雷达资料同化对2016年6月23日阜宁龙卷模拟的改进
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摘 要 基于 GSI(Community Gridpoint Statistical Interpolation)同化系统和 WRFCWeather Research and Forecasting)模式， 探讨了多部多普勒雷达的反射率因子和径向速度资料同化对2016年6月23日江苏阜宁龙卷模拟的改进效果和影响过程。 结果表明：1)仅同化雷达反射率因子和仅同化径向速度均能在一定程度上改进模式对阜宁龙卷及其环境场的模拟，且雷达 径向速度同化的改进作用更大；同时同化两种资料改进效果最佳。(2)雷达反射率因子同化是利用复杂云分析技术，直接修
陈锋，董美莹，冀春晓，梁旭东.2019.雷达资料同化对2016年6月23日阜宁龙卷模拟的改进.气象学报，77(3)405426 Chen Feng, Don犵 Meiying, Ji Chunxiao, Liang Xudong. 2019. Improving the simulation of the tornado occurring in Funing on 23
June 2016 by using radar data assimilation. Acta Meteorologica Sinica , 77(3) ： 405-426
Abstract The reflectivity and radial velocity data from multiple Doppler radars were assimilated by the Community Gridpoint Statistical Interpolation (GSI) system, and a tornado occurred in Funing on 23 June 2016 was then simulated and studied by u sing the Weather Research and Forecasting (WRF) model. The main results are as follows. (1) The simulations can be im proved to some extent by assimilating either radar reflectivity or radial velocity. The experiment with both the radar reflectivity andradialvelocityassimilatedshowthebestresult, andtheradialvelocityplaysamoreimportantrolethanthereflectivity．(2) Assimilation of radar reflectivity by using complex cloud analysis system can efficiently adjust the initial hydrometeors and ther mal fields, which makes an important contribution to the adjustment of water vapor and thermal conditions. Assimilation of radarradialvelocityviathethree-dimensionalvariationaldataassimilationsystemdirectlyafectsthewindfieldandsubsequently affects the water vapor transport, hydrometeors and instability, which makes an important contribution to the adjustment of dynamcandthermalcondtons.Assmlatonofboththeradarreflectvtyandtheradalveloctycancombnetheradvantages toobtanabestbalanceamongdynamc，watervaporandthermalcondtons. (3) Wthassmlatonofboththeradarreflectvtyandtheradalvelocty，thestorm wththevortexstructureoftornadonearFunngcanbesmulatedbythemodel.Thesmulated storm occurrence, development, track, surface hourly maximum wind speed and precipitation agree well with observa tions ,although certain gaps still exist between the simulation and observations with respect to the strength and structure of the vortex. Keywords Radar data assimilation, Tornado, Numerical simulation
doi：10. 11676/qxxb2019. 025
气象学报
雷达资料同化对2016年6月23日 阜宁龙卷模拟的改进*
陈锋1董美莹1冀春晓1梁旭东2
CHEN Feng1 DONG Meiying1 JI C江省气象科学研究所，杭州，310008 2. 中国气象科学研究院灾害天气国家重点实验室，北京，100081 1. Zhejiang Institute of Meteorological Sciences , Hangzhou 310008, China 2. State Key Laboratrry of Severe Weathrr , Chinese Academy of Meteorological Sciencss , Beijing 100081, China 2018-04-27 收稿,018-10-16 改回.
陈锋，董美莹，冀春晓，梁旭东.2019.雷达资料同化对2016年6月23日阜宁龙卷模拟的改进.气象学报，77(3)405426 Chen Feng, Don犵 Meiying, Ji Chunxiao, Liang Xudong. 2019. Improving the simulation of the tornado occurring in Funing on 23
June 2016 by using radar data assimilation. Acta Meteorologica Sinica , 77(3) ： 405-426
Abstract The reflectivity and radial velocity data from multiple Doppler radars were assimilated by the Community Gridpoint Statistical Interpolation (GSI) system, and a tornado occurred in Funing on 23 June 2016 was then simulated and studied by u sing the Weather Research and Forecasting (WRF) model. The main results are as follows. (1) The simulations can be im proved to some extent by assimilating either radar reflectivity or radial velocity. The experiment with both the radar reflectivity andradialvelocityassimilatedshowthebestresult, andtheradialvelocityplaysamoreimportantrolethanthereflectivity．(2) Assimilation of radar reflectivity by using complex cloud analysis system can efficiently adjust the initial hydrometeors and ther mal fields, which makes an important contribution to the adjustment of water vapor and thermal conditions. Assimilation of radarradialvelocityviathethree-dimensionalvariationaldataassimilationsystemdirectlyafectsthewindfieldandsubsequently affects the water vapor transport, hydrometeors and instability, which makes an important contribution to the adjustment of dynamcandthermalcondtons.Assmlatonofboththeradarreflectvtyandtheradalveloctycancombnetheradvantages toobtanabestbalanceamongdynamc，watervaporandthermalcondtons. (3) Wthassmlatonofboththeradarreflectvtyandtheradalvelocty，thestorm wththevortexstructureoftornadonearFunngcanbesmulatedbythemodel.Thesmulated storm occurrence, development, track, surface hourly maximum wind speed and precipitation agree well with observa tions ,although certain gaps still exist between the simulation and observations with respect to the strength and structure of the vortex. Keywords Radar data assimilation, Tornado, Numerical simulation
doi：10. 11676/qxxb2019. 025
气象学报
雷达资料同化对2016年6月23日 阜宁龙卷模拟的改进*
陈锋1董美莹1冀春晓1梁旭东2
CHEN Feng1 DONG Meiying1 JI C江省气象科学研究所，杭州，310008 2. 中国气象科学研究院灾害天气国家重点实验室，北京，100081 1. Zhejiang Institute of Meteorological Sciences , Hangzhou 310008, China 2. State Key Laboratrry of Severe Weathrr , Chinese Academy of Meteorological Sciencss , Beijing 100081, China 2018-04-27 收稿,018-10-16 改回.