Project Number: 1265-13610-027-56
Project Type: Specific Cooperative Agreement

Start Date: Jul 01, 2006
End Date: Jun 30, 2011

Objective:
Work with University of Alabama to assimilate soil moisture estimates from the ALEXI model into numerical weather prediction models and ascertain the resulting improvement in weather forecast accuracy. Compare ALEXI soil moisture maps with spatially distributed measurements, and improve model representation of soil moisture based on these comparisons. Continued maintenance of real-time ALEXI execution over the continental U.S. Evaluate the utility of using these ALEXI-derived moisture fields to initialize regional weather forecasting models and improve predictions of local and regional weather.

Approach:
The ALEXI model has been run daily on a 10 km resolution grid covering the continental U.S. from the years 2002 to present. ALEXI diagnoses a fraction of potential evapotranspiration (fPET) for both the surface layer (0 ¿ 5 cm) and root-zone (5 ¿ 200 cm), given a calculation of the potential ET associated with the canopy and soil components of each pixel scene. These fPET values can be directly related to a fraction of available water, which in turn can be used to calculate volumetric soil moisture for a given soil texture. ALEXI-derived volumetric soil moisture estimates will be validated with respect to spatially distributed measurement datasets, such as from the Oklahoma Mesonet. These fields will then be used to initialize mesoscale simulations using both the MM5 and Weather Research and Forecasting (WRF) models. Impacts on forecast accuracy will be quantified through statistical verification techniques. In conjunction with this research, researchers at the University of Alabama will maintain real-time execution of the ALEXI model and the associated data archive. Work with University of Alabama scientists to fully implement ALEXI model computations with weather forecasting models over a variety of climatic regions in the continental U.S. having a range of landscape properties and vegetation cover.