第二松花江流域夏季降水年际增量预测模型研究  

Study on Interannual Incremental Prediction Model of Summer Precipitation over the Second Songhua River Valley

作　　者：姜忠宝[1,2] 王秀娟 陈长胜[3] 李尚锋 JIANG Zhongbao;WANG Xiujuan;CHEN Changsheng;LI Shangfeng(Climate Center of Jilin Province,Changchun 130062,China;Jilin Provincial Key Laboratory of Changbai Mountain Meteorology&Climate Change,Changchun 130062,China;Meteorological Observatory of Jilin Province,Changchun 130062,China;Key Laboratory of Cloud-Precipitation Physics and Severe Storms of Chinese Academy of Sciences,Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 100029,China;University of Chinese Academy of Sciences,Beijing 100049,China;Institute of Meteorological Sciences of Jilin Province,Changchun 130062,China;Laboratory of Research for Middle-High Latitude Circulation Systems and East Asian Monsoon,Changchun 130062,China)

机构地区：[1]吉林省气候中心,吉林长春130062 [2]长白山气象与气候变化吉林省重点实验室,吉林长春130062 [3]吉林省气象台,吉林长春130062 [4]中国科学院大气物理研究所云降水物理与强风暴重点实验室,北京100029 [5]中国科学院大学,北京100049 [6]吉林省气象科学研究所,吉林长春130062 [7]中高纬度环流系统与东亚季风研究开放实验室,吉林长春130062

出　　处：《沙漠与绿洲气象》2020年第5期115-121,共7页Desert and Oasis Meteorology

基　　金：国家自然科学基金项目(41875119);中国气象局省级气象科研所科技创新发展项目(SSFZ201806);吉林省气象局科研项目(201709)。

摘　　要：利用1980—2016年第二松花江流域(SSR)夏季(6—8月)平均降水量资料、NCEP/NCAR再分析月平均环流场资料、NOAA的月平均海温场资料,采用年际增量预测方法,通过分析与SSR夏季降水年际增量相关的环流及海温,确定了超前12个月内的6个预测因子,包括:11月东亚200 hPa纬向风、12月西藏高原-2指数、12月赤道中东太平洋200 hPa纬向风、2月印度洋海温、10月西太平洋暖池海温、4月东亚100 hPa经向风。在此基础上利用这6个预测因子,利用1980—2010资料建立SSR夏季降水年际增量的统计预测模型,最后根据年际增量给出SSR夏季降水的预测结果。经检验,1981—2010年SSR夏季降水年际增量的预测拟合系数是0.83,SSR夏季降水预测结果拟合系数为0.67,SSR夏季降水预测结果相对均方根误差为15%,均通过了显著性检验;对2011—2016年进行试报实验,该模型也很好地预测出降水的年际增量变化趋势,除2014年以外,SSR夏季降水预测结果相对均方根误差绝对值都控制在23%以内,2016年仅为-9.9%。因此,通过预测降水的年际增量,进而再预测降水的方法,具有一定的预测技巧,可作为有效方法投入实际业务应用。Based on the summer(June-August)average precipitation observation data during 1980-2016 over the Second Songhua River(SSR)valley,the monthly NCEP/NCAR reanalysis data,and the monthly NOAA sea surface temperature(SST)data,the atmospheric circulation and sea surface temperature anomalies associated with the year-to-year increments of summer precipitation were analyzed.Six key predictors within 12 months in advance were identified by using a year-to-year incremental approach,including the East Asia 200 hPa zonal wind in November,the Tibet Plateau-2 rate of SSR summer precipitation annual increment is 0.83,the fitting coefficient of SSR summer precipitation forecast is 0.67,and the relative root mean square error of SSR summer precipitation forecast is 15%.The prediction test in 2011-2016 shows that the model could well predict the trends of interannual increment of precipitation,except for 2014.the absolute value of relative root mean square error of seasonal precipitation forecast results is controlled within 23%,only-9.9%in 2016.Therefore,the proposed prediction model can be used as an effective method in the practical applications.

关 键 词：第二松花江流域 夏季降水 预测模型 年际增量 

分 类 号：P333[天文地球—水文科学] TP391.9[水利工程—水文学及水资源]