The Southern Ocean supergyre: a unifying dynamical framework identified by machine learning ...
Data for " Sonnewald, M., Reeve, K., and Lguensat, R., The Southern Ocean supergyre: a unifying dynamical framework identified by machine learning. In press, Commun Earth Environ ." Included: Barotropic vorticity terms, labels arrived at in Sonnewald et al., 2019, additional fields for plo...
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Online Access: | https://dx.doi.org/10.5281/zenodo.7783326 https://zenodo.org/record/7783326 |
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ftdatacite:10.5281/zenodo.7783326 2023-05-15T18:23:42+02:00 The Southern Ocean supergyre: a unifying dynamical framework identified by machine learning ... Sonnewald, Maike Reeve, Krissy A. Lguensat, Redouane 2023 https://dx.doi.org/10.5281/zenodo.7783326 https://zenodo.org/record/7783326 unknown Zenodo https://dx.doi.org/10.5281/zenodo.7783325 Open Access Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 info:eu-repo/semantics/openAccess Oceanography FOS Earth and related environmental sciences Southern Ocean Unsupervised Machine Learning JournalArticle ScholarlyArticle article-journal 2023 ftdatacite https://doi.org/10.5281/zenodo.778332610.5281/zenodo.7783325 2023-04-03T17:51:47Z Data for " Sonnewald, M., Reeve, K., and Lguensat, R., The Southern Ocean supergyre: a unifying dynamical framework identified by machine learning. In press, Commun Earth Environ ." Included: Barotropic vorticity terms, labels arrived at in Sonnewald et al., 2019, additional fields for plotting for the readers convenience. Additional data for the ECCOv4 model can be found here including velocities. Sonnewald, M . , Wunsch, C. and Heimbach, P. Unsupervised Learning Reveals Geography of Global Ocean Dynamical Regions, 2019, Journal of Earth and Space Science. ... : {"references": ["Sonnewald et al., 2023, The Southern Ocean supergyre: a unifying dynamical framework identified by machine learning. Available: Researchsquare"]} ... Article in Journal/Newspaper Southern Ocean DataCite Metadata Store (German National Library of Science and Technology) Southern Ocean |
institution |
Open Polar |
collection |
DataCite Metadata Store (German National Library of Science and Technology) |
op_collection_id |
ftdatacite |
language |
unknown |
topic |
Oceanography FOS Earth and related environmental sciences Southern Ocean Unsupervised Machine Learning |
spellingShingle |
Oceanography FOS Earth and related environmental sciences Southern Ocean Unsupervised Machine Learning Sonnewald, Maike Reeve, Krissy A. Lguensat, Redouane The Southern Ocean supergyre: a unifying dynamical framework identified by machine learning ... |
topic_facet |
Oceanography FOS Earth and related environmental sciences Southern Ocean Unsupervised Machine Learning |
description |
Data for " Sonnewald, M., Reeve, K., and Lguensat, R., The Southern Ocean supergyre: a unifying dynamical framework identified by machine learning. In press, Commun Earth Environ ." Included: Barotropic vorticity terms, labels arrived at in Sonnewald et al., 2019, additional fields for plotting for the readers convenience. Additional data for the ECCOv4 model can be found here including velocities. Sonnewald, M . , Wunsch, C. and Heimbach, P. Unsupervised Learning Reveals Geography of Global Ocean Dynamical Regions, 2019, Journal of Earth and Space Science. ... : {"references": ["Sonnewald et al., 2023, The Southern Ocean supergyre: a unifying dynamical framework identified by machine learning. Available: Researchsquare"]} ... |
format |
Article in Journal/Newspaper |
author |
Sonnewald, Maike Reeve, Krissy A. Lguensat, Redouane |
author_facet |
Sonnewald, Maike Reeve, Krissy A. Lguensat, Redouane |
author_sort |
Sonnewald, Maike |
title |
The Southern Ocean supergyre: a unifying dynamical framework identified by machine learning ... |
title_short |
The Southern Ocean supergyre: a unifying dynamical framework identified by machine learning ... |
title_full |
The Southern Ocean supergyre: a unifying dynamical framework identified by machine learning ... |
title_fullStr |
The Southern Ocean supergyre: a unifying dynamical framework identified by machine learning ... |
title_full_unstemmed |
The Southern Ocean supergyre: a unifying dynamical framework identified by machine learning ... |
title_sort |
southern ocean supergyre: a unifying dynamical framework identified by machine learning ... |
publisher |
Zenodo |
publishDate |
2023 |
url |
https://dx.doi.org/10.5281/zenodo.7783326 https://zenodo.org/record/7783326 |
geographic |
Southern Ocean |
geographic_facet |
Southern Ocean |
genre |
Southern Ocean |
genre_facet |
Southern Ocean |
op_relation |
https://dx.doi.org/10.5281/zenodo.7783325 |
op_rights |
Open Access Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.5281/zenodo.778332610.5281/zenodo.7783325 |
_version_ |
1766203777885405184 |