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一次高原强降水过程的对流尺度集合预报试验及诊断分析

刘侃 陈超辉 何宏让 姜勇强

气象科学2024,Vol.44Issue(5):847-856,10.
气象科学2024,Vol.44Issue(5):847-856,10.DOI:10.12306/2023jms.0071

一次高原强降水过程的对流尺度集合预报试验及诊断分析

Convective-scale ensemble forecast experiment and diagnostic analysis of a high-altitude heavy precipitation process

刘侃 1陈超辉 1何宏让 1姜勇强1

作者信息

  • 1. 国防科技大学气象海洋学院,长沙 410073
  • 折叠

摘要

Abstract

The GPM(Global Precipitation Measurement)satellite data and ERA5(ECMWF Reanalysis v5)were used to perform ensemble forecast simulation,evaluation and diagnostic analysis on a severe precipitation event that occurred in the southwest plateau region of China on May 9-10,2014.Results found that the WRF model successfully reproduces the severe precipitation event,and the ensemble average forecast generated using the BGM(Breeding Growth Mode)and LBGM(Local Breeding Growth Mode)initial perturbation methods had better forecast accuracy than the control forecast,with the LBGM evaluation producing better results.The severe precipitation area was located in a region of high atmospheric moisture divergence and low-level convergence,and the distribution of negative vertical vorticity and positive vertical vorticity in the upper and lower levels of the atmosphere corresponded to the precipitation area.The study also identified the positive and tilted pressure of wet potential vorticity as having a certain indicative significance for severe precipitation,with the negative MPV1 region at 850 hPa and the positive MPV2 region corresponding well with the precipitation band and intensity development.The LBGM scheme exhibits superior improvement in rainfall intensity compared to the BGM scheme,primarily due to the more realistic simulation of water vapor flux divergence and vorticity in the LBGM scheme.

关键词

对流尺度集合预报/强降水成因/动力场诊断/机理分析

Key words

convection-allowing ensemble forecasting/cause of heavy rainfall/dynamic diagnosis/mechanistic analysis

分类

天文与地球科学

引用本文复制引用

刘侃,陈超辉,何宏让,姜勇强..一次高原强降水过程的对流尺度集合预报试验及诊断分析[J].气象科学,2024,44(5):847-856,10.

基金项目

国家自然科学基金资助项目(42275169 ()

42205045) ()

湖南省自然科学基金资助项目(2022JJ30660) (2022JJ30660)

气象科学

OACSTPCD

1009-0827

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