Tropical Cyclone Track Forecasting Using Fused Deep Learning From Aligned Reanalysis Data

Tropical Cyclone Track Forecasting Using Fused Deep Learning From Aligned Reanalysis Data

The forecast of tropical cyclone trajectories is crucial for the protection of people and property. Although forecast dynamical models can provide high-precision short-term forecasts, they are computationally demanding, and current statistical forecasting models have much room for improvement given...

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Bibliographic Details
Main Authors: Sophie Giffard-Roisin, Mo Yang, Guillaume Charpiat, Christina Kumler Bonfanti, Balázs Kégl, Claire Monteleoni
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-01-01
Series:Frontiers in Big Data
Subjects:
tropical cyclones
machine learning
fused deep learning
tracking forecast
reanalysis data
Online Access:https://www.frontiersin.org/article/10.3389/fdata.2020.00001/full

Internet

https://www.frontiersin.org/article/10.3389/fdata.2020.00001/full

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