Metadata-Version: 1.1
Name: ILAMB
Version: 2.5
Summary: The International Land Model Benchmarking Package
Home-page: https://bitbucket.org/ncollier/ilamb
Author: Nathan Collier
Author-email: nathaniel.collier@gmail.com
License: UNKNOWN
Description: ILAMB 2.5 Release
        =================
        
        We are pleased to announce a new version of the ILAMB package. In
        addition to a new version, the ILAMB repository is now hosted at:
        
          `https://github.com/rubisco-sfa/ILAMB <https://github.com/rubisco-sfa/ILAMB>`_
        
        This release includes some interface improvements as well as core
        technology enhancements increasing speed and reliability. See the
        following list for major changes:
        
        * The landing `page <http://www.ilamb.org/CMIP6/historical/>`_
          generated from `ilamb-run` has received an overhaul. We have merged
          the two tabs with the image and data into one dynamic table which
          can be clicked. Clicking on a row header will either expand the row
          or take you to the dataset page. Clicking on a particular model's
          square will take you to the dataset page with that particular model
          highlighted. In addition to this, you can now select which scalar
          you wish to plot in the table (i.e. Overall Score, Bias Score) over
          any region included in the study.
        * The appearance of the `Data Information` tabs on the dataset pages
          has been greatly enhanced. References can be included in the netCDF
          files in Bibtex format and will be rendered inside of
          ILAMB. Hyperlinks also will be detected and rendered as clickable
          links in the output pages. Thanks to Mingquan Mu for this addition.
        * Added a soil carbon temperature sensitivity metric from Charlie
          Koven, added this to our curated configure file `cmip.cfg`.
        * The CO2 emulation code will now account for ocean and fossil fuel
          fluxes when emulating the land model's `nbp`. Thanks to Ke Xu for this
          contribution.
        * We have added new datasets `LORA
          <http://dx.doi.org/10.25914/5b612e993d8ea>`_ for runoff and `DOLCE
          <http://dx.doi.org/10.4225/41/58980b55b0495>`_ for latent
          heat. While these datasets include uncertainty estimates, we are
          currently not making use of them in our analysis.
        * We have replaced `basemap <https://github.com/matplotlib/basemap>`_
          in favor of `cartopy <https://github.com/SciTools/cartopy>`_ as the
          tool for plotting on maps. Not only is this needed as basemap is
          being deprecated, but plotting is now approximately 10x faster. For
          the most part, this change will be invisible to the user.
        * Added options and structure to `ilamb-run` to improve runtimes. If
          running a large set of models on a cluster, we recommend first
          running with the `--skip_plots` option and using a low number of
          processes per node. This is because memory utilization tends to
          dominate the analysis phase and you do not want to run out. Then you
          can submit a second job without `--skip_plots` and using a large
          number of processes per node.
        * Intermediate files generated during `ilamb-run` will now include a
          `complete` flag, initialized to `False` and only flagged true if the
          file closed at the end of the analysis phase without error. This
          helps us reinitialize `ilamb-run` when a parallel run crashes and
          leaves file present and not corrupted, but neither complete.
        * If the `psutil` python package is installed, `ilamb-run` will now
          log the peak memory being used during the analysis phase in the
          logfiles along with the node name and process rank. This is to help
          in memory debugging for when high resolution models are being run.
        * In addition to this, `ilamb-run` now caches the model initialization
          process which should speed up re-initialization for when multiple
          jobs must be submitted.
        * Added initial support for uncertainty bounds in the
          ILAMB.Variable. If uncertainty is included in the observations, such
          as in the Hoffman `nbp` dataset, then ILAMB will automatically
          operate of it and show it as a shading in plots without changes to
          your scripts.
        * `ilamb-fetch` now will correctly try to decode server SSL
          certificates before downloading files. However, the authority that
          `www.ilamb.org` uses to create its certificates is not in the list
          that python supports. Your browser maintains a different list of
          authorities, which is why you can navigate to sites like `this
          <http://www.ilamb.org/CMIP6/historical/>`_. You will likely need to
          run with the `--no-check-certificate` option which implies that you
          trust that we are who we say we are.
        
        Useful Information
        ------------------
        
        * `Documentation <https://www.ilamb.org/doc/>`_ - installation and
          basic usage tutorials
        * Sample Output
          
          * `CMIP6 <http://www.ilamb.org/CMIP6/historical/>`_ - land comparison against a collection of CMIP6 models
          * `CMIP5 vs CMIP6 <http://www.ilamb.org/CMIP6/historical/>`_ - land comparison against a collection of CMIP5 and CMIP6 models
          * `IOMB <http://www.ilamb.org/IOMB/>`_ - ocean comparison against a few ocean models
        
        * `Paper <https://doi.org/10.1029/2018MS001354>`_ published in JAMES
          which details the design and methodology employed in the ILAMB
          package. If you find the package or the output helpful in your
          research or development efforts, we kindly ask you to cite this
          work.
        
        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.
        
        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.
        
Keywords: benchmarking,earth system modeling,climate modeling,model intercomparison
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Classifier: Operating System :: MacOS
Classifier: Operating System :: POSIX
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: Python :: 3
