Hubei Key Laboratory of Marine Geological Resources, China University of Geosciences, Wuhan, 430000, China
Laboratory for Regional Oceanography and Numerical Modeling, Pilot National Laboratory for Marine Science and Technology (Qingdao), Qingdao,
266000, China
Southern Marine Science and Engineering Guangdong Laboratory
(Guangzhou), Guangzhou, 511458, China
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Total: 4,181
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Views and downloads (calculated since 15 Sep 2021)
Cumulative views and downloads
(calculated since 15 Sep 2021)
Total article views: 2,931 (including HTML, PDF, and XML)
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1,917
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2,931
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HTML: 1,917
PDF: 912
XML: 102
Total: 2,931
Supplement: 201
BibTeX: 141
EndNote: 131
Views and downloads (calculated since 03 Jan 2022)
Cumulative views and downloads
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Total article views: 1,250 (including HTML, PDF, and XML)
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821
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1,250
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Total: 1,250
BibTeX: 10
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Views and downloads (calculated since 15 Sep 2021)
Cumulative views and downloads
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Viewed (geographical distribution)
Total article views: 4,181 (including HTML, PDF, and XML)
Thereof 4,102 with geography defined
and 79 with unknown origin.
Total article views: 2,931 (including HTML, PDF, and XML)
Thereof 2,903 with geography defined
and 28 with unknown origin.
Total article views: 1,250 (including HTML, PDF, and XML)
Thereof 1,199 with geography defined
and 51 with unknown origin.
Sea surface wind and waves are important ocean parameters that can be continuously observed by meteorological buoys. Meteorological buoys are sparse in the ocean due to their high cost of deployment and maintenance. In contrast, low-cost compact wave buoys are suited for deployment in large numbers. Although wave buoys are not designed for wind measurement, we found that deep learning can estimate wind from wave measurements accurately, making wave buoys a good-quality data source for sea wind.
Sea surface wind and waves are important ocean parameters that can be continuously observed by...