%0 Journal Article
%T An Improved, Downscaled, Fine Model for Simulation of Daily Weather States<br>
%A JIANG Zhihong
%A DING Yuguo
%A ZHENG Chunyu
%A CHEN Weilin
%A <br>
%J 大气科学进展
%D 2011
%I 
%X 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.
%K stochastic simulation
%K daily weather state series
%K Markov chain
%K state vector<br>
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=E62459D214FD64A3C8082E4ED1ABABED5711027BBBDDD35B&cid=28A2F569B2458C17&jid=5434AFBF6CB6E7E8D67733B541F211C7&aid=B0A3094CBEF84E91870DF64E3FD91712&yid=9377ED8094509821&vid=D3E34374A0D77D7F&iid=B31275AF3241DB2D&sid=A621DEC64CBC4DA1&eid=29BFCA84676506CC&journal_id=0256-1530&journal_name=大气科学进展&referenced_num=0&reference_num=20