this value to NaN
+        LLOD_value: -888888 # Opt Set this value to LLOD_setvalue
+        LLOD_setvalue: 0.0 # Opt Set LLOD_value=LLOD_setvalue, applied AFTER unit_scale and obs_unit
+        ylabel_plot: 'NO (ppbv)' #Optional to set ylabel so can include units and/or instr etc.
+        vmin_plot: 0.0 #Opt Min for y-axis during plotting. To apply to a plot, change restrict_yaxis = True.
+        vmax_plot: 20.0 #Opt Max for y-axis during plotting. To apply to a plot, change restrict_yaxis = True.
+        vdiff_plot: 15.0 #Opt +/- range to use in bias plots. To apply to a plot, change restrict_yaxis = True.
+        nlevels_plot: 21 #Opt number of levels used in colorbar for contourf plot.
+      'NO2_CL_RYERSON':
+        nan_value: -777777 # Set this value to NaN
+        LLOD_value: -888888 # Opt Set this value to LLOD_setvalue
+        LLOD_setvalue: 0.0 # Opt Set LLOD_value=LLOD_setvalue, applied AFTER unit_scale and obs_unit
+        ylabel_plot: 'NO2 (ppbv)' #Optional to set ylabel so can include units and/or instr etc.
+        vmin_plot: 0.0 #Opt Min for y-axis during plotting. To apply to a plot, change restrict_yaxis = True.
+        vmax_plot: 20.0 #Opt Max for y-axis during plotting. To apply to a plot, change restrict_yaxis = True.
+        vdiff_plot: 15.0 #Opt +/- range to use in bias plots. To apply to a plot, change restrict_yaxis = True.
+        nlevels_plot: 21 #Opt number of levels used in colorbar for contourf plot.
+      'Latitude_YANG':
+            rename: latitude # name to convert this variable to
+            unit_scale: 1 #Opt Scaling factor 
+            unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+      'Longitude_YANG':
+            rename: longitude # name to convert this variable to
+            unit_scale: 1 #Opt Scaling factor 
+            unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+      'P_BUI':
+            rename: pressure_obs # name to convert this variable to
+            unit_scale: 100 #Opt Scaling factor 
+            unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+      'MSL_GPS_Altitude_YANG':
+          rename: altitude # name to convert this variable to
+          unit_scale: 1 #Opt Scaling factor 
+          unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+   
+plots:
+  plot_grp1:
+    type: 'timeseries' # plot type
+    fig_kwargs: #Opt to define figure options
+      figsize: [12,6] # figure size if multiple plots
+    default_plot_kwargs: # Opt to define defaults for all plots. Model kwargs overwrite these.
+      linewidth: 2.0
+      markersize: 10.
+    text_kwargs: #Opt
+      fontsize: 18.
+    domain_type: ['all'] #List of domain types: 'all' or any domain in obs file. (e.g., airnow: epa_region, state_name, siteid, etc.) 
+    domain_name: ['CONUS'] #List of domain names. If domain_type = all domain_name is used in plot title.
+    data: ['firexaq_wrfchem_v4.2','firexaq_wrfchem_v4.2_test'] # make this a list of pairs in obs_model where the obs is the obs label and model is the model_label
+    data_proc:
+      #See 'altitde_yax2' list below for secondary y-axis options
+      #altitude_variable: altitude  
+      #altitude_ticks: 1000  # Altitude tick interval in meters (for secondary y-axis for altitude (m))
+      rem_obs_nan: True # True: Remove all points where model or obs variable is NaN. False: Remove only points where model variable is NaN.
+      ts_select_time: 'time' #Time used for avg and plotting: Options: 'time' for UTC or 'time_local'
+      ts_avg_window: #'H' # pandas resample rule (e.g., 'H', 'D'). No averaging is done if ts_avg_window is null or not specified.
+      set_axis: False #If select True, add vmin_plot and vmax_plot for each variable in obs.
+      #vmin2, vmax2 filter not needed as filter_dict option added in 'altitude_yax2' to subset the paireddf as per altitude secondary-axis limits
+      #vmin2: #0  #Optional
+      #vmax2: #5000 #12000 #Optional #Subset limits for secondary y-axis (altitude_variable) 
+      altitude_yax2:
+        altitude_variable: altitude
+        altitude_ticks: 1000
+        ylabel2: Altitude (m)
+        plot_kwargs_y2:
+          color: g
+        altitude_unit: m
+        altitude_scaling_factor: 1
+        filter_dict: #Default is min and max if filter_dict doesn't define the options below (or if they are commented out)
+          altitude:
+            oper: "between"
+            value: [2000,8000] # values are [vmin_y2, vmax_y2] 
+  plot_grp2:
+    type: 'vertprofile'  # plot type
+    fig_kwargs:  # Opt to define figure options
+      figsize: [10, 14]  # figure size
+    default_plot_kwargs:  # Opt to define defaults for all plots. Model kwargs overwrite these.
+      linewidth: 4.0
+      markersize: 10.
+    text_kwargs:  # Opt
+      fontsize: 18.
+    domain_type: ['all']  # List of domain types: 'all' or any domain in obs file. (e.g., airnow: epa_region, state_name, siteid, etc.)
+    domain_name: ['CONUS']  # List of domain names. If domain_type = all, domain_name is used in plot title.
+    data: ['firexaq_wrfchem_v4.2','firexaq_wrfchem_v4.2_test']  # make this a list of pairs in obs_model where the obs is the obs label and model is the model_label
+    data_proc:
+      rem_obs_nan: True  # True: Remove all points where model or obs variable is NaN. False: Remove only points where model variable is NaN.
+      set_axis: False  # If set to True, add vmin_plot and vmax_plot for each variable in obs.
+      interquartile_style: 'shading' # or 'box'
+    #TO DO: altitude_variable: 'Static_Pressure_YANG' or 'pressure_obs' (=P_BUI(hPa)*100) (pressure in Pa)  # ISSUE created: Add capability of the altitude variable to take pressure as an option to MSL height
+    altitude_variable: altitude #'MSL_GPS_Altitude_YANG' #'ALTITUDE' in m or desired unit
+    #vertprofile_bins: [0, 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, 10000]   # Specify the Pressure altitude bin size in hPa    
+    vertprofile_bins: [0, 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, 10000, 11000, 12000] # meters
+    #vertprofile_bins: [0, 1000, 2000, 3000, 4000, 5000] # meters # Needs to be specified as per min and max altitude (vmin, vmax)
+    vmin: #0  #Optional
+    vmax: #5000 # Optional #'vertprofile bins' need to be edited as per min and max altitude (i.e., vmin and vmax, if specified)
+
+  plot_grp3:
+    type: 'violin'
+    fig_kwargs:
+      figsize: [10, 8]
+    text_kwargs:
+      fontsize: 25.
+    domain_type: ['all']
+    domain_name: ['CONUS']
+    data: ['firexaq_wrfchem_v4.2','firexaq_wrfchem_v4.2_test']
+    data_proc:
+      rem_obs_nan: True 
+      set_axis: False
+
+    
+  plot_grp4:
+    type: 'scatter_density'
+    fig_kwargs:
+      figsize: [10, 10]
+    default_plot_kwargs:
+      linewidth: 4.0
+      markersize: 10.
+    text_kwargs:
+      fontsize: 18.
+    domain_type: ['all']
+    domain_name: ['CONUS']
+    data: ['firexaq_wrfchem_v4.2','firexaq_wrfchem_v4.2_test']
+    data_proc:
+      rem_obs_nan: True
+      set_axis: False #True
+      vmin_x: #0
+      vmax_x: #100
+      vmin_y: #0
+      vmax_y: #100
+    color_map: #'RdBu_r' # Default Colormap for the density plot can be used. Options include:
+                        # 'viridis', 'plasma', 'inferno', 'magma', 'cividis',
+                        # 'jet', 'hot', 'cool', 'spring', 'summer', 'autumn', 'winter',
+                        # 'RdBu_r', 'seismic', 'coolwarm',
+                        # 'Blues', 'BuGn', 'YlOrRd', 'Greys'
+        #To use a custom colormap: Use the following options otherwise use the above default color_map(s) AND COMMENT THESE
+        colors: ['royalblue', 'cyan', 'yellow', 'orange']
+        over: 'red'
+        under: 'blue'
+    xlabel: 'Model'
+    ylabel: 'Observation'
+    title: 'Scatter Density Plot'
+    fill: True #True #False              # Set to True if you want to fill the area under the density curve (for kde plot), False for sactterplot
+    shade_lowest: True #False      # Set to True if you want to shade the lowest contour (if fill=TRUE for KDE plots)
+    # Add other seaborn.kdeplot keyword arguments here as needed
+    vcenter: #0  # Central value for TwoSlopeNorm
+    extensions: ['min', 'max']  # Extensions for the colorbar  
+  plot_grp5:
+    type: 'taylor' # plot type
+    fig_kwargs: #Opt to define figure options
+      figsize: [8,8] # figure size if multiple plots
+    default_plot_kwargs: # Opt to define defaults for all plots. Model kwargs overwrite these.
+      linewidth: 2.0
+      markersize: 10.
+    text_kwargs: #Opt
+      fontsize: 16.
+    domain_type: ['all'] #List of domain types: 'all' or any domain in obs file. (e.g., airnow: epa_region, state_name, siteid, etc.) 
+    domain_name: ['CONUS'] #List of domain names. If domain_type = all domain_name is used in plot title.
+    data: ['firexaq_wrfchem_v4.2','firexaq_wrfchem_v4.2_test'] # make this a list of pairs in obs_model where the obs is the obs label and model is the model_label
+    data_proc:
+      rem_obs_nan: True # True: Remove all points where model or obs variable is NaN. False: Remove only points where model variable is NaN.
+      set_axis: True #If select True, add ty_scale for each variable in obs.
+  plot_grp6:
+    type: 'boxplot' # plot type
+    fig_kwargs: #Opt to define figure options
+      figsize: [8, 6] # figure size 
+    text_kwargs: #Opt
+      fontsize: 20.
+    domain_type: ['all'] #List of domain types: 'all' or any domain in obs file. (e.g., airnow: epa_region, state_name, siteid, etc.) 
+    domain_name: ['CONUS'] #List of domain names. If domain_type = all domain_name is used in plot title.
+    data: ['firexaq_wrfchem_v4.2','firexaq_wrfchem_v4.2_test'] # make this a list of pairs in obs_model where the obs is the obs label and model is the model_label
+    data_proc:
+      rem_obs_nan: True # True: Remove all points where model or obs variable is NaN. False: Remove only points where model variable is NaN.
+      set_axis: False #If select True, add vmin_plot and vmax_plot for each variable in obs.
+stats:
+  #Stats require positive numbers, so if you want to calculate temperature use Kelvin!
+  #Wind direction has special calculations for AirNow if obs name is 'WD'
+  stat_list: ['MB', 'MdnB','R2', 'RMSE'] #List stats to calculate. Dictionary of definitions included in plots/proc_stats.py Only stats listed below are currently working.
+  #Full calc list ['STDO', 'STDP', 'MdnNB','MdnNE','NMdnGE', 'NO','NOP','NP','MO','MP', 'MdnO', 'MdnP', 'RM', 'RMdn', 'MB', 'MdnB', 'NMB', 'NMdnB', 'FB', 'ME','MdnE','NME', 'NMdnE', 'FE', 'R2', 'RMSE','d1','E1', 'IOA', 'AC']
+  round_output: 2 #Opt, defaults to rounding to 3rd decimal place.
+  output_table: False #Always outputs a .txt file. Optional to also output as a table.
+  output_table_kwargs: #Opt 
+    figsize: [7, 3] # figure size 
+    fontsize: 12.
+    xscale: 1.4
+    yscale: 1.4
+    edges: 'horizontal'
+  domain_type: ['all'] #List of domain types: 'all' or any domain in obs file. (e.g., airnow: epa_region, state_name, siteid, etc.) 
+  domain_name: ['CONUS'] #List of domain names. If domain_type = all domain_name is used in plot title.
+  data: ['firexaq_wrfchem_v4.2','firexaq_wrfchem_v4.2_test'] # make this a list of pairs in obs_model where the obs is the obs label and model is the model_label
+
+
diff --git a/examples/yaml/control_wrfchem_ground.yaml b/examples/yaml/control_wrfchem_ground.yaml
new file mode 100755
index 00000000..7d3aa252
--- /dev/null
+++ b/examples/yaml/control_wrfchem_ground.yaml
@@ -0,0 +1,98 @@
+# General Description:  
+# Any key that is specific for a plot type will begin with ts for timeseries, ty for taylor
+# Opt: Specifying the variable or variable group is optional
+# For now all plots except time series average over the analysis window. 
+# Seting axis values - If set_axis = True in data_proc section of each plot_grp the yaxis for the plot will be set based on the values specified in the obs section for each variable. If set_axis is set to False, then defaults will be used. 'vmin_plot' and 'vmax_plot' are needed for 'timeseries', 'spatial_overlay', and 'boxplot'. 'vdiff_plot' is needed for 'spatial_bias' plots and'ty_scale' is needed for 'taylor' plots. 'nlevels' or the number of levels used in the contour plot can also optionally be provided for spatial_overlay plot. If set_axis = True and the proper limits are not provided in the obs section, a warning will print, and the plot will be created using the default limits.
+analysis:
+  start_time: '2021-07-25-00:00:00' #UTC
+  end_time: '2021-07-25-23:00:00' #UTC
+  output_dir: /wrk/charkins/melodies_monet/aircraft/develop_aircraft_ground/Output #Opt if not specified plots stored in code directory.
+  debug: True
+model:
+  wrfchem_v4.2: # model label
+    files: /wrk/users/charkins/MM_data/pasadena_ground_ict/corresponding_model/0725/wrfout_d01_2021-07-25_*
+    mod_type: 'wrfchem'
+    mod_kwargs: 
+      mech: 'racm_esrl_vcp'
+    mapping: #model species name : obs species name
+      pasadena_ground:
+        PM2_5_DRY: "AerComp_OrganicAerosol_PM1" # not correct species pairing but using as example
+    plot_kwargs: #Opt
+      color: 'dodgerblue'
+      marker: '^'
+      linestyle: ':' 
+obs:
+  pasadena_ground: # obs label
+    filename: '/wrk/users/charkins/MM_data/pasadena_ground_ict/20210725/recap-CIT-AMS1-NR-PM1_CITLL_20210725_RB.ict'
+    obs_type: ground
+    ground_coordinate: {'latitude':34.136363,'longitude':-118.126817}
+    #resample: '600S' #10 min so works on Hera as a test. Can comment this if submitting a job. 
+    variables: #Opt 
+      'AerComp_OrganicAerosol_PM1': 
+        unit_scale: 1 #Opt Scaling factor 
+        unit_scale_method: '*' #Opt Multiply = '*' , Add = '+', subtract = '-', divide = '/'
+        ylabel_plot: 'PM1 (units?)'
+
+plots:
+  plot_grp1:
+    type: 'timeseries' # plot type
+    fig_kwargs: #Opt to define figure options
+      figsize: [12,6] # figure size if multiple plots
+    default_plot_kwargs: # Opt to define defaults for all plots. Model kwargs overwrite these.
+      linewidth: 2.0
+      markersize: 10.
+    text_kwargs: #Opt
+      fontsize: 18.
+    domain_type: ['all'] #List of domain types: 'all' or any domain in obs file. (e.g., airnow: epa_region, state_name, siteid, etc.) 
+    domain_name: ['CONUS'] #List of domain names. If domain_type = all domain_name is used in plot title.
+    data: ['pasadena_ground_wrfchem_v4.2'] # make this a list of pairs in obs_model where the obs is the obs label and model is the model_label
+    data_proc:
+      rem_obs_nan: True # True: Remove all points where model or obs variable is NaN. False: Remove only points where model variable is NaN.
+      ts_select_time: 'time' #Time used for avg and plotting: Options: 'time' for UTC or 'time_local'
+      ts_avg_window: 'H' # Options: None for no averaging or list pandas resample rule (e.g., 'H', 'D')
+      set_axis: False #If select True, add vmin_plot and vmax_plot for each variable in obs.
+  plot_grp2:
+    type: 'taylor' # plot type
+    fig_kwargs: #Opt to define figure options
+      figsize: [8,8] # figure size if multiple plots
+    default_plot_kwargs: # Opt to define defaults for all plots. Model kwargs overwrite these.
+      linewidth: 2.0
+      markersize: 10.
+    text_kwargs: #Opt
+      fontsize: 16.
+    domain_type: ['all'] #List of domain types: 'all' or any domain in obs file. (e.g., airnow: epa_region, state_name, siteid, etc.) 
+    domain_name: ['CONUS'] #List of domain names. If domain_type = all domain_name is used in plot title.
+    data: ['pasadena_ground_wrfchem_v4.2'] # make this a list of pairs in obs_model where the obs is the obs label and model is the model_label
+    data_proc:
+      rem_obs_nan: True # True: Remove all points where model or obs variable is NaN. False: Remove only points where model variable is NaN.
+      set_axis: True #If select True, add ty_scale for each variable in obs.
+  plot_grp3:
+    type: 'boxplot' # plot type
+    fig_kwargs: #Opt to define figure options
+      figsize: [8, 6] # figure size 
+    text_kwargs: #Opt
+      fontsize: 20.
+    domain_type: ['all'] #List of domain types: 'all' or any domain in obs file. (e.g., airnow: epa_region, state_name, siteid, etc.) 
+    domain_name: ['CONUS'] #List of domain names. If domain_type = all domain_name is used in plot title.
+    data: ['pasadena_ground_wrfchem_v4.2'] # make this a list of pairs in obs_model where the obs is the obs label and model is the model_label
+    data_proc:
+      rem_obs_nan: True # True: Remove all points where model or obs variable is NaN. False: Remove only points where model variable is NaN.
+      set_axis: False #If select True, add vmin_plot and vmax_plot for each variable in obs.
+
+
+stats:
+  #Stats require positive numbers, so if you want to calculate temperature use Kelvin!
+  #Wind direction has special calculations for AirNow if obs name is 'WD'
+  stat_list: ['MB', 'MdnB','R2', 'RMSE'] #List stats to calculate. Dictionary of definitions included in plots/proc_stats.py Only stats listed below are currently working.
+  #Full calc list ['STDO', 'STDP', 'MdnNB','MdnNE','NMdnGE', 'NO','NOP','NP','MO','MP', 'MdnO', 'MdnP', 'RM', 'RMdn', 'MB', 'MdnB', 'NMB', 'NMdnB', 'FB', 'ME','MdnE','NME', 'NMdnE', 'FE', 'R2', 'RMSE','d1','E1', 'IOA', 'AC']
+  round_output: 2 #Opt, defaults to rounding to 3rd decimal place.
+  output_table: False #Always outputs a .txt file. Optional to also output as a table.
+  output_table_kwargs: #Opt 
+    figsize: [7, 3] # figure size 
+    fontsize: 12.
+    xscale: 1.4
+    yscale: 1.4
+    edges: 'horizontal'
+  domain_type: ['all'] #List of domain types: 'all' or any domain in obs file. (e.g., airnow: epa_region, state_name, siteid, etc.) 
+  domain_name: ['CONUS'] #List of domain names. If domain_type = all domain_name is used in plot title.
+  data: ['pasadena_ground_wrfchem_v4.2'] # make this a list of pairs in obs_model where the obs is the obs label and model is the model_label
diff --git a/examples/yaml/supplementary_yaml/aircraft_looping_file_pairs.yaml b/examples/yaml/supplementary_yaml/aircraft_looping_file_pairs.yaml
new file mode 100755
index 00000000..4acb4ef5
--- /dev/null
+++ b/examples/yaml/supplementary_yaml/aircraft_looping_file_pairs.yaml
@@ -0,0 +1,17 @@
+# This is an example file for specifying groups of files to loop over when using .util.tools.loop_pairing()
+#
+# First group for pairings. The name of this group, 0722, will be the prefix of the saved netcdf files 
+# each top level group will always consist of only 'model' and 'obs' as groups
+'0722': # file prefix label to be used when saving this group
+  model: 
+    # under model this will have pairs of [model dataset name as in control file]: [filenames to open]
+    wrfchem_v4.2: '/wrk/users/charkins/melodies-monet_data/wrfchem/run_CONUS_fv19_BEIS_1.0xISO_RACM_v4.2.2_racm_berk_vcp_noI_phot/0722/*'
+  obs: 
+    # under model this will have pairs of [model dataset name as in control file]: [filenames to open]
+    firexaq: '/wrk/d2/rschwantes/obs/firex-aq/R1/10s_merge/firexaq-mrg10-dc8_merge_20190722_R1.ict'
+# Second group for pairings. The name of this group, 0722, will be the prefix of the saved netcdf files 
+'0905': # file prefix label to be used when saving this group
+  model:
+    wrfchem_v4.2: '/wrk/users/charkins/melodies-monet_data/wrfchem/run_CONUS_fv19_BEIS_1.0xISO_RACM_v4.2.2_racm_berk_vcp_noI_phot_soa/0905/*'
+  obs:
+    firexaq: '/wrk/d2/rschwantes/obs/firex-aq/R1/10s_merge/firexaq-mrg10-dc8_merge_20190905_R1.ict'
diff --git a/melodies_monet/driver.py b/melodies_monet/driver.py
index e32b1492..ece76c30 100644
--- a/melodies_monet/driver.py
+++ b/melodies_monet/driver.py
@@ -120,6 +120,8 @@ def __init__(self):
         self.sat_type = None
         self.data_proc = None
         self.variable_dict = None
+        self.resample = None
+        self.time_var = None
 
