摘要
利用中国科学院大气物理研究所(IAP,Institute of Atmospheric Physics)3个大气环流模式(AGCM,Atmospheric General Circulation Model)和欧洲多模式集合预报计划(DEMETER,Development of a European Multimodel Ensemble System for Seasonal-to-Interannual Prediction)中7个海气耦合模式(CGCM,Coupled General Circulation Model)的1981—2000年共20 a集合回报结果,比较了不同模式在热带地区,尤其是热带西太平洋地区夏季平均降水的可预测性差异。结果表明:所有模式都能够较好地再现这20 a平均降水的空间分布特征;IAP 9层AGCM最好地再现了热带西太平洋地区,尤其是140°E以西地区降水异常的主要空间特征,而CGCM则对海洋上空的降水异常特征有较好的回报能力。回报的降水异常量值偏弱和系统偏移使得IAP的AGCM原始回报技巧评分明显低于CGCM,但是经过统计订正后AGCM对热带夏季降水表现出与CGCM相当的可预测性。统计订正方法对部分CGCM模式的预报评分也有改进效果,但是当模式原始预报评分较好时订正方法的效果并不明显。对于IAP模式,随着IAP大气模式的不断改进,模式对热带西太平洋降水预测改进最为明显,但是在太平洋东部地区,IAP大气模式依然存在降水异常偏弱的不足。
Understanding the predictability of a numerical model is an essential step before that model is added to a super ensemble prediction system.It is also very important for the development of that model.But forecast noise easily hinders the thorough understanding of the predictability of a model.The forecast always consists of useful forecast information and forecast noises,but sometimes,the proportion of forecast noises are remarkable big,especially for the primary stage of the model development.The forecast will be far apart from the observation when the forecast noises are stronger than the useful forecast information.The predictability evaluation should focus on the useful forecast information which is only decided by the physical characteristics and dynamic properties of the model.Then a valuable statistical correction method is necessary for the reasonable evaluation of the model predictability.This paper evaluates the predictability of three Atmospheric General Circulation Models(AGCM)and seven Coupled General Circulation Models(CGCM)before and after the statistical correction.We selected three AGCMs of Institute of Atmospheric Physics(IAP),for the comparison,seven CGCMs were also selected from the Development of a European Multimodel Ensemble System for Seasonal to Interannual Prediction project(DEMETER),the potential predictability of these AGCMs and CGCMs on summer rainfall in tropical regions,especially in the tropical western Pacific region is evaluated.Results indicate that:All of these models are able to reproduce well the spatial features of mean rainfall of the past20years,but there are obviously differences between models for precipitation anomalies.In order to reduce the distraction of noises,the Singular Value Decomposition(SVD)method is used to estimate the predictability of models for main spatial features of observed precipitation anomalies.IAP9AGCM has the maximum similarity of the first SVD modes to the observed one,which means IAP9AGCM can reproduce the main feature of observed precipitation
作者
黄瑜
秦正坤
HUANG Yu;QIN Zhengkun(College of Math & Statics,Nanjing University of Information Science & Technology,Nanjing 210044,China;Joint Center for Data Assimilation Research and Applications,Nanjing University of Information Science & Technology,Nanjing 210044,China)
出处
《大气科学学报》
CSCD
北大核心
2017年第4期508-518,共11页
Transactions of Atmospheric Sciences
基金
国家重点研发计划(2016YFC0402702)
国家自然科学基金资助项目(41475103)
关键词
多模式
可预测性
订正
热带西太平洋
夏季降水
multi model
predictability
correction
tropical western Pacific
summer rainfall
