Composite Analysis-Based Machine Learning for Prediction of Tropical Cyclone-Induced Sea Surface Height Anomaly

Composite Analysis-Based Machine Learning for Prediction of Tropical Cyclone-Induced Sea Surface Height Anomaly

Sea surface height anomaly (SSHA) induced by tropical cyclones (TCs) is closely associated with oscillations and is a crucial proxy for thermocline structure and ocean heat content in the upper ocean. The prediction of TC-induced SSHA, however, has been rarely investigated. This study presents a new...

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Bibliographic Details
Main Authors: Hongxing Cui, Danling Tang, Huizeng Liu, Yi Sui, Xiaowei Gu
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Composite analysis
machine learning
random forest
sea surface height anomaly
tropical cyclones
Online Access:https://ieeexplore.ieee.org/document/10049845/

Internet

https://ieeexplore.ieee.org/document/10049845/

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