     def __repr__(self):
         return (
@@ -131,6 +133,7 @@ def __repr__(self):
             f"    type={self.type!r},\n"
             f"    type={self.data_proc!r},\n"
             f"    variable_dict={self.variable_dict!r},\n"
+            f"    resample={self.resample!r},\n"
             ")"
         )
 
@@ -184,18 +187,58 @@ def open_obs(self, time_interval=None, control_dict=None):
                         self.obj = xr.open_mfdataset(files)
                     else:
                         self.obj = xr.open_dataset(files[0])
-                elif extension in ['.ict', '.icarrt']:
-                    assert len(files) == 1, "monetio.icarrt.add_data can only read one file"
-                    self.obj = mio.icarrt.add_data(files[0])
+                elif extension in ['.ict', '.icartt']:
+                    assert len(files) == 1, "monetio.icartt.add_data can only read one file"
+                    self.obj = mio.icartt.add_data(files[0])
+                elif extension in ['.csv']:
+                    from .util.read_util import read_aircraft_obs_csv
+                    assert len(files) == 1, "MELODIES-MONET can only read one csv file"
+                    self.obj = read_aircraft_obs_csv(filename=files[0],time_var=self.time_var)
                 else:
                     raise ValueError(f'extension {extension!r} currently unsupported')
             except Exception as e:
                 print('something happened opening file:', e)
                 return
-
+        
+        self.add_coordinates_ground() # If ground site then add coordinates based on yaml if necessary
         self.mask_and_scale()  # mask and scale values from the control values
+        self.rename_vars() # rename any variables as necessary 
+        self.resample_data()
         self.filter_obs()
 
+    def add_coordinates_ground(self):
+        """Add latitude and longitude coordinates to data when the observation type is ground and 
+        ground_coordinate is specified
+        
+        Returns
+        -------
+        None
+        """
+                
+        # If ground site
+        if self.obs_type == 'ground':
+            if self.ground_coordinate and isinstance(self.ground_coordinate,dict):
+                self.obj['latitude'] = xr.ones_like(self.obj['time'],dtype=np.float64)*self.ground_coordinate['latitude']
+                self.obj['longitude'] = xr.ones_like(self.obj['time'],dtype=np.float64)*self.ground_coordinate['longitude']
+            elif self.ground_coordinate and ~isinstance(self.ground_coordinate,dict): 
+                raise TypeError(f'The ground_coordinate option must be specified as a dict with keys latitude and longitude.')
+
+    def rename_vars(self):
+        """Rename any variables in observation with rename set.
+        
+        Returns
+        -------
+        None
+        """
+        data_vars = self.obj.data_vars
+        if self.variable_dict is not None:
+            for v in data_vars:
+                if v in self.variable_dict:
+                    d = self.variable_dict[v]
+                    if 'rename' in d:
+                        self.obj = self.obj.rename({v:d['rename']})
+                        self.variable_dict[d['rename']] = self.variable_dict.pop(v)
+
     def open_sat_obs(self,time_interval=None):
         """Methods to opens satellite data observations. 
         Uses in-house python code to open and load observations.
@@ -260,8 +303,8 @@ def filter_obs(self):
         
