IAP AGCM 4.1对淮河流域夏季降水的预报技巧评估  

Evaluation on the forecast skill of summer rainfall over Huaihe River Basin with IAP AGCM4.1

作　　者：陈子煊 林朝晖[2,3] 江志红[1,2] 俞越[3,4] CHEN Zixuan;LIN Zhaohui;JIANG Zhihong;YU Yue(Key Laboratory of Meteorological Disaster,Ministry of Education（KLME）/Joint International Research Laboratory of Climate and Environment Change（ILCEC）,Nanjing University of Information Science ＆ Technology,Nanjing 210044,China;Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters,Nanjing University of Information Science ＆ Technology,Nanjing 210044,China;International Center for Climate and Environment Sciences,Institute of Atmospheric Physics,Chinese Academy of Sciences,Be（ing 100029,China;University of Chinese Academy of Sciences,Beijing 100049,China)

机构地区：[1]南京信息工程大学气象灾害教育部重点实验室/气候与环境变化国际联合实验室,南京210044 [2]南京信息工程大学气象灾害预报预警与评估协同创新中心,南京210044 [3]中国科学院大气物理研究所国际气候与环境科学中心,北京100029 [4]中国科学院大学,北京100049

出　　处：《气象科学》2018年第4期489-497,共9页Journal of the Meteorological Sciences

基　　金：公益性行业(气象)科研专项重点项目(GYHY201406021);国家重点研发计划项目(2016YFC0402702);国家自然科学基金资助项目(41575095)

摘　　要：基于中国科学院大气物理研究所新一代大气环流模式IAP AGCM 4.1共30 a(1981—2010年)的集合回报试验结果,评估了模式对淮河流域夏季降水的预报技巧。分析结果表明,模式总体上可以较好地再现出淮河流域夏季平均降水南多北少的空间分布特征,其中模式模拟的6月降水量与观测值的空间相关可达0.93。但降水强度与观测相比具有系统性的偏差,且模式模拟的降水年际变率显著偏弱。基于降水距平相关系数的确定性预报技巧分析表明,模式对流域西南部夏季降水的预测技巧较高,达到0.2以上,且模式对6月降水异常的预测能力相对最好,7月次之。针对淮河不同子流域的预报技巧分析表明,IAP AGCM 4. 1对蚌埠、鲁台子、王家坝水文控制站以上集水面积的夏季面雨量异常具有一定的预报技巧,30 a集合回报的时间相关系数分别为0. 11、0. 13、0. 16。基于降水等级的概率预报技巧评估表明,模式对7月淮河流域南部少雨事件具有很好的预报能力,同时对6月流域中部多雨事件的预报技巧也较高。The forecast skill of summer ranifall over Huaihe River Basin（ HRB） was evaluated based on the 30-year ensemble hindcasting experiment from 1981 to 2010 of IAP Atmospheric General Circulation Model Version 4.1（ IAP AGCM4.1）. The results show that the IAP AGCM4.1 can generally reproduce the observed spatial distribution of summer-averaged rainfall over the HRB, the spatial correlation coefficient between precipitation and observation simulated by the model reaches 0.93 for June.However,systematic bias can be found in rainfall intensity and observation,and the rainfall interannual variability simulated by the model is also significantly weaker than the observation. The deterministicpredictive skill of summer rainfall over HRB by IAP AGCM4. 1, in terms of anomaly correlation coefficient（ ACC）,was found to be relatively higher in Southwestern HRB,where the ACC is larger than0.2. The deterministic rainfall forecast skill for the whole HRB is the highest for June,and July is the second. For the mean areal rainfall of main sub-catchments in Huaihe River,IAP AGCM4.1 does show certain forecast skill,with ACC reaching 0. 11 for Bengbu drainage basin,0. 13 for Lutaizi drainage basin,and 0.16 for Wangjiaba drainage basin,respectively. Based on the probabilistic forecast skill using rainfall,it’s found that the IAP AGCM4.1 shows a high skill in forecasting the below-normal rainfall events occurred in Southern part of HRB in July,and the above-normal rainfall events in the central part of HRB in June.

关 键 词：IAP AGCM 4. 1大气环流模式 季节预测 淮河流域 夏季旱涝 面雨量 

分 类 号：P457.6[天文地球—大气科学及气象学]