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强对流临近预警中集合预报成员的即时分析——以陇东一次暴雨过程ECMWF集合预报应用为例
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  • 英文篇名:Real-Time Analysis of Ensemble Member in Severe Convection Warning——A Case of ECMWF Ensemble Prediction Apply to Heavy Rainfall of Eastern Gansu
  • 作者:傅朝 ; 刘维成 ; 杨晓军 ; 聂灿奇 ; 彭筱
  • 英文作者:FU Zhao;LIU Weicheng;YANG Xiaojun;NIE Canqi;PENG Xiao;Lanzhou Central Meteorological Observatory;
  • 关键词:ECMWF集合预报 ; 集合成员 ; 暴雨 ; 即时分析
  • 英文关键词:ECMWF ensemble prediction;;ensemble member;;heavy rainfall;;real-time analysis
  • 中文刊名:高原气象
  • 英文刊名:Plateau Meteorology
  • 机构:兰州中心气象台;
  • 出版日期:2018-12-14 16:37
  • 出版单位:高原气象
  • 年:2019
  • 期:01
  • 基金:公益性行业(气象)科研专项(GYHY201306006);; 国家自然科学基金项目(41505036);; 国家科技支撑计划项目(2015BAC03B06);; 甘肃省气象局气象科研项目(青年优秀科技人才专项)
  • 语种:中文;
  • 页:146-158
  • 页数:13
  • CN:62-1061/P
  • ISSN:1000-0534
  • 分类号:P456;P458.121.1
摘要
2015年5月31日甘肃陇东地区出现一次暴雨天气过程,ECMWF集合预报系统的降水预报只有1个成员(简称EM-p)预报出暴雨,并且EM-p对预报暴雨落区、量级和降水时段的预报与观测实况基本接近。本文通过对EM-p和集合预报系统控制成员预报效果的对比分析,以及EM-p与实况的对比分析表明,EM-p对产生暴雨的对流参数预报完全符合本地经验指标,虽然对低层急流预报出现一定程度偏差,但对低层辐合区(暴雨落区)位置的预报与观测实况极为接近,因此EM-p成员能够为暴雨的短时预报和临近预警提供可靠的定量依据,可有效提前暴雨预警时间。通过分析,期望为如何利用ECMWF集合预报有效判断低概率但高影响天气的发生提供一些有益的思路。
        As for the heavy rain occurred in the eastern Gansu on 31 May 2015,only one ensemble-member( shorten as EM-p) of ECMWF ensemble forecast system predicted this heavy rain process accurately. The data of the predicted precipitation area,intensity,and rainfall time by EM-p are closer to that of the observation. In this paper,a comparative analysis of the forecast of EM-p,the forecast of control ensemble-member,and observation was conducted. The result indicated that the predicted convection parameters of the heavy rain by EM-p are consistent with the local experience. EM-p can accurately predict the location of the lower-level convergence area( the heavy rain area) although with a deviation in the prediction of lower-level jet. Therefore,EM-p can provide a reliable basis for the short-term forecast and warning of heavy rain,which can also advance the heavy rain warning time effectively. It is hoped to provide a reference for howto improve the forecasting ability of lowprobability but high impact weather by using the ECMWF ensemble forecast system by analyzing this case.
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