摘要
天气雷达对中小尺度灾害性天气具有较强的监测预警能力,对研究中小尺度对流系统的云雨结构、理解降水内部的热力学和动力学过程有很大的帮助。单站点地基雷达受到诸如电磁波衰减、地物干扰等影响,在探测上存在一些限制。为了扩大天气雷达探测区域,需要采用多部天气雷达组网联合探测。然而雷达组网的各雷达之间没有进行统一标定,影响雷达网资料一致性、组网拼图,以及使雷达资料在数值模式同化的应用中受到限制。本文以TRMM(Tropical Rainfall Measuring Mission)卫星搭载的经过精确标定的测雨雷达PR(Precipitation Radar)数据产品作为标准参照源,订正地基雷达GR(Ground-based Radar)的反射率因子偏差。为了减小PR与GR之间观测值对比的不一致性,利用最佳配对数据对比法(ABCD, Available Best Comparable Dataset法),对2008年1月至2014年9月间,江苏省六部地基雷达(南京、常州、连云港、南通、徐州、盐城)的反射率因子值进行订正。最后对方法的应用范围、存在的问题及未来展望进行了讨论。
The weather radar has a strong ability of monitoring and early warning for small and medium-scale disastrous weather,which is of great help to study the cloud-rain structure of small and medium-scale convective systems and understand the thermodynamics and dynamics processes inside the precipitation.The single-site ground-based radars are subject to such effects as the attenuation of electromagnetic waves and the interference of ground objects,and there are some limitations in detection.In order to extend the weather radar detection area,multiple weather radar networks are needed for joint detection.However,there is no uniform calibration among radars of the radar network,which affects the data consistency of radar network,the networking mosaic,and limits the application of radar data in numerical model assimilation.In this paper,the accurately calibrated Precipitation Radar(PR)data product on the Tropical Rainfall Measuring Mission(TRMM)satellite is used as a standard reference source to correct the reflectivity factor deviation of the Ground-based Radar(GR).In order to reduce the inconsistency between the observed values of PR and GR,the Available Best Comparable Dataset(ABCD)method is used to correct the reflectivity factor deviation of six GRs in Jiangsu Province(Nanjing,Changzhou,Lianyungang,Nantong,Xuzhou,Yancheng)from January 2008 to September 2014.Finally,the application scope,existing problems and future prospects of the method are discussed.
作者
韩静
楚志刚
王振会
徐芬
冷亮
朱艺青
HAN Jing;CHU Zhigang;WANG Zhenhui;XU Fen;LENG Liang;ZHU Yiqing(Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters,CMA Key Laboratory for Aerosol-Cloud-Precipitation,Nanjing University of Information Science & Technology,Nanjing 210044,China;School of Atmospheric Physics,Nanjing University of Information Science & Technology,Nanjing 210044,China;Hainan Institute of Meteorological Sciences,Haikou 570203,China;South China Sea Meteorology and Disaster Mitigation Research Key Laboratory,Haikou 570203,China;Jiangsu Institute of Meteorological Sciences,Nanjing 210009,China;Wuhan Institute of Heavy Rain,Wuhan 430074,China)
出处
《气象科学》
北大核心
2019年第1期93-103,共11页
Journal of the Meteorological Sciences
基金
公益性行业科研专项(GYHY201306078)
国家自然科学基金资助项目(41275043)
江苏高校优势学科建设工程资助项目(PAPD)