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Multi-Scale Synthesis and Terrestrial Model Intercomparison Project – A Systematic Approach for Evaluating Land-Atmosphere Flux Estimates

Deborah Nicole Huntzinger, Northern Arizona University, deborah.huntzinger@nau.edu
Christopher R Schwalm, Northern Arizona University, christopher.schwalm@nau.edu (Presenter)
Anna M Michalak, Stanford University, michalak@stanford.edu
Mac Post, ORNL, postwmiii@ornl.gov
Kevin M Schaefer, National Snow and Ice Data Center, kevin.schaefer@nsidc.org
Andy Jacobson, University of Colorado and NOAA Earth System Research Lab, andy.jacobson@noaa.gov
Yaxing Wei, ORNL, weiy@ornl.gov
Robert B. Cook, Environmental Sciences Division, ORNL, cookrb@ornl.gov

The Multi-scale Synthesis and Model Intercomparison Project (MsTMIP) is a formal model intercomparison effort focused on improving the diagnosis and attribution of carbon exchange at regional and global scales. Over 20 different terrestrial biospheric models are participating in the MsTMIP effort, and here we present the initial results from the MsTMIP activity. Model estimates of the land sink (NEE) and gross primary productivity (GPP) are examined globally and regionally to assess trends among models and their geographic distribution. We examine how model estimates of NEE and GPP from 1900 to 2010 diverge with time, and to what extent the initial state of carbon pools, sensitivity to forcing factors, and differences in model formulation contribute to this divergence. Structural differences (i.e., which processes are included) among the participating models are evaluated using dendrograms. These visualizations are also used to test whether models with similar structural attributes produce similar estimates of NEE and GPP over time. Finally, we link differences in model estimates to each model’s sensitivity to key forcing factors including climate variability, CO2 fertilization, nitrogen limitation, and land cover / land-use change.

Presentation Type:  Poster

Session:  Poster Session 2-B   (Wed 4:30 PM)

Associated Project(s): 

Poster Location ID: 76

 


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