A Simple Model for Land Surface Parameterization and Modeling

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9725698FriedlThis proposal addresses the need for improved methods to routinely monitor key variables within soil-vegetation-atmosphere-transfer (SVAT) parameterizations nested within climate and numerical weather forecasting models. To this end, a two year research plan is described to refine and validate a simple model to parameterize land surface processes in SVAT models using remotely sensed data sources. Key variables within this framework are surface temperature, vegetation type and amount, and surface moisture status. The proposed methodology builds off previous research and model development related to relationships among surface energy balance, vegetation cover, and surface temperature using data from FIFE. This work will continue to focus on analysis and modeling of these relationships in semi-arid regions. The research will refine a modeling strategy that is based on principles of land surface energy balance and which includes treatment of soil-vegetation micrometeorology, but which at the same time is simple enough to be implemented operationally using satellite data in association with minimal in-situ ground measurements. Specific tasks to be performed as part of this research are (1) the integration and validation of a soil heat and temperature model with a two-layer land surface energy balance model; and (2) development and testing of inversion modeling strategies to estimate land surface properties and energy balance components from satellite data. The proposed research has the potential to provide a simple, operational, yet accurate method to initialize, updata and validate land surface parameterizations within hydrologic and atmospheric circulation models. As such it is highly relevant to ongoing global change research programs including the GEWEX continental Scale International Project (GCIP) and the Earth Observing Systems (EOS).