To correct the model errors in analogue-dynamical prediction,a new idea of using the analogue prediction of principal components of model errors,instead of analogue prediction of model error directly,is proposed.By decomposing the empirical orthogonal function,the principal components of the model errors are divided into two parts subjectively：predictable and unpredictable.For the predictable part,it is analogically predicted by the scheme of dynamical and optimal configuration of multiple predictors;while for the unpredictable part,it is estimated by average of the system.Based on the National Climate Center（NCC） of China operational seasonal prediction model results for the period 1983-2010 and the US National Weather Service Climate Prediction Center merged analysis of precipitation in the same period,together with the 74 circulation indices of NCC Climate System Diagnostic Division and 40 climate indices of NOAA of US during 1951-2010,the method is implemented in objective and quantitative prediction of monsoon precipitation in Northeast China.The independent sample validation shows that this technique has effectively improved the monsoon precipitation prediction skill during 2005-2010,for which the averaged anomaly correlation coefficients and the system correct of errors are 0.29 and 0.04 respectively.This study demonstrates that the analogue-dynamical approach can enhance the prediction level of NCC operational seasonal forecast model obviously.%针对相似动力预报中模式预报误差的估计问题,提出将模式误差的直接相似订正问题转化成模式误差主分量的相似预报问题.客观上将模式误差主分量分成可预报和不可预报两部分,对于可预报主分量采用最优多因子动态配置方案进行相似预报,而对于不可预报部分则用系统平均代替.基于国家气候中心季节预报业务模式、美国气候预报中心组合降雨分析资料及国家气候中心气候系统诊断预报室74项环流指数和美国国家海洋和大气管理局的40个气候指数,对东北区域汛期降水进行了预报试验.2005—2010年6年独立样本检验预报平均距平相关系数为0.29,较系统误差订正预报的0.04有较大提高,证实该方案能提高国家气候中心季节预报业务模式汛期降水预报水平.
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