ILAMB 2.4

The International Land Model Benchmarking Package

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

  • CLM - land comparison against 3 CLM versions

  • CMIP5 - land comparison against a collection of CMIP5 models

  • IOMB - ocean comparison against a few ocean models

• Paper published in JAMES which details the design and methodology employed in the ILAMB package. If you find the package or the ouput helpful in your research or development efforts, we kindly ask you to cite this work.

ILAMB 2.4 Release

This release marks an important technical shift in ILAMB development–ILAMB v2.4 and onward will be python3 only. If you are new to python, it might seem strange that python3 has been released for 10 years and yet python2 is still ubiquitous. There is now an official announcement that python2 will reach its end of life at the end of 2019. Furthermore there is a growing list of popular python packages (most of our dependencies) that are phasing out support for python2 during this year. So in keeping with this community trend, the last version of ILAMB which will be compatible with python2.7x is 2.3.1, version 2.4 and beyond will by python3 only.

Part of my reason for sticking with python2 for so long was that ILAMB was designed to run on large machines whose software stacks are often not frequently updated. I wanted to ensure that ILAMB would run on old software. However, this is less an issue as computing centers are moving away from providing users with python packages they load via center-supported environment modules and towards users creating personalized environments using conda. Look for the ilamb.yml file in the repository which conda can use to create an environment that will support an ILAMB installation. If these words do not mean anything to you, look for a more detailed explanation in the tutorials which have be rewritten to reflect this shift.

We have published a paper in JAMES which details the methodology which this package implements. If you find ILAMB helpful in your research, we would appreciate a citation to this work as it helps us communicate the impact that these investments have on the community.

The collection of land surface confrontations now includes the emulation of CO₂fluxes. The default setup is to compare nbp fluxes to those recorded at a subset of NOAA sites, but this is configurable from inside the configure file. Browse the CMIP5 output for an overview of what this addition provides.

Finally, we are making some shifts in how we support ILAMB. Until now, I have directed user questions to my personal email. This is still ok, however consider joining the ILAMB mailing list and sending your questions there. Not only does this open up your question to being answered more quickly by the community, but the answers are searchable which may help the next user. In addition to this, we have a Slack channel if you prefer to ask your questions there. This has more of a chat interface but the conversations are all still public and searchable by the members.

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.