Rapid intensification forecast for tropical cyclone by combining Multi-ConvLSTM model with infrared and microwave satellite images

Chuan-Hui Zhang; Chang-Jiang Zhang

doi:10.1117/12.2661748

12 April 2023 Rapid intensification forecast for tropical cyclone by combining Multi-ConvLSTM model with infrared and microwave satellite images

Chuan-Hui Zhang, Chang-Jiang Zhang

Author Affiliations +

Proceedings Volume 12565, Conference on Infrared, Millimeter, Terahertz Waves and Applications (IMT2022); 125650Y (2023) https://doi.org/10.1117/12.2661748
Event: Conference on Infrared, Millimeter, Terahertz Waves and Applications (IMT2022), 2022, Shanghai, China

Abstract

The prediction of rapid intensification (RI) is an important part of tropical cyclone (TC) intensity change prediction task, RI is defined as TC subsequent intensity change increase greater than a certain threshold. Accurately predicting RI can help improve the accuracy of TC intensity prediction, thereby reducing people's economic and property losses. In recent years, an increasing number of researchers have started to use satellite imagery for RI prediction. In this study, deep learning is utilized to combine infrared with microwave satellite images for RI prediction of TCs. The core idea can be formulated as follows: The residual image between feature of historical satellite image sequence and current satellite image is taken as the final feature matrix. Multilayer ConvLSTM is used to extract the features of historical satellite image sequence (time resolution is three hours), the residual image between the generated feature and the current satellite image is taken as the feature matrix. Finally the feature matrix is input into the classifier to predict RI. Experiment shows that in the prediction problem of RI for TCs (when the RI threshold is 35kt) our method on the test dataset has reached 0.552 at probability of detection (POD), and the false alarm ratio (FAR) reached 0.847, and heidke skill score (HSS) reached 0.186. Compared with the current methods only using satellite images to the prediction of RI, our method reduced FAR by 1.7%, improved POD by 15.4% and HSS by 13.4%.

Citation Download Citation

Chuan-Hui Zhang and Chang-Jiang Zhang "Rapid intensification forecast for tropical cyclone by combining Multi-ConvLSTM model with infrared and microwave satellite images", Proc. SPIE 12565, Conference on Infrared, Millimeter, Terahertz Waves and Applications (IMT2022), 125650Y (12 April 2023); https://doi.org/10.1117/12.2661748

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KEYWORDS

Satellite imaging

Satellites

Earth observing sensors

Data modeling

Education and training

Infrared imaging

Infrared radiation

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