基于1980-2015年6-8月CWRF模式(Climate-Weather Research and Forecasting model)14种方案的模拟结果和全国逐日降水观测资料,对比了Q-lin,Q-tri,RQ-lin,RQ-tri,SSP-lin和CDFt 6种误差订正方法对CWRF模式控制化方案(C1)模拟中国东部夏...基于1980-2015年6-8月CWRF模式(Climate-Weather Research and Forecasting model)14种方案的模拟结果和全国逐日降水观测资料,对比了Q-lin,Q-tri,RQ-lin,RQ-tri,SSP-lin和CDFt 6种误差订正方法对CWRF模式控制化方案(C1)模拟中国东部夏季日极端降水的订正效果,以CWRF模式14种方案日极端降水的模拟效果排名为基础,对比了模拟效果较好的4种方案集合、模拟较差的4种方案集合以及14种方案集合的订正效果,选出相对较好的订正方案进一步评估其成员集合后订正和成员分别订正后再集合的订正效果,结果表明:采用6种误差订正方法均可明显减少日极端降水模拟误差,其中RQ-lin方法订正效果最佳。CWRF模式对中国东部的极端降水指数均表现出较好的模拟能力,不同参数化集合方案得到14种方案成员先订正再集合与观测日极端降水平均值最为接近,研究结果对于改进模拟结果、提高其预测能力有重要应用价值。展开更多
A new analog error correction （AEC） scheme based on the moving North Pacific index （MNPI） is designed in this study. This scheme shows obvious improvement in the prediction skill of the operational coupled general...A new analog error correction （AEC） scheme based on the moving North Pacific index （MNPI） is designed in this study. This scheme shows obvious improvement in the prediction skill of the operational coupled general circulation model （CGCM） of the National Climate Center of China for the rainy season rainfall （RSR） anomaly pattern correlation coefficient （ACC） over the mid-to-lower reaches of the Yangtze River （MLRYR）. A comparative analysis indicates that the effectiveness of the new scheme using the MNPI is better than the system error correction scheme using the North Pacific index （NPI）. A Euclidean distance- weighted mean rather than a traditional arithmetic mean, is applied to the integration of the analog year＇s prediction error fields. By using the MNPI AEC scheme, independent sample hindcasts of RSR during the period 2003-2009 are then evaluated. The results show that the new scheme exhibited a higher forecast skill during 2003-2009, with an average ACC of 0.47; while the ACC for the NPI case was only 0.19. Furthermore, the forecast skill of the RSR over the MLRYR is examined. In the MNPI case, empirical orthogonal function （EOF） was used in the degree compression of the prediction error fields from the CCCM, whereas the AEC scheme was applied only to its first several EOF components for which the accumulative explained variance accounted for 80% of the total variance. This further improved the ACC of the independent sample hindcasts to 0.55 during the 7-yr period.展开更多
文摘基于1980-2015年6-8月CWRF模式(Climate-Weather Research and Forecasting model)14种方案的模拟结果和全国逐日降水观测资料,对比了Q-lin,Q-tri,RQ-lin,RQ-tri,SSP-lin和CDFt 6种误差订正方法对CWRF模式控制化方案(C1)模拟中国东部夏季日极端降水的订正效果,以CWRF模式14种方案日极端降水的模拟效果排名为基础,对比了模拟效果较好的4种方案集合、模拟较差的4种方案集合以及14种方案集合的订正效果,选出相对较好的订正方案进一步评估其成员集合后订正和成员分别订正后再集合的订正效果,结果表明:采用6种误差订正方法均可明显减少日极端降水模拟误差,其中RQ-lin方法订正效果最佳。CWRF模式对中国东部的极端降水指数均表现出较好的模拟能力,不同参数化集合方案得到14种方案成员先订正再集合与观测日极端降水平均值最为接近,研究结果对于改进模拟结果、提高其预测能力有重要应用价值。
基金Supported by the National(Key)Basic Research and Development(973)Program of China(2013CB430204)National Natural Science Foundation of China(41305100 and 41105055)China Meteorological Administration Special Public Welfare Research Fund(GYHY201306021)
文摘A new analog error correction （AEC） scheme based on the moving North Pacific index （MNPI） is designed in this study. This scheme shows obvious improvement in the prediction skill of the operational coupled general circulation model （CGCM） of the National Climate Center of China for the rainy season rainfall （RSR） anomaly pattern correlation coefficient （ACC） over the mid-to-lower reaches of the Yangtze River （MLRYR）. A comparative analysis indicates that the effectiveness of the new scheme using the MNPI is better than the system error correction scheme using the North Pacific index （NPI）. A Euclidean distance- weighted mean rather than a traditional arithmetic mean, is applied to the integration of the analog year＇s prediction error fields. By using the MNPI AEC scheme, independent sample hindcasts of RSR during the period 2003-2009 are then evaluated. The results show that the new scheme exhibited a higher forecast skill during 2003-2009, with an average ACC of 0.47; while the ACC for the NPI case was only 0.19. Furthermore, the forecast skill of the RSR over the MLRYR is examined. In the MNPI case, empirical orthogonal function （EOF） was used in the degree compression of the prediction error fields from the CCCM, whereas the AEC scheme was applied only to its first several EOF components for which the accumulative explained variance accounted for 80% of the total variance. This further improved the ACC of the independent sample hindcasts to 0.55 during the 7-yr period.
