PermaModel project enables the broader use of permafrost models and consists of several permafrost models representing a range of capability and complexity. The PermaModel provides easy online access to everyone who want to use permafrost models, but lack the expertise and resources to develop them. It includes multiple sets of sample inputs representing a variety of conditions and locations to enable immediate use of any out of three permafrost models. It is built on the Community Surface Dynamics Modeling System (CSDMS) Modeling Framework platform. CSDMS provides an on-line environment where users can link and run models from multiple Earth science disciplines. We hope that the simple user interfaces, easy online access, open source models, and quick visualization tools can make permafrost models accessible to a broad audience well beyond the permafrost research community. These new easy-to-use modeling tools could be useful to wide-range of users beyond the research community, such as educators, students, and policy-makers.
Permamodel is a collection of numerical permafrost models
Calculates the frost number--an indication of the probability of finding permafrost--at a site. There are different versions of the frost number depending on what data area available at the site.
The air frost number requires some indication of the annual temperature cycle.
The surface frost number also requires indication of the year's precipitation.
The Stefan frost number additionally incorporates soil information.
A sample project that exists as an aid to the Python Packaging User Guide <https://packaging.python.org>'s Tutorial on Packaging and Distributing Projects <https://packaging.python.org/en/latest/distributing.html>.
This projects does not aim to cover best practices for Python project development as a whole. For example, it does not provide guidance or tool recommendations for version control, documentation, or testing.
Implements a semi-empirical/analytical solution to soil conditions, please cite:
Wang, K., Jafarov, E., & Overeem, I. (2020). Sensitivity evaluation of the Kudryavtsev permafrost model. Science of The Total Environment, 137538. https://doi.org/10.1016/j.scitotenv.2020.137538
Overeem, I., E. Jafarov, K. Wang, K. Schaefer, S. Stewart, G. Clow, M. Piper, and Y. Elshorbany (2018). A modeling toolbox for permafrost landscapes. Eos. https://doi.org/10.1029/2018EO105155.
GIPL is a detailed numerical model that solves for the temperature profile of a soil column given its material properties and the temperature and precipitation conditions it experiences. For more information please see https://github.com/Elchin/GIPL
The suite of permamodel routines as well as some useful ancillary packages can be installed using the bash script:
permamodel/permamodel/examples/install_pm.sh
If this file is downloaded to your system, you can change it to executable and run it with:
chmod +x ./install_pm.sh ./install_pm.sh
By default, this will install a Python 2.7 environment and the permamodel suite to the subdirectory ./pm_env (or a different subdirectory, if specified as a command line argument to install_pm.sh).