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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ftcopernicus:oai:publications.copernicus.org:os85759 2023-05-15T13:24:17+02:00 A clustering-based approach to ocean model–data comparison around Antarctica Sun, Qiang Little, Christopher M. Barthel, Alice M. Padman, Laurie 2021-01-19 application/pdf https://doi.org/10.5194/os-17-131-2021 https://os.copernicus.org/articles/17/131/2021/ eng eng doi:10.5194/os-17-131-2021 https://os.copernicus.org/articles/17/131/2021/ eISSN: 1812-0792 Text 2021 ftcopernicus https://doi.org/10.5194/os-17-131-2021 2021-01-25T17:22:13Z 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 sparsity of observations of the ACSS, this technique is a promising tool for the evaluation of a larger model ensemble (e.g., CMIP6) on a circum-Antarctic basis. Text Amundsen Sea Antarc* Antarctic Antarctica Ross Sea Copernicus Publications: E-Journals Amundsen Sea Antarctic Ross Sea The Antarctic Ocean Science 17 1 131 145 |
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Open Polar |
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Copernicus Publications: E-Journals |
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ftcopernicus |
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English |
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 sparsity of observations of the ACSS, this technique is a promising tool for the evaluation of a larger model ensemble (e.g., CMIP6) on a circum-Antarctic basis. |
format |
Text |
author |
Sun, Qiang Little, Christopher M. Barthel, Alice M. Padman, Laurie |
spellingShingle |
Sun, Qiang Little, Christopher M. Barthel, Alice M. Padman, Laurie A clustering-based approach to ocean model–data comparison around Antarctica |
author_facet |
Sun, Qiang Little, Christopher M. Barthel, Alice M. Padman, Laurie |
author_sort |
Sun, Qiang |
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 |
publishDate |
2021 |
url |
https://doi.org/10.5194/os-17-131-2021 https://os.copernicus.org/articles/17/131/2021/ |
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 |
eISSN: 1812-0792 |
op_relation |
doi:10.5194/os-17-131-2021 https://os.copernicus.org/articles/17/131/2021/ |
op_doi |
https://doi.org/10.5194/os-17-131-2021 |
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Ocean Science |
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17 |
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1 |
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131 |
op_container_end_page |
145 |
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1766378510338752512 |