海洋预报2024，Vol.41Issue(6)：23-31,9.DOI:10.11737/j.issn.1003-0239.2024.06.003
基于深度学习的大风订正预报研究
Research on wind speed forecasting correction based on deep learning
摘要
Abstract
A novel wind speed prediction model,the ResNet-LSTM model,is proposed combining the Long Short-Term Memory(LSTM)model and Residual Network(ResNet)model.By using 39 kinds of numerical weather forecasting products from the European Center for Medium Range Weather Forecasting(ECMWF),a deep learning model is trained to correct wind speed forecasts.The results show that compared with the ECMWF results,the TS score of the ResNet-LSTM model for gusts above level 6 has been increased by over 50％.Further analysis shows that the ResNet-LSTM model can effectively solve the fail report problem and improve wind speed forecasting corrections.关键词
残差神经网络/长短期记忆网络/风速/预报/订正Key words
ResNet model/Long Short Term Memory neural network,wind speed/forecasting,correction分类
天文与地球科学引用本文复制引用
杨凡,刘志丰,任兆鹏,崔天伦,于洋..基于深度学习的大风订正预报研究[J].海洋预报,2024,41(6):23-31,9.基金项目
青岛市气象局课题(2021qdqxz02、2019qdqxz01) （2021qdqxz02、2019qdqxz01）
山东省气象局项目(2022SDQN06). （2022SDQN06）
