Articles | Volume 18, issue 4
https://doi.org/10.5194/essd-18-2929-2026
https://doi.org/10.5194/essd-18-2929-2026
Data description article
 | 
28 Apr 2026
Data description article |  | 28 Apr 2026

Global open-ocean daily turbulent heat flux dataset (1992–2020) from SSM/I via deep learning

Haoyu Wang, Mengjiao Wang, and Xiaofeng Li

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Short summary
DeepFlux provides a global, gap-free, daily record of air temperature, humidity, and turbulent heat flux from 1992 to 2020. Using satellite data and deep learning, it fills missing observations and delivers continuous estimates. Tests against in situ measurements show it is closer to reality and more reliable than existing products. This open resource supports improved climate studies and model evaluation.
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