摘要
利用欧洲中心(European Center for Medium-Range Weather Forecasts,ECMWF)ERA-interim再分析资料、常规气象观测资料及多普勒雷达资料,对辽宁省境内发生的2007年"0304"、2009年"0212"和2017年"0221"共3次暴雪过程进行对比分析,主要研究3次暴雪过程的大尺度环流背景条件、气团、水汽来源及雷达回波和雷达参量特征的异同。结果表明:辽宁省3次暴雪过程均为受高空槽影响产生的,高空低槽配合地面冷锋或倒槽,导致动力抬升条件增强;来自不同水汽源地的气团和冷暖气团的交绥是暴雪过程增强的关键因素;降雪过程的雷达回波强度不超过40 d Bz,回波顶高低于10 km;雷达参量Z_(max)和Z_(mean15)的演变与降雪过程强弱的变化对应较好,强回波中心增强和及地的时段与主要降雪时段较一致,可以揭示系统强度的变化和降水粒子的下落,对降雪天气具有一定的预报意义。
Three heavy snow processes occurring in Liaoning province on March 4,2007, February 12,2009, and February 21,2017 respectively, were investigated based on the ECMWF (European Center for Medium-Range Weather Forecasts) ERA-interim reanalysis data, convention observations and echo data from the Doppler radar. The similarities and differences of the large scale circulation background, air mass source, vapor source and characteristics of the radar echo parameter of these three processes were studied. The results indicate that the three events are all caused by the influences of the upper-level trough. The upper-level trough cooperated with the surface inverted trough or cold front strengthens the dynamic lift. The air masses from different water vapor sources and the convergence of cold and warm air are the key factors to strengthen the snowfall processes. The reflectivity of the snowfall process is usually below 40 dBz, and the maximum echo depth is less than 10 km. The maximum reflectivity (ZmAx) and the average value of the radar reflectivity larger than 15 dBz (Zmeanl5) at each level within the thunderstorm correspond very well with the process of snowfall and reveal the intensity change of the systems and the drop conditions of the precipitation particles. It is important to the forecasting of rainfall.
作者
胡鹏宇
徐爽
陈传雷
杨磊
纪永明
孙丽
HU Peng-yu;XU Shuang;CHEN Chuan-lei;YANG Lei;Jt Yong-ming;SUN Li(Liaoning Meteorological Disaster Monitoring and Early Warning Center,Shenyang 110166,China;Shenyang Meteorological Service,Shenyang 110168,China;Weather Modification Office in Liaoning Province,Shenyang l10166,China)
出处
《气象与环境学报》
2018年第3期18-27,共10页
Journal of Meteorology and Environment
基金
中国气象局预报员专项(CMAYBY2017-015)
辽宁省气象局科学技术项目(BA201809)共同资助