华北汛期降水多因子相似订正方案与预报试验  

Estimating the Prediction Errors of Dynamical Climate Model on the Basis of Prophase Key Factors in North China

作　　者：杨杰[1] 赵俊虎[1] 郑志海[2] 熊开国[1] 沈柏竹 

机构地区：[1]兰州大学大气科学学院,兰州730000 [2]国家气候中心气候研究开放实验室,北京100081

出　　处：《大气科学》2012年第1期11-22,共12页Chinese Journal of Atmospheric Sciences

基　　金：国家自然科学基金资助项目41105055;40930952;全球变化重大研究计划2012CB955902;公益性行业(气象)科研专项GY-HY201006016;GYHY201106015

摘　　要：本文基于动力—相似预报的基本原理,在已初步建立的华北汛期降水模式的动态最优多因子组合相似订正方案工作基础上,研究前期关键因子之间的相互配置对夏季降水的影响,挑选关键的大气环流预报因子。根据预报年前期气候因子的异常状况,通过EOF压缩自由度进行相似年选取,进一步构建了基于前期异常信号的汛期降水相似订正预报方案。研究发现,预报年前期大气环流中异常因子个数的偏多或偏少与该年华北降水的多寡呈现较好的对应关系,并以异常因子的个数状况作为判断该年是否为异常年的标准,将异常多因子方案与动态最优多因子方案相结合,建立模式误差相似订正的多因子综合预报方案。通过诊断分析发现,该方案对降水异常年有着较好的针对性。2003～2009年7年的独立样本回报结果表明:该方法进一步提高了模式对华北汛期降水的预报能力,将华北汛期降水预报的距平相关系数(ACC)平均分从系统订正结果的0.38提高至0.61,具有良好的业务应用前景。Based on the basic principle of dynamical analogue prediction, the authors have established the optimal dynamic multi-factor schemes to revise prediction errors. In this paper, the authors studied the correlations between the interactions of prophase key factors and the precipitation of rainy season in China and found the key atmospheric circulation predictor. According to the predictors which are abnormal in prophase, the authors compressed the di- mensions of the factors to select the similar years through EOF analysis. Furthermore, a new dynamical analogue prediction scheme is constructed, which is based on the anomalous signals of prophase environment field. Analyses show that there is a good corresponding relationship between precipitation in North China and numbers of atmos- pheric circulation factors which are abnormal in prophase. The authors developed a comprehensive scheme to revise prediction errors of numerical model combined with the abnormal factors scheme and the optimal dynamic multi-fac-tor scheme. Through the diagnostic analysis, the authors found that the comprehensive scheme has a good adapta- bility. Results of independent sample return during 2003 - 2009 show that the anomaly correlation coefficient （ACC） score has increased from 0.38 to 0. 61. The similarity revised method has further improved the prediction capacity of numerical model and has a good application prospect for summer precipitation in North China.

关 键 词：汛期降水 异常因子 模式误差估计 预测 

分 类 号：P426[天文地球—大气科学及气象学]