论文

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

  • 傅朝 ,
  • 刘维成 ,
  • 杨晓军 ,
  • 聂灿奇 ,
  • 彭筱
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  • 兰州中心气象台, 甘肃 兰州 730020

收稿日期: 2018-01-09

  网络出版日期: 2019-02-28

基金资助

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)

Real-Time Analysis of Ensemble Member in Severe Convection Warning——A Case of ECMWF Ensemble Prediction Apply to Heavy Rainfall of Eastern Gansu

  • FU Zhao ,
  • LIU Weicheng ,
  • YANG Xiaojun ,
  • NIE Canqi ,
  • PENG Xiao
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  • Lanzhou Central Meteorological Observatory, Lanzhou 730020, Gansu, China

Received date: 2018-01-09

  Online published: 2019-02-28

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。

本文引用格式

傅朝 , 刘维成 , 杨晓军 , 聂灿奇 , 彭筱 . 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[J]. 高原气象, 2019 , 38(1) : 143 -155 . DOI: 10.7522/j.issn.1000-0534.2018.00061

Abstract

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 how to improve the forecasting ability of low probability but high impact weather by using the ECMWF ensemble forecast system by analyzing this case.

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