Beyond the Backbone: A Quantitative Review of Deep-Learning Architectures for Tropical Cyclone Track Forecasting

Beyond the Backbone: A Quantitative Review of Deep-Learning Architectures for Tropical Cyclone Track Forecasting

Accurate forecasting of tropical cyclone (TC) tracks is critical for disaster preparedness and risk mitigation. While traditional numerical weather prediction (NWP) systems have long served as the backbone of operational forecasting, they face limitations in computational cost and sensitivity to ini...

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Bibliographic Details
Main Authors: He Huang, Difei Deng, Liang Hu, Yawen Chen, Nan Sun
Format: Article
Language:English
Published: MDPI AG 2025-08-01
Series:Remote Sensing
Subjects:
tropical cyclone forecasting
deep learning
artificial intelligence
track prediction
tropical cyclone forecasting review
Online Access:https://www.mdpi.com/2072-4292/17/15/2675
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