主分量逐步筛选因子典型相关分析及其预报试验  

STEPWISE SCREENING CCA BASED ON PRINCIPAL COMPONENTS AND ITS FORECASTING EXPERIMENTS

作　　者：黄嘉佑[1] 黄茂怡[1] 

机构地区：[1]北京大学地球物理系,北京100871

出　　处：《应用气象学报》2000年第A06期72-78,共7页Journal of Applied Meteorological Science

基　　金：国家“九五”重中之重科技攻关项目“我国短期气候预测系统的研究”96-908-04-01-3专题;国家重点基础研究发展规划项目“我国重大气候和天气灾害形成机理和预测理论的研究”G1998040901-1的资助。

摘　　要：该文提出用主分量逐步筛选因子典型相关分析作短期气候的预测方法 .对长江上游三峡地区夏季汛期 ( 6～ 8月 )作预报试验 .结果表明此方法能进行物理因子提取和分析 。A new method-stepwise screening CCA based on principal components-is proposed as a useful tool of short term climate forecasting. Using the method, experiments are made on the forecasting of summer precipitation of the Sanxia District. The results indicate that the method can be used in the extraction and analysis of physical factors which influence the short term climate and performs fairly well in the forecasting.

关 键 词：因子分析 典型相关分析 预报 

分 类 号：P456[天文地球—大气科学及气象学]