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An Tropical Cyclone Intensity Prediction MethodBased on Spatial-Temporal Features(PDF)

南京师范大学学报（工程技术版）[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2019年03期
Page:
1-
Research Field:
计算机工程
Publishing date:

Info

Title:
An Tropical Cyclone Intensity Prediction MethodBased on Spatial-Temporal Features
Author(s):
Hao Kun; Zhang Tiankun; Shi Zhenwei
School of Astronautics,Beihang University,Beijing 100083,China
Keywords:
tropical cyclone; spatial-temporal features; intensity prediction; deep learning
PACS:
TP391
DOI:
10.3969/j.issn.1672-1292.2019.03.001
Abstract:
Tropical Cyclone(TC)is a destructive weather system,which causes disasters every year in China. At present,researchers usually develop statistical forecast methods for TC intensity forecast. They use the climatic persistence factors to develop a regression model for the future intensity of TC. Such model,however,needs a complex procedure of feature selection and lacks the use of information in the surrounding environment. So the forecast accuracy has not been significantly improved over the recent years. This paper proposes a TC intensity prediction model that can extract spatial and temporal features simultaneously. As for the influence of environmental physical factors on TC,the convolutional layer is used to learn its spatial information,and the recurrent neural unit is used to model the historical time series of tropical cyclone to achieve an end-to-end prediction. Having tested the TC samples in the Northwest Pacific,the results show that our spatial-temporal intensity prediction network is superior to other forecast methods published by Shanghai Typhoon Institute(STI)in the corresponding period,so it can be used as a new intelligent prediction model to provide valuable objective reference for forecasters.

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Last Update: 2019-09-30