热带气象学报2024，Vol.40Issue(6)：1005-1017,13.DOI:10.16032/j.issn.1004-4965.2024.089
基于改进U-Net模型的湖南地区定量降水预报订正试验
Research on Quantitative Precipitation Correction Forecasting Based on the Improved U-Net Model in Hunan
摘要
Abstract
This study presents a quantitative precipitation forecasting correction experiment in Hunan Province based on an improved U-Net model.Utilizing precipitation data from 1912 ground observation stations in Hunan during the rainy season from April to September between 2017 and 2022,along with the optimal factor set of the European Centre for Medium-Range Weather Forecast-Integrated Forecasting System(ECMWF-IFS)model,we developed an hourly precipitation forecasting correction model(SARU)on the basis of the U-Net model,integrating residual networks and attention mechanism networks.The model's forecast results for the 2023 rainy season were compared with those corrected by using the optimal threat score(OTS)method and those from the CMA-SH9 model.The results show that:(1)The SARU model's overall accuracy in clear/rainy forecasts,correlation coefficient,mean absolute error,and bias were 0.87,0.17,0.35,and 0.73,respectively,all of which outperformed the OTS model and the CMA-SH9 model,especially in central Hunan,where SARU showed a clear advantage in forecasting trends and magnitudes;its false alarm and missed forecast ratios were nearly equal,contrasting with the OTS model's significantly higher missed forecast ratio and the CMA-SH9 model's opposite trend.(2)The SARU model's forecasts of categorized precipitation frequency were closer to actual observations than the OTS model and the CMA-SH9 model,particularly for precipitation exceeding 20 mm,where it was under-predicted by 27.29%,significantly better than the OTS model's under-prediction of 85.54%and the CMA-SH9 model's over-prediction of 95.50%.(3)For hourly precipitation at levels of[5,10),[10,20),and≥20 mm,the SARU model achieved the best threat score(TS),probability of detection,false alarm ratio,and missed alarm ratio,particularly for short-term heavy precipitation,where it significantly outperformed the CMA-SH9 model,while the OTS model's forecasting capability was notably insufficient.(4)Nocturnal rainfall was pronounced in Hunan,with a noticeable increase in the frequency of short-term heavy rainfall during the night(0200-0800 BJT).The SARU model effectively captured the nocturnal characteristics of short-term heavy rainfall,with TS notably increasing at night,peaking around 0500 BJT at approximately 0.07,markedly outperforming the CMA-SH9 model and OTS model.关键词
SARU/订正试验/U-Net/OTS/逐小时降水预报/夜雨特征Key words
SARU/Correction/U-Net/OTS/hourly precipitation forecasting/nocturnal rainfall characteristics分类
天文与地球科学引用本文复制引用
周莉,许霖,陈鹤,兰明才,欧小锋,周悦,谢忆南,肖思晗..基于改进U-Net模型的湖南地区定量降水预报订正试验[J].热带气象学报,2024,40(6):1005-1017,13.基金项目
湖南省自然科学基金项目-青年基金(2022JJ40214) （2022JJ40214）
湖南省气象局2022年重点课题(XQKJ22A005) （XQKJ22A005）
中国气象局创新发展专项(CXFZ2023J025) （CXFZ2023J025）
中国气象局气象能力提升联合研究专项(23NLTSZ005) （23NLTSZ005）
全国暴雨研究开放基金(BYKJ2024M08)共同资助 （BYKJ2024M08）
