An Improved, Downscaled, Fine Model for Simulation of Daily Weather States

In this study, changes in daily weather states weretreated as a complex Markov chain process, based on acontinuous-time watershed model (soil water assessment tool, SWAT)developed by the Agricultural Research Service at the U.S.Department of Agriculture (USDA-ARS). A finer classification usingtotal cloud amount for dry states was adopted, and dry days wereclassified into three states: clear, cloudy, and overcast (rainfree). Multistate transition models for dry- and wet-day series wereconstructed to comprehensively downscale the simulation of regionaldaily climatic states. The results show that the finer, improved,downscaled model overcame the oversimplified treatment of atwo-weather state model and is free of the shortcomings of amultistate model that neglects finer classification of dry days(i.e., finer classification was applied only to wet days). As aresult, overall simulation of weather states based on the SWATgreatly improved, and the improvement in simulating dailytemperature and radiation was especially significant.