气象学报2025，Vol.83Issue(5)：1286-1300,15.DOI:10.11676/qxxb2025.20240119
基于CMA_CPSv3和CWRF气候模式对2021年7月河南持续性强降水的动力降尺度预测试验研究
Dynamical downscaling prediction of persistent heavy rainfall in Henan province in July 2021 based on CMA_CPSv3 and CWRF climate models
摘要
Abstract
An unprecedented persistent heavy precipitation occurred in Henan province during 17-22 July 2021,causing huge economic losses.Currently,extreme precipitation forecasting is still a hotspot and a difficult issue in sub-seasonal climate prediction research.Regional climate models provide a new way to further improve sub-seasonal precipitation forecasting in China with finer spatial resolution and better parameterization of physical processes compared to that of the global models.This study uses the regional Climate-Weather Research and Forecasting model(CWRF)nested with the China Meteorological Administration Climate Prediction System version 3(CMA_CPSv3)to improve prediction capabilities for this persistent heavy precipitation event.It is shown that the spatial distribution,magnitude,and forecast accuracy of precipitation predicted by CWRF are improved compared to that predicted by CMA_CPSv3.Although both models underestimate the amount of precipitation,the CWRF forecasts larger accumulated precipitation and spatial distribution of precipitation is more consistent with observation.CWRF forecasts initialized on 26 June and 29 June are better than that of CMA_CPSv3 on the same initial dates.The CWRF significantly improves the forecast of low-level wind fields and low-level jets in East Asia compared with the CMA_CPSv3.The CWRF is particularly effective in improving the simulation of directions of low-level jets and water vapor fluxes,allowing water vapor to converge on the windward slopes of mountain ranges and providing favorable water vapor conditions for precipitation.The CWRF better forecasts the water vapor flux convergence and ascending motions over Zhengzhou,and all these improvements lead to higher precipitation forecasting skill of CWRF.关键词
CWRF/CMA_CPSv3/动力降尺度/持续性强降水/次季节预报Key words
CWRF/CMA_CPSv3/Dynamical downscaling/Persistent heavy rainfall/Subseasonal prediction分类
大气科学引用本文复制引用
郝天雨,董李丽,李清泉,谢冰,赵崇博,郭莉,梁信忠..基于CMA_CPSv3和CWRF气候模式对2021年7月河南持续性强降水的动力降尺度预测试验研究[J].气象学报,2025,83(5):1286-1300,15.基金项目
国家重点研发计划项目(2022YFE0136000)、国家自然科学基金项目(U2242207、41790471)、中国气象局气象能力提升联合研究专项青年项目(22NLTSQ007)、中国气象局创新发展专项项目(CXFZ2023J003). （2022YFE0136000）
