热带气象学报2024，Vol.40Issue(6)：882-895,14.DOI:10.16032/j.issn.1004-4965.2024.077
基于DSTFN(Deep Spatio-Temprral Fusion Network)模型的热带气旋轨迹预测方法
Tropical Cyclone Track Prediction Method Based on DSTFN Model
摘要
Abstract
In the context of global climate change,more and more regions are facing the threat of tropical cyclones.Therefore,accurate prediction of changes in the tracks of tropical cyclones is essential for meteorological warning and disaster reduction.However,existing tropical cyclone prediction methods based on deep learning have limitations in modeling the spatio-temporal correlation of tropical cyclones.In the present study,we proposed a new deep spatio-temporal fusion network(DSTFN)model to improve the prediction accuracy and stability of tropical cyclone tracks.We developed the CaConvNeXt-GRU model,which effectively integrated the ConvNeXt model and the gated recurrent unit,to extract complex nonlinear spatio-temporal features in the 3D time series data of tropical cyclones.Meanwhile,the convolutional block attention module was introduced to automatically focus on the features that were affected more heavily by different isobaric surfaces on tropical cyclones.Moreover,we designed a staged training strategy to realize the effective integration of different modules through pre-training,joint training,and overall training.To evaluate the proposed model,we conducted extensive experiments on the International Best Track Archive for Climate Stewardship(IBTrACS)and the ERA5 dataset.Overall,in predicting tropical cyclone tracks for the next 24 hours,the DSTFN model reduced the average prediction error by about 13.71 km compared to existing tropical cyclone track prediction models based on deep learning.关键词
热带气旋/路径预测/DSTFN模型/CaConvNeXt-GRU模型/时空序列预测Key words
tropical cyclone/path prediction/DSTFN model/CaConvNeXt-GRU model/spatio-temporal series prediction分类
天文与地球科学引用本文复制引用
方巍,杜娟,齐媚涵,胡鹏昱..基于DSTFN(Deep Spatio-Temprral Fusion Network)模型的热带气旋轨迹预测方法[J].热带气象学报,2024,40(6):882-895,14.基金项目
国家自然科学基金项目(42075007) （42075007）
苏州大学江苏省计算机信息处理技术重点实验室开放研究基金(KJS2275) （KJS2275）
中国气象局交通气象重点开放实验室开放研究基金(BJG202306) （BJG202306）
中国气象局流域强降水重点开放实验室开放研究基金(2023BHR-Y14) （2023BHR-Y14）
江苏省研究生科研与实践创新计划项目(SJCX24_0476、SJCX24_0477)共同资助 （SJCX24_0476、SJCX24_0477）
