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我国华东地区月尺度气候动力预测的研究:(Ⅱ) 嵌套模式的回报评估
引用本文:席朝笠,曾新民,李宁.我国华东地区月尺度气候动力预测的研究:(Ⅱ) 嵌套模式的回报评估[J].气象科学,2007,27(4):355-364.
作者姓名:席朝笠  曾新民  李宁
作者单位:1. 解放军理工大学气象学院,南京,211101
2. 解放军理工大学气象学院,南京,211101;教育部中尺度灾害性天气重点实验室,南京210093
摘    要:采用数值模式方法对我国华东地区进行月尺度短期气候预测。预测框架由改进的低分辨率全球环流模式T63 L9嵌套并入了水文模型VXM的区域气候模式RegCM3构成,根据嵌套气候模式的积分结果,经剔除系统误差后制作短期气候预报。本文利用国家气候中心的评分方法对2003、2004两年的降水和地表气温回报结果作了评估;还将本系统的预报结果与CMAP降水资料、NMC温度资料及全国160站的观测资料进行了对比。结果表明,该系统可以比较稳定地对我国华东地区的降水和温度进行月尺度预测。

关 键 词:嵌套气候模式  动力预测  回报评估
收稿时间:2005-10-18
修稿时间:2006-07-04

STUDY ON MONTHLY-SCALE CLIMATE FORECAST BY DYNAMICAL APPROACH FOR EAST CHINA, PART Ⅱ:EVALUATION OF HINDCASTS OF THE NESTED MODELS
Xi Chaoli,Zeng Xinmin and Li Ning.STUDY ON MONTHLY-SCALE CLIMATE FORECAST BY DYNAMICAL APPROACH FOR EAST CHINA, PART Ⅱ:EVALUATION OF HINDCASTS OF THE NESTED MODELS[J].Scientia Meteorologica Sinica,2007,27(4):355-364.
Authors:Xi Chaoli  Zeng Xinmin and Li Ning
Institution:1.Institute of Meteorology, PLA University of Science and Engineering, Nanjing 211101;2.Key Laboratory for Mesoscale Severe Weather of Ministry of Education, Nanjing 210093
Abstract:This paper presents a numerical modeling method for monthly-scale regional climate prediction for East China.The main dynamic framework of the forecast system is composed of an improved coarse-resolution general circulation model(GCM),i.e.,T63L9,and a nested fine-resolution regional climate model,i.e.,RegCM3,into which the hydrological model VXM is incorporated.The forecast is made from the integration results of the nested models with systematic errors being eliminated to some extent.The results of the temperature and precipitation for 2003 and 2004 are evaluated following the evaluation methods by National Climate Center.In addition,the results of the forecast system are compared with CMAP reanalysis data,NMC temperature reanalysis data and the data of 160 stations in China.All these results show that the system can forecast stably the precipitation and the temperature for East China on monthly scale,and the system can be applied for climate operational application.
Keywords:Nested climate models Dynamical prediction Hindcast evaluation
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