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Jose M. Gutierrez edited this page Apr 19, 2018 · 8 revisions

downscaleR builds on the data structures of the climate4R bundle (regular and irregular/station grids). The manipulation and transformation functions for these data structures are packed in transformeR, which allows to easily perform typical climate data postprocessing in a flexible way, including:

  • Spatial and temporal subsetting and aggregation
  • Regridding and interpolation
  • Detrending and application of different time filters
  • EOF/PCA analysis
  • Clustering and weather typing (soon available).
  • etc.

It also contains several buit-in climate datasets (data(package = "transformeR")) and provides parallel computing support and different internal utilities for the R package downscaleR. For details and worked examples on the use of transformeR go to the corresponding wiki.

NOTE: The utilities in transformeR were formerly part of downscaleR (up to v1.3-4). Since downscaleR v2.0-0, these are in transformeR and downscaleR is strictly aimed to statistical downscaling and bias correction.

downscaleR - Santander MetGroup (Univ. Cantabria - CSIC)

  1. Package Installation
  2. Data manipulation with transformeR
  3. Bias Correction
    1. Calibration and cross validation
      1. Working with a moving window
    2. Bias correction of climate change projections
    3. Bias correction of seasonal forecasts
    4. How to contribute with new bias correction methods
  4. Downscaling: Perfect Prognosis Approach
    1. Preparing predictor data
    2. Training and cross-validation
    3. Downscaling climate change projections
    4. Downscaling seasonal forecasts
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