长江中游临近预报业务系统(MYNOS)及其应用  

Nowcasting & Warning Operational System in the Middle Reaches of the Yangtze with Its Implementation

作　　者：万玉发[1] 王志斌[1] 张家国[2] 吴翠红[2] 吴涛[2] 王珏[2] 

机构地区：[1]中国气象局武汉暴雨研究所,武汉430074 [2]武汉中心气象台,武汉430074

出　　处：《应用气象学报》2013年第4期504-512,共9页Journal of Applied Meteorological Science

基　　金：湖北省科技攻关计划项目(2004AA306B01);中国气象局气象新技术推广项目(CMATG2007M19);中国气象局气象关键技术集成与应用项目(CAMGJ2012M32)

摘　　要：针对长江中游强风暴天气特点和现代预报业务需求,在借鉴世界临近预报系统,特别是美国的Auto-Nowcaster和WDSS-Ⅱ以及英国的GANDOLF等先进经验的基础上,以我国多普勒天气雷达网为重要技术手段,结合数值预报等信息资源,于2007年研究建成长江中游临近预报业务系统(MYNOS)。MYNOS主要技术方法包括:雷达与雨量计实时同步积分结合的降水估算方法(RASIM),雷达反演参量与中尺度模式输出物理量相结合的强风暴性质自动识别和追踪技术,基于暴雨回波生命史特性约束下的多尺度合成降水量临近预报,基于数值预报模式和模糊逻辑学的强对流天气分类落区潜势预报,集GIS功能并整合各种定量监测与预警产品于一体的短时预报工作站。MYNOS已成为短时临近预报业务的支撑平台,其中实时生成的流域定量降水估算与临近预报、强对流天气分类潜势诊断与识别预警产品等成为日常预报业务的重要参考依据。In order to meet the need for modern operational forecasting of severe storm events in the middle reaches of the Yangtze, MYNOS （Nowcasting ＆ warning Operational System in the Middle reaches of theY- angtze）, an advanced and useful nowcasting system, is originally established in 2007 based on the experi- ences of the advanced nowcasting systems Auto-Nowcaster and WDSS-II of USA and GANDOLF of UK. MYNOS combines the resources of new generation radar network in China with the data from numerical weather prediction. Several advanced techniques and methods are developed and adopted as follows. Quali- ty control of radar reflectivity field and the precipitation echo classification are achieved by identifying the structures of the vertical gradient and horizontal textures of radar reflectivity echoes. Real time formation technique of vertical reflectivity profile （VPR） is developed and used for vertical calibration of precipitation reflectivity factor. Important concepts of ＂quasi same-rain-volume sample＂ and ＂hourly equivalent reflec- tivity factor＂ are proposed, and the synchronously integrated method of radar and rain gauge （RASIM） is established. The cell gravity potential energy, as an important physical component of radar for describing the life span of storms, is proposed. The technique for automatic identification and tracking of severe weather is developed by means of radar derived parameters and the meso-scale output of physical parame- ters. The multi-scale characteristics of storm echoes through their life courses are analyzed and the echo filtering technique is studied, and the multi-scale precipitation nowcasting confined to the life time of each scale echo is realized. Potential forecasting products for severe convection meteorological phenomena （tor- rential rain, hail, thunderstorm, etc. ） are developed based on numerical models and fuzzy logics. The problem of image registration and animation in ordinary GIS （Geographic Information System） is solved by introducing custom

关 键 词：长江中游临近预报业务系统 强对流 定量监测 自动识别 

分 类 号：P456[天文地球—大气科学及气象学]