         Returns
         -------
-            None
-        """
+        None
+        """ 
         if self.data_proc is not None:
             if 'filter_dict' in self.data_proc:
                 filter_dict = self.data_proc['filter_dict']
@@ -307,6 +350,7 @@ def mask_and_scale(self):
                         self.obj[v].data = self.obj[v].where(self.obj[v] <= d['obs_max'])
                     if 'nan_value' in d:
                         self.obj[v].data = self.obj[v].where(self.obj[v] != d['nan_value'])
+                    
                     # Then apply a correction if needed for the units.
                     if 'unit_scale' in d:
                         scale = d['unit_scale']
@@ -321,6 +365,22 @@ def mask_and_scale(self):
                             self.obj[v].data += scale
                         elif d['unit_scale_method'] == '-':
                             self.obj[v].data += -1 * scale
+                    
+                    # Then replace LLOD_value with LLOD_setvalue (after unit conversion)
+                    if 'LLOD_value' in d:
+                        self.obj[v].data = self.obj[v].where(self.obj[v] != d['LLOD_value'],d['LLOD_setvalue'])
+
+    def resample_data(self):
+        """Resample the obs df based on the value set in the control file.
+        
+        Returns
+        -------
+        None
+        """ 
+                        
+        ##Resample the data
+        if self.resample is not None:
+            self.obj = self.obj.resample(time=self.resample).mean(dim='time')
 
     def obs_to_df(self):
         """Convert and reformat observation object (:attr:`obj`) to dataframe.
@@ -507,6 +567,23 @@ def open_model_files(self, time_interval=None, control_dict=None):
                 else:
                     self.obj = xr.open_dataset(self.files[0],**self.mod_kwargs)
         self.mask_and_scale()
+        self.rename_vars() # rename any variables as necessary 
+
+    def rename_vars(self):
+        """Rename any variables in model with rename set.
+        
+        Returns
+        -------
+        None
+        """ 
+        data_vars = self.obj.data_vars
+        if self.variable_dict is not None:
+            for v in data_vars:
+                if v in self.variable_dict:
+                    d = self.variable_dict[v]
+                    if 'rename' in d:
+                        self.obj = self.obj.rename({v:d['rename']})
+                        self.variable_dict[d['rename']] = self.variable_dict.pop(v)
 
     def mask_and_scale(self):
         """Mask and scale model data including unit conversions.
@@ -618,8 +695,10 @@ def read_control(self, control=None):
             self.control_dict = yaml.safe_load(stream)
 
         # set analysis time
-        self.start_time = pd.Timestamp(self.control_dict['analysis']['start_time'])
-        self.end_time = pd.Timestamp(self.control_dict['analysis']['end_time'])
+        if 'start_time' in self.control_dict['analysis'].keys():
+            self.start_time = pd.Timestamp(self.control_dict['analysis']['start_time'])
+        if 'end_time' in self.control_dict['analysis'].keys():
+            self.end_time = pd.Timestamp(self.control_dict['analysis']['end_time'])
         if 'output_dir' in self.control_dict['analysis'].keys():
             self.output_dir = os.path.expandvars(
                     self.control_dict['analysis']['output_dir'])
@@ -866,6 +945,12 @@ def open_obs(self, time_interval=None, load_files=True):
                     o.debug = self.control_dict['obs'][obs]['debug']
                 if 'variables' in self.control_dict['obs'][obs].keys():
                     o.variable_dict = self.control_dict['obs'][obs]['variables']
+                if 'resample' in self.control_dict['obs'][obs].keys():
+                    o.resample = self.control_dict['obs'][obs]['resample']
+                if 'time_var' in self.control_dict['obs'][obs].keys():
+                    o.time_var = self.control_dict['obs'][obs]['time_var']
+                if 'ground_coordinate' in self.control_dict['obs'][obs].keys():
+                    o.ground_coordinate = self.control_dict['obs'][obs]['ground_coordinate']
                 if 'sat_type' in self.control_dict['obs'][obs].keys():
                     o.sat_type = self.control_dict['obs'][obs]['sat_type']
                 if load_files:
@@ -901,6 +986,10 @@ def pair_data(self, time_interval=None):
                 # get the variables to pair from the model data (ie don't pair all data)
                 keys = [key for key in mod.mapping[obs_to_pair].keys()]
                 obs_vars = [mod.mapping[obs_to_pair][key] for key in keys]
+                if mod.variable_dict is not None:
+                    mod_vars = [key for key in mod.variable_dict.keys()]
+                else:
+                    mod_vars = []
                 
                 # unstructured grid check - lon/lat variables should be explicitly added 
                 # in addition to comparison variables
@@ -909,8 +998,10 @@ def pair_data(self, time_interval=None):
                     for ll in lonlat_list:
                         if ll in mod.obj.data_vars:
                             keys += [ll]
-                model_obj = mod.obj[keys]
-                
+                if mod.variable_dict is not None:
+                    model_obj = mod.obj[keys+mod_vars]
+                else:
+                    model_obj = mod.obj[keys]
                 ## TODO:  add in ability for simple addition of variables from
 
                 # simplify the objs object with the correct mapping variables
@@ -947,6 +1038,81 @@ def pair_data(self, time_interval=None):
                     self.paired[label] = p
                     p.obj = p.fix_paired_xarray(dset=p.obj)
                     # write_util.write_ncf(p.obj,p.filename) # write out to file
+                    
+                # if aircraft (aircraft observation)
+                elif obs.obs_type.lower() == 'aircraft':
+                    from .util.tools import vert_interp
+                    # convert this to pandas dataframe unless already done because second time paired this obs
+                    if not isinstance(obs.obj, pd.DataFrame):
+                        obs.obj = obs.obj.to_dataframe()
+                    
+                    #drop any variables where coords NaN
+                    obs.obj = obs.obj.reset_index().dropna(subset=['pressure_obs','latitude','longitude']).set_index('time')
+                    
+                    # do the facy trick to convert to get something useful for MONET
+                    # this converts to dimensions of x and y
+                    # you may want to make pressure / msl a coordinate too
+                    new_ds_obs = obs.obj.rename_axis('time_obs').reset_index().monet._df_to_da().set_coords(['time_obs','pressure_obs'])
+                    
+                    #Nearest neighbor approach to find closest grid cell to each point.
+                    ds_model = m.util.combinetool.combine_da_to_da(model_obj,new_ds_obs,merge=False)
+                    #Interpolate based on time in the observations
+                    ds_model = ds_model.interp(time=ds_model.time_obs.squeeze())
+                    
+                    paired_data = vert_interp(ds_model,obs.obj,keys+mod_vars)
+                    print('After pairing: ', paired_data)
+                    # this outputs as a pandas dataframe.  Convert this to xarray obj
+                    p = pair()
+                    p.type = 'aircraft'
+                    p.radius_of_influence = None
+                    p.obs = obs.label
+                    p.model = mod.label
+                    p.model_vars = keys
+                    p.obs_vars = obs_vars
+                    p.filename = '{}_{}.nc'.format(p.obs, p.model)
+                    p.obj = paired_data.set_index('time').to_xarray().expand_dims('x').transpose('time','x')
+                    label = "{}_{}".format(p.obs, p.model)
+                    self.paired[label] = p
+                    # write_util.write_ncf(p.obj,p.filename) # write out to file
+                
+                # If mobile surface data or single ground site surface data
+                elif obs.obs_type.lower() == 'mobile' or obs.obs_type.lower() == 'ground':
+                    from .util.tools import mobile_and_ground_pair
+                    # convert this to pandas dataframe unless already done because second time paired this obs
+                    if not isinstance(obs.obj, pd.DataFrame):
+                        obs.obj = obs.obj.to_dataframe()
+                    
+                    #drop any variables where coords NaN
+                    obs.obj = obs.obj.reset_index().dropna(subset=['latitude','longitude']).set_index('time')
+                    
+                    # do the facy trick to convert to get something useful for MONET
+                    # this converts to dimensions of x and y
+                    # you may want to make pressure / msl a coordinate too
+                    new_ds_obs = obs.obj.rename_axis('time_obs').reset_index().monet._df_to_da().set_coords(['time_obs'])
+                    
+                    #Nearest neighbor approach to find closest grid cell to each point.
+                    ds_model = m.util.combinetool.combine_da_to_da(model_obj,new_ds_obs,merge=False)
+                    #Interpolate based on time in the observations
+                    ds_model = ds_model.interp(time=ds_model.time_obs.squeeze())
+                    
+                    paired_data = mobile_and_ground_pair(ds_model,obs.obj,keys+mod_vars)
+                    print('After pairing: ', paired_data)
+                    # this outputs as a pandas dataframe.  Convert this to xarray obj
+                    p = pair()
+                    if obs.obs_type.lower() == 'mobile':
+                        p.type = 'mobile'
+                    elif obs.obs_type.lower() == 'ground':
+                        p.type = 'ground'
+                    p.radius_of_influence = None
+                    p.obs = obs.label
+                    p.model = mod.label
+                    p.model_vars = keys
+                    p.obs_vars = obs_vars
+                    p.filename = '{}_{}.nc'.format(p.obs, p.model)
+                    p.obj = paired_data.set_index('time').to_xarray().expand_dims('x').transpose('time','x')
+                    label = "{}_{}".format(p.obs, p.model)
+                    self.paired[label] = p
+                
                 # TODO: add other network types / data types where (ie flight, satellite etc)
                 # if sat_swath_clm (satellite l2 column products)
                 elif obs.obs_type.lower() == 'sat_swath_clm':
@@ -1050,12 +1216,10 @@ def plotting(self):
         """
         import matplotlib.pyplot as plt
         pair_keys = list(self.paired.keys())
-        if self.paired[pair_keys[0]].type.lower() == 'pt_sfc':
-            from .plots import surfplots as splots,savefig
-            if self.debug: print('using surfplots')
-        else:
+        if self.paired[pair_keys[0]].type.lower() in ['sat_grid_clm','sat_swath_clm']:
             from .plots import satplots as splots,savefig
-            if self.debug: print('using satplots')
+        else: 
+            from .plots import surfplots as splots, savefig
 
         # Disable figure count warning
         initial_max_fig = plt.rcParams["figure.max_open_warning"]
@@ -1071,9 +1235,18 @@ def plotting(self):
         #     1) a singular plot type
         #     2) multiple paired datasets or model datasets depending on the plot type
         #     3) kwargs for creating the figure ie size and marker (note the default for obs is 'x')
+
+        # Loop through the plot_dict items
         for grp, grp_dict in plot_dict.items():
+            
+            # Read the interquartile_style argument (for vertprofile plot type) if it exists
+            if grp_dict.get('type') == 'vertprofile':
+                interquartile_style = grp_dict.get('data_proc', {}).get('interquartile_style', 'shading')
+            else:
+                interquartile_style = None
+
             pair_labels = grp_dict['data']
-            # get the plot type
+            # Get the plot type
             plot_type = grp_dict['type']
 
             #read-in special settings for multi-boxplot
@@ -1081,6 +1254,7 @@ def plotting(self):
                 region_name = grp_dict['region_name'] 
                 region_list = grp_dict['region_list']
                 model_name_list = grp_dict['model_name_list']     
+            
 
             # first get the observational obs labels
             pair1 = self.paired[list(self.paired.keys())[0]]
@@ -1107,14 +1281,7 @@ def plotting(self):
                             modvar = modvar + '_new'
                             
                         # for pt_sfc data, convert to pandas dataframe, format, and trim
-                        if obs_type == 'pt_sfc':
-                            # convert to dataframe
-                            pairdf_all = p.obj.to_dataframe(dim_order=["time", "x"])
-                            # Select only the analysis time window.
-                            pairdf_all = pairdf_all.loc[self.start_time : self.end_time]
-                        
-                        # keep data in xarray, fix formatting, and trim
-                        elif obs_type in ["sat_swath_sfc", "sat_swath_clm", 
+                        if obs_type in ["sat_swath_sfc", "sat_swath_clm", 
                                                                         "sat_grid_sfc", "sat_grid_clm", 
                                                                         "sat_swath_prof"]:
                              # convert index to time; setup for sat_swath_clm
@@ -1131,6 +1298,11 @@ def plotting(self):
                                 pairdf_all = p.obj
                             # Select only the analysis time window.
                             pairdf_all = pairdf_all.sel(time=slice(self.start_time,self.end_time))
+                        else:
+                            # convert to dataframe
+                            pairdf_all = p.obj.to_dataframe(dim_order=["time", "x"])
+                            # Select only the analysis time window.
+                            pairdf_all = pairdf_all.loc[self.start_time : self.end_time]
                             
                         # Determine the default plotting colors.
                         if 'default_plot_kwargs' in grp_dict.keys():
@@ -1187,6 +1359,8 @@ def plotting(self):
                         else:
                             use_percentile = None
 
+                        
+
                         # Determine outname
                         outname = "{}.{}.{}.{}.{}.{}.{}".format(grp, plot_type, obsvar, startdatename, enddatename, domain_type, domain_name)
 
