Project Number: 1265-13610-027-02
Project Type: Specific Cooperative Agreement

Start Date: Jun 19, 2007
End Date: Mar 31, 2012

Objective:
Work with Oklahoma University to evaluate the impacts of land cover changes, namely the agricultural harvesting of winter wheat in the Southern Great Plains, and resulting effects on water and energy exchange. Collect and process supporting flux, weather and ground-based measurements during the CLASIC field experiment, to be conducted in Oklahoma during 2007. Evaluate the effects of these changes within the ALEXI/DisALEXI surface energy balance modeling. Provide an analysis of the Little Washita flux tower network as well as the full MESONET flux/soil moisture profile network from the CLASIC period through dry down periods in 2007. In addition, to follow the 2008 growing season using the MESONET network in order to investigate if ALEXI/disALEXI can track the impact of land surface (profile moisture/surface flux) memory. The analyses of the ground-based data set of fluxes and soil moisture profile conditions will provide unique spatial distributions of the land moisture and heat flux states from the MESONET network (supplemented with flux towers operating from CLASIC for 2007) for validating ALEX/DisALEXI regional output of land surface states for the 2007 and 2008 growing seasons in Oklahoma.

Approach:
The cooperative work proposed here will assess the accuracy of ALEXI/DisALEXI-derived surface flux and moisture fields by comparing with a tower network of local weather, soil moisture and surface energy balance observations being coordinated by USDA-ARS Hydrology and Remote Sensing Laboratory and the Oklahoma Climatological Survey, a research unit of the College of Atmospheric and Geographic Sciences at the Oklahoma University. In addition, the utility of using surface flux fields and soil moisture states produced by the DisALEXI/ALEXI modeling framework for improving the initialization fields commonly used in current operational weather forecast models, known to be flawed, will be evaluated. The improvement in predictions of water vapor transport, precipitation and cloud cover will be compared against the ground and aircraft data collected during CLASIC.