The International Land Model Benchmarking Package
Project description
The International Land Model Benchmarking (ILAMB) project is a model-data intercomparison and integration project designed to improve the performance of land models and, in parallel, improve the design of new measurement campaigns to reduce uncertainties associated with key land surface processes. Building upon past model evaluation studies, the goals of ILAMB are to:
develop internationally accepted benchmarks for land model performance, promote the use of these benchmarks by the international community for model intercomparison,
strengthen linkages between experimental, remote sensing, and climate modeling communities in the design of new model tests and new measurement programs, and
support the design and development of a new, open source, benchmarking software system for use by the international community.
It is the last of these goals to which this repository is concerned. We have developed a python-based generic benchmarking system, initially focused on assessing land model performance.
Useful Information
Documentation - installation and basic usage tutorials
Sample Output
If you find the package or the ouput helpful in your research or development efforts, we kindly ask you to cite the following reference (DOI:10.18139/ILAMB.v002.00/1251621).
ILAMB 2.2 Release
We are pleased to announce version 2.2 of the ILAMB python package. Among many small bugfixes and enhancements, the new version contains the following new features:
A new installed command ilamb-fetch has been included which can be run to automatically download the observational datasets. Running this command after the data has been downloaded will check your collection for updates and consistency.
A new installed command ilamb-doctor has been included which can be run with options similar to ilamb-run to help identify which values a particular configure file needs in order to run.
ILAMB will now check the spatial extents of all the models present in the current run and clip away to the largest shared extent. This allows ILAMB to be applied to regional models.
User-defined regions can now be added at runtime either by specifying latitude/longitude bounds, or a mask in a netCDF4 file. For specifics, consult the regions tutorial.
Added a runoff and evaporative fraction benchmark to the ILAMB canon, removed the GFED3 and GFED4 burned area data products.
Added many more plots to the generic output including the RMSE and the score maps.
The ILAMB core has been enhanced to better handle depths. This has enabled ocean comparisons among others.
An initial collection of ocean datasets has been assembled in the demo/iomb.cfg file for ocean benchmarking.
The plotting phase of ilamb-run may now be skipped with the --skip_plots option.
Relationship overall scores are now available in an image on the main html output page.
Additional tutorials have been added to explain these new features.
Funding
This research was performed for the Reducing Uncertainties in Biogeochemical Interactions through Synthesis and Computation (RUBISCO) Scientific Focus Area, which is sponsored by the Regional and Global Climate Modeling (RGCM) Program in the Climate and Environmental Sciences Division (CESD) of the Biological and Environmental Research (BER) Program in the U.S. Department of Energy Office of Science.
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