我国东部夏季降水量统计降尺度的可预测性研究  

A STUDY OF PREDICTABILITY FOR SUMMER PRECIPITATION ON EAST CHINA USING DOWNSCALING TECHNIQUES

作　　者：魏凤英[1] 黄嘉佑[2] 

机构地区：[1]中国气象科学研究院灾害天气国家重点实验室,北京100081 [2]北京大学物理学院大气科学系,北京100871

出　　处：《热带气象学报》2010年第4期483-488,共6页Journal of Tropical Meteorology

基　　金：行业科研专项(GYHY200706005;GY20090601);"十一五"国家科技支撑项目(2006BAD04B01);灾害天气国家重点实验室自主研究基金共同资助

摘　　要：利用1951—2007年逐月的北半球500 hPa高度场资料,使用降尺度技术和偏最小二乘回归方法,对我国东部夏季6—8月降水量作可预测性研究。用全球大气与热带太平洋相耦合的数值模式(CGCM)输出的500 hPa高度场作为因子场,利用建立的预报模型作预报试验。试验结果表明,以北半球东亚40°E^180°地区的500 hPa高度场是较佳的降尺度因子场。预报模型的建立与使用的提取主分量个数和资料时期有关,提取主分量数在4~7、样本容量取32~43时有较好的预测效果。试验结果还表明,以CGCM模式输出的500 hPa高度场作为因子场进行预测,有一定的预测能力。The predictability is researched by downscaling techniques and partial least square regression for summer （Jun-Aug） precipitation on East China, using the data of 500 hPa height field on North Hemisphere during the period of 1951-2007.the prediction experiments are in progress using the prediction model, which has been built by the downscaling method, and the data of factors of the 500 hPa height field from the model output of CGCM. The results show that the 500 hPa height （factor） field of 40 °E-180 °on East Asia of North Hemisphere is the best downscaling area for the precipitation prediction. The predictability about the downscaling model is related with the number of the principal components extracted by partial least square regression. The better prediction effects using the downscaling model are made by the extracted component number of 4-7 and sample of 32-43. The results are also showed that the better predictability on the downscaling model using the factor field from the model output of CGCM is found.

关 键 词：气候学 预报方法 偏最小二乘回归 统计降尺度 

分 类 号：P426.6[天文地球—大气科学及气象学]