A clustering-based approach to ocean model–data comparison around Antarctica

The Antarctic Continental Shelf seas (ACSS) are a critical, rapidly changing element of the Earth system. Analyses of global-scale general circulation model (GCM) simulations, including those available through the Coupled Model Intercomparison Project, Phase 6 (CMIP6), can help reveal the origins of...

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Bibliographic Details
Published in:Ocean Science
Main Authors: Q. Sun, C. M. Little, A. M. Barthel, L. Padman
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2021
Subjects:
geo
Online Access:https://doi.org/10.5194/os-17-131-2021
https://os.copernicus.org/articles/17/131/2021/os-17-131-2021.pdf
https://doaj.org/article/8b79d77df40b4a33b1ffb828f6c71365
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spelling fttriple:oai:gotriple.eu:oai:doaj.org/article:8b79d77df40b4a33b1ffb828f6c71365 2023-05-15T13:24:15+02:00 A clustering-based approach to ocean model–data comparison around Antarctica Q. Sun C. M. Little A. M. Barthel L. Padman 2021-01-01 https://doi.org/10.5194/os-17-131-2021 https://os.copernicus.org/articles/17/131/2021/os-17-131-2021.pdf https://doaj.org/article/8b79d77df40b4a33b1ffb828f6c71365 en eng Copernicus Publications doi:10.5194/os-17-131-2021 1812-0784 1812-0792 https://os.copernicus.org/articles/17/131/2021/os-17-131-2021.pdf https://doaj.org/article/8b79d77df40b4a33b1ffb828f6c71365 undefined Ocean Science, Vol 17, Pp 131-145 (2021) geo envir Journal Article https://vocabularies.coar-repositories.org/resource_types/c_6501/ 2021 fttriple https://doi.org/10.5194/os-17-131-2021 2023-01-22T17:11:17Z The Antarctic Continental Shelf seas (ACSS) are a critical, rapidly changing element of the Earth system. Analyses of global-scale general circulation model (GCM) simulations, including those available through the Coupled Model Intercomparison Project, Phase 6 (CMIP6), can help reveal the origins of observed changes and predict the future evolution of the ACSS. However, an evaluation of ACSS hydrography in GCMs is vital: previous CMIP ensembles exhibit substantial mean-state biases (reflecting, for example, misplaced water masses) with a wide inter-model spread. Because the ACSS are also a sparely sampled region, grid-point-based model assessments are of limited value. Our goal is to demonstrate the utility of clustering tools for identifying hydrographic regimes that are common to different source fields (model or data), while allowing for biases in other metrics (e.g., water mass core properties) and shifts in region boundaries. We apply K-means clustering to hydrographic metrics based on the stratification from one GCM (Community Earth System Model version 2; CESM2) and one observation-based product (World Ocean Atlas 2018; WOA), focusing on the Amundsen, Bellingshausen and Ross seas. When applied to WOA temperature and salinity profiles, clustering identifies “primary” and “mixed” regimes that have physically interpretable bases. For example, meltwater-freshened coastal currents in the Amundsen Sea and a region of high-salinity shelf water formation in the southwestern Ross Sea emerge naturally from the algorithm. Both regions also exhibit clearly differentiated inner- and outer-shelf regimes. The same analysis applied to CESM2 demonstrates that, although mean-state model biases in water mass T–S characteristics can be substantial, using a clustering approach highlights that the relative differences between regimes and the locations where each regime dominates are well represented in the model. CESM2 is generally fresher and warmer than WOA and has a limited fresh-water-enriched coastal regimes. Given the ... Article in Journal/Newspaper Amundsen Sea Antarc* Antarctic Antarctica Ross Sea Unknown Amundsen Sea Antarctic Ross Sea The Antarctic Ocean Science 17 1 131 145
institution Open Polar
collection Unknown
op_collection_id fttriple
language English
topic geo
envir
spellingShingle geo
envir
Q. Sun
C. M. Little
A. M. Barthel
L. Padman
A clustering-based approach to ocean model–data comparison around Antarctica
topic_facet geo
envir
description The Antarctic Continental Shelf seas (ACSS) are a critical, rapidly changing element of the Earth system. Analyses of global-scale general circulation model (GCM) simulations, including those available through the Coupled Model Intercomparison Project, Phase 6 (CMIP6), can help reveal the origins of observed changes and predict the future evolution of the ACSS. However, an evaluation of ACSS hydrography in GCMs is vital: previous CMIP ensembles exhibit substantial mean-state biases (reflecting, for example, misplaced water masses) with a wide inter-model spread. Because the ACSS are also a sparely sampled region, grid-point-based model assessments are of limited value. Our goal is to demonstrate the utility of clustering tools for identifying hydrographic regimes that are common to different source fields (model or data), while allowing for biases in other metrics (e.g., water mass core properties) and shifts in region boundaries. We apply K-means clustering to hydrographic metrics based on the stratification from one GCM (Community Earth System Model version 2; CESM2) and one observation-based product (World Ocean Atlas 2018; WOA), focusing on the Amundsen, Bellingshausen and Ross seas. When applied to WOA temperature and salinity profiles, clustering identifies “primary” and “mixed” regimes that have physically interpretable bases. For example, meltwater-freshened coastal currents in the Amundsen Sea and a region of high-salinity shelf water formation in the southwestern Ross Sea emerge naturally from the algorithm. Both regions also exhibit clearly differentiated inner- and outer-shelf regimes. The same analysis applied to CESM2 demonstrates that, although mean-state model biases in water mass T–S characteristics can be substantial, using a clustering approach highlights that the relative differences between regimes and the locations where each regime dominates are well represented in the model. CESM2 is generally fresher and warmer than WOA and has a limited fresh-water-enriched coastal regimes. Given the ...
format Article in Journal/Newspaper
author Q. Sun
C. M. Little
A. M. Barthel
L. Padman
author_facet Q. Sun
C. M. Little
A. M. Barthel
L. Padman
author_sort Q. Sun
title A clustering-based approach to ocean model–data comparison around Antarctica
title_short A clustering-based approach to ocean model–data comparison around Antarctica
title_full A clustering-based approach to ocean model–data comparison around Antarctica
title_fullStr A clustering-based approach to ocean model–data comparison around Antarctica
title_full_unstemmed A clustering-based approach to ocean model–data comparison around Antarctica
title_sort clustering-based approach to ocean model–data comparison around antarctica
publisher Copernicus Publications
publishDate 2021
url https://doi.org/10.5194/os-17-131-2021
https://os.copernicus.org/articles/17/131/2021/os-17-131-2021.pdf
https://doaj.org/article/8b79d77df40b4a33b1ffb828f6c71365
geographic Amundsen Sea
Antarctic
Ross Sea
The Antarctic
geographic_facet Amundsen Sea
Antarctic
Ross Sea
The Antarctic
genre Amundsen Sea
Antarc*
Antarctic
Antarctica
Ross Sea
genre_facet Amundsen Sea
Antarc*
Antarctic
Antarctica
Ross Sea
op_source Ocean Science, Vol 17, Pp 131-145 (2021)
op_relation doi:10.5194/os-17-131-2021
1812-0784
1812-0792
https://os.copernicus.org/articles/17/131/2021/os-17-131-2021.pdf
https://doaj.org/article/8b79d77df40b4a33b1ffb828f6c71365
op_rights undefined
op_doi https://doi.org/10.5194/os-17-131-2021
container_title Ocean Science
container_volume 17
container_issue 1
container_start_page 131
op_container_end_page 145
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