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基于CMA-BJ的北京地区雷达弱回波区径向风同化及其对暴雨预报的影响

刘心智 范水勇 陈耀登 陈敏

热带气象学报2026,Vol.42Issue(2):250-260,11.
热带气象学报2026,Vol.42Issue(2):250-260,11.DOI:10.16032/j.issn.1004-4965.2026.022

基于CMA-BJ的北京地区雷达弱回波区径向风同化及其对暴雨预报的影响

Radial Velocity Assimilation Within the Weak Echo Region in Beijing Based on CMA-BJ and Its Impact on Heavy Rainfall Prediction

刘心智 1范水勇 2陈耀登 1陈敏2

作者信息

  • 1. 南京信息工程大学气候系统预测与变化应对全国重点实验室/气象灾害教育部重点实验室/气象灾害预报预警与评估协同创新中心,江苏 南京 210044
  • 2. 北京城市气象研究院,北京 100089
  • 折叠

摘要

Abstract

In order to utilize radial velocity observations within the weak echo region and investigate the application of their assimilation on regional model forecasts,a cyclic assimilation and forecasting experiment based on the CMA-BJ 2.0 system was conducted for a heavy precipitation event in southwestern Beijing.The data analysis revealed that the radial velocity in the weak echo region is primarily distributed around the periphery of the convection,with substantial data available at both high and low atmospheric levels.The cyclic assimilation and forecasting experiment demonstrate that assimilating radar radial velocity observations in weak echo region,in addition to those from strong echo region assimilation,can gradually enhance the overall dynamics of the analyzed field.Furthermore,this approach improves the forecast accuracy of conventional elements in both the high and low atmospheric layers.This results in more reasonable adjustments to the dynamics,thermal,and water vapor fields of the model,effectively enhancing the prediction of 3 h and 6 h precipitation.The study highlights the significant role of radial velocity assimilation within the weak echo region in improving convective forecasting,providing valuable insights for operational applications.

关键词

雷达资料同化/弱回波/径向风/对流预报

Key words

radar data assimilation/weak echoes/radial velocity/convective forecasts

分类

天文与地球科学

引用本文复制引用

刘心智,范水勇,陈耀登,陈敏..基于CMA-BJ的北京地区雷达弱回波区径向风同化及其对暴雨预报的影响[J].热带气象学报,2026,42(2):250-260,11.

基金项目

国家自然科学基金项目(U2442218、U2442601) (U2442218、U2442601)

气象灾害教育部重点实验室&气象灾害预报预警与评估协同创新中心联合开放课题(KLME202306)共同资助 (KLME202306)

热带气象学报

1004-4965

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