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Stochastic modeling of daily precipitation in China 被引量:10

中国天气发生器的降水模拟
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摘要 A stochastic model for daily precipitation simulation in China was developedbased on the framework of a 'Richardson-type' weather generator that is an important tool instudying impacts of weather/climate on a variety of systems including ecosystem and risk assessment.The purpose of this work is to develop a weather generator for applications in China. The focus ison precipitation simulation since determination of other weather variables such as temperature isdependent on precipitation simulation. A framework of first order Markov Chain with GammaDistribution for daily precipitation is adopted in this work. Based on this framework, fourparameters of precipitation simulation for each month at 672 stations all over China were determinedusing daily precipitation data from 1961 to 2000. Compared with previous works, our estimation forthe parameters was made for more stations and longer observations, which makes the weather generatormore applicable and reliable. Spatial distributions of the four parameters are analyzed in aregional climate context. The seasonal variations of these parameters at five stations representingregional differences are discussed. Based on the estimated monthly parameters at 672 stations, dailyprecipitations for any period can be simulated. A 30-year simulation was made and compared withobservations during 1971-2000 in terms of annual and monthly statistics. The results aresatisfactory, which demonstrates the usefulness of the weather generator. A stochastic model for daily precipitation simulation in China was developedbased on the framework of a 'Richardson-type' weather generator that is an important tool instudying impacts of weather/climate on a variety of systems including ecosystem and risk assessment.The purpose of this work is to develop a weather generator for applications in China. The focus ison precipitation simulation since determination of other weather variables such as temperature isdependent on precipitation simulation. A framework of first order Markov Chain with GammaDistribution for daily precipitation is adopted in this work. Based on this framework, fourparameters of precipitation simulation for each month at 672 stations all over China were determinedusing daily precipitation data from 1961 to 2000. Compared with previous works, our estimation forthe parameters was made for more stations and longer observations, which makes the weather generatormore applicable and reliable. Spatial distributions of the four parameters are analyzed in aregional climate context. The seasonal variations of these parameters at five stations representingregional differences are discussed. Based on the estimated monthly parameters at 672 stations, dailyprecipitations for any period can be simulated. A 30-year simulation was made and compared withobservations during 1971-2000 in terms of annual and monthly statistics. The results aresatisfactory, which demonstrates the usefulness of the weather generator.
出处 《Journal of Geographical Sciences》 SCIE CSCD 2004年第4期417-426,共10页 地理学报(英文版)
基金 National Meteorological Center Project,Distinguished Overseas Scholar Foundation of CAS,科技部资助项目,Chinese Ministry of Water Resources, The Swedish Research Council fund
关键词 weather generator PRECIPITATION markov Chain gamma distribution China weather generator precipitation markov Chain gamma distribution China
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