CONTROL ID: 1819758

TITLE: Design and Development of a Community Carbon Cycle Benchmarking System for CMIP5 Models

AUTHORS (FIRST NAME, LAST NAME): Mingquan Mu1, Forrest M. Hoffman1, 2, David M. Lawrence3, William J. Riley4, Gretchen Keppel-Aleks1, James Tremper Randerson1

INSTITUTIONS (ALL): 1. Earth System Science, University of California Irvine, Irvine, CA, United States.
2. Computational Earth Sciences Group, Oak Ridge National Laboratory, Oak Ridge, TN, United States.
3. National Center for Atmospheric Research, Boulder, CO, United States.
4. Lawrence Berkeley National Laboratory, Berkeley, CA, United States.

ABSTRACT BODY: Benchmarking has been widely used to assess the ability of atmosphere, ocean, sea ice, and land surface models to capture the spatial and temporal variability of observations during the historical period. For the carbon cycle and terrestrial ecosystems, the design and development of an open-source community platform has been an important goal as part of the International Land Model Benchmarking (ILAMB) project. Here we designed and developed a software system that enables the user to specify the models, benchmarks, and scoring systems so that results can be tailored to specific model intercomparison projects. We used this system to evaluate the performance of CMIP5 Earth system models (ESMs). Our scoring system used information from four different aspects of climate, including the climatological mean spatial pattern of gridded surface variables, seasonal cycle dynamics, the amplitude of interannual variability, and long-term decadal trends. We used this system to evaluate burned area, global biomass stocks, net ecosystem exchange, gross primary production, and ecosystem respiration from CMIP5 historical simulations. Initial results indicated that the multi-model mean often performed better than many of the individual models for most of the observational constraints.

INDEX TERMS: 0428 BIOGEOSCIENCES Carbon cycling, 1622 GLOBAL CHANGE Earth system modeling, 3275 MATHEMATICAL GEOPHYSICS Uncertainty quantification, 0530 COMPUTATIONAL GEOPHYSICS Data presentation and visualization.
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