Surface Energy Flux Estimation Using Diurnal Surface Temperature Modeling at BEAREX08

Obtaining accurate estimates of the spatial distribution of surface energy fluxes through remote sensing techniques would be helpful for modeling daily evapotranspiration (ET) over crops such as cotton. Experience with energy balance models shows that techniques incorporating thermal infrared observations are particularly useful because departures from standardized ET estimates can be detected. Practical remote sensing from satellite platforms, however, precludes acquisitions at both high temporal and spatial resolutions. Consequently continuous estimation of surface fluxes over crops is not feasible without supplemental methods. One such method utilizes land surface temperature (LST) observations acquired from ground-based radiometers, which are then spatially extrapolated. The extrapolation process is constrained by vegetation densities and a sinusoidal/exponential diurnal LST model. Using data acquired from the BEAREX 2008, spatially and temporally continuous surface energy fluxes were estimated for cotton growing between June and August 2008. Results from these estimates, including comparisons against daily ET observations obtained from large, monolithic weighing lysimeters, will be discussed.