王启光, 封国林, 支蓉, 赵俊虎. 2012: 长江中下游汛期降水数值预报业务模式误差场预报研究. 气象学报, (4): 789-796. DOI: 10.11676/qxxb2012.064
引用本文: 王启光, 封国林, 支蓉, 赵俊虎. 2012: 长江中下游汛期降水数值预报业务模式误差场预报研究. 气象学报, (4): 789-796. DOI: 10.11676/qxxb2012.064
WANG Qiguang, FENG Guolin, ZHI Rong, ZHAO Junhu. 2012: A study of the error field of the flood period precipitation of the mid-lower reaches of the Yangtze River as predicted by an operational numerical prediction model. Acta Meteorologica Sinica, (4): 789-796. DOI: 10.11676/qxxb2012.064
Citation: WANG Qiguang, FENG Guolin, ZHI Rong, ZHAO Junhu. 2012: A study of the error field of the flood period precipitation of the mid-lower reaches of the Yangtze River as predicted by an operational numerical prediction model. Acta Meteorologica Sinica, (4): 789-796. DOI: 10.11676/qxxb2012.064

长江中下游汛期降水数值预报业务模式误差场预报研究

A study of the error field of the flood period precipitation of the mid-lower reaches of the Yangtze River as predicted by an operational numerical prediction model

  • 摘要: 根据中国国家气候中心(NCC)数值预报业务模式(ONPM)预报结果,利用气候因子对业务模式的误差场进行预报试验。文中所用114项逐月气候因子在历年汛期前期总会出现部分因子异常的状况,在此基础上对因子异常的相似阈值进行数值试验,提出利用交叉检验平均距平相关系数(ACC)的大小来确定相似阈值的方法。依此选择影响该区域的前期关键异常因子,根据该部分因子的相似程度选取相似年,同时对模式误差场利用经验正交函数压缩维度,用前3个主分量对模式误差制作预报,针对业务模式的预报误差场,提出了根据因子异常挑选相似和压缩维度的一个预报方法。2005—2009年独立样本回报结果表明,该方法可以将5 a平均距平相关系数由系统误差订正的0.22提高到0.47,具有较好的业务应用价值。

     

    Abstract: The accuracy of the precipitation prediction is enhanced in the mid lower reaches of the Yangtze River in summer, by using the climate factors and based on the analyses of the error filed of the operational numerical prediction model (ONPM) from National Climate Center (NCC). It is found that there are some factors (among the 114 monthly climate factors) that are anomalous before a certain summer. We use the cross-examination to determine the similar threshold by cross-checking the size of an average ACC. Choosing the key anomaly factors impacted the region, picking out the analogue years based on the anomaly degree of the factors, reducing the dimensions of the model’s errors by EOF, making the prediction for the model’s errors using the first three principal components, then the method to aim at the ONPM is proposed based on the factor anomaly and reducing dimensions of the errors of the model. The ACC can be improved up to 0.47 through the method from 0.22 as was corrected by the system’s averaged dependent sample hindcast from 2005 to 2009, which shows good prospect of its operational application.

     

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