Improved forecasting of extreme hurricane events by integrating spatio-temporal CNN-RF learning of tropical cyclone characteristics

Improved forecasting of extreme hurricane events by integrating spatio-temporal CNN-RF learning of tropical cyclone characteristics

Assessing hurricane predictions in a changing climate is one of the most challenging weather forecast problems today. Furthermore, effectively integrating information-rich features that are specific to the growth of hurricanes proves to be a difficult task due to the anticipated nonlinear interactio...

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Bibliographic Details
Main Authors: Javier Martinez-Amaya, Nicolas Longépé, Veronica Nieves, Jordi Muñoz-Marí
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-07-01
Series:Frontiers in Earth Science
Subjects:
hybrid modeling
convolutional neural network
spatio-temporal analysis
machine learning decision tree
tropical cyclone feature extraction
extreme hurricane prediction
Online Access:https://www.frontiersin.org/articles/10.3389/feart.2023.1223154/full

Internet

https://www.frontiersin.org/articles/10.3389/feart.2023.1223154/full

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