A deep-learning estimate of the decadal trends in the Southern Ocean carbon storage
Dissolved carbon concentrations in the ocean interior are computed by a deep-learning model using ocean surface data. In the Southern Ocean, they decreased in the 1990s-2000s and increased since 2010, reducing anthropogenic carbon uptake potential.
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2022
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ftdoajarticles:oai:doaj.org/article:84db0987ad5e4517a023ff711867bc0d 2023-05-15T18:23:47+02:00 A deep-learning estimate of the decadal trends in the Southern Ocean carbon storage Varvara E. Zemskova Tai-Long He Zirui Wan Nicolas Grisouard 2022-07-01T00:00:00Z https://doi.org/10.1038/s41467-022-31560-5 https://doaj.org/article/84db0987ad5e4517a023ff711867bc0d EN eng Nature Portfolio https://doi.org/10.1038/s41467-022-31560-5 https://doaj.org/toc/2041-1723 doi:10.1038/s41467-022-31560-5 2041-1723 https://doaj.org/article/84db0987ad5e4517a023ff711867bc0d Nature Communications, Vol 13, Iss 1, Pp 1-11 (2022) Science Q article 2022 ftdoajarticles https://doi.org/10.1038/s41467-022-31560-5 2022-12-30T22:24:51Z Dissolved carbon concentrations in the ocean interior are computed by a deep-learning model using ocean surface data. In the Southern Ocean, they decreased in the 1990s-2000s and increased since 2010, reducing anthropogenic carbon uptake potential. Article in Journal/Newspaper Southern Ocean Directory of Open Access Journals: DOAJ Articles Southern Ocean Nature Communications 13 1 |
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Open Polar |
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Directory of Open Access Journals: DOAJ Articles |
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ftdoajarticles |
language |
English |
topic |
Science Q |
spellingShingle |
Science Q Varvara E. Zemskova Tai-Long He Zirui Wan Nicolas Grisouard A deep-learning estimate of the decadal trends in the Southern Ocean carbon storage |
topic_facet |
Science Q |
description |
Dissolved carbon concentrations in the ocean interior are computed by a deep-learning model using ocean surface data. In the Southern Ocean, they decreased in the 1990s-2000s and increased since 2010, reducing anthropogenic carbon uptake potential. |
format |
Article in Journal/Newspaper |
author |
Varvara E. Zemskova Tai-Long He Zirui Wan Nicolas Grisouard |
author_facet |
Varvara E. Zemskova Tai-Long He Zirui Wan Nicolas Grisouard |
author_sort |
Varvara E. Zemskova |
title |
A deep-learning estimate of the decadal trends in the Southern Ocean carbon storage |
title_short |
A deep-learning estimate of the decadal trends in the Southern Ocean carbon storage |
title_full |
A deep-learning estimate of the decadal trends in the Southern Ocean carbon storage |
title_fullStr |
A deep-learning estimate of the decadal trends in the Southern Ocean carbon storage |
title_full_unstemmed |
A deep-learning estimate of the decadal trends in the Southern Ocean carbon storage |
title_sort |
deep-learning estimate of the decadal trends in the southern ocean carbon storage |
publisher |
Nature Portfolio |
publishDate |
2022 |
url |
https://doi.org/10.1038/s41467-022-31560-5 https://doaj.org/article/84db0987ad5e4517a023ff711867bc0d |
geographic |
Southern Ocean |
geographic_facet |
Southern Ocean |
genre |
Southern Ocean |
genre_facet |
Southern Ocean |
op_source |
Nature Communications, Vol 13, Iss 1, Pp 1-11 (2022) |
op_relation |
https://doi.org/10.1038/s41467-022-31560-5 https://doaj.org/toc/2041-1723 doi:10.1038/s41467-022-31560-5 2041-1723 https://doaj.org/article/84db0987ad5e4517a023ff711867bc0d |
op_doi |
https://doi.org/10.1038/s41467-022-31560-5 |
container_title |
Nature Communications |
container_volume |
13 |
container_issue |
1 |
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1766203892872249344 |