Key Laboratory of Research on Marine Hazards Forecasting, National
Marine Environmental Forecasting Center, Ministry of Natural Resources,
Beijing, 100081, China
Jiang Zhu
Institute of Atmospheric Physics, Chinese Academy of Sciences,
Beijing, 100029, China
Junqiang Song
College of Meteorology and Oceanography, National University of
Defense Technology, Changsha, 410073, China
Hongze Leng
College of Meteorology and Oceanography, National University of
Defense Technology, Changsha, 410073, China
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Total article views: 4,614 (including HTML, PDF, and XML)
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3,514
984
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4,614
224
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149
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Supplement: 224
BibTeX: 119
EndNote: 149
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634
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1,108
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15
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Total article views: 5,722 (including HTML, PDF, and XML)
Thereof 5,527 with geography defined
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Total article views: 4,614 (including HTML, PDF, and XML)
Thereof 4,490 with geography defined
and 124 with unknown origin.
Total article views: 1,108 (including HTML, PDF, and XML)
Thereof 1,037 with geography defined
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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.
A high-resolution gridded dataset is crucial for understanding ocean processes at various...
