Do Global Models Properly Represent the Feedback between Land and Atmosphere?

Paul A. Dirmeyer Center for Ocean–Land–Atmosphere Studies, Calverton, Maryland

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Randal D. Koster Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland

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Zhichang Guo Center for Ocean–Land–Atmosphere Studies, Calverton, Maryland

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Abstract

The Global Energy and Water Cycle Experiment/Climate Variability and Predictability (GEWEX/CLIVAR) Global Land–Atmosphere Coupling Experiment (GLACE) has provided an estimate of the global distribution of land–atmosphere coupling strength during boreal summer based on the results from a dozen weather and climate models. However, there is a great deal of variation among models, attributable to a range of sensitivities in the simulation of both the terrestrial and atmospheric branches of the hydrologic cycle. It remains an open question whether any of the models, or the multimodel estimate, reflects the actual pattern and strength of land–atmosphere coupling in the earth’s hydrologic cycle. The authors attempt to diagnose this by examining the local covariability of key atmospheric and land surface variables both in models and in those few locations where comparable, relatively complete, long-term measurements exist. Most models do not encompass well the observed relationships between surface and atmospheric state variables and fluxes, suggesting that these models do not represent land–atmosphere coupling correctly. Specifically, there is evidence that systematic biases in near-surface temperature and humidity among all models may contribute to incorrect surface flux sensitivities. However, the multimodel mean generally validates better than most or all of the individual models. Regional precipitation behavior (lagged autocorrelation and predisposition toward maintenance of extremes) between models and observations is also compared. Again a great deal of variation is found among the participating models, but remarkably accurate behavior of the multimodel mean.

Corresponding author address: Dr. Paul A. Dirmeyer, Center for Ocean–Land–Atmosphere, 4041 Powder Mill Road, Suite 302, Calverton, MD 20705-3016. Email: dirmeyer@cola.iges.org

Abstract

The Global Energy and Water Cycle Experiment/Climate Variability and Predictability (GEWEX/CLIVAR) Global Land–Atmosphere Coupling Experiment (GLACE) has provided an estimate of the global distribution of land–atmosphere coupling strength during boreal summer based on the results from a dozen weather and climate models. However, there is a great deal of variation among models, attributable to a range of sensitivities in the simulation of both the terrestrial and atmospheric branches of the hydrologic cycle. It remains an open question whether any of the models, or the multimodel estimate, reflects the actual pattern and strength of land–atmosphere coupling in the earth’s hydrologic cycle. The authors attempt to diagnose this by examining the local covariability of key atmospheric and land surface variables both in models and in those few locations where comparable, relatively complete, long-term measurements exist. Most models do not encompass well the observed relationships between surface and atmospheric state variables and fluxes, suggesting that these models do not represent land–atmosphere coupling correctly. Specifically, there is evidence that systematic biases in near-surface temperature and humidity among all models may contribute to incorrect surface flux sensitivities. However, the multimodel mean generally validates better than most or all of the individual models. Regional precipitation behavior (lagged autocorrelation and predisposition toward maintenance of extremes) between models and observations is also compared. Again a great deal of variation is found among the participating models, but remarkably accurate behavior of the multimodel mean.

Corresponding author address: Dr. Paul A. Dirmeyer, Center for Ocean–Land–Atmosphere, 4041 Powder Mill Road, Suite 302, Calverton, MD 20705-3016. Email: dirmeyer@cola.iges.org

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