@@ -1235,7 +1409,7 @@ def plotting(self):
                             pairdf_all = pairdf_all.loc[pairdf_all[grp_var].isin(grp_select[grp_var].values)]
 
                         # Drop NaNs if using pandas 
-                        if obs_type == 'pt_sfc':
+                        if obs_type in ['pt_sfc','aircraft','mobile','ground']:
                             if grp_dict['data_proc']['rem_obs_nan'] == True:
                                 # I removed drop=True in reset_index in order to keep 'time' as a column.
                                 pairdf = pairdf_all.reset_index().dropna(subset=[modvar, obsvar])
@@ -1314,15 +1488,54 @@ def plotting(self):
                             else:
                                 vmin = None
                                 vmax = None
-                            # Select time to use as index. 
+                            # Select time to use as index.
                             # 2024-03-01 MEB needs to only apply if pandas. fails for xarray
-                            if obs_type == 'pt_sfc':
+                            if isinstance(pairdf,pd.core.frame.DataFrame):
                                 pairdf = pairdf.set_index(grp_dict['data_proc']['ts_select_time'])
-                            # Specify ts_avg_window if noted in yaml file. 
+                            # Specify ts_avg_window if noted in yaml file. #qzr++
                             if 'ts_avg_window' in grp_dict['data_proc'].keys():
                                 a_w = grp_dict['data_proc']['ts_avg_window']
                             else:
-                                a_w = None  
+                                a_w = None
+
+                            #Steps needed to subset paired df if secondary y-axis (altitude_variable) limits are provided, 
+                            #ELSE: make_timeseries from surfaceplots.py plots the whole df by default
+                            #Edit below to accomodate 'ground' or 'mobile' where altitude_yax2 is not needed for timeseries
+                            altitude_yax2 = grp_dict['data_proc'].get('altitude_yax2', {})
+
+                            # Extract vmin_y2 and vmax_y2 from filter_dict
+                            # Check if 'filter_dict' exists and 'altitude' is a key in filter_criteria
+                            # Extract vmin_y2 and vmax_y2 from filter_dict
+                            #Better structure for filter_dict (min and max secondary axis) to be optional below
+                            filter_criteria = (
+                                altitude_yax2.get('filter_dict', None)
+                                if isinstance(altitude_yax2, dict)
+                                else None
+                            )
+                            
+                            
+                            if filter_criteria and 'altitude' in filter_criteria:
+                                vmin_y2, vmax_y2 = filter_criteria['altitude']['value']
+                            elif filter_criteria is None:
+                                if 'altitude' in pairdf.columns:
+                                    vmin_y2 = pairdf['altitude'].min()
+                                    vmax_y2 = pairdf['altitude'].max()
+                                else:
+                                    vmin_y2 = vmax_y2 = None
+                            else:
+                                vmin_y2 = vmax_y2 = None
+                            
+                                
+                            # Check if filter_criteria exists and is not None (Subset the data based on filter criteria if provided)
+                            if filter_criteria:
+                                for column, condition in filter_criteria.items():
+                                    operation = condition['oper']
+                                    value = condition['value']
+                                    
+                                    if operation == "between" and isinstance(value, list) and len(value) == 2:
+                                        pairdf = pairdf[pairdf[column].between(vmin_y2, vmax_y2)]
+                            
+                            # Now proceed wit plotting, call the make_timeseries function with the subsetted pairdf (if vmin2 and vmax2 are not nOne) otherwise whole df                                 
                             if p_index == 0:
                                 # First plot the observations.
                                 ax = splots.make_timeseries(
@@ -1358,13 +1571,246 @@ def plotting(self):
                                 text_dict=text_dict,
                                 debug=self.debug
                             )
+
+                            # Extract text_kwargs from the appropriate plot group
+                            text_kwargs = grp_dict.get('text_kwargs', {'fontsize': 20})  # Default to fontsize 20 if not defined                            
+
                             # At the end save the plot.
                             if p_index == len(pair_labels) - 1:
+                                # Adding Altitude variable as secondary y-axis to timeseries (for, model vs aircraft) qzr++
+                                if 'altitude_yax2' in grp_dict['data_proc'] and 'altitude_variable' in grp_dict['data_proc']['altitude_yax2']:
+                                    altitude_yax2 = grp_dict['data_proc']['altitude_yax2']
+                                    ax = airplots.add_yax2_altitude(ax, pairdf, altitude_yax2, text_kwargs, vmin_y2, vmax_y2)
                                 savefig(outname + '.png', logo_height=150)
-                                del (ax, fig_dict, plot_dict, text_dict, obs_dict, obs_plot_dict) #Clear axis for next plot.
-                    
-                     
-                        if plot_type.lower() == 'boxplot':
+                                del (ax, fig_dict, plot_dict, text_dict, obs_dict, obs_plot_dict)  # Clear axis for next plot.
+                                
+                            # At the end save the plot.
+                            ##if p_index == len(pair_labels) - 1:
+                                #Adding Altitude variable as secondary y-axis to timeseries (for, model vs aircraft) qzr++
+                                
+                                #Older approach without 'altitude_yax2' control list in YAML now commented out
+                                ##if grp_dict['data_proc'].get('altitude_variable'):
+                                  ##  altitude_variable = grp_dict['data_proc']['altitude_variable']
+                                  ##  altitude_ticks = grp_dict['data_proc'].get('altitude_ticks', 1000)  # Get altitude tick interval from YAML or default to 1000
+                                  ##  ax = airplots.add_yax2_altitude(ax, pairdf, altitude_variable, altitude_ticks, text_kwargs)
+                                ##savefig(outname + '.png', logo_height=150)
+                                ##del (ax, fig_dict, plot_dict, text_dict, obs_dict, obs_plot_dict) #Clear axis for next plot.
+                                
+                        #qzr++ Added vertprofile plotype for aircraft vs model comparisons         
+                        elif plot_type.lower() == 'vertprofile':
+                            if set_yaxis == True:
+                                if all(k in obs_plot_dict for k in ('vmin_plot', 'vmax_plot')):
+                                    vmin = obs_plot_dict['vmin_plot']
+                                    vmax = obs_plot_dict['vmax_plot']
+                                else:
+                                    print('Warning: vmin_plot and vmax_plot not specified for ' + obsvar + ', so default used.')
+                                    vmin = None
+                                    vmax = None
+                            else:
+                                vmin = None
+                                vmax = None
+                            # Select altitude variable from the .yaml file
+                            altitude_variable = grp_dict['altitude_variable']
+                            # Define the bins for binning the altitude
+                            bins = grp_dict['vertprofile_bins']
+                            if p_index == 0:
+                                # First plot the observations.
+                                ax = airplots.make_vertprofile(
+                                    pairdf,
+                                    column=obsvar,
+                                    label=p.obs,
+                                    bins=bins,
+                                    altitude_variable=altitude_variable,
+                                    ylabel=use_ylabel,
+                                    vmin=vmin,
+                                    vmax=vmax,
+                                    domain_type=domain_type,
+                                    domain_name=domain_name,
+                                    plot_dict=obs_dict,
+                                    fig_dict=fig_dict,
+                                    text_dict=text_dict,
+                                    debug=self.debug,
+                                    interquartile_style=interquartile_style 
+                            )
+                            
+                            # For all p_index plot the model.
+                            ax = airplots.make_vertprofile(
+                                pairdf,
+                                column=modvar,
+                                label=p.model,
+                                ax=ax,
+                                bins=bins,
+                                altitude_variable=altitude_variable,
+                                ylabel=use_ylabel,
+                                vmin=vmin,
+                                vmax=vmax,
+                                domain_type=domain_type,
+                                domain_name=domain_name,
+                                plot_dict=plot_dict,
+                                text_dict=text_dict,
+                                debug=self.debug,
+                                interquartile_style=interquartile_style 
+                            )
+                            
+                            
+                            # At the end save the plot.
+                            if p_index == len(pair_labels) - 1:
+                                savefig(outname + '.png', logo_height=150)
+                                del (ax, fig_dict, plot_dict, text_dict, obs_dict, obs_plot_dict) # Clear axis for next plot.
+
+                        
+                        elif plot_type.lower() == 'violin':
+                            if set_yaxis:
+                                if all(k in obs_plot_dict for k in ('vmin_plot', 'vmax_plot')):
+                                    vmin = obs_plot_dict['vmin_plot']
+                                    vmax = obs_plot_dict['vmax_plot']
+                                else:
+                                    print('Warning: vmin_plot and vmax_plot not specified for ' + obsvar + ', so default used.')
+                                    vmin = None
+                                    vmax = None
+                            else:
+                                vmin = None
+                                vmax = None
+                            
+                            # Initialize the combined DataFrame for violin plots and labels/colors list
+                            if p_index == 0:
+                                comb_violin = pd.DataFrame()
+                                label_violin = []
+
+                                                       
+                            # Define a default color for observations
+                            default_obs_color = 'gray'  # Default color for observations
+                            
+                            # Inside your loop for processing each pair
+                            obs_label = p.obs
+                            model_label = p.model
+                            
+                            # Retrieve plot_kwargs for observation
+                            if hasattr(self.obs[p.obs], 'plot_kwargs') and self.obs[p.obs].plot_kwargs is not None:
+                                obs_dict = self.obs[p.obs].plot_kwargs
+                            else:
+                                obs_dict = {'color': default_obs_color}
+                            
+                            # Retrieve plot_kwargs for the model
+                            model_dict = self.models[p.model].plot_kwargs if self.models[p.model].plot_kwargs is not None else {'color': 'blue'} # Fallback color for models, in case it's missing
+                            
+                            # Call calculate_violin for observation data
+                            if p_index ==0:
+                                comb_violin, label_violin = airplots.calculate_violin(
+                                    df=pairdf,
+                                    column=obsvar,
+                                    label=obs_label,
+                                    plot_dict=obs_dict,
+                                    comb_violin=comb_violin,
+                                    label_violin=label_violin
+                                )
+                            
+                            # Call calculate_violin for model data
+                            comb_violin, label_violin = airplots.calculate_violin(
+                                df=pairdf,
+                                column=modvar,
+                                label=model_label,
+                                plot_dict=model_dict,
+                                comb_violin=comb_violin,
+                                label_violin=label_violin
+                            )
+
+                            
+                            # For the last pair, create the violin plot
+                            if p_index == len(pair_labels) - 1:
+                                airplots.make_violin_plot(
+                                    comb_violin=comb_violin,
+                                    label_violin=label_violin,
+                                    ylabel=use_ylabel,
+                                    vmin=vmin,
+                                    vmax=vmax,
+                                    outname=outname,
+                                    domain_type=domain_type,
+                                    domain_name=domain_name,
+                                    fig_dict=fig_dict,
+                                    text_dict=text_dict,
+                                    debug=self.debug
+                                )
+                            
+                            # Clear the variables for the next plot if needed
+                            if p_index == len(pair_labels) - 1:
+                                del (comb_violin, label_violin, fig_dict, plot_dict, text_dict, obs_dict, obs_plot_dict)
+
+                        
+
+                        elif plot_type.lower() == 'scatter_density':
+                            scatter_density_config = grp_dict
+
+                            
+                            # Extract relevant parameters from the configuration
+                            color_map = scatter_density_config.get('color_map', 'viridis')
+                            fill = scatter_density_config.get('fill', False)
+                            print(f"Value of fill after reading from scatter_density_config: {fill}") #Debugging
+
+                            
+                            vmin_x = scatter_density_config.get('vmin_x', None)
+                            vmax_x = scatter_density_config.get('vmax_x', None)
+                            vmin_y = scatter_density_config.get('vmin_y', None)
+                            vmax_y = scatter_density_config.get('vmax_y', None)
+                                                    
+                            # Accessing the correct model and observation configuration/labels/variables
+                            model_label = p.model
+                            obs_label = p.obs
+                            
+                            try:
+                                mapping = self.control_dict['model'][model_label]['mapping'][obs_label]
+                            except KeyError:
+                                print(f"Error: Mapping not found for model label '{model_label}' with observation label '{obs_label}' in scatter_density plot")
+                                continue  # Skip this iteration if mapping is not found
+                            
+                            obs_config = self.control_dict['obs'][obs_label]['variables'] # Accessing the correct observation configuration
+
+                            
+                            # Extract ylabel_plot for units extraction
+                            ylabel_plot = obs_config.get(obsvar, {}).get('ylabel_plot', f"{obsvar} (units)")
+                            title = ylabel_plot
+                            units = ylabel_plot[ylabel_plot.find("(")+1 : ylabel_plot.find(")")]
+                            xlabel = f"Model {modvar} ({units})"
+                            ylabel = f"Observation {obsvar} ({units})"
+
+                            
+
+                            
+                            # Exclude keys from kwargs that are being passed explicitly
+                            excluded_keys = ['color_map', 'fill', 'vmin_x', 'vmax_x', 'vmin_y', 'vmax_y', 'xlabel', 'ylabel', 'title', 'data']
+                            kwargs = {key: value for key, value in scatter_density_config.items() if key not in excluded_keys}
+                            if 'shade_lowest' in kwargs:
+                                kwargs['thresh'] = 0
+                                del kwargs['shade_lowest']
+
+
+
+                            
+                            # Create the scatter density plot
+                            print(f"Processing scatter density plot for model '{model_label}' and observation '{obs_label}'...")
+                            ax = airplots.make_scatter_density_plot(
+                                pairdf,
+                                mod_var=modvar,
+                                obs_var=obsvar,
+                                color_map=color_map,
+                                xlabel=xlabel,
+                                ylabel=ylabel,
+                                title=title,
+                                fill=fill,
+                                vmin_x=vmin_x,
+                                vmax_x=vmax_x,
+                                vmin_y=vmin_y,
+                                vmax_y=vmax_y,
+                                **kwargs                            
+                            )
+
+                            # Save the scatter density plot for the current pair immediately
+                            outname_pair = f"{outname}_{obs_label}_vs_{model_label}.png"
+                            print(f"Saving scatter density plot to {outname_pair}...")  # Debugging print statement
+                            plt.savefig(outname_pair)
+                            plt.close()  # Close the current figure
+                            
+                        elif plot_type.lower() == 'boxplot':
                             if set_yaxis == True:
                                 if all(k in obs_plot_dict for k in ('vmin_plot', 'vmax_plot')):
                                     vmin = obs_plot_dict['vmin_plot']
@@ -1496,6 +1942,10 @@ def plotting(self):
                             if p_index == len(pair_labels) - 1:
                                 savefig(outname + '.png', logo_height=70)
                                 del (dia, fig_dict, plot_dict, text_dict, obs_dict, obs_plot_dict) #Clear info for next plot.
+                       
+
+                        
+                        
                         elif plot_type.lower() == 'spatial_bias':
                             if set_yaxis == True:
                                 if 'vdiff_plot' in obs_plot_dict.keys():
diff --git a/melodies_monet/plots/__init__.py b/melodies_monet/plots/__init__.py
index c87e68d9..7d90b186 100644
--- a/melodies_monet/plots/__init__.py
+++ b/melodies_monet/plots/__init__.py
@@ -12,6 +12,7 @@
 __all__ = (
     "savefig",
     "surfplots",
+    "aircraftplots",
 )
 
