An assessment of regional sea ice predictability in the Arctic ocean
Arctic sea ice plays a central role in the Earth’s climate. Changes in the sea ice on seasonal-to-interannual timescales impact ecosystems, populations and a growing number of stakeholders. A prerequisite for achieving better sea ice predictions is a better understanding of the underlying mechanisms...
Published in: | Climate Dynamics |
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Main Authors: | , , , |
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Format: | Article in Journal/Newspaper |
Language: | English |
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Springer
2019
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Subjects: | |
Online Access: | http://hdl.handle.net/2117/166401 https://doi.org/10.1007/s00382-018-4592-6 |
id |
ftupcatalunyair:oai:upcommons.upc.edu:2117/166401 |
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record_format |
openpolar |
institution |
Open Polar |
collection |
Universitat Politècnica de Catalunya, BarcelonaTech: UPCommons - Global access to UPC knowledge |
op_collection_id |
ftupcatalunyair |
language |
English |
topic |
Àrees temàtiques de la UPC::Energies Sea ice--Arctic regions Sea ice Regional Arctic Predictability Clima--Observacions |
spellingShingle |
Àrees temàtiques de la UPC::Energies Sea ice--Arctic regions Sea ice Regional Arctic Predictability Clima--Observacions Cruz-García, Rubén Guemas, Virginie Chevallier, Matthieu Massonnet, François An assessment of regional sea ice predictability in the Arctic ocean |
topic_facet |
Àrees temàtiques de la UPC::Energies Sea ice--Arctic regions Sea ice Regional Arctic Predictability Clima--Observacions |
description |
Arctic sea ice plays a central role in the Earth’s climate. Changes in the sea ice on seasonal-to-interannual timescales impact ecosystems, populations and a growing number of stakeholders. A prerequisite for achieving better sea ice predictions is a better understanding of the underlying mechanisms of sea ice predictability. Previous studies have shown that sea ice predictability depends on the predictand (area, extent, volume), region, and the initial and target dates. Here we investigate seasonal-to-interannual sea ice predictability in so-called “perfect-model” 3-year-long experiments run with six global climate models initialized in early July. Consistent with previous studies, robust mechanisms for reemergence are highlighted, i.e. increases in the autocorrelation of sea ice properties after an initial loss. Similar winter sea ice extent reemergence is found for HadGEM1.2, GFDL-CM3 and E6F, while a long sea ice volume persistence is confirmed for all models. The comparable predictability characteristics shown by some of the peripheral regions of the Atlantic side illustrate that robust similarities can be found even if models have distinct sea ice states. The analysis of the regional sea ice predictability in EC-Earth2.3 demonstrates that Arctic basins can be classified according to three distinct regimes. The central Arctic drives most of the pan-Arctic sea ice volume persistence. In peripheral seas, we find predictability for the sea ice area in winter but low predictability throughout the rest of the year, due to the particularly unpredictable sea ice edge location. The Labrador Sea stands out among the considered regions, with sea ice predictability extending up to 1.5 years if the oceanic conditions upstream are known. We thank Jonathan Day and Steffen Tietsche for providing the data for the ocean heat transport into the Arctic; Nicolau Manubens, Javier Vegas-Regidor and Pierre-Antoine Bretonnière for the technical support; Pablo Ortega for useful comments on the pre-submission draft. We thank Javier García-Serrano for useful discussions regarding this study and Alasdair Hunter for the revision of the English. We give thanks to two anonymous reviewers for their insightful comments that improved the manuscript. The R-package s2dverification was used for processing the data and calculating different scores (Manubens et al. 2018). We acknowledge the Ariane tool and its creators (http://stockage.univ-brest.fr/~grima/Ariane/). We also thank the projects APPLICATE (H2020 GA 727862), INTAROS (H2020 GA 727890), the programme Copernicus and the fellowships Ramón y Cajal (MINECO) and Formación de Profesorado Universitario (FPU; Ministerio de Educación, Cultura y Deporte) for funding this work. Peer Reviewed Postprint (author's final draft) |
author2 |
Barcelona Supercomputing Center |
format |
Article in Journal/Newspaper |
author |
Cruz-García, Rubén Guemas, Virginie Chevallier, Matthieu Massonnet, François |
author_facet |
Cruz-García, Rubén Guemas, Virginie Chevallier, Matthieu Massonnet, François |
author_sort |
Cruz-García, Rubén |
title |
An assessment of regional sea ice predictability in the Arctic ocean |
title_short |
An assessment of regional sea ice predictability in the Arctic ocean |
title_full |
An assessment of regional sea ice predictability in the Arctic ocean |
title_fullStr |
An assessment of regional sea ice predictability in the Arctic ocean |
title_full_unstemmed |
An assessment of regional sea ice predictability in the Arctic ocean |
title_sort |
assessment of regional sea ice predictability in the arctic ocean |
publisher |
Springer |
publishDate |
2019 |
url |
http://hdl.handle.net/2117/166401 https://doi.org/10.1007/s00382-018-4592-6 |
long_lat |
