大气科学2025，Vol.49Issue(6)：1711-1726,16.DOI:10.3878/j.issn.1006-9895.2501.24061
基于多源资料融合集成的短时强降水短时临近预报技术
Short-Term Nowcasting Forecast Technology for Short-Time Heavy Precipitation Based on Multi-source Data Fusion Integration
摘要
Abstract
A forecast model for short-time heavy precipitation(greater than 20 mm h-1)for 1-12 h at 1-h intervals in Fujian Province and its neighboring provinces is established based on neighborhood analysis with an optimal TS(threat score).This model utilizes real-time precipitation observational data from automatic weather stations,0-120 min quantitative precipitation forecast from SWAN-QPF(Severe Weather Automatic Nowcasting)of the China Meteorological Administration,and forecast precipitation data from global and regional models during April-September 2021-2023.A neighborhood test with a radius of 40 km is adopted.The results indicate that the accuracy of the nowcast in the initial hours is greatly improved by incorporating real-time precipitation observations to forecast the short-time heavy precipitation(persistence forecast)compared with forecasts based on multimodel optimal weight integration.After the optimal elimination threshold correction,the TS can reach 37.5%for 2021 and 32.2%in 2022 for 1-h forecast lead time when the forecast precipitation is calculated using 10 min real-time precipitation prior to the forecast production,with a neighborhood radius(Ri)of 0.5° and the average of the top 5(Ntop=5)heavy precipitation stations within Ri.The TS can reach 22.2%for 2021 and 19.5%in 2022 in 2-h forecast lead time.The TS of the consensus forecast combining global and regional models with optimized weights can reach 16.2%for 2021 and 16.6%in 2022 for 1-h forecast lead time(18.0%and 14.2%in 2-h forecast lead time,respectively)when the forecast precipitation is calculated using Ri=0.6° for each model and Ntop=15.The SWAN-QPF short-time heavy precipitation predictions revised by the optimal elimination threshold(with Ri=0.3° and Ntop=15)are also better than the multimodel optimal weight integration,but they are less effective than predictions using real-time observational precipitation in the first few hours.For the 3-12-h forecast lead time,multimodel optimal weight integration is better than the other two methods.The above mentioned multisource data,revised by the optimal elimination threshold,are further integrated with optimized weights for 1-4-h forecast lead time,whereas multimodel optimal weight integration is adopted in the 5-12-h forecast lead time to establish the short-time heavy precipitation model for 1-12-h forecast lead time at 1-h intervals.The parameters trained with 2021 and 2022 data are applied to forecast short-time heavy precipitation in Fujian in 2023,yielding TS of 42.7%,28.8%,23.1%,and 20.2%for the 1-4-h forecast lead time,respectively,with all values exceeding 17%for the 5-12-h forecast lead time.关键词
短时强降水/持续性预报/有效邻域半径/最优时段累计降水量Key words
Short-time heavy precipitation/Persistence forecast/Effective neighborhood radius/Cumulated precipitation in optimal period分类
天文与地球科学引用本文复制引用
张海燕,吴启树,危国飞,付超,林子伦..基于多源资料融合集成的短时强降水短时临近预报技术[J].大气科学,2025,49(6):1711-1726,16.基金项目
福建省自然科学基金项目2024Y0076、2022J011078、2023J011333,福建省气象局开放式气象科学研究基金项目2023KJ03,福建省自然科学基金社会发展引导性(重点)项目2025Y0064,软件自动生成与智能服务四川省重点实验室开放课题2022KFKT(10)013 Natural Science Foundation of Fujian(Grants 2024Y0076,2022J011078,2023J011333),Open Meteorological Science Research Fund of Fujian Meteorological Bureau(Grant 2023KJ03),Social Development Guiding(Key)Project of the Natural Science Foundation of Fujian(Grant 2025Y0064),Software Automatic Generation and Intelligent Service Sichuan Key Laboratory Open Project(Grant 2022KFKT(10)013) （重点）
