| description abstract | mong the uncertain consequences of climate change on agriculture are changes in timing and quantity of precipitation together with predicted higher temperatures and changes in length of growing season. The understanding of how these uncertainties will affect water use in semiarid irrigated agricultural regions depends on accurate simulations of the terrestrial water cycle and, especially, evapotranspiration. The authors test the hypothesis that the vertical canopy structure, coupled with horizontal variation in this vertical structure, which is associated with ecosystem type, has a strong impact on landscape evapotranspiration. The practical result of this hypothesis, if true, is validation that coupling the Advanced Canopy?Atmosphere?Soil Algorithm (ACASA) and the Weather Research and Forecasting (WRF) models provides a method for increased accuracy of regional evapotranspiration estimates.ACASA?WRF was used to simulate regional evapotranspiration from irrigated almond orchards over an entire growing season. The ACASA model handles all surface and vegetation interactions within WRF. ACASA is a multilayer soil?vegetation?atmosphere transfer model that calculates energy fluxes, including evapotranspiration, within the atmospheric surface layer.The model output was evaluated against independent evapotranspiration estimates based on eddy covariance. Results indicate the model accurately predicts evapotranspiration at the tower site while producing consistent regional maps of evapotranspiration (900?1100 mm) over a large area (1600 km2) at high spatial resolution (?x = 0.5 km).Modeled results were within observational uncertainties for hourly, daily, and seasonal estimates. These results further show the robustness of ACASA?s ability to simulate surface exchange processes accurately in a complex numerical atmospheric forecast model such as WRF. | |
