摘要
An effective improvement on the empirical orthogonal function(EOF)–based bias correctionmethod for seasonal forecasts is proposed in this paper,by introducing a stepwise regression method into the process of EOF time series correction.Using 30-year(1981–2010)hindcast results from IAP AGCM4.1(the latest version of this model),the improved method is validated for the prediction of summer(June–July–August)rainfall anomalies in Southeast China.The results in terms of the pattern correction coefficient(PCC)of rainfall anomalies shows that the 30-year-averaged prediction skill improves from 0.01 to 0.06 with the original correction method,and to 0.29 using the improved method.The applicability in real-time prediction is also investigated,using 2016 summer rainfall prediction as a test case.With a PCC of 0.59,the authors find that the new correction method significantly improves the prediction skill;the PCC using the direct prediction of the model is?0.04,and using the old bias correction method it is 0.37.
本文针对短期气候预测中的EOF误差订正方法,提出基于逐步回归改进EOF订正模态的选取及确定各模态对应时间系数的方法。改进后的订正方法显著提高了IAP AGCM4.1对中国东南地区夏季降水异常的预测技巧,30年(1981–2010年)平均的观测与订正后的模式回报夏季降水距平的空间相关系数(PCC)达到0.29,远高于订正前的0.01。该方法应用于2016年夏季降水的实际预测检验表明,采用改进后的订正方法可使得预测与模式预测结果的PCC提高到0.59,显著优于采用了改进前的订正方法的结果(PCC=0.37)。
基金
jointly supported by the National Key Research and Development Program of China [grant number2016YFC0402702]
the Key Project of the Meteorological Public Welfare Research Program [grant number GYHY201406021]
the National Natural Science Foundation of China [grant numbers 41575095 and 41661144032]
