全球辐射通量资料在汛期降水预测中的应用试验  

The Test for Quantitative Precipitation Prediction of Flood Season by Use of Radiative Flux Data

作　　者：胡波 俞善贤 滕卫平 毛燕军[3] 

机构地区：[1]浙江省气象台,杭州310017 [2]浙江省气象科学研究所,杭州310017 [3]浙江省气候中心,杭州310017

出　　处：《科技通报》2013年第7期30-37,42,共9页Bulletin of Science and Technology

基　　金：浙江省科技厅重点项目(气候模式统计降尺度集成技术的应用研究)资助(2005C23077)

摘　　要：利用NCEP常规和导出月平均资料,采用旋转EOF、典型相关分析等方法分析浙江梅汛期和汛期降水量的空间分布,提取典型相关变量作为预报初选因子。然后根据因子差异法选取三种建模方案,分别构建浙江省梅汛期和汛期雨量BP人工神经网络预报模型,并连续进行四年预报检验,结果显示最佳的预报方案平均ps评分分别达到69分和84分,比较好的预报出降水趋势;最后对预报因子空间进行分析表明:(1)NCEP导出资料在汛期降水预测中具有重要作用;(2)梅汛期和汛期因子在全球范围内均有五个集中区,其中四个区分别与ENSO、冰岛低压、阿留申低压等大气活动中心相对应;(3)较长时段的汛期雨量预报需要考虑南半球和北半球的大气环流因子影响;(4)大气能量收支因子对短期气候预测具有十分重要意义。Based on REOF and CCA methods,the rainfall between May and July and between May and September at 38 stations in flood season from 1961 to 2005 are analyzesd and the canonical variables are taken as prediction factors by use of NCEP monthly data.Then based on three schemes the BP artificial neural network prediction models are set up.The results of prediction tests from 2006 to 2009 show that the ps scores for the best scheme reach 69 and 84 corresponding to May to July and May to September respectively.The spatial analyses of prediction factors show that（1） The derived NCEP reanalysis data play an important role.（2） The factors of May to July and May to September have five concentration zones.The four zones are corresponding to atmospheric active centers of ENSO、Iceland depression and Aleutian depression.（3） The precipitation prediction of longer flood season needs to consider both the factors of circulation of north and south hemishere.（4） The budget factors of atmospheric energy are very important to climate prediction.

关 键 词：旋转EOF 典型相关分析 汛期 雨量预测 因子集中区 

分 类 号：P457.6[天文地球—大气科学及气象学]