中国天气发生器的降水模拟
收稿日期: 2004-01-11
修回日期: 2004-04-23
网络出版日期: 2004-09-25
基金资助
国家气象中心项目 (ZK2003C-12); 中国科学院海外杰出学者基金; 科技部项目 (2001BA611B-01); 瑞典STINT基金会资助项目
Precipitation Simulation in China with a Weather Generator
Received date: 2004-01-11
Revised date: 2004-04-23
Online published: 2004-09-25
Supported by
National Meteorological Center Project, No.ZK2003C-12; Distinguished Overseas Scholar Foundation of CAS, Ministry of Science and Technology of China, No.2001BA611B-01; The Swedish Foundation for International Cooperation in Research and High Education
天气发生器是气候影响评价研究的重要工具，在气候变化、地球生态系统及极端气候事件发生的风险分析等方面有着广泛的应用。为了建立一个适用于中国广大地区的天气发生器，需要对各种模拟模型及其参数的估计进行深入的研究。其中降水的模拟及其参数的估计是关键，因为气温、辐射等其他气候要素的模拟依赖于降水的发生。本文重点介绍了常用的随机降水模拟模型：两状态一阶马尔科夫链和两参数GAMMA分布。根据中国672个气象站点1961~2000年的逐日降水资料，计算了降水转移概率P (WD)、P (WW) 及GAMMA分布参数ALPHA和BETA，并分析了4个参数在中国各地的空间分布特征与不同地区各参数的季节分布特征。最后根据各地不同月份计算的四个降水模拟参数对中国各地的逐日降水进行模拟，并利用1971~2000年的实测数据对30年模拟结果在统计意义上进行了检验，模拟结果较好。
廖要明,张强,陈德亮 . 中国天气发生器的降水模拟[J]. 地理学报, 2004 , 59(5) : 689 -698 . DOI: 10.11821/xb200405006
Weather generator is an important tool in studying 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 is on precipitation simulation since determination of other weather variables such as temperature is dependent on precipitation simulation. A framework of first order Markov Chain with Gamma Distribution for daily precipitation is adopted in this work. Based on this framework four parameters for precipitation simulation for each month at 672 stations all over China are determined using daily precipitation data from 1961 to 2000. Compared with previous works, our estimation for the parameters is made for more stations and longer observations, which makes the weather generator more applicable and reliable. The spatial distribution of the four parameters is analyzed in a regional climate context. The seasonal variation of the parameters at five stations representing regional differences is discussed. Based on the estimated monthly parameters at the 672 stations, daily precipitations for any period of time can be simulated. A 30 year simulation is made and compared with observations during 1971-2000 in terms of annual and monthly statistics.
Key words： weather generator; precipitation; Markov Chain; Gamma Distribution; China
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