 LOGO_PATH = Path(__file__).parent / "../data/MM_logo.png"
@@ -19,3 +20,4 @@
 savefig = partial(monet_savefig, logo=LOGO_PATH, loc=2, decorate=True, bbox_inches="tight", dpi=200)
 
 from . import surfplots
+from . import aircraftplots
diff --git a/melodies_monet/plots/aircraftplots.py b/melodies_monet/plots/aircraftplots.py
new file mode 100755
index 00000000..3ee5a03a
--- /dev/null
+++ b/melodies_monet/plots/aircraftplots.py
@@ -0,0 +1,812 @@
+# Copyright (C) 2022 National Center for Atmospheric Research and National Oceanic and Atmospheric Administration
+# SPDX-License-Identifier: Apache-2.0
+#
+'''
+aircraftplots.py
+this code is designed for plotting aircraft specific
+plot types 
+'''
+
+import os
+import monetio as mio
+import monet as monet
+import seaborn as sns
+from monet.util.tools import calc_8hr_rolling_max, calc_24hr_ave
+import xarray as xr
+import pandas as pd
+import numpy as np
+import cartopy.crs as ccrs
+import matplotlib as mpl
+import matplotlib.pyplot as plt
+from numpy import corrcoef
+sns.set_context('paper')
+from monet.plots.taylordiagram import TaylorDiagram as td
+from matplotlib.colors import TwoSlopeNorm, ListedColormap, LinearSegmentedColormap
+from matplotlib.patches import Rectangle
+from matplotlib.ticker import FuncFormatter
+from monet.util.tools import get_epa_region_bounds as get_epa_bounds 
+import math
+from ..plots import savefig
+from .surfplots import make_24hr_regulatory,calc_24hr_ave_v1,make_8hr_regulatory,calc_8hr_rolling_max_v1,calc_default_colors,new_color_map,map_projection,get_utcoffset,make_timeseries,make_taylor,calculate_boxplot,make_boxplot
+
+
+# Define a custom formatting function 
+def custom_yaxis_formatter(x, pos):
+    if x == int(x):
+        return str(int(x))
+    else:
+        return str(x)
+
+def make_spatial_bias(df, df_reg=None, column_o=None, label_o=None, column_m=None, 
+                      label_m=None, ylabel = None, ptile = None, vdiff=None,
+                      outname = 'plot', 
+                      domain_type=None, domain_name=None, fig_dict=None, 
+                      text_dict=None,debug=False):
+        
+    """Creates surface spatial bias plot. 
+    
+    Parameters
+    ----------
+    df : pandas.DataFrame
+        model/obs paired data to plot
+    df_reg : pandas.DataFrame
+        model/obs paired regulatory data to plot
+    column_o : str
+        Column label of observation variable to plot
+    label_o : str
+        Name of observation variable to use in plot title 
+    column_m : str
+        Column label of model variable to plot
+    label_m : str
+        Name of model variable to use in plot title
+    ylabel : str
+        Title of colorbar axis
+    ptile : integer
+        Percentile calculation
+    vdiff : float
+        Min and max value to use on colorbar axis
+    outname : str
+        file location and name of plot (do not include .png)
+    domain_type : str
+        Domain type specified in input yaml file
+    domain_name : str
+        Domain name specified in input yaml file
+    fig_dict : dictionary
+        Dictionary containing information about figure
+    text_dict : dictionary
+        Dictionary containing information about text
+    debug : boolean
+        Whether to plot interactively (True) or not (False). Flag for 
+        submitting jobs to supercomputer turn off interactive mode.
+        
+    Returns
+    -------
+    plot 
+        surface bias plot
+        
+    """
+    if debug == False:
+        plt.ioff()
+        
+    def_map = dict(states=True,figsize=[10, 5])
+    if fig_dict is not None:
+        map_kwargs = {**def_map, **fig_dict}
+    else:
+        map_kwargs = def_map
+        
+    #If not specified use the PlateCarree projection
+    if 'crs' not in map_kwargs:
+        map_kwargs['crs'] = ccrs.PlateCarree()
+  
+    #set default text size
+    def_text = dict(fontsize=20)
+    if text_dict is not None:
+        text_kwargs = {**def_text, **text_dict}
+    else:
+        text_kwargs = def_text
+        
+    # set ylabel to column if not specified.
+    if ylabel is None:
+        ylabel = column_o
+     
+    if ptile is None:
+        ylabel = 'Mean '+ylabel
+    else:
+        ylabel = '{:02d}'.format(ptile)+'th percentile '+ylabel
+ 
+    if df_reg is not None:
+        # JianHe: include options for percentile calculation (set in yaml file)
+        if ptile is None:
+            df_mean=df_reg.groupby(['siteid'],as_index=False).mean()
+        else:
+            df_mean=df_reg.groupby(['siteid'],as_index=False).quantile(ptile/100.)
+
+        #Specify val_max = vdiff. the sp_scatter_bias plot in MONET only uses the val_max value
+        #and then uses -1*val_max value for the minimum.
+        ax = monet.plots.sp_scatter_bias(
+            df_mean, col1=column_o+'_reg', col2=column_m+'_reg', map_kwargs=map_kwargs,val_max=vdiff,
+            cmap="OrangeBlue", edgecolor='k',linewidth=.8)
+    else:
+        # JianHe: include options for percentile calculation (set in yaml file)
+        if ptile is None:
+            df_mean=df.groupby(['siteid'],as_index=False).mean()
+        else:
+            df_mean=df.groupby(['siteid'],as_index=False).quantile(ptile/100.)
+       
+        #Specify val_max = vdiff. the sp_scatter_bias plot in MONET only uses the val_max value
+        #and then uses -1*val_max value for the minimum.
+        ax = monet.plots.sp_scatter_bias(
+            df_mean, col1=column_o, col2=column_m, map_kwargs=map_kwargs,val_max=vdiff,
+            cmap="OrangeBlue", edgecolor='k',linewidth=.8)
+    
+    if domain_type == 'all':
+        latmin= 25.0
+        lonmin=-130.0
+        latmax= 50.0
+        lonmax=-60.0
+        plt.title(domain_name + ': ' + label_m + ' - ' + label_o,fontweight='bold',**text_kwargs)
+    elif domain_type == 'epa_region' and domain_name is not None:
+        latmin,lonmin,latmax,lonmax,acro = get_epa_bounds(index=None,acronym=domain_name)
+        plt.title('EPA Region ' + domain_name + ': ' + label_m + ' - ' + label_o,fontweight='bold',**text_kwargs)
+    else:
+        latmin= math.floor(min(df.latitude))
+        lonmin= math.floor(min(df.longitude))
+        latmax= math.ceil(max(df.latitude))
+        lonmax= math.ceil(max(df.longitude))
+        plt.title(domain_name + ': ' + label_m + ' - ' + label_o,fontweight='bold',**text_kwargs)
+    
+    if 'extent' not in map_kwargs:
+        map_kwargs['extent'] = [lonmin,lonmax,latmin,latmax]  
+    ax.axes.set_extent(map_kwargs['extent'],crs=ccrs.PlateCarree())
+    
+    #Update colorbar
+    f = plt.gcf()
+    model_ax = f.get_axes()[0]
+    cax = f.get_axes()[1]
+    #get the position of the plot axis and use this to rescale nicely the color bar to the height of the plot.
+    position_m = model_ax.get_position()
+    position_c = cax.get_position()
+    cax.set_position([position_c.x0, position_m.y0, position_c.x1 - position_c.x0, (position_m.y1-position_m.y0)*1.1])
+    cax.set_ylabel(ylabel,fontweight='bold',**text_kwargs)
+    cax.tick_params(labelsize=text_kwargs['fontsize']*0.8,length=10.0,width=2.0,grid_linewidth=2.0)    
+    
+    #plt.tight_layout(pad=0)
+    savefig(outname + '.png', loc=4, logo_height=120)
+    
+####NEW function for adding 'altitude' variable as secondary y- axis (qzr++)
+def add_yax2_altitude(ax, pairdf, altitude_yax2, text_kwargs, vmin_y2, vmax_y2): 
+
+    """Creates secondary y-axis (altitude) for timeseries plot.
+    
+    Parameters
+    ----------
+    ax : ax
+        Matplotlib ax from previous occurrences so it can overlay obs and model results on the same plot.
+    pairdf : pandas.DataFrame
+        Model/obs paired data to plot.
+    text_kwargs : dictionary
+        Dictionary containing information about text.
+    altitude_yax2: dictionary
+        Secondary y-axis (altitude) control options, including altitude_variable, altitude_ticks, etc.
+    vmin_y2, vmax_y2: the value[0], value[1] respectively defined in filter_dict in altitude_yax2 in YAML control option 
+                
+    Returns
+    -------
+    ax : ax
+        Matplotlib ax such that driver.py can iterate to overlay multiple models on the same plot.
+    """
+    ax2 = ax.twinx()
+    
+    # Fetch altitude parameters from altitude_yax2
+    altitude_variable = altitude_yax2['altitude_variable']
+    altitude_ticks = altitude_yax2['altitude_ticks']
+    plot_kwargs_y2 = altitude_yax2.get('plot_kwargs_y2', {})
+    ylabel2 = altitude_yax2.get('ylabel2', 'Altitude')
+    
+    # Plot altitude
+    ax2.plot(pairdf.index, pairdf[altitude_variable], **plot_kwargs_y2, label=ylabel2)
+    
+    # Set labels, ticks, and limits
+    ax2.set_ylabel(ylabel2, fontweight='bold', fontsize=text_kwargs['fontsize'], color=plot_kwargs_y2.get('color', 'g'))
+    ax2.tick_params(axis='y', labelcolor=plot_kwargs_y2.get('color', 'g'), labelsize=text_kwargs['fontsize'] * 0.8)
+    ax2.set_ylim(vmin_y2, vmax_y2) 
+    ax2.set_xlim(ax.get_xlim())
+    start_tick = max(0, vmin_y2 - altitude_ticks)
+    ax2.yaxis.set_ticks(np.arange(start_tick, vmax_y2 + altitude_ticks + 1, altitude_ticks))
+
+    # Extract the current legend and add a custom legend for the altitude line
+    lines, labels = ax.get_legend_handles_labels()
+    lines.append(ax2.get_lines()[0])
+    labels.append(ylabel2)
+    ax.legend(lines, labels, frameon=False, fontsize=text_kwargs['fontsize'], bbox_to_anchor=(1.15, 0.9), loc='center left')
+
+    return ax
+
+                              
+####NEW vertprofile has option for both shading (for interquartile range) or box (interquartile range)-whisker (10th-90th percentile bounds) (qzr++)
+def make_vertprofile(df, column=None, label=None, ax=None, bins=None, altitude_variable=None, ylabel=None,
+                     vmin=None, vmax=None, 
+                     domain_type=None, domain_name=None,
+                     plot_dict=None, fig_dict=None, text_dict=None, debug=False, interquartile_style=None):
+    """Creates altitude profile plot.
+    
+    Parameters
+    ----------
+    df : pandas.DataFrame
+        Model/obs paired data to plot.
+    column : str
+        Column label of variable to plot.
+    label : str
+        Name of variable to use in plot legend.
+    ax : ax
+        Matplotlib ax from previous occurrence so it can overlay obs and model results on the same plot.
+    bins : int or array-like
+        Bins for binning the altitude variable.
+    altitude_variable: str
+        The Altitude variable in the paired df e.g., 'MSL_GPS_Altitude_YANG'
+    ylabel : str
+        Title of y-axis.
+    vmin : float
+        Min value to use on y-axis.
+    vmax : float
+        Max value to use on y-axis.
+    domain_type : str
+        Domain type specified in input yaml file
+    domain_name : str
+        Domain name specified in input yaml file
+    plot_dict : dictionary
+        Dictionary containing information about plotting for each pair
+        (e.g., color, linestyle, markerstyle).
+    fig_dict : dictionary
+        Dictionary containing information about the figure.
+    text_dict : dictionary
+        Dictionary containing information about text.
+    debug : bool
+        Whether to plot interactively (True) or not (False). Flag for submitting jobs to supercomputer turn off interactive mode.
+    interquartile_style= str
+        Whether the vertical profile uses shading or box style for interquartile range
+        
+    Returns
+    -------
+    ax : ax
+        Matplotlib ax such that driver.py can iterate to overlay multiple models on the same plot.
+    """
+    if debug == False:
+        plt.ioff()
+    
+    # First, define items for all plots
+    # Set default text size
+    def_text = dict(fontsize=14)
+    if text_dict is not None:
+        text_kwargs = {**def_text, **text_dict}
+    else:
+        text_kwargs = def_text
+    
+    # Set ylabel to column if not specified
+    if ylabel is None:
+        ylabel = column
+    if label is not None:
+        plot_dict['label'] = label
+    if vmin is not None and vmax is not None:
+        plot_dict['ylim'] = [vmin, vmax]
+    # Scale the fontsize for the x and y labels by the text_kwargs
+    plot_dict['fontsize'] = text_kwargs['fontsize'] * 0.8
+
+      
+                         
+    # Then, if no plot has been created yet, create a plot and plot the obs
+    if ax is None: 
+        # First define the colors for the observations
+        obs_dict = dict(color='k', linestyle='-', marker='*', linewidth=1.2, markersize=6.)
+        if plot_dict is not None:
+            # Whatever is not defined in the yaml file is filled in with the obs_dict here
+            plot_kwargs = {**obs_dict, **plot_dict} 
+        else:
+            plot_kwargs = obs_dict
+        # Create the figure
+        if fig_dict is not None:
+            f, ax = plt.subplots(**fig_dict)    
+        else: 
+            f, ax = plt.subplots(figsize=(10, 6))
+       
+        # Bin the altitude variable and calculate median and interquartiles
+        altitude_bins = pd.cut(df[altitude_variable], bins=bins)
+        # Calculate the midpoints of the altitude bins
+        bin_midpoints = altitude_bins.apply(lambda x: x.mid)
+        # Convert bin_midpoints to a column in the DataFrame
+        df['bin_midpoints'] = bin_midpoints
+        median = df.groupby(altitude_bins, observed=True)[column].median()
+        q1 = df.groupby(altitude_bins, observed=True)[column].quantile(0.25)
+        q3 = df.groupby(altitude_bins, observed=True)[column].quantile(0.75)
+        # Convert bin_midpoints to a numerical data type
+        df['bin_midpoints'] = df['bin_midpoints'].astype(float)
+
+        p5 = df.groupby(altitude_bins, observed=True)[column].quantile(0.05)
+        p10 = df.groupby(altitude_bins, observed=True)[column].quantile(0.10)
+        p90 = df.groupby(altitude_bins, observed=True)[column].quantile(0.90)
+        p95 = df.groupby(altitude_bins, observed=True)[column].quantile(0.95)
+        
+        # Calculate the mean of bin_midpoints grouped by altitude bins
+        binmidpoint = df.groupby(altitude_bins, observed=True)['bin_midpoints'].mean()
+
+        ##Plotting vertprofile starts
+        plot_kwargs_fillbetween = plot_kwargs.copy()
+        del plot_kwargs_fillbetween['marker']
+        del plot_kwargs_fillbetween['markersize']
+        del plot_kwargs_fillbetween['fontsize']
+
+       
+        # Copy the plot_kwargs outside the loop
+        plot_kwargs_fillbox = plot_kwargs.copy()
+        
+
+        # Define box properties for transparency
+        boxprops = {
+            'facecolor': 'none',  # Transparent facecolor
+        }
+
+        # Track labels that have been added to the legend
+        labels_added_to_legend = set()
+        
+        # Plot shaded interquartiles
+        plot_kwargs_fillbetween['label'] = f"{label} (interquartile 25th-75th percentile range)"
+        if interquartile_style == 'shading':
+            ax.fill_betweenx(binmidpoint.values, q1.values, q3.values, alpha=0.3, **plot_kwargs_fillbetween)
+        
+        # For interquartile_style == 'box' case
+        elif interquartile_style == 'box':
+            box_data = []
+            for idx in range(len(q1)):
+                # Create a dictionary for each box with the required statistics
+                box_data.append({
+                    'med': median.values[idx],
+                    'q1': q1.values[idx],
+                    'q3': q3.values[idx],
+                    'whislo': p10.values[idx],
+                    'whishi': p90.values[idx],
+                    'fliers': []
+                })        
+            
+            # Creating a vertical boxplot for each bin
+            for idx, data in enumerate(box_data):                
+                # Get the color for the label from plot_kwargs or use a default color
+                color = plot_kwargs_fillbox.get('color', 'black')
+                                                        
+                # Determine if the label should be added to the legend (only once for each label)
+                legend_label = label if idx == 0 else None
+
+                # Box properties
+                boxprops = {
+                    'facecolor': 'none',  # Transparent face color
+                    'edgecolor': color,   # Edge color matching the median line color
+                    'linewidth': 2        # Thickness of the box
+                }
+
+                # Whisker properties
+                whiskerprops = {
+                'color': color,       # Whisker color
+                'linewidth': 2        # Thickness of the whiskers
+                }
+
+                # Median line properties
+                medianprops = {
+                    'color': 'none'       # Transparent color for median line
+                }
+
+                capprops = {'color': color, 'linewidth': 2} # Whisker end bar properties
+
+                # Create the box plot
+                ax.bxp([data], vert=False, positions=[binmidpoint.values[idx]],
+                       widths=500, meanline=True, patch_artist=True, 
+                       boxprops=boxprops, whiskerprops=whiskerprops, medianprops=medianprops,
+                      capprops=capprops)
+
+                # Optional: Add a legend entry for the box (only once)
+                if legend_label and idx == 0:
+                    box_legend_artist = Rectangle((0, 0), 1, 1, facecolor='none', edgecolor=color, linewidth=2)
+                    ax.legend([box_legend_artist], [f"{legend_label} (box-whisker)"], loc='upper left')
+            
+
+        plot_kwargs['label'] = f"{label} (median)"
+        median_line_df = pd.DataFrame(data={'median': median.values, 'binmidpoint': binmidpoint.values})
+        ax = median_line_df.plot(x='median', y='binmidpoint', ax=ax, legend=True, **plot_kwargs)
+    
+    # If plot has been created, add to the current axes
+    else:
+        # This means that an axis handle already exists, so use it to plot the model output
