气象2025，Vol.51Issue(5)：566-580,15.DOI:10.7519/j.issn.1000-0526.2025.011501
基于MODE方法的2022年极端"龙舟水"模式降水预报偏差特征
Model Forecast Biases for the Extreme Dragon-Boat Precipitation in 2022 Based on the MODE Method
摘要
Abstract
From 21 May to 21 June 2022,the heaviest dragon-boat precipitation process in the last decade occurred in South China.This extreme precipitation process,featured with strong extremity,large accu-mulated rainfall and frequent occurrence of severe rainfall,caused significant economic losses.In this paper,the forecast products from two operational models,TRAMS and ECMWF,which are commonly used in South China,are selected to divide the torrential rain processes during dragon-boat precipitation into front-zone torrential rain and warm-sector torrential rain.The results are verified and evaluated,so as to under-stand the characteristics of the two models' biases for the front-zone torrential rain and warm-sector tor-rential rain under the background of the extreme dragon-boat precipitation.Compared with the traditional point-to-point method,the MODE method can effectively avoid the phenomenon of high false alarm ratio caused by precipitation position deviation in the model.Further analysis of the number,position,precipi-tation area and intensity of torrential rain objects based on MODE method shows that the high-resolution model TRAMS has better ability to identify and match torrential rain objects than the global model ECMWF.The location of warm-sector torrential rain predicted by TRAMS is mostly biased to the east,while the front-zone torrential rain predicted by ECMWF is basically biased to the north.The deviations in precipita-tion position in the above two are closely related to the forecast errors of southerly airflow at low altitude by different models.The area prediction of the front-zone torrential rain by TRAMS is close to the obser-vation,but the forecast area of warm-sector torrential rain is larger.The forecast areas by ECMWF for both front-zone torrential rain and warm-sector torrential rain are smaller.The prediction of torrential rain intensity and extreme value by TRAMS is closer to the observation than that by ECMWF,but it still un-derestimates the extreme precipitation.This study can provide new experience for forecasters to under-stand the prediction biases of different operational models for dragon-boat precipitation process.It also has some reference values for model developers to further carry out research on error source diagnosis and tech-nical improvement of TRAMS model.关键词
"龙舟水"/锋面暴雨/暖区暴雨/检验评估/模式预报Key words
dragon-boat precipitation/front-zone torrential rain/warm-sector torrential rain/verification and evaluation/numerical model分类
大气科学引用本文复制引用
高翠翠,陈浩伟,徐道生,林晓霞,张邦林..基于MODE方法的2022年极端"龙舟水"模式降水预报偏差特征[J].气象,2025,51(5):566-580,15.基金项目
国家自然科学基金项目(U2142213、42075014)、广东省气象局科研项目(GRMC2022M24、GRMC2023M48、GRMC2023M02)和中国气象局城市气象重点开放实验室开放基金(LUM-2023-07)共同资助 （U2142213、42075014）