ENVELOPE(-57.950,-57.950,-63.950,-63.950) ENVELOPE(-63.717,-63.717,-64.283,-64.283) |
geographic |
Arctic Arctic Ocean Ortega Pablo |
geographic_facet |
Arctic Arctic Ocean Ortega Pablo |
genre |
Arctic Arctic Arctic Ocean Labrador Sea Sea ice |
genre_facet |
Arctic Arctic Arctic Ocean Labrador Sea Sea ice |
op_relation |
https://link.springer.com/article/10.1007/s00382-018-4592-6 info:eu-repo/grantAgreement/EC/H2020/727862/EU/Advanced Prediction in Polar regions and beyond: Modelling, observing system design and LInkages associated with ArctiC ClimATE change/APPLICATE info:eu-repo/grantAgreement/EC/H2020/727890/EU/Integrated Arctic observation system/INTAROS Cruz-García, R. [et al.]. An assessment of regional sea ice predictability in the Arctic ocean. "Climate Dynamics", Juliol 2019, vol. 53, núm. 1-2, p. 427-440. 0930-7575 http://hdl.handle.net/2117/166401 doi:10.1007/s00382-018-4592-6 |
op_rights |
Open Access |
op_doi |
https://doi.org/10.1007/s00382-018-4592-6 |
container_title |
Climate Dynamics |
container_volume |
53 |
container_issue |
1-2 |
container_start_page |
427 |
op_container_end_page |
440 |
_version_ |
1766295224167956480 |
spelling |
ftupcatalunyair:oai:upcommons.upc.edu:2117/166401 2023-05-15T14:22:41+02:00 An assessment of regional sea ice predictability in the Arctic ocean Cruz-García, Rubén Guemas, Virginie Chevallier, Matthieu Massonnet, François Barcelona Supercomputing Center 2019-07 14 p. application/pdf http://hdl.handle.net/2117/166401 https://doi.org/10.1007/s00382-018-4592-6 eng eng Springer https://link.springer.com/article/10.1007/s00382-018-4592-6 info:eu-repo/grantAgreement/EC/H2020/727862/EU/Advanced Prediction in Polar regions and beyond: Modelling, observing system design and LInkages associated with ArctiC ClimATE change/APPLICATE info:eu-repo/grantAgreement/EC/H2020/727890/EU/Integrated Arctic observation system/INTAROS Cruz-García, R. [et al.]. An assessment of regional sea ice predictability in the Arctic ocean. "Climate Dynamics", Juliol 2019, vol. 53, núm. 1-2, p. 427-440. 0930-7575 http://hdl.handle.net/2117/166401 doi:10.1007/s00382-018-4592-6 Open Access Àrees temàtiques de la UPC::Energies Sea ice--Arctic regions Sea ice Regional Arctic Predictability Clima--Observacions Article 2019 ftupcatalunyair https://doi.org/10.1007/s00382-018-4592-6 2021-02-26T15:06:24Z Arctic sea ice plays a central role in the Earth’s climate. Changes in the sea ice on seasonal-to-interannual timescales impact ecosystems, populations and a growing number of stakeholders. A prerequisite for achieving better sea ice predictions is a better understanding of the underlying mechanisms of sea ice predictability. Previous studies have shown that sea ice predictability depends on the predictand (area, extent, volume), region, and the initial and target dates. Here we investigate seasonal-to-interannual sea ice predictability in so-called “perfect-model” 3-year-long experiments run with six global climate models initialized in early July. Consistent with previous studies, robust mechanisms for reemergence are highlighted, i.e. increases in the autocorrelation of sea ice properties after an initial loss. Similar winter sea ice extent reemergence is found for HadGEM1.2, GFDL-CM3 and E6F, while a long sea ice volume persistence is confirmed for all models. The comparable predictability characteristics shown by some of the peripheral regions of the Atlantic side illustrate that robust similarities can be found even if models have distinct sea ice states. The analysis of the regional sea ice predictability in EC-Earth2.3 demonstrates that Arctic basins can be classified according to three distinct regimes. The central Arctic drives most of the pan-Arctic sea ice volume persistence. In peripheral seas, we find predictability for the sea ice area in winter but low predictability throughout the rest of the year, due to the particularly unpredictable sea ice edge location. The Labrador Sea stands out among the considered regions, with sea ice predictability extending up to 1.5 years if the oceanic conditions upstream are known. We thank Jonathan Day and Steffen Tietsche for providing the data for the ocean heat transport into the Arctic; Nicolau Manubens, Javier Vegas-Regidor and Pierre-Antoine Bretonnière for the technical support; Pablo Ortega for useful comments on the pre-submission draft. We thank Javier García-Serrano for useful discussions regarding this study and Alasdair Hunter for the revision of the English. We give thanks to two anonymous reviewers for their insightful comments that improved the manuscript. The R-package s2dverification was used for processing the data and calculating different scores (Manubens et al. 2018). We acknowledge the Ariane tool and its creators (http://stockage.univ-brest.fr/~grima/Ariane/). We also thank the projects APPLICATE (H2020 GA 727862), INTAROS (H2020 GA 727890), the programme Copernicus and the fellowships Ramón y Cajal (MINECO) and Formación de Profesorado Universitario (FPU; Ministerio de Educación, Cultura y Deporte) for funding this work. Peer Reviewed Postprint (author's final draft) Article in Journal/Newspaper Arctic Arctic Arctic Ocean Labrador Sea Sea ice Universitat Politècnica de Catalunya, BarcelonaTech: UPCommons - Global access to UPC knowledge Arctic Arctic Ocean Ortega ENVELOPE(-57.950,-57.950,-63.950,-63.950) Pablo ENVELOPE(-63.717,-63.717,-64.283,-64.283) Climate Dynamics 53 1-2 427 440 |