+        altitude_bins = pd.cut(df[altitude_variable], bins=bins)
+        # Calculate the midpoints of the altitude bins
+        bin_midpoints = altitude_bins.apply(lambda x: x.mid)
+        # Convert bin_midpoints to a column in the DataFrame
+        df['bin_midpoints'] = bin_midpoints
+        # can be .groupby(bin_midpoints) as well (qzr)
+        median = df.groupby(altitude_bins, observed=True)[column].median()
+        q1 = df.groupby(altitude_bins, observed=True)[column].quantile(0.25)
+        q3 = df.groupby(altitude_bins, observed=True)[column].quantile(0.75)
+        # Convert bin_midpoints to a numerical data type
+        df['bin_midpoints'] = df['bin_midpoints'].astype(float)
+
+        # Calculate the 10th, 90th, 5th, and 95th percentiles
+        p10 = df.groupby(altitude_bins, observed=True)[column].quantile(0.10)
+        p90 = df.groupby(altitude_bins, observed=True)[column].quantile(0.90)
+        p5 = df.groupby(altitude_bins, observed=True)[column].quantile(0.05)
+        p95 = df.groupby(altitude_bins, observed=True)[column].quantile(0.95)
+
+        # Calculate the mean of bin_midpoints grouped by altitude bins
+        binmidpoint = df.groupby(altitude_bins, observed=True)['bin_midpoints'].mean()
+          
+        plot_kwargs_fillbetween = plot_dict.copy()
+        del plot_kwargs_fillbetween['marker']
+        del plot_kwargs_fillbetween['markersize']
+        del plot_kwargs_fillbetween['fontsize']  
+        
+        # Copy the plot_kwargs outside the loop
+        plot_kwargs_fillbox = plot_dict.copy()
+        
+        # Define box properties for transparency
+        boxprops = {
+            'facecolor': 'none',  # Transparent facecolor
+        }
+
+        # Track labels that have been added to the legend
+        labels_added_to_legend = set()
+        
+        plot_kwargs_fillbetween['label'] = f"{label} (interquartile 25th-75th percentile range)"
+        if interquartile_style == 'shading':
+            ax.fill_betweenx(binmidpoint.values, q1.values, q3.values, alpha=0.3, **plot_kwargs_fillbetween)
+        # For interquartile_style == 'box' case
+        elif interquartile_style == 'box':
+            box_data = []
+            for idx in range(len(q1)):
+                # Create a dictionary for each box with the required statistics
+                box_data.append({
+                    'med': median.values[idx],
+                    'q1': q1.values[idx],
+                    'q3': q3.values[idx],
+                    'whislo': p10.values[idx],
+                    'whishi': p90.values[idx],
+                    'fliers': []
+                })
+
+            # Creating a vertical boxplot for each bin
+            for idx, data in enumerate(box_data):
+                # Get the color for the label from plot_kwargs or use a default color
+                color = plot_kwargs_fillbox.get('color', 'black')
+
+                # Determine if the label should be added to the legend (only once for each label)
+                legend_label = label if idx == 0 else None
+
+                # Box properties
+                boxprops = {
+                    'facecolor': 'none',  # Transparent face color
+                    'edgecolor': color,   # Edge color matching the median line color
+                    'linewidth': 2        # Thickness of the box
+                }
+
+                # Whisker properties
+                whiskerprops = {
+                'color': color,       # Whisker color
+                'linewidth': 2        # Thickness of the whiskers
+                }
+
+                # Median line properties
+                medianprops = {
+                    'color': 'none'       # Transparent color for median line
+                }
+
+                capprops = {'color': color, 'linewidth': 2} # Whisker end bar properties
+
+                # Create the box plot
+                ax.bxp([data], vert=False, positions=[binmidpoint.values[idx]],
+                       widths=500, meanline=True, patch_artist=True, 
+                       boxprops=boxprops, whiskerprops=whiskerprops, medianprops=medianprops,
+                      capprops=capprops)
+
+                # Optional: Add a legend entry for the box (only once)
+                if legend_label and idx == 0:
+                    box_legend_artist = Rectangle((0, 0), 1, 1, facecolor='none', edgecolor=color, linewidth=2)
+                    ax.legend([box_legend_artist], [f"{legend_label} (box-whisker)"], loc='upper left')
+            
+        # Plot median line
+        plot_dict['label'] = f"{label} (median)"
+        median_line_df = pd.DataFrame(data={'median': median.values, 'binmidpoint': binmidpoint.values})
+        ax = median_line_df.plot(x='median', y='binmidpoint', ax=ax, legend=True, **plot_dict)
+        
+    
+    if interquartile_style == 'box':
+        # Add text to legend (adjust the x and y coordinates to place the text below the legend)
+        plt.text(1.12, 0.7, 'Bounds of box: Interquartile range\nWhiskers: 10th and 90th percentiles', transform=ax.transAxes, fontsize=text_kwargs['fontsize']*0.8)
+    # Apply the custom formatter to the y-axis (round off y-axis tick labels if after decimal its just zero)
+    ax.yaxis.set_major_formatter(FuncFormatter(custom_yaxis_formatter))                     
+    # Set parameters for all plots
+    ax.set_ylabel('Altitude (m)', fontweight='bold', **text_kwargs) 
+    ax.set_xlabel(ylabel, fontweight='bold', **text_kwargs) 
+    ax.legend(frameon=False,fontsize=text_kwargs['fontsize']*0.8)
+    ax.tick_params(axis='both',length=10.0,direction='inout')
+    ax.tick_params(axis='both',which='minor',length=5.0,direction='out')
+    #Adjust label position                         
+    ax.legend(frameon=False, fontsize=text_kwargs['fontsize']*0.8, bbox_to_anchor=(1.1, 0.9), loc='center left')
+
+    if domain_type is not None and domain_name is not None:
+        if domain_type == 'epa_region':
+            ax.set_title('EPA Region ' + domain_name,fontweight='bold',**text_kwargs)
+        else:
+            ax.set_title(domain_name,fontweight='bold',**text_kwargs)         
+                
+    breakpoint() #debug
+                         
+    return ax
+
+
+##NEW Scatter Density Plot for model obs pairs (matplotlib scatter plot if fill=False or seaborn kde sactter density plot if fill= True)
+def make_scatter_density_plot(df, mod_var=None, obs_var=None, ax=None, color_map='viridis', xlabel=None, ylabel=None, title=None, fill=False, vmin_x=None, vmax_x=None, vmin_y=None, vmax_y=None, **kwargs):
+    
+    """  
+    Creates a scatter density plot for the specified column (variable) in the paired DataFrame (df).
+
+    Parameters
+    --------
+
+    df: dataframe
+        Paired DataFrame containing the model and observation data to plot
+    obs_var: str
+        obs variable name in mapped pairs
+    mod_var: str
+        model variable name in mapped pairs
+    ax: Matplotlib axis from a previous occurrence to overlay obs and model results on the same plot
+    color_map: str
+        Colormap for the density (optional)
+    xlabel: str
+        Label for the x-axis (optional)
+    ylabel: str
+        Label for the y-axis (optional)
+    title: str
+        Title for the plot (optional)
+    fill: bool
+        Fill set to True for seaborn kde plot
+    **kwargs: dict 
+        Additional keyword arguments for customization
+
+    Returns
+    -------
+    ax : ax
+        Matplotlib ax such that driver.py can iterate to overlay multiple models on the same plot.
+    """
+
+    # Create a custom colormap based on color_map options in yaml or just use default colormap id color_map is just a string (e.g. viridis)
+    # Determine the normalization based on vcenter
+    vcenter = kwargs.get('vcenter', None)
+    
+    if vcenter is not None:
+        norm = TwoSlopeNorm(vcenter=vcenter, vmin=vmin_x, vmax=vmax_x)
+    else:
+        norm = None  # This means we'll use a default linear normalization
+
+    extensions = kwargs.get('extensions', None)  # Extract extensions for the colorbar
+    
+    # Check if the color_map key from the YAML file provides a dictionary 
+    # (indicating a custom colormap) or just a string (indicating a built-in colormap like 'magma', 'viridis' etc.).
+    color_map_config = color_map
+
+    #print(f"Color Map Config: {color_map_config}") #Debugging
+    
+    if isinstance(color_map_config, dict):
+        colors = color_map_config['colors']
+        over = color_map_config.get('over', None)
+        under = color_map_config.get('under', None)
+        
+        cmap = (mpl.colors.ListedColormap(colors)
+                .with_extremes(over=over, under=under))
+    else:
+        cmap = plt.get_cmap(color_map_config)
+
+    # Debug print statement to check the colormap configuration
+    #print(f"Using colormap: {cmap}") #Debugging
+
+    if isinstance(cmap, mpl.colors.ListedColormap):
+        cmap = LinearSegmentedColormap.from_list("custom", cmap.colors)
+
+
+    # Check if 'ax' is None and create a new subplot if needed
+    if ax is None:
+        fig, ax = plt.subplots()
+        
+    x_data = df[mod_var]
+    y_data = df[obs_var]
+
+    if fill:  # For KDE plot
+        #print("Generating KDE plot...")
+    
+        # Check the type of the colormap and set Seaborn's palette accordingly
+        if isinstance(cmap, mpl.colors.ListedColormap):
+            sns.set_palette(cmap.colors)
+        elif isinstance(cmap, mpl.colors.LinearSegmentedColormap):
+            # If it's a LinearSegmentedColormap, extract N colors from the colormap
+            N = 256
+            sns.set_palette([cmap(i) for i in range(N)])
+    
+        # Create the KDE fill plot using seaborn
+        plot = sns.kdeplot(x=x_data.dropna(), y=y_data.dropna(), cmap=cmap, norm=norm, fill=True, ax=ax, 
+                           **{k: v for k, v in kwargs.items() if k in sns.kdeplot.__code__.co_varnames})
+        colorbar_label = 'Density'
+        
+        # Get the QuadMesh object from the Axes for the colorbar and explicitly set its colormap
+        mappable = ax.collections[0]
+        mappable.set_cmap(cmap)
+        
+    else:  # For scatter plot using matplotlib
+        #print("Generating scatter plot...")
+        plot = plt.scatter(x_data, y_data, c=y_data, cmap=cmap, norm=norm, marker='o', 
+                           **{k: v for k, v in kwargs.items() if k in plt.scatter.__code__.co_varnames})
+        units = ylabel[ylabel.find("(")+1: ylabel.find(")")]
+        colorbar_label = units  # Units for scatter plot
+        mappable = plot
+
+    
+    # Set plot labels and titles
+    if xlabel:
+        plt.xlabel(xlabel, fontweight='bold')
+    if ylabel:
+        plt.ylabel(ylabel, fontweight='bold')
+    if title:
+        plt.title(title, fontweight='bold')
+    if vmin_x is not None:
+        plt.xlim(left=vmin_x)
+    if vmax_x is not None:
+        plt.xlim(right=vmax_x)
+    if vmin_y is not None:
+        plt.ylim(bottom=vmin_y)
+    if vmax_y is not None:
+        plt.ylim(top=vmax_y)
+
+    
+    # Handle the colorbar using the mappable object
+    if extensions:
+        cbar = plt.colorbar(mappable, extend='both', ax=ax)  # Extends the colorbar at both ends
+    else:
+        cbar = plt.colorbar(mappable, ax=ax)
+    cbar.set_label(colorbar_label)
+
+    plt.show()
+
+    return ax
+
+
+##NEW Violin plot 
+def calculate_violin(df, column=None, label=None, 
+                     plot_dict=None, comb_violin=None, label_violin=None):
+    """
+    Combines data into an acceptable format for violin plots, similar to calculate_boxplot for box plots.
+    
+    Parameters
+    ----------
+    df : pandas.DataFrame
+        DataFrame containing the model/obs paired data to plot.
+    column : str
+        Column label of the variable to plot.
+    label : str
+        Name of the variable to use in the plot legend.
+    plot_dict : dict
+        Dictionary containing color information for the plot.
+    comb_violin : pandas.DataFrame
+        DataFrame containing information to create violin plots from previous occurrences,
+        to overlay multiple model results on one plot.
+    label_violin : list
+        List of dictionaries with string labels and colors to use in the violin plot from previous occurrences,
+        to overlay multiple model results on one plot.
+        
+    Returns
+    -------
+    comb_violin : pandas.DataFrame
+        DataFrame containing information to create violin plots.
+    label_violin : list
+        List of dictionaries with string labels and colors to use in the violin plot.
+    """
+    if comb_violin is None and label_violin is None:
+        comb_violin = pd.DataFrame()
+        label_violin = []
+    #First define the colors for the observations.
+    obs_dict = dict(color='gray', linestyle='-',marker='x', linewidth=1.2, markersize=6.)
+    if plot_dict is not None:
+        #Whatever is not defined in the yaml file is filled in with the obs_dict here.
+        plot_kwargs = {**obs_dict, **plot_dict}
+    ##else:
+      ##  plot_kwargs = obs_dict
+    #else:
+    ##plot_kwargs = plot_dict
+    #For all, a column to the dataframe and append the label info to the list.
+    plot_kwargs['column'] = column
+    plot_kwargs['label'] = label
+    ##if df_reg is not None:
+      ##  comb_violin[label] = df_reg[column+'_reg']
+    ##else:
+    comb_violin[label] = df[column]
+    label_violin.append(plot_kwargs)
+    
+    return comb_violin, label_violin
+
+def make_violin_plot(comb_violin, label_violin, outname='plot',
+                     domain_type=None, domain_name=None,
+                     fig_dict=None, text_dict=None, debug=False,
+                     ylabel=None, vmin=None, vmax=None):  
+    """
+    Creates a violin plot using combined data from multiple model/observation datasets.
+
+    Parameters
+    ----------
+    comb_violin : pandas.DataFrame
+        DataFrame containing combined data for all datasets to be plotted.
+    label_violin : list
+        List of dictionaries with string labels and colors to use in the violin plot.
+    outname : str
+        File location and name of plot (do not include .png).
+    domain_type : str
+        Domain type specified in the input yaml file.
+    domain_name : str
+        Domain name specified in the input yaml file.
+    fig_dict : dict
+        Dictionary containing information about figure properties.
+    text_dict : dict
+        Dictionary containing information about text properties.
+    debug : bool
+        If True, the plot will be shown interactively. Useful for debugging.
+    ylabel : str, optional
+        The label for the y-axis.
+    vmin : float, optional
+        The minimum value for the y-axis.
+    vmax : float, optional
+        The maximum value for the y-axis.
+
+    Returns
+    -------
+    None
+    """
+
+    if not debug:
+        plt.ioff()
+    
+    # Set the order and palette based on label_violin
+    order = [item['label'] for item in label_violin]
+    palette = {item['label']: item['color'] for item in label_violin}
+
+    # Initialize figure
+    if fig_dict is not None:
+        plt.figure(**fig_dict)
+    
+    # Convert the DataFrame to long-form or "tidy" format suitable for sns.violinplot
+    melted_comb_violin = pd.melt(comb_violin, var_name='group', value_name='value')
+    
+    # Create the violin plot
+    
+    # Updated sns.violinplot call
+    # Use 'hue' parameter and set 'orient' to 'v' for vertical orientation
+    sns.violinplot(x='group', y='value', data=melted_comb_violin, hue='group', palette=palette, cut=0, orient='v', density_norm='width', inner='quartile')
+
+
+
+
+
+    # Set labels and title using text_dict
+    
+    # Set labels and title
+    def_text = dict(fontsize=14)
+    text_kwargs = {**def_text, **text_dict} if text_dict else def_text
+    plt.xlabel('', weight='bold', fontsize=text_kwargs['fontsize'])
+    plt.ylabel(ylabel if ylabel else 'Value', weight='bold', fontsize=text_kwargs['fontsize'])
+    
+    # Set y-axis limits if provided
+    if vmin is not None and vmax is not None:
+        plt.ylim(vmin, vmax)
+    
+    # Set title
+    if domain_type and domain_name:
+        plt.title(f"Violin Plot for {domain_type} - {domain_name}", fontweight='bold')
+
+    # Finalize and save plot
+    plt.tight_layout()
+    savefig(f"{outname}.png", loc=4, logo_height=100, dpi=300)
+    
+    # Close the plot if not in debug mode
+    if not debug:
+        plt.close()
+
diff --git a/melodies_monet/plots/surfplots.py b/melodies_monet/plots/surfplots.py
index 2ab10341..73c7826c 100755
--- a/melodies_monet/plots/surfplots.py
+++ b/melodies_monet/plots/surfplots.py
@@ -974,7 +974,7 @@ def make_boxplot(comb_bx, label_bx, ylabel = None, vmin = None, vmax = None, out
                                'markersize': 20.0}}
     sns.set_style("whitegrid")
     sns.set_style("ticks")
-    sns.boxplot(ax=ax,x="variable", y="value",data=pd.melt(comb_bx), **boxplot_kwargs)
+    sns.boxplot(ax=ax,x="variable", y="value",data=pd.melt(comb_bx), hue="variable", **boxplot_kwargs)
     ax.set_xlabel('')
     ax.set_ylabel(ylabel,fontweight='bold',**text_kwargs)
     ax.tick_params(labelsize=text_kwargs['fontsize']*0.8)
diff --git a/melodies_monet/util/__init__.py b/melodies_monet/util/__init__.py
index 3dda947e..110e9e8d 100644
--- a/melodies_monet/util/__init__.py
+++ b/melodies_monet/util/__init__.py
@@ -1,4 +1,5 @@
 # Copyright (C) 2022 National Center for Atmospheric Research and National Oceanic and Atmospheric Administration
 # SPDX-License-Identifier: Apache-2.0
 #
+
 __all__ = ['write_util','read_util','tools','satellite_utilites','hdfio','test_hdfio']
diff --git a/melodies_monet/util/read_util.py b/melodies_monet/util/read_util.py
index b505ebf2..e2b0965f 100644
--- a/melodies_monet/util/read_util.py
+++ b/melodies_monet/util/read_util.py
@@ -183,3 +183,35 @@ def xarray_to_class(class_type,group_ds):
         class_dict[group]=c
 
