Unsupervised clustering of Southern Ocean Argo float temperature profiles
The Southern Ocean has complex spatial variability, characterized by sharp fronts, steeply tilted isopycnals, and deep seasonal mixed layers. Methods of defining Southern Ocean spatial structures traditionally rely on somewhat ad hoc combinations of physical, chemical, and dynamic properties. As a s...
Published in: | Journal of Geophysical Research: Oceans |
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ftnerc:oai:nora.nerc.ac.uk:519667 2023-05-15T13:49:34+02:00 Unsupervised clustering of Southern Ocean Argo float temperature profiles Jones, Dan Holt, Harry Meijers, Andrew Shuckburgh, Emily 2019-05-04 text http://nora.nerc.ac.uk/id/eprint/519667/ https://nora.nerc.ac.uk/id/eprint/519667/1/Jones_et_al-2019-Journal_of_Geophysical_Research__Oceans.pdf https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2018JC014629 en eng https://nora.nerc.ac.uk/id/eprint/519667/1/Jones_et_al-2019-Journal_of_Geophysical_Research__Oceans.pdf Jones, Dan orcid:0000-0002-8701-4506 Holt, Harry; Meijers, Andrew orcid:0000-0003-3876-7736 Shuckburgh, Emily orcid:0000-0001-9206-3444 . 2019 Unsupervised clustering of Southern Ocean Argo float temperature profiles. Journal of Geophysical Research: Oceans, 124 (1). 390-402. https://doi.org/10.1029/2018JC014629 <https://doi.org/10.1029/2018JC014629> cc_by_4 CC-BY Publication - Article PeerReviewed 2019 ftnerc https://doi.org/10.1029/2018JC014629 2023-02-04T19:46:21Z The Southern Ocean has complex spatial variability, characterized by sharp fronts, steeply tilted isopycnals, and deep seasonal mixed layers. Methods of defining Southern Ocean spatial structures traditionally rely on somewhat ad hoc combinations of physical, chemical, and dynamic properties. As a step toward an alternative approach for describing spatial variability in temperature, here we apply an unsupervised classification technique (i.e., Gaussian mixture modeling or GMM) to Southern Ocean Argo float temperature profiles. GMM, without using any latitude or longitude information, automatically identifies several spatially coherent circumpolar classes influenced by the Antarctic Circumpolar Current. In addition, GMM identifies classes that bear the imprint of mode/intermediate water formation and export, large‐scale gyre circulation, and the Agulhas Current, among others. Because GMM is robust, standardized, and automated, it can potentially be used to identify structures (such as fronts) in both observational and model data sets, possibly making it a useful complement to existing classification techniques. Article in Journal/Newspaper Antarc* Antarctic Southern Ocean Natural Environment Research Council: NERC Open Research Archive Antarctic Southern Ocean The Antarctic Journal of Geophysical Research: Oceans 124 1 390 402 |
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Open Polar |
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Natural Environment Research Council: NERC Open Research Archive |
op_collection_id |
ftnerc |
language |
English |
description |
The Southern Ocean has complex spatial variability, characterized by sharp fronts, steeply tilted isopycnals, and deep seasonal mixed layers. Methods of defining Southern Ocean spatial structures traditionally rely on somewhat ad hoc combinations of physical, chemical, and dynamic properties. As a step toward an alternative approach for describing spatial variability in temperature, here we apply an unsupervised classification technique (i.e., Gaussian mixture modeling or GMM) to Southern Ocean Argo float temperature profiles. GMM, without using any latitude or longitude information, automatically identifies several spatially coherent circumpolar classes influenced by the Antarctic Circumpolar Current. In addition, GMM identifies classes that bear the imprint of mode/intermediate water formation and export, large‐scale gyre circulation, and the Agulhas Current, among others. Because GMM is robust, standardized, and automated, it can potentially be used to identify structures (such as fronts) in both observational and model data sets, possibly making it a useful complement to existing classification techniques. |
format |
Article in Journal/Newspaper |
author |
Jones, Dan Holt, Harry Meijers, Andrew Shuckburgh, Emily |
spellingShingle |
Jones, Dan Holt, Harry Meijers, Andrew Shuckburgh, Emily Unsupervised clustering of Southern Ocean Argo float temperature profiles |
author_facet |
Jones, Dan Holt, Harry Meijers, Andrew Shuckburgh, Emily |
author_sort |
Jones, Dan |
title |
Unsupervised clustering of Southern Ocean Argo float temperature profiles |
title_short |
Unsupervised clustering of Southern Ocean Argo float temperature profiles |
title_full |
Unsupervised clustering of Southern Ocean Argo float temperature profiles |
title_fullStr |
Unsupervised clustering of Southern Ocean Argo float temperature profiles |
title_full_unstemmed |
Unsupervised clustering of Southern Ocean Argo float temperature profiles |
title_sort |
unsupervised clustering of southern ocean argo float temperature profiles |
publishDate |
2019 |
url |
http://nora.nerc.ac.uk/id/eprint/519667/ https://nora.nerc.ac.uk/id/eprint/519667/1/Jones_et_al-2019-Journal_of_Geophysical_Research__Oceans.pdf https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2018JC014629 |
geographic |
Antarctic Southern Ocean The Antarctic |
geographic_facet |
Antarctic Southern Ocean The Antarctic |
genre |
Antarc* Antarctic Southern Ocean |
genre_facet |
Antarc* Antarctic Southern Ocean |
op_relation |
https://nora.nerc.ac.uk/id/eprint/519667/1/Jones_et_al-2019-Journal_of_Geophysical_Research__Oceans.pdf Jones, Dan orcid:0000-0002-8701-4506 Holt, Harry; Meijers, Andrew orcid:0000-0003-3876-7736 Shuckburgh, Emily orcid:0000-0001-9206-3444 . 2019 Unsupervised clustering of Southern Ocean Argo float temperature profiles. Journal of Geophysical Research: Oceans, 124 (1). 390-402. https://doi.org/10.1029/2018JC014629 <https://doi.org/10.1029/2018JC014629> |
op_rights |
cc_by_4 |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.1029/2018JC014629 |
container_title |
Journal of Geophysical Research: Oceans |
container_volume |
124 |
container_issue |
1 |
container_start_page |
390 |
op_container_end_page |
402 |
_version_ |
1766251753540419584 |