热带气象学报2026，Vol.42Issue(4)：589-600,12.DOI:10.16032/j.issn.1004-4965.2026.055
基于TimeSformer模型的台风强度实时预报
Real-time Typhoon Intensity Forecasting Based on TimeSformer
摘要
Abstract
This study proposes a real-time 24-hour typhoon intensity forecasting model based on the TimeSformer architecture,which is capable of effectively extracting spatiotemporal features from meteorological fields.The model was trained on ERA5 reanalysis data(1990-2021)and validated using both ERS5 test data and real-time ECMWF forecast data.To enhance model performance,a track representation layer was incorporated into the input data,which reduced the Mean Square Error(MSE)on the test set by 1.84 m2·s-2 compared to the control experiment.Additionally,sensitivity experiments on upper-level isobaric elements reveals that optimal performance was achieved using only the five pressure levels(200 hPa,500 hPa,700 hPa,850 hPa,and 950 hPa),with a mean absolute error(MAE)of 3.24 m·s-1 on 623 ERA5 test samples from 2022-2023.When applied to real-time ECMWF forecast data(260 test samples during 2022-2023),the model achieved an MAE of 3.56 m·s-1,a slight increase compared to direct ERA5-based validation(with an MAE increase of 0.32 m·s-1),but still substantially lower than those errors from the two mainstream operational NCEP(4.52 m·s-1)and ECMWF(8.11 m·s-1)models,respectively.These results demonstrate that the proposed model offers a robust and reliable tool for operational typhoon intensity forecasting.关键词
台风强度预报/实时预报/深度学习/TimeSformerKey words
typhoon intensity forecasting/real-time forecasting/deep learning/TimeSformer分类
天文与地球科学引用本文复制引用
渠鸿宇,董林,向纯怡,李响,王剑..基于TimeSformer模型的台风强度实时预报[J].热带气象学报,2026,42(4):589-600,12.基金项目
中国气象局创新发展专项(CXFZ2024J006) （CXFZ2024J006）
自然资源部海洋灾害预报技术重点实验室开放基金项目(LOMF2204) （LOMF2204）
国家重点研发计划2023YFC3107902)共同资助 （）
