Reconstruction of the Subsurface Temperature and Salinity in the South China Sea Using Deep-Learning Techniques with a Physical Guidance

In this paper, we develop a deep learning neural network characterized by feature fusion and physical guidance (denoted as FFPG-net) for reconstructing subsurface sea temperature (T) and salinity (S) from sea surface data. Designed with the idea of feature fusion, FFPG-net combines the deep learning...

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Bibliographic Details

Published in:	Remote Sensing
Main Authors:	Qianlong Zhao, Shaotian Li, Yuting Cai, Guoqiang Zhong, Shiqiu Peng
Format:	Article
Language:	English
Published:	MDPI AG 2025-08-01
Subjects:	deep learning physical guidance reconstruction of subsurface temperature and salinity vertical EOF decomposition
Online Access:	https://www.mdpi.com/2072-4292/17/17/2954