Earth System Science Data
Earth System Science Data
Earth System Science Data
Articles | Volume 14, issue 11
Articles | Volume 14, issue 11
https://doi.org/10.5194/essd-14-5037-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-14-5037-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 14, issue 11
Data description paper
 | 
18 Nov 2022
Data description paper |  | 18 Nov 2022

Reconstructing ocean subsurface salinity at high resolution using a machine learning approach

Tian Tian, Lijing Cheng, Gongjie Wang, John Abraham, Wangxu Wei, Shihe Ren, Jiang Zhu, Junqiang Song, and Hongze Leng

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Latest update: 19 Apr 2024
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Short summary
A high-resolution gridded dataset is crucial for understanding ocean processes at various spatiotemporal scales. Here we used a machine learning approach and successfully reconstructed a high-resolution (0.25° × 0.25°) ocean subsurface (1–2000 m) salinity dataset for the period 1993–2018 (monthly) by merging in situ salinity profile observations with high-resolution satellite remote-sensing data. This new product could be useful in various applications in ocean and climate fields.
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