基于SCE-UA算法的多模式降雨集成预报技术研究
|
摘要
高精度的降雨预报对于防汛决策具有重要指导意义.以中国气象局GRAPES_MESO模式、中国气象局T639模式、美国国家环境预报中心GFS模式和上海区域中尺度SMS-WARMS模式为基础,采用SCE-UA算法估计各预报模式权重系数,通过加权平均建立多模式降雨集成预报,并以宁波市2016年8月1日至2016年10月31日和2017年9月1日至2017年11月30日的降雨过程为例,从均方根误差、相关系数、TS评分等多个方面分析集成预报的预报效果.结果表明:基于SCE-UA算法的多模式降雨集成预报的预报效果不仅优于各单一预报模式,而且优于遗传算法和BP神经网络集成预报,表现出较好的适用性.
Predicting with high-precision precipitation is a key for flood control decision-making. Based on the data collected from GRAPES_MESO and T639 of China Meteorological Administration, GFS of National Centers for Environmental Prediction and SMS-WARMS of Shanghai, SCE-UA algorithm is used to estimate the weighting of each forecast model. With the weighting estimated, the multi-model integrated precipitation is established. Using the data from Ningbo precipitation occurrences between August 1, 2016 and October 31, 2016, as well as from September 1, 2017 to November 30, 2017, the integrated forecast result is analyzed from a variety of indices such as root-mean-square error, correlation coefficient and TS grade. The result indicates that the integrated forecast based on SCE-UA is more accurate and applicable than not only those from individual forecast models but also those based on genetic algorithm and BP integrated forecast models.
Predicting with high-precision precipitation is a key for flood control decision-making. Based on the data collected from GRAPES_MESO and T639 of China Meteorological Administration, GFS of National Centers for Environmental Prediction and SMS-WARMS of Shanghai, SCE-UA algorithm is used to estimate the weighting of each forecast model. With the weighting estimated, the multi-model integrated precipitation is established. Using the data from Ningbo precipitation occurrences between August 1, 2016 and October 31, 2016, as well as from September 1, 2017 to November 30, 2017, the integrated forecast result is analyzed from a variety of indices such as root-mean-square error, correlation coefficient and TS grade. The result indicates that the integrated forecast based on SCE-UA is more accurate and applicable than not only those from individual forecast models but also those based on genetic algorithm and BP integrated forecast models.
引文
[1]吴振玲,潘璇,董昊,等.天津市多模式气温集成预报方法[J].应用气象学报,2014,25(3):293-301.
[2]章祖迪,陈淑琴,何文岳,等.海上雷雨大风形成机制的分析[J].宁波大学学报(理工版),2004,17(2):134-137.
[3]董海萍,张秀丽,郭卫东.多模式超级集合预报的应用研究[EB/OL].[2018-01-18].http://xueshu.baidu.com.
[4]赵成武.短时降水的超级集合预报算法研究[D].长沙:国防科学技术大学,2014.
[5]李倩,胡邦辉,王学忠,等.基于BP人工神经网络的区域温度多模式集成预报试验[J].干旱气象,2011,29(2):231-235.
[6]熊聪聪,耿世洁,董昊.基于混合算法的降水集成预报研究[J].计算机工程与科学,2016,38(10):2147-2152.
[7]李致家.现代水文模拟与预报技术[M].南京:河海大学出版社,2010:258-262.
[8]董洁平,李致家,戴健男.基于SCE-UA算法的新安江模型参数优化及应用[J].河海大学学报(自然科学版),2012,40(5):485-490.
[9]朱兵,何晓燕,王素芬,等.基于SCE-UA算法的新安江日模型参数优化稳定性分析[J].水电能源科学,2016(11):9-12.
[10]邓元倩,李致家,刘甲奇,等.基于SCE-UA算法新安江模型在沣河流域的应用[J].水资源与水工程学报,2017,28(3):27-31.
[11]陈桂英.权重分布法集成预报试验[J].应用气象学报,2000,11(S1):51-57.
[12]Duan Q Y,Gupta V K,Sorooshian S.Shuffled complex evolution approach for effective and efficient global minimization[J].Journal of Optimization Theory&Applications,1993,76(3):501-521.
[13]董海萍,张秀丽,郭卫东,等.2010年8月环流形势的多模式超级集合预报[J].应用气象学报,2013,24(5):606-616.
[14]熊聪聪,王静,宋鹏,等.遗传算法在多模式集成天气预报中的应用[J].天津科技大学学报,2008,23(4):80-84.
[2]章祖迪,陈淑琴,何文岳,等.海上雷雨大风形成机制的分析[J].宁波大学学报(理工版),2004,17(2):134-137.
[3]董海萍,张秀丽,郭卫东.多模式超级集合预报的应用研究[EB/OL].[2018-01-18].http://xueshu.baidu.com.
[4]赵成武.短时降水的超级集合预报算法研究[D].长沙:国防科学技术大学,2014.
[5]李倩,胡邦辉,王学忠,等.基于BP人工神经网络的区域温度多模式集成预报试验[J].干旱气象,2011,29(2):231-235.
[6]熊聪聪,耿世洁,董昊.基于混合算法的降水集成预报研究[J].计算机工程与科学,2016,38(10):2147-2152.
[7]李致家.现代水文模拟与预报技术[M].南京:河海大学出版社,2010:258-262.
[8]董洁平,李致家,戴健男.基于SCE-UA算法的新安江模型参数优化及应用[J].河海大学学报(自然科学版),2012,40(5):485-490.
[9]朱兵,何晓燕,王素芬,等.基于SCE-UA算法的新安江日模型参数优化稳定性分析[J].水电能源科学,2016(11):9-12.
[10]邓元倩,李致家,刘甲奇,等.基于SCE-UA算法新安江模型在沣河流域的应用[J].水资源与水工程学报,2017,28(3):27-31.
[11]陈桂英.权重分布法集成预报试验[J].应用气象学报,2000,11(S1):51-57.
[12]Duan Q Y,Gupta V K,Sorooshian S.Shuffled complex evolution approach for effective and efficient global minimization[J].Journal of Optimization Theory&Applications,1993,76(3):501-521.
[13]董海萍,张秀丽,郭卫东,等.2010年8月环流形势的多模式超级集合预报[J].应用气象学报,2013,24(5):606-616.
[14]熊聪聪,王静,宋鹏,等.遗传算法在多模式集成天气预报中的应用[J].天津科技大学学报,2008,23(4):80-84.