Predicting rapid intensification of tropical cyclones in the western North Pacific: a machine learning and net energy gain rate approach

Predicting rapid intensification of tropical cyclones in the western North Pacific: a machine learning and net energy gain rate approach

In this study, a machine learning (ML)-based Tropical Cyclones (TCs) Rapid Intensification (RI) prediction model has been developed by using the Net Energy Gain Rate Index (NGR). This index realistically captures the energy exchanges between the ocean and the atmosphere during the intensification of...

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Bibliographic Details
Main Authors: Sung-Hun Kim, Woojeong Lee, Hyoun-Woo Kang, Sok Kuh Kang
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-01-01
Series:Frontiers in Marine Science
Subjects:
rapid intensification of the tropical cyclone
drag coefficient
tropical cyclone-ocean interaction
tropical cyclone-induced vertical ocean mixing
machine learning
Online Access:https://www.frontiersin.org/articles/10.3389/fmars.2023.1296274/full

Internet

https://www.frontiersin.org/articles/10.3389/fmars.2023.1296274/full

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