摘要
利用WRF(Weather Research and Forecast)模式及WRFDA(WRF model data assimilation system)系统,针对2017年台风“天鸽”个例通过同化雷达径向速度(Vr)和反射率因子(RF),研究水凝物控制变量的雷达资料同化对台风分析预报的影响。研究表明:雷达径向速度的直接同化有效地改进了模式初始场中台风涡旋区的中小尺度信息,分析场中产生了气旋性的风场增量,对模式背景场中的台风有显著增强作用。通过在传统控制变量中扩展针对水凝物的控制变量可有效地同化雷达反射率因子资料,对初始场的水物质进行调整,并对随后确定性预报的台风路径和强度都有一定的正效果。此外,相比没有水凝物控制变量的雷达同化试验,加入了水凝物控制变量的雷达资料同化试验降水预报效果更好。这为将我国近海的地基多普勒天气雷达用于台风初始化分析和预报提供了一定的技术支撑和保障。
In the present study,the impact of radar radial velocity and reflectivity assimilation using hydrometeor control variables on the analyses and forecast of Typhoon Hato was investigated using the Weather Research and Forecast model and its data assimilation system.It was found that the direct assimilation of radar radial velocity effectively improved the small-and-meso scale data in the typhoon vortex area and generated a cyclonic wind field increment in the analysis field,which significantly enhanced the typhoon in the background field of the model.With the introduction of the control variables of hydrometeors to the traditional control variables,the radar reflectivity factor data can be effectively assimilated,the hydrometeors in the initial field can be adjusted,and it had a positive effect on the subsequent deterministic forecast of the track and intensity of the typhoon.In addition,compared with the radar assimilation trial without hydrometeor control variables,the trial with hydrometeor control variables can produce a better precipitation forecast.These results could help ensure full use of the ground-based Doppler weather radar in offshore China.
作者
沈菲菲
闵锦忠
吴乃庚
李泓
束艾青
王易
欧紫娴
SHEN Feifei;MIN Jinzhong;WU Naigeng;LI Hong;SHU Aiqing;WANG Yi;OU Zixian(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;Shanghai Typhoon Institute,China Meteorological Administration,Shanghai 200030,China;Guangzhou Institute of Tropical and Marine Meteorology/Guangdong Provincial Key Laboratory of Regional Numerical Weather Prediction,China Meteorological Administration,Guangzhou 510641,China;The Institute of Atmospheric Environment,China Meteorological Administration,Shenyang 110166,China;Heavy Rain and Drought-Flood Disasters in Plateau and Basin Key Laboratory of Sichuan Province,Chengdu 610225,China;Jiangsu Meteorological Observatory,Nanjing 210008,China)
出处
《热带气象学报》
CSCD
北大核心
2023年第1期23-36,共14页
Journal of Tropical Meteorology
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(U2242212、42075014、41805070、41575107)
上海市优秀学术/技术带头人计划(21XD1404500)
上海台风研究基金项目(TFJJ202107)
广东省自然科学基金项目(2021A1515011539)
高原与盆地暴雨旱涝灾害四川省重点实验室开放研究基金项目(SZKT201901)
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(2020SYIAE07)
江苏省气象局科研重点项目(KZ202001)共同资助。
