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title: ILAMB
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ILAMB
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International Land Model Benchmarking
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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, described below, the goals of ILAMB are to:

1. develop internationally accepted benchmarks for land model performance,

2. promote the use of these benchmarks by the international community for model intercomparison,

3. strengthen linkages between experimental, remote sensing, and climate modeling communities in the design of new model tests and new measurement programs, and

4. support the design and development of a new, open source, benchmarking software system for use by the international community.

<table align="right"><tr><td><a border="0" target="_blank" href="https://www.ilamb.org/meetings/washington2016/2016_ILAMB_Report_V10_web.pdf"><img width="193" height="250" src="https://www.ilamb.org/meetings/washington2016/2016_ILAMB_Report_cover_small.jpg"></a></td></tr></table>

Improving the representation of the carbon cycle and land surface
processes in climate models requires extensive comparison of model results
with observations. This process is difficult and time intensive. Past
data-model intercomparisons have strengthened the representation
of key processes in land models, but often this information has not
been easily accessible for use by other modeling teams or in future
intercomparisons. Specifically, there is a large cost in developing
the infrastructure to make meaningful model-data comparisons, even when
the data are freely and easily available. Further, the development of
sophisticated model diagnostics programs—that can fully exploit
the richness of large Earth System data sets like satellite or
Fluxnet measurements—are outside the scope of any single modeling
center. Thus, an important direction for the field is the development
of a community-based model evaluation system that is open source and
modular, allowing for contributions by many different modeling and
measurement teams.

Multiple past intercomparison efforts provide a foundation a new
international benchmarking activity. C4MIP provided the community with an
elegant conceptual framework for diagnosing the causes of model-to-model
differences in feedback strength (Friedlingstein et al., 2006; Gregory et
al., 2009). The Carbon-Land Model Intercomparison Project (C-LAMP) also
was a first step in this direction (Hoffman et al., 2008; Randerson et
al., 2009). Nine different classes of observations were used to evaluate
two biogeochemistry models (CASA′ and CN) within the Community Climate
System Model. For each class of observations, the models received a
score based on the quality of the fit with the measurements. Information
from different data streams were weighted by the relative importance
of the observational constraint, the uncertainty in the observations,
and the uncertainty in the model. The code and model output from C-LAMP
is publicly available and is now being used by several modeling centers
in Europe and in the U.S.

<strong>Quick links</strong>:&nbsp;
<a href="https://bitbucket.org/ncollier/ilamb">Repository</a>,
<a href="http://ilamb.ornl.gov/doc/install.html">Installation</a>,
<a href="http://ilamb.ornl.gov/doc/tutorial.html">Tutorials</a>,
<a href="http://ilamb.ornl.gov/CMIP5">CMIP5 Results</a>,
<a href="http://ilamb.ornl.gov/CLM">CLM Results</a>

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