我国西南秋季降水影响因子分析及季节预测  

Influencing Factor and Seasonal Prediction of Autumn Precipitation in Southwest China

作　　者：张俊凯 陶丽[1,3] ZHANG Junkai;TAO Li(School of Atmospheric Sciences,Nanjing University of Information Science and Technology,Nanjing 210044;Yunnan Lincang Meteorological Bureau,Lincang 677099;Key Laboratory of Meteorological Disaster,Ministry of Education(KLME)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD),Nanjing University of Information Science and Technology,Nanjing 210044)

机构地区：[1]南京信息工程大学大气科学学院,南京210044 [2]云南省临沧市气象局,临沧677099 [3]南京信息工程大学气象灾害教育部重点实验室/气象灾害预报预警与评估协同创新中心,南京210044

出　　处：《大气科学》2024年第6期2264-2283,共20页Chinese Journal of Atmospheric Sciences

基　　金：国家自然科学基金重点项目42230105。

摘　　要：本文主要利用信息流特有的因果关系,筛选我国西南秋季降水EOF主导模态PC系数的预报因子,并通过留一法(leave-one-out)和多元线性逐步回归建立西南秋季降水预报模型,最后对模型的预报技巧进行了评估检验。由经验正交函数(EOF)得到的1979~2020年我国西南秋季降水前两个主导模态分别为全区一致型和马鞍型,分别与东部El Niño发展型、中部El Niño发展型联系密切。回报的PC1和PC2与实际PC序列在1980~2015年拟合期相关系数分别为0.89和0.83,同号率分别为90%和83%。在后报检验的2016~2020年5年中,预报的PC1和PC2均有4年与实际PC同位相,同号率为80%。1980~2015年预报重构场与观测降水距平场的空间相关系数(ACC)36年的平均值达到0.48,超过1/2的年份ACC大于0.5,区域平均时间相关系数(TCC)为0.48。本文还通过预报的PC1和PC2进行相似年预报,以弥补重构场降水量级较小的缺陷。This study examined the predictors for the dominant EOF modes of autumn precipitation in Southwest China(SWC)based on the causality of information flow.A statistical model of autumn precipitation in SWC was then established.Finally,the prediction skills of the empirical model were evaluated.The first two dominant modes of autumn precipitation during 1979–2020 in SWC are the basin mode and saddle mode,which were obtained by empirical orthogonal function(EOF).These modes are closely related to the development of eastern and central El Niño.The predictors of the PCs of the first two dominant modes were chosen based on the causality of information flow.A multiple linear stepwise regression with a leave-one-out method was employed to further select the predictors and establish a statistical model.During the training period between 1980 and 2015,the correlation coefficients between the predicted PC1 and PC2 and the actual PCs were found to be 0.89 and 0.83,respectively.Additionally,the sign coincidence rates were determined to be 90%and 83%,respectively.In the forecast years from 2016 to 2020,the predicted PC1 and PC2 are in phase with the actual PCs in four years,with a sign coincidence rate of 80%.During the 36-year training period from 1980 to 2015,the averaged anomalous pattern correlation coefficient(ACC)between the reconstructed precipitation with the predicted PCs and the observed precipitation anomalies is 0.48.The ACC exceeds 0.5 for more than half the years.The regional average temporal correlation coefficient(TCC)is 0.48.Additionally,a similar-year forecast was conducted with predicted PC1 and PC2,which was employed to address the limitations in the reconstructed field regarding precipitation data.

关 键 词：主导模态 信息流 西南秋季降水 预报模型 

分 类 号：P456[天文地球—大气科学及气象学]