     return class_dict
+
+def read_aircraft_obs_csv(filename,time_var=None):
+    """Function to read .csv formatted aircraft observations.
+
+    Parameters
+    ----------
+    filename : str 
+        Filename of .csv file to be read
+    time_var : optional
+        The variable in the dataset that should be converted to 
+        datetime format, renamed to `time` and set as a dimension.
+        
+    Returns
+    -------
+    ds_out : xarray.Dataset
+        Xarray dataset containing information from .csv file
+
+    """
+    import xarray as xr
+    import pandas as pd
+    
+    df = pd.read_csv(filename)
+    if time_var is not None:
+        df.rename(columns={time_var:'time'},inplace=True)
+        df['time']  = pd.to_datetime(df['time'])
+        
+    # Sort the values based on time
+    df.sort_values(by='time',inplace=True,ignore_index=True)
+        
+    df.set_index('time',inplace=True)
+    
+    return xr.Dataset.from_dataframe(df)
diff --git a/melodies_monet/util/tools.py b/melodies_monet/util/tools.py
index 09a4fa8f..95cb19cc 100644
--- a/melodies_monet/util/tools.py
+++ b/melodies_monet/util/tools.py
@@ -271,3 +271,190 @@ def get_epa_region_df(df):
         df.loc[con, 'EPA_INDEX'] = i + 1
         df.loc[con, 'EPA_ACRO'] = acro
     return df
+
+def resample_stratify(da, levels, vertical, axis=1,interpolation='linear',extrapolation='nan'):
+    import stratify
+    import xarray as xr
+
+    result = stratify.interpolate(levels, vertical.chunk().data, da.chunk().data, axis=axis,
+                                 interpolation = interpolation,extrapolation = extrapolation)
+    dims = da.dims
+    out = xr.DataArray(result, dims=dims)
+    for i in dims:
+        if i != "z":
+            out[i] = da[i]
+    out.attrs = da.attrs.copy()
+    if len(da.coords) > 0:
+        for i in da.coords:
+            if i != "z":
+                out.coords[i] = da.coords[i]
+    return out
+
+def vert_interp(ds_model,df_obs,var_name_list):
+    import xarray as xr
+    from pandas import merge_asof, Series
+
+    var_out_list = []
+    for var_name in var_name_list:
+        if var_name == 'pressure_model':
+            out = resample_stratify(ds_model[var_name],sorted(ds_model.pressure_obs.squeeze().values,reverse=True),
+                                      ds_model['pressure_model'],axis=1,
+                                      interpolation='linear',extrapolation='nan')
+            #Use extrapolation nan for the pressure so that later you can assign the nan values to the pressure_obs value 
+            #instead of the midpoint of the edge model cells. This is needed for the pairing later on.
+        else:
+            out = resample_stratify(ds_model[var_name],sorted(ds_model.pressure_obs.squeeze().values,reverse=True),
+                                  ds_model['pressure_model'],axis=1,
+                                  interpolation='linear',extrapolation='nearest')
+        out.name = var_name
+        var_out_list.append(out)
+
+    df_model = xr.merge(var_out_list).to_dataframe().reset_index()
+    df_model.fillna({'pressure_model':df_model.pressure_obs},inplace=True)
+    df_model.drop(labels=['x','y','z','pressure_obs','time_obs'], axis=1, inplace=True)
+    df_model.rename(columns={'pressure_model':'pressure_obs'}, inplace=True)
+
+    final_df_model = merge_asof(df_obs, df_model, 
+                            by=['latitude', 'longitude', 'pressure_obs'], 
+                            on='time', direction='nearest')
+
+    return final_df_model
+
+def mobile_and_ground_pair(ds_model,df_obs, var_name_list):
+    import xarray as xr
+    from pandas import merge_asof, Series
+    
+    var_out_list = []
+    # Extract just the surface level data from correct model variables
+    # if there is a z dimension, extract the surface, otherwise assume data is at surface and issue warning
+    if 'z' in ds_model.dims:
+        for var_name in var_name_list:
+            out = ds_model[var_name].isel(z=0)
+            out.name = var_name
+            var_out_list.append(out)
+    else:
+        print('WARNING: No z dimension in model, assuming all data at surface.')
+        for var_name in var_name_list:
+            out = ds_model[var_name]
+            out.name = var_name
+            var_out_list.append(out)
+    
+    df_model = xr.merge(var_out_list).to_dataframe().reset_index()
+    df_model.drop(labels=['x','y','time_obs'], axis=1, inplace=True)
+
+    final_df_model = merge_asof(df_obs, df_model, 
+                            by=['latitude', 'longitude'], 
+                            on='time', direction='nearest')
+
+    return final_df_model
+
+def find_obs_time_bounds(files=[],time_var=None):
+    """Function to read a series of ict files and print a list of min and max times for each.
+
+    Parameters
+    ----------
+    files : str or iterable
+        str or list of str containing filenames that should be read.
+        
+    time_var : str
+        Optional, variable name that should be assumed to be time when reading aircaft csv files.
+
+    Returns
+    -------
+    bounds : dict
+        Dict containing time bounds for each file.
+
+    """
+    import os 
+    import monetio as mio
+    import xarray as xr
+    
+    if isinstance(files,str):
+        files = [files]
+    
+    bounds = {}
+    for file in files:
+        _, extension = os.path.splitext(files[0])
+        try:
+            if extension in {'.nc', '.ncf', '.netcdf', '.nc4'}:
+                obs = xr.open_dataset(file)
+            elif extension in ['.ict', '.icartt']:
+                obs = mio.icartt.add_data(file)
+            elif extension in ['.csv']:
+                from .read_util import read_aircraft_obs_csv
+                obs = read_aircraft_obs_csv(filename=file,time_var=time_var)
+            else:
+                raise ValueError(f'extension {extension!r} currently unsupported')
+        except Exception as e:
+            print('something happened opening file:', e)
+            return
+        
+        time_min = obs['time'].min()
+        time_max = obs['time'].max()
+        
+        print('For {}, time bounds are, Min: {}, Max: {}'.format(file,time_min,time_max))
+        bounds[file] = {'Min':time_min,'Max':time_max}
+
+        del obs
+        
+    return bounds
+
+def loop_pairing(control,file_pairs_yaml='',file_pairs={},save_types=['paired']):
+    """Function to loop over sets of pairings and save them out as multiple netcdf files.
+    
+    Parameters
+    ----------
+    control : str
+        str containing path to control file.
+        
+    file_pairs : dict (optional)
+        Dict containing filenames for obs and models. This should be specified if file_pairs_yaml is not. 
+        An example can be found below::
+        
+            file_pairs = {'0722':{'model':{'wrfchem_v4.2':'/wrk/users/charkins/melodies-monet_data/wrfchem/run_CONUS_fv19_BEIS_1.0xISO_RACM_v4.2.2_racm_berk_vcp_noI_phot/0722/*'},
+                          'obs':{'firexaq':'/wrk/d2/rschwantes/obs/firex-aq/R1/10s_merge/firexaq-mrg10-dc8_merge_20190722_R1.ict'}},
+                '0905':{'model':{'wrfchem_v4.2':'/wrk/users/charkins/melodies-monet_data/wrfchem/run_CONUS_fv19_BEIS_1.0xISO_RACM_v4.2.2_racm_berk_vcp_noI_phot_soa/0905/*'},
+                        'obs':{'firexaq':'/wrk/d2/rschwantes/obs/firex-aq/R1/10s_merge/firexaq-mrg10-dc8_merge_20190905_R1.ict'}}
+                }
+        
+    file_pairs_yaml : str (optional)
+        str containing path to a yaml file with file pairings. 
+        An example of the yaml file can be found in ``examples/yaml/supplementary_yaml/aircraft_looping_file_pairs.yaml``
+        
+    save_types : list (optional)
+        List containing the types of data to save to netcdf. Can include any of 'paired', 'models', and 'obs'
+    
+    Returns
+    -------
+    None
+
+    """
+    from melodies_monet import driver
+    
+    if file_pairs_yaml:
+        import yaml
+        with open(file_pairs_yaml, 'r') as stream:
+            file_pairs = yaml.safe_load(stream)
+    
+    for file in file_pairs.keys():
+    
+        an = driver.analysis()
+        an.control=control
+        an.read_control()
+    
+        for model in an.control_dict['model']:
+            an.control_dict['model'][model]['files'] = file_pairs[file]['model'][model]
+        for obs in an.control_dict['obs']:
+            an.control_dict['obs'][obs]['filename'] = file_pairs[file]['obs'][obs]
+        
+        an.control_dict['analysis']['save']={}
+        an.save={}
+        for t in save_types:
+            an.control_dict['analysis']['save'][t]={'method':'netcdf','prefix':file,'data':'all'}
+            an.save[t]={'method':'netcdf','prefix':file,'data':'all'}
+        
+        an.open_models()
+        an.open_obs()
+        an.pair_data()
+        an.save_analysis()
+
diff --git a/melodies_monet/util/write_util.py b/melodies_monet/util/write_util.py
index 1173405c..563839b2 100644
--- a/melodies_monet/util/write_util.py
+++ b/melodies_monet/util/write_util.py
@@ -7,6 +7,8 @@
 def write_analysis_ncf(obj, output_dir='', fn_prefix=None, keep_groups=None, title=''):
     """Function to write netcdf4 files with some compression for floats from an attribute of the
     analysis class (models, obs, paired). Writes the objects within the attribute as separate files.
+    Any characters in variable names that are not allowed in netcdf4 variables names will be dropped.
+    Full variable names will always be saved in the variable attribute `long_name`.
 
