Ensemble forecast of tropical cyclone tracks based on deep neural networks

Chong WANG; Qing XU; Yongcun CHENG; Yi PAN; Hong LI

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Ensemble forecast of tropical cyclone tracks based on deep neural networks

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A nonlinear artificial intelligence ensemble forecast model has been developed in this paper for predicting tropical cyclone(TC)tracks based on the deep neural network(DNN)by using the 24-h forecast data from the China Meteorological Administration(CMA),Japan Meteorological Agency(JMA)and Joint Typhoon Warning Center(JTWC).Data from a total of 287 TC cases over the Northwest Pacific Ocean from 2004 to 2015 were used to train and validate the DNN based ensemble forecast(DNNEF)model.The comparison of model results with Best Track data of TCs shows that the DNNEF model has a higher accuracy than any individual forecast center or the traditional ensemble forecast model.The average 24-h forecast error of 82 TCs from 2016 to 2018 is 63 km,which has been reduced by 17.1%,16.0%,20.3%,and 4.6%,respectively,compared with that of CMA,JMA,JTWC,and the error-estimation based ensemble method.The results indicate that the nonlinear DNNEF model has the capability of adjusting the model parameter dynamically and automatically,thus improving the accuracy and stability of TC prediction.

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来源
《地球科学前沿：英文版》 |2022年第3期|671-677|共7页
作者
Chong WANG; Qing XU; Yongcun CHENG; Yi PAN; Hong LI;
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作者单位

Key Laboratory of Marine Hazards Forecasting(Ministry of Natural Resources);

Hohai University;

Nanjing 210098;

China;

College of Marine Technology;

Faculty of Information Science and Engineering;

Ocean University of China;

Qingdao 266100;

China;

Southern Marine Science and Engineering Guangdong Laboratory(Guangzhou);

Guangzhou 511458;

China;

PIESAT Information Technology Co.Ltd.;

Beijing 100195;

China;

College of Harbor;

Coastal and Offshore Engineering;

Hohai University;

Nanjing 210098;

China;

Shanghai Typhoon Institute;

China Meteorological Administration;

Shanghai 200030;

China;

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原文格式 PDF
正文语种 chi
中图分类天气预报;
关键词
tropical cyclone track; deep neural network; ensemble forecast;

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1. Ensemble Forecast for Tropical Cyclone Based on CNOP-P Method:A Case Study of WRF Model and Two Typhoons [J] . 袁时金 ,施博 ,赵紫君 . 热带气象学报:英文版 . 2022,第2期
2. A Hybrid Neural Network Model for Marine Dissolved Oxygen Concentrations Time-Series Forecasting Based on Multi-Factor Analysis and a Multi-Model Ensemble [J] . Hui Liu ,Rui Yang ,Zhu Duan . 工程(英文) . 2021,第12期
3. Telecommunication traffic forecasting based on BP neural network trained by PSO [C] . DONG Xian ,XU Bing-ji . 2011年中国智能自动化会议 . 2011
4. Research on Pedestrian Detection and Tracking Technology Based on Convolution Neural Network [A] . Ge Wang . 2019

Ensemble forecast of tropical cyclone tracks based on deep neural networks

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