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...
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ftunivcam:oai:www.repository.cam.ac.uk:1810/302833 2024-01-14T10:01:35+01:00 Unsupervised Clustering of Southern Ocean Argo Float Temperature Profiles Jones, DC Holt, HJ Meijers, AJS Shuckburgh, E 2019 application/pdf https://www.repository.cam.ac.uk/handle/1810/302833 https://doi.org/10.17863/CAM.49907 eng eng Wiley-Blackwell http://dx.doi.org/10.1029/2018jc014629 Journal of Geophysical Research: Oceans https://www.repository.cam.ac.uk/handle/1810/302833 doi:10.17863/CAM.49907 All rights reserved 37 Earth Sciences 3708 Oceanography 14 Life Below Water Article 2019 ftunivcam https://doi.org/10.17863/CAM.49907 2023-12-21T23:27:44Z 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. Natural Environment Research Council (NERC). Grant Numbers: NE/N018028/1, NE/N018095/1, NE/L002434/1 Article in Journal/Newspaper Antarc* Antarctic Southern Ocean Apollo - University of Cambridge Repository Antarctic Southern Ocean The Antarctic |
institution |
Open Polar |
collection |
Apollo - University of Cambridge Repository |
op_collection_id |
ftunivcam |
language |
English |
topic |
37 Earth Sciences 3708 Oceanography 14 Life Below Water |
spellingShingle |
37 Earth Sciences 3708 Oceanography 14 Life Below Water Jones, DC Holt, HJ Meijers, AJS Shuckburgh, E Unsupervised Clustering of Southern Ocean Argo Float Temperature Profiles |
topic_facet |
37 Earth Sciences 3708 Oceanography 14 Life Below Water |
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. Natural Environment Research Council (NERC). Grant Numbers: NE/N018028/1, NE/N018095/1, NE/L002434/1 |
format |
Article in Journal/Newspaper |
author |
Jones, DC Holt, HJ Meijers, AJS Shuckburgh, E |
author_facet |
Jones, DC Holt, HJ Meijers, AJS Shuckburgh, E |
author_sort |
Jones, DC |
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 |
publisher |
Wiley-Blackwell |
publishDate |
2019 |
url |
https://www.repository.cam.ac.uk/handle/1810/302833 https://doi.org/10.17863/CAM.49907 |
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://www.repository.cam.ac.uk/handle/1810/302833 doi:10.17863/CAM.49907 |
op_rights |
All rights reserved |
op_doi |
https://doi.org/10.17863/CAM.49907 |
_version_ |
1788067346298961920 |