     Parameters
     ----------
@@ -43,6 +45,26 @@ def write_analysis_ncf(obj, output_dir='', fn_prefix=None, keep_groups=None, tit
         print('Writing:', output_name)
         
         dset=obj[group].obj
+                
+        # Write long_name and remove any illegal characters from variable names 
+        rename_dict={}
+        allowed_chars = ['a','b','c','d','e','f','g','h','i','j','k','l','m',
+                            'n','o','p','q','r','s','t','u','v','w','x','y','z',
+                            'A','B','C','D','E','F','G','H','I','J','K','L','M',
+                            'N','O','P','Q','R','S','T','U','V','W','X','Y','Z'
+                            '0','1','2','3','4','5','6','7','8','9',
+                            '_','.','@','+','-']
+        for i in dset.variables:
+            dset[i].attrs['long_name']=i
+            illegal_chars = i.translate(str.maketrans('','',"".join(allowed_chars)))
+            if illegal_chars:
+                rename_dict[i]= i.translate(str.maketrans('','',"".join(illegal_chars)))
+        if rename_dict:
+            dset = dset.rename(rename_dict)
+            print('WARNING: The following variables have been renamed due to illegal characters in the variable name for netcdf4 format. ')
+            print('The original variable names can be found in the `long_name` variable attribute. ')
+            print(list(rename_dict.keys()))
+        
         comp = dict(zlib=True, complevel=7)
         encoding = {}
         for i in dset.data_vars.keys():
@@ -50,6 +72,7 @@ def write_analysis_ncf(obj, output_dir='', fn_prefix=None, keep_groups=None, tit
             #     print("Compressing: {}, original_dtype: {}".format(i, dset[i].dtype))
             #     dset[i] = compress_variable(dset[i])
                 encoding[i] = comp
+        
         dset.attrs['title'] = title
         dset.attrs['format'] = 'NetCDF-4'
         dset.attrs['date_created'] = pd.to_datetime('today').strftime('%Y-%m-%d')