Relationships between Arctic sea ice drift and strength modelled by NEMO-LIM3.6
Sea ice cover and thickness have substantially decreased in the Arctic Ocean since the beginning of the satellite era. As a result, sea ice strength has been reduced, allowing more deformation and fracturing and leading to increased sea ice drift speed. We use the version 3.6 of the global ocean–sea...
Published in: | The Cryosphere |
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Main Authors: | , , , , , |
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Format: | Article in Journal/Newspaper |
Language: | English |
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European Geosciences Union (EGU)
2017
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Online Access: | http://hdl.handle.net/2117/112431 https://doi.org/10.5194/tc-11-2829-2017 |
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ftupcatalunya:oai:upcommons.upc.edu:2117/112431 |
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Universitat Politècnica de Catalunya (UPC): Theses and Dissertations Online (TDX) |
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ftupcatalunya |
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English |
topic |
Àrees temàtiques de la UPC::Desenvolupament humà i sostenible Sea ice Arctic Ocean Sea ice cover Model experiments Glaç |
spellingShingle |
Àrees temàtiques de la UPC::Desenvolupament humà i sostenible Sea ice Arctic Ocean Sea ice cover Model experiments Glaç Docquier, David Massonnet, François Barthélemy, Antoine Tandon, Neil F. Lecomte, Olivier Fichelet, Thierry Relationships between Arctic sea ice drift and strength modelled by NEMO-LIM3.6 |
topic_facet |
Àrees temàtiques de la UPC::Desenvolupament humà i sostenible Sea ice Arctic Ocean Sea ice cover Model experiments Glaç |
description |
Sea ice cover and thickness have substantially decreased in the Arctic Ocean since the beginning of the satellite era. As a result, sea ice strength has been reduced, allowing more deformation and fracturing and leading to increased sea ice drift speed. We use the version 3.6 of the global ocean–sea ice NEMO-LIM model (Nucleus for European Modelling of the Ocean coupled to the Louvain-la-Neuve sea Ice Model), satellite, buoy and submarine observations, as well as reanalysis data over the period from 1979 to 2013 to study these relationships. Overall, the model agrees well with observations in terms of sea ice extent, concentration and thickness. The seasonal cycle of sea ice drift speed is reasonably well reproduced by the model. NEMO-LIM3.6 is able to capture the relationships between the seasonal cycles of sea ice drift speed, concentration and thickness, with higher drift speed for both lower concentration and lower thickness, in agreement with observations. Model experiments are carried out to test the sensitivity of Arctic sea ice drift speed, thickness and concentration to changes in sea ice strength parameter P*. These show that higher values of P* generally lead to lower sea ice deformation and lower sea ice thickness, and that no single value of P* is the best option for reproducing the observed drift speed and thickness. The methodology proposed in this analysis provides a benchmark for a further model intercomparison related to the relationships between sea ice drift speed and strength, which is especially relevant in the context of the upcoming Coupled Model Intercomparison Project 6 (CMIP6). David Docquier and Antoine Barthélemy work on the PRIMAVERA project (PRocess-based climate sIMulation: AdVances in high-resolution modelling and European climate Risk Assessment), which is funded by the European Commission’s Horizon 2020 programme, grant agreement no. 641727. François Massonnet is funded by the Belgian Fonds National de la Recherche Scientifique (FNRS) and was funded by the Ministerio de Economía, Industria y Competitividad (MINECO). Neil F. Tandon is supported by the Canadian Sea Ice and Snow Evolution (CanSISE) Network. Olivier Lecomte is a research assistant within the Belgian FNRS. The present research benefited from computational resources made available on the Tier-1 supercomputer of the Fédération Wallonie-Bruxelles, infrastructure funded by the Walloon Region under the grant agreement no. 1117545. Computational resources have also been provided by the Consortium des Équipements de Calcul Intensif (CÉCI), funded by the Fonds de la Recherche Scientifique de Belgique (F.R.S.-FNRS) under grant no. 2.5020.11. We would like to thank Hugues Goosse, Martin Vancoppenolle, Jonathan Raulier and Véronique Dansereau for their very helpful comments regarding this study. We also acknowledge Pierre-Yves Barriat for his help in using computing resources at UCL and Damien François for his advice in improving Python scripts. Finally, we thank the editor Dirk Notz and the two anonymous reviewers for helping to improve the original paper. Peer Reviewed Postprint (published version) |
author2 |
Barcelona Supercomputing Center |
format |
Article in Journal/Newspaper |
author |
Docquier, David Massonnet, François Barthélemy, Antoine Tandon, Neil F. Lecomte, Olivier Fichelet, Thierry |
author_facet |
Docquier, David Massonnet, François Barthélemy, Antoine Tandon, Neil F. Lecomte, Olivier Fichelet, Thierry |
author_sort |
Docquier, David |
title |
Relationships between Arctic sea ice drift and strength modelled by NEMO-LIM3.6 |
title_short |
Relationships between Arctic sea ice drift and strength modelled by NEMO-LIM3.6 |
title_full |
Relationships between Arctic sea ice drift and strength modelled by NEMO-LIM3.6 |
