云迹风在热带气旋路径数值预报中的应用研究  

IMPACT OF FOUR-DIMENSIONAL VARIATIONAL DATA ASSIMILATION OF THE CLOUD DRIFT WIND DATA ON TROPICAL CYCLONE TRACK NUMERICAL FORECAST

作　　者：王栋梁[1] 梁旭东[1] 端义宏[1] 

机构地区：[1]上海台风研究所,上海200030

出　　处：《气象学报》2005年第3期351-358,共8页Acta Meteorologica Sinica

基　　金：科技部专项"中国台风数值预报模式系统的关键技术研究"资助课题

摘　　要：通过一系列四维变分同化试验对GMS5卫星资料反演的云迹风资料在西北太平洋热带气旋的初始化及路径数值预报中的作用进行研究,同化资料为中国国家卫星气象中心提供的GMS5水汽和红外云迹风资料,其中70%在400hPa以上,50%集中在200～300hPa。应用美国NCAR/PSU中尺度模式MM5及其四维变分同化系统,同化窗口为6h,对初始时刻和6h后的云迹风进行同化。同化前对云迹风资料进行了简单的类似ECMWF初值检验方法的质量控制。对2002年8个西北太平洋热带气旋共进行了22组试验。结果表明,采用四维变分同化技术同化云迹风对热带气旋路径预报有一定改善,12,24,36和48h预报的平均距离误差分别降低5%,12%,10%和7%,但同化云迹风的作用与初始气旋强度有关。选择初始中心海平面气压960hPa作为强、弱气旋的分类标准,则11个较强气旋平均路径误差12h减小了13%,12h以后的预报误差减小率维持在20%以上。而对于11个较弱气旋,平均路径误差反而略有增加,说明同化云迹风资料对不同初始强度的气旋作用也有所不同。其主要原因是由于强度较强的热带气旋往往具有较为深厚的垂直结构,因此受高层大气流场的影响更明显;同时,较弱热带气旋的云迹风观测相对稀少且凌乱,并且更容易受环境气流的影响,因此对于较弱的热带气旋,当模式变量与模式或变量之间在同化后不够协调的话,就会产生负效应。The Objective of this study is to carry out a set of four-dimensional variational (4DVAR) experiments to assess the impact of cloud-drift wind data from the operational Geosynchronous Meteorological Satellite 5 (GMS-5) on improvement of the initial conditionals and numerical track predictions of tropical cyclones (TCs) in the western North Pacific (WNP).The data assimilated were derived from GMS-5 infrared and water vapor imageries and provided by the China National Satellite Meteorological Center. About 70% of the multispectral winds are observed above 400 hPa, and 50% of the data are between 200 and 300 hPa. Experiments were carried out using the Pennsylvania State University-National Center for Atmospheric Research nonhydrostatic Mesoscale Model version 5 (MM5) and its 4DVAR system. A 6-h assimilation window was used to incorporate the cloud-drift wind data at the initial and 6 h later. A simple quality control similar to the first-guess check in the ECMWF system was used here.Twenty-two cases were examined for 8 different WNP TCs in 2002. Forecasts up to 48 h were performed with the original and 4DVAR-assimilated optimal initial conditions. The 4DVAR assimilation of the cloud-drift wind observations led to significant improvements, with the relative reductions in track error by 5% at 12 h, 12% at 24 h, 10% at 36 h and 7% at 48 h on average. But the effectiveness of the assimilation of the cloud-drift wind data apparently varies with TC intensity. If a central pressure of 960 hPa is selected as the demarcation between strong and weak TCs, the mean track error reductions for the 11 strong TCs range from 13% at 12 h to over 20% after 12 h. However, for 11 weak TCs, slight increases in the average track errors were observed. The results suggest that assimilation of the cloud-drift wind data for TCs of different initial intensity has different impact on TC track forecast. This is apparently because stronger TCs are affected to a larger extent by the upper tropospheric circulation, and they usually have a deeper ve

关 键 词：数值预报 云迹风 应用 国家卫星气象中心 中尺度模式MM5 热带气旋路径预报 四维变分同化 西北太平洋 ECMWF 2002年 海平面气压 风资料 资料反演 同化试验 NCAR 质量控制 检验方法 平均距离 气旋强度 分类标准 预报误差 

分 类 号：P456.7[天文地球—大气科学及气象学] P412.15