西南夏季降水多因子降维客观预测方法研究  

Multifactor Descending Dimension Method of Objective Forecast for Summer Precipitation in Southwest China

作　　者：庞轶舒 周斌[1] 祝从文[3] 秦宁生[2] 杨严 PANG Yishu;ZHOU Bin;ZHU Congwen;Qin Ningsheng;YANG Yan(Sichuan Climate Center,Chengdu 610072;Institute of Plateau Meteorology,China Meteorological Administration/Heavy Rain and Drought-Flood Disasters in Plateau and Basin Key Laboratory of Sichuan Province,Chengdu 610072;Chinese Academy of Meteorological Sciences,Beijing 100081;Jiangsu Zhenjiang Meteorological Bureau,Zhenjiang 212003)

机构地区：[1]四川省气候中心,成都610072 [2]中国气象局成都高原气象研究所/高原与盆地暴雨旱涝灾害四川省重点实验室,成都610072 [3]中国气象科学研究院机构,北京100081 [4]江苏省镇江市气象局,镇江212003

出　　处：《大气科学》2021年第3期471-486,共16页Chinese Journal of Atmospheric Sciences

基　　金：中国气象局成都高原气象研究所创新团队项目BROP202043;国家自然科学基金项目41772173;高原与盆地暴雨旱涝灾害四川省重点实验室科技发展基金项目省重点实验室2018-青年-06、SCQXKJQN2019006;四川省科技计划项目2019YJ0620;中国气象局气候变化专项CCSF202034。

摘　　要：本文改进了现有的多模态时间稳定性判别标准,提出一种筛选稳定高相关预测信号的思路,对1981~2016年西南夏季降水距平百分率多模态的时间稳定性、时空特征和可预测模态关键信号等进行了分析研究,在此基础上构建了多因子降维预测模型。结果表明,前9个模态在预测时效为3年和近10年内稳定,累计方差贡献率占70%,是西南夏季降水的主要模态。结合稳定高相关概念和最优子集回归方法得到主模态PC(Principal Component)系数的最优预测信号和预测方程。回报检验结果表明,各方程对PC系数有较好的拟合效果,复相关系数为0.62~0.84,均通过了99.99%的显著性检验,同号率均大于69%。构建的多因子降维预测模型对西南夏季降水的空间分布,正负趋势和异常级有较好的回报效果:距平相关系数(Anomaly Correlation Coefficient,简称ACC)平均值为0.58;时间相关系数(Temporal Correlation Coefficient,简称TCC)在除零星站点外的整个区域通过90%的显著性检验,且大部分区域通过99.9%的显著性检验;趋势异常综合评分(PS)平均分为84,其中区域降水最异常的十年,PS平均分为87.1。经过13年(1971~1980年和2017~2019年)的预报检验,该模型的PS平均分为72。其中2017~2019年的PS均分为77,优于发布预测评分。In this paper,the existing criteria of EOF(Empirical Orthogonal Function)modes temporal stability are improved,and a scheme for electing stable high correlation prediction signals is proposed.Moreover,the temporal stability of EOF modes,the temporal and spatial characteristics,and the key signals to predictable modes of summer precipitation anomaly percentage from 1981 to 2016 in Southwest China are analyzed.Hence,a multi-factor descending dimension prediction model is established.The results show that the first nine modes are stable within 3 years lead and in recent 10 years for climate prediction.They account for nearly 70%of the variance contribution rate and primary to summer precipitation anomaly percentage in Southwest China.The optimal prediction signals and the corresponding equations for primary PCs(Principal Component)are selected and built with the stable high correlation concept and the optimal subset regression method.These equations are recognized for having good capabilities for PC fitting.Their complex correlation coefficients range from 0.62 to 0.84,all passing the significance test of 99.99%,and their sign coincidence rates are greater than 69%.The prediction model built on that basis has a good hindcast skill for the spatial distribution,variation trend,and abnormal level of summer precipitation in Southwest China.Its mean ACC(Anomaly Correlation Coefficient)score is 0.58.The TCCs(Temporal Correlation Coefficient)pass the 90%significance test in the whole region except for sporadic stations and pass the 99.9%significance test in most areas.While the mean PS(Prediction Score)score is 84,the mean PS score is 87.1 for precipitation in the most abnormal 10 years.According to forecast test in 13 years(1971-1980 and 2017-2019),this model’s mean PS score is 72,and the mean PS score is 77,which is higher than that of published forecasts in 2017-2019.

关 键 词：西南夏季降水 多因子 时间稳定模态 稳定高相关 预测模型 

分 类 号：P456.8[天文地球—大气科学及气象学]