FY-2G云导风资料同化在台风“天鸽”数值预报中的应用  

Application of FY-2G AMVs data assimilation in typhoon"Hato"numerical forecasting

作　　者：许冬梅[1,2,3] 束艾青 李泓 吴海英[5] 何志新[6] 沈菲菲[1,2,4] 庄雨馨[1] XU Dongmei;SHU Aiqing;LI Hong;WU Haiying;HE Zhixin;SHEN Feifei;ZHUANG Yuxin(Key Laboratory of Meteorological Disaster,Ministry of Education(KLME)/Joint International Research Laboratory of Climate and Environment Change(ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD),Nanjing University of Information Science&Technology,Nanjing 210044 China;Heavy Rain and Drought-Flood Disasters in Plateau and Basin Key Laboratory of Sichuan Province,Chengdu 610225 China;The Institute of Atmospheric Environment,China Meteorological Administration,Shenyang 110000 China;Shanghai Typhoon Institute,China Meteorological Administration,Shanghai 200030 China;Jiangsu Meteorological Observatory,Nanjing 210041 China;Anhui Meteorological Observatory,Hefei 230031 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合作联合实验室/气象灾害预报预警与评估协同创新中心,江苏南京210044 [2]高原与盆地暴雨旱涝灾害四川省重点实验室,四川成都610225 [3]中国气象局沈阳大气环境研究所,辽宁沈阳110000 [4]中国气象局上海台风研究所,上海200030 [5]江苏省气象台,江苏南京210041 [6]安徽省气象台,安徽合肥230031

出　　处：《海洋预报》2022年第1期56-66,共11页Marine Forecasts

基　　金：国家自然科学基金重大项目(42192553);国家自然科学基金项目(G41805016,G41805070);江苏省自然科学基金项目(BK20201506);上海市优秀学术/技术带头人计划(项目编号:21XD1404500);上海台风研究基金项目(TFJJ202107,TFJJ201909);四川省重点实验室开放研究基金项目(SZKT201901,SZKT201904,SZKT202002);中国气象局沈阳大气环境研究所和东北冷涡研究重点开放实验室联合开放基金项目(2020SYIAE02,2020SYIAE07)。

摘　　要：以2017年8月登陆我国的13号台风“天鸽”为个例,采用美国全球预报系统资料作为背景场,利用WRF中尺度数值模式及天气研究和预报模式同化系统中的三维变分模块,探究了新一代静止卫星FY-2G云导风资料同化对台风预报的影响。研究结果表明:云导风资料同化模拟的台风路径、强度和最大风速与实况更加接近。与控制试验相比,云导风资料同化能够为背景场提供丰富的风矢量信息,增强台风周围对流云及其引导气流的强度,从而较好地模拟台风的内部结构,对影响其发展和维持的水汽条件与动力条件进行改进。In order to explore the influence of FY-2G AMVs data assimilation on typhoon forecast,FY-2G AMVs data assimilation and numerical simulation experiments are conducted in this paper by taking typhoon Hato(No.1713)as an example that landed in China in August 2017.The Global Forecasting System data are used as background,and the mesoscale numerical model and data assimilation method are the WRF and 3DVAR data assimilation module of the Weather Research and Forecasting model Data Assimilation system,respectively.The results show that the typhoon track,intensity,and maximum wind speed simulated with AMVs data assimilation match better with the observation.Compared with the control experiment,AMVs data assimilation can provide abundant wind vector information in the background field and enhance the strength of convective clouds around the typhoon and its steering flow.Therefore,the internal structure of typhoon can be well simulated,and the water vapor condition and dynamic condition that affect the development and maintenance of the typhoon can be improved.

关 键 词：FY-2G云导风 WRF模式 3DVAR 数值预报 

分 类 号：P457.8[天文地球—大气科学及气象学]