Monthly Simulation of Surface Layer Fluxes and Soil Properties during FIFE

Michael G. Bosilovich Department of Earth and Atmospheric Sciences, Purdue University, West Lafayette, Indiana

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Wen-yih Sun Department of Earth and Atmospheric Sciences, Purdue University, West Lafayette, Indiana

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Abstract

Global change and regional climate experiments with atmospheric numerical models rely on the parameterization of the surface boundary in order to evaluate impact on society and agriculture. In this paper, several surface modeling strategies have been examined in order to test their ability to simulate for a period of one month, and hence, their impact on short-term and regional climate modeling. The interaction between vegetation and soil models is also discussed. The resolution of a multiple-level soil model, the method of computing moisture availability, the Force–Restore Method, and vegetation parameterization were studied by comparing model-simulated soil temperature, soil moisture, and surface energy budget with observations and intercomparison of the simulations.

The increase of model soil resolution improved both the simulation of daytime ground heat flux and latent heat. Evaporation from the soil surface with more coarse resolution soil was larger than the higher resolution simulation, but transpiration and the simulation of soil water were similar for each case. The Alpha method of moisture availability allowed less soil evaporation under stressed conditions than the Beta method. The soil water became larger than the observations, and more transpiration occurred. The Force–Restore Method simulations produced reasonable results, when coupled with the vegetation model. Eliminating the vegetation model from several of the previous cases, however, produced significant variability between different soil models. It is possible that this variability could affect long-term GCM sensitivity simulations.

* Current affiliation: Universities Space Research Association, NASA/Goddard Space Flight Center, Greenbelt, Maryland.

Corresponding author address: Michael G. Bosilovich, Universities Space Research Association, NASA/Goddard Space Flight Center, Greenbelt, MD 20771.

Abstract

Global change and regional climate experiments with atmospheric numerical models rely on the parameterization of the surface boundary in order to evaluate impact on society and agriculture. In this paper, several surface modeling strategies have been examined in order to test their ability to simulate for a period of one month, and hence, their impact on short-term and regional climate modeling. The interaction between vegetation and soil models is also discussed. The resolution of a multiple-level soil model, the method of computing moisture availability, the Force–Restore Method, and vegetation parameterization were studied by comparing model-simulated soil temperature, soil moisture, and surface energy budget with observations and intercomparison of the simulations.

The increase of model soil resolution improved both the simulation of daytime ground heat flux and latent heat. Evaporation from the soil surface with more coarse resolution soil was larger than the higher resolution simulation, but transpiration and the simulation of soil water were similar for each case. The Alpha method of moisture availability allowed less soil evaporation under stressed conditions than the Beta method. The soil water became larger than the observations, and more transpiration occurred. The Force–Restore Method simulations produced reasonable results, when coupled with the vegetation model. Eliminating the vegetation model from several of the previous cases, however, produced significant variability between different soil models. It is possible that this variability could affect long-term GCM sensitivity simulations.

* Current affiliation: Universities Space Research Association, NASA/Goddard Space Flight Center, Greenbelt, Maryland.

Corresponding author address: Michael G. Bosilovich, Universities Space Research Association, NASA/Goddard Space Flight Center, Greenbelt, MD 20771.

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