title_fullStr |
Relationships between Arctic sea ice drift and strength modelled by NEMO-LIM3.6 |
title_full_unstemmed |
Relationships between Arctic sea ice drift and strength modelled by NEMO-LIM3.6 |
title_sort |
relationships between arctic sea ice drift and strength modelled by nemo-lim3.6 |
publisher |
European Geosciences Union (EGU) |
publishDate |
2017 |
url |
http://hdl.handle.net/2117/112431 https://doi.org/10.5194/tc-11-2829-2017 |
geographic |
Arctic Arctic Ocean |
geographic_facet |
Arctic Arctic Ocean |
genre |
Arctic Arctic Ocean Sea ice |
genre_facet |
Arctic Arctic Ocean Sea ice |
op_relation |
https://www.the-cryosphere.net/11/2829/2017/ info:eu-repo/grantAgreement/EC/H2020/641727/EU/PRocess-based climate sIMulation: AdVances in high resolution modelling and European climate Risk Assessment/PRIMAVERA |
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Attribution-NonCommercial-NoDerivs 3.0 Spain http://creativecommons.org/licenses/by-nc-nd/3.0/es/ Open Access |
op_rightsnorm |
CC-BY-NC-ND |
op_doi |
https://doi.org/10.5194/tc-11-2829-2017 |
container_title |
The Cryosphere |
container_volume |
11 |
container_issue |
6 |
container_start_page |
2829 |
op_container_end_page |
2846 |
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1766330942570364928 |
spelling |
ftupcatalunya:oai:upcommons.upc.edu:2117/112431 2023-05-15T14:58:49+02:00 Relationships between Arctic sea ice drift and strength modelled by NEMO-LIM3.6 Docquier, David Massonnet, François Barthélemy, Antoine Tandon, Neil F. Lecomte, Olivier Fichelet, Thierry Barcelona Supercomputing Center 2017-12-12 18 p. http://hdl.handle.net/2117/112431 https://doi.org/10.5194/tc-11-2829-2017 eng eng European Geosciences Union (EGU) https://www.the-cryosphere.net/11/2829/2017/ info:eu-repo/grantAgreement/EC/H2020/641727/EU/PRocess-based climate sIMulation: AdVances in high resolution modelling and European climate Risk Assessment/PRIMAVERA Attribution-NonCommercial-NoDerivs 3.0 Spain http://creativecommons.org/licenses/by-nc-nd/3.0/es/ Open Access CC-BY-NC-ND Àrees temàtiques de la UPC::Desenvolupament humà i sostenible Sea ice Arctic Ocean Sea ice cover Model experiments Glaç Article 2017 ftupcatalunya https://doi.org/10.5194/tc-11-2829-2017 2019-09-29T09:19:39Z Sea ice cover and thickness have substantially decreased in the Arctic Ocean since the beginning of the satellite era. As a result, sea ice strength has been reduced, allowing more deformation and fracturing and leading to increased sea ice drift speed. We use the version 3.6 of the global ocean–sea ice NEMO-LIM model (Nucleus for European Modelling of the Ocean coupled to the Louvain-la-Neuve sea Ice Model), satellite, buoy and submarine observations, as well as reanalysis data over the period from 1979 to 2013 to study these relationships. Overall, the model agrees well with observations in terms of sea ice extent, concentration and thickness. The seasonal cycle of sea ice drift speed is reasonably well reproduced by the model. NEMO-LIM3.6 is able to capture the relationships between the seasonal cycles of sea ice drift speed, concentration and thickness, with higher drift speed for both lower concentration and lower thickness, in agreement with observations. Model experiments are carried out to test the sensitivity of Arctic sea ice drift speed, thickness and concentration to changes in sea ice strength parameter P*. These show that higher values of P* generally lead to lower sea ice deformation and lower sea ice thickness, and that no single value of P* is the best option for reproducing the observed drift speed and thickness. The methodology proposed in this analysis provides a benchmark for a further model intercomparison related to the relationships between sea ice drift speed and strength, which is especially relevant in the context of the upcoming Coupled Model Intercomparison Project 6 (CMIP6). David Docquier and Antoine Barthélemy work on the PRIMAVERA project (PRocess-based climate sIMulation: AdVances in high-resolution modelling and European climate Risk Assessment), which is funded by the European Commission’s Horizon 2020 programme, grant agreement no. 641727. François Massonnet is funded by the Belgian Fonds National de la Recherche Scientifique (FNRS) and was funded by the Ministerio de Economía, Industria y Competitividad (MINECO). Neil F. Tandon is supported by the Canadian Sea Ice and Snow Evolution (CanSISE) Network. Olivier Lecomte is a research assistant within the Belgian FNRS. The present research benefited from computational resources made available on the Tier-1 supercomputer of the Fédération Wallonie-Bruxelles, infrastructure funded by the Walloon Region under the grant agreement no. 1117545. Computational resources have also been provided by the Consortium des Équipements de Calcul Intensif (CÉCI), funded by the Fonds de la Recherche Scientifique de Belgique (F.R.S.-FNRS) under grant no. 2.5020.11. We would like to thank Hugues Goosse, Martin Vancoppenolle, Jonathan Raulier and Véronique Dansereau for their very helpful comments regarding this study. We also acknowledge Pierre-Yves Barriat for his help in using computing resources at UCL and Damien François for his advice in improving Python scripts. Finally, we thank the editor Dirk Notz and the two anonymous reviewers for helping to improve the original paper. Peer Reviewed Postprint (published version) Article in Journal/Newspaper Arctic Arctic Ocean Sea ice Universitat Politècnica de Catalunya (UPC): Theses and Dissertations Online (TDX) Arctic Arctic Ocean The Cryosphere 11 6 2829 2846 |