Defining Southern Ocean fronts using unsupervised classification

Oceanographic fronts are transitions between thermohaline structures with different characteristics. Such transitions are ubiquitous, and their locations and properties affect how the ocean operates as part of the global climate system. In the Southern Ocean, fronts have classically been defined usi...

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Main Authors: Thomas, Simon D. A., Jones, Daniel C., Faul, Anita, Mackie, Erik, Pauthenet, Etienne
Format: Text
Language:English
Published: 2021
Subjects:
Online Access:https://doi.org/10.5194/os-2021-40
https://os.copernicus.org/preprints/os-2021-40/
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spelling ftcopernicus:oai:publications.copernicus.org:osd94515 2023-05-15T18:24:56+02:00 Defining Southern Ocean fronts using unsupervised classification Thomas, Simon D. A. Jones, Daniel C. Faul, Anita Mackie, Erik Pauthenet, Etienne 2021-05-20 application/pdf https://doi.org/10.5194/os-2021-40 https://os.copernicus.org/preprints/os-2021-40/ eng eng doi:10.5194/os-2021-40 https://os.copernicus.org/preprints/os-2021-40/ eISSN: 1812-0792 Text 2021 ftcopernicus https://doi.org/10.5194/os-2021-40 2021-05-24T16:22:13Z Oceanographic fronts are transitions between thermohaline structures with different characteristics. Such transitions are ubiquitous, and their locations and properties affect how the ocean operates as part of the global climate system. In the Southern Ocean, fronts have classically been defined using a small number of continuous, circumpolar features in sea surface height or dynamic height. Modern observational and theoretical developments are challenging and expanding this traditional framework to accommodate a more complex view of fronts. Here we present a complementary new approach for calculating fronts using an unsupervised classification method called Gaussian mixture modelling and a novel inter-class parameter called the I -metric. The I -metric approach produces a probabilistic view of front location, emphasising the fact that the boundaries between water masses are not uniformly sharp across the entire Southern Ocean. The I -metric approach uses thermohaline information from a range of depth levels, making it more general than approaches that only use near-surface properties. We train the statistical model on data from an observationally-constrained state estimate for more uniform spatial and temporal coverage. The probabilistic boundaries appear to be relatively sharp in the open ocean and somewhat diffuse near large topographic features, possibly highlighting the importance of topographically-induced mixing. For comparison with a more localised method, we use edge detection in principal component space and correlate the edges with surface velocities. The I -metric approach may prove to be a useful method for inter-model comparison, as it uses the thermohaline structure of those models instead of tracking somewhat ad-hoc values of sea surface height and/or dynamic height, which can vary considerably between models. In addition, the general I -metric approach allows front definitions to shift with changing temperature and salinity structures, which may be useful for characterising fronts in a changing climate. Text Southern Ocean Copernicus Publications: E-Journals Southern Ocean
institution Open Polar
collection Copernicus Publications: E-Journals
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language English
description Oceanographic fronts are transitions between thermohaline structures with different characteristics. Such transitions are ubiquitous, and their locations and properties affect how the ocean operates as part of the global climate system. In the Southern Ocean, fronts have classically been defined using a small number of continuous, circumpolar features in sea surface height or dynamic height. Modern observational and theoretical developments are challenging and expanding this traditional framework to accommodate a more complex view of fronts. Here we present a complementary new approach for calculating fronts using an unsupervised classification method called Gaussian mixture modelling and a novel inter-class parameter called the I -metric. The I -metric approach produces a probabilistic view of front location, emphasising the fact that the boundaries between water masses are not uniformly sharp across the entire Southern Ocean. The I -metric approach uses thermohaline information from a range of depth levels, making it more general than approaches that only use near-surface properties. We train the statistical model on data from an observationally-constrained state estimate for more uniform spatial and temporal coverage. The probabilistic boundaries appear to be relatively sharp in the open ocean and somewhat diffuse near large topographic features, possibly highlighting the importance of topographically-induced mixing. For comparison with a more localised method, we use edge detection in principal component space and correlate the edges with surface velocities. The I -metric approach may prove to be a useful method for inter-model comparison, as it uses the thermohaline structure of those models instead of tracking somewhat ad-hoc values of sea surface height and/or dynamic height, which can vary considerably between models. In addition, the general I -metric approach allows front definitions to shift with changing temperature and salinity structures, which may be useful for characterising fronts in a changing climate.
format Text
author Thomas, Simon D. A.
Jones, Daniel C.
Faul, Anita
Mackie, Erik
Pauthenet, Etienne
spellingShingle Thomas, Simon D. A.
Jones, Daniel C.
Faul, Anita
Mackie, Erik
Pauthenet, Etienne
Defining Southern Ocean fronts using unsupervised classification
author_facet Thomas, Simon D. A.
Jones, Daniel C.
Faul, Anita
Mackie, Erik
Pauthenet, Etienne
author_sort Thomas, Simon D. A.
title Defining Southern Ocean fronts using unsupervised classification
title_short Defining Southern Ocean fronts using unsupervised classification
title_full Defining Southern Ocean fronts using unsupervised classification
title_fullStr Defining Southern Ocean fronts using unsupervised classification
title_full_unstemmed Defining Southern Ocean fronts using unsupervised classification
title_sort defining southern ocean fronts using unsupervised classification
publishDate 2021
url https://doi.org/10.5194/os-2021-40
https://os.copernicus.org/preprints/os-2021-40/
geographic Southern Ocean
geographic_facet Southern Ocean
genre Southern Ocean
genre_facet Southern Ocean
op_source eISSN: 1812-0792
op_relation doi:10.5194/os-2021-40
https://os.copernicus.org/preprints/os-2021-40/
op_doi https://doi.org/10.5194/os-2021-40
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