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

作者：Jiang Zhihong; Ding Yuguo^*; Zheng Chunyu; Chen Weilin

来源：Advances in Atmospheric Sciences, 2011, 28(6): 1357-1366.

DOI：10.1007/s00376-011-0086-8

• stochastic simulation
• daily weather state series
• Markov chain
• state vector

In this study, changes in daily weather states were treated as a complex Markov chain process, based on a continuous-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 using total cloud amount for dry states was adopted, and dry days were classified into three states: clear, cloudy, and overcast (rain free). Multistate transition models for dry- and wet-day series were constructed to comprehensively downscale the simulation of regional daily climatic states. The results show that the finer, improved, downscaled model overcame the oversimplified treatment of a two-weather state model and is free of the shortcomings of a multistate model that neglects finer classification of dry days (i.e., finer classification was applied only to wet days). As a result, overall simulation of weather states based on the SWAT greatly improved, and the improvement in simulating daily temperature and radiation was especially significant.

• 出版日期2011-11
• 单位南京信息工程大学