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...

Descripción completa

Detalles Bibliográficos
Autores: Cruz-García, Rubén, Guemas, Virginie, Chevallier, Matthieu, Massonnet, François
Tipo de recurso: artículo
Fecha de publicación:2019
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/166401
Acceso en línea:https://hdl.handle.net/2117/166401
https://dx.doi.org/10.1007/s00382-018-4592-6
Access Level:acceso abierto
Palabra clave:Sea ice--Arctic regions
Sea ice
Regional
Arctic
Predictability
Clima--Observacions
Àrees temàtiques de la UPC::Energies
id ES_697490c19095e827a24a970e1936aeac
oai_identifier_str oai:upcommons.upc.edu:2117/166401
network_acronym_str ES
network_name_str España
repository_id_str
spelling An assessment of regional sea ice predictability in the Arctic oceanCruz-García, RubénGuemas, VirginieChevallier, MatthieuMassonnet, FrançoisSea ice--Arctic regionsSea iceRegionalArcticPredictabilityClima--ObservacionsÀrees temàtiques de la UPC::EnergiesArctic 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 ReviewedSpringer20192019-07-0120192019-07-18journal articlehttp://purl.org/coar/resource_type/c_6501AMhttp://purl.org/coar/version/c_ab4af688f83e57aainfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/166401https://dx.doi.org/10.1007/s00382-018-4592-6reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)InglésengEuropean Commission http://doi.org/10.13039/100010661 Horizon 2020 Framework Programme 727862 Advanced Prediction in Polar regions and beyond: Modelling, observing system design and LInkages associated with ArctiC ClimATE changeEuropean Commission http://doi.org/10.13039/100010661 Horizon 2020 Framework Programme 727890 Integrated Arctic observation systemopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/1664012026-05-27T15:37:01Z
dc.title.none.fl_str_mv An assessment of regional sea ice predictability in the Arctic ocean
title An assessment of regional sea ice predictability in the Arctic ocean
spellingShingle An assessment of regional sea ice predictability in the Arctic ocean
Cruz-García, Rubén
Sea ice--Arctic regions
Sea ice
Regional
Arctic
Predictability
Clima--Observacions
Àrees temàtiques de la UPC::Energies
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 An assessment of regional sea ice predictability in the Arctic ocean
dc.creator.none.fl_str_mv Cruz-García, Rubén
Guemas, Virginie
Chevallier, Matthieu
Massonnet, François
author Cruz-García, Rubén
author_facet Cruz-García, Rubén
Guemas, Virginie
Chevallier, Matthieu
Massonnet, François
author_role author
author2 Guemas, Virginie
Chevallier, Matthieu
Massonnet, François
author2_role author
author
author
dc.subject.none.fl_str_mv Sea ice--Arctic regions
Sea ice
Regional
Arctic
Predictability
Clima--Observacions
Àrees temàtiques de la UPC::Energies
topic Sea ice--Arctic regions
Sea ice
Regional
Arctic
Predictability
Clima--Observacions
Àrees temàtiques de la UPC::Energies
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.
publishDate 2019
dc.date.none.fl_str_mv 2019
2019-07-01
2019
2019-07-18
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
AM
http://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/166401
https://dx.doi.org/10.1007/s00382-018-4592-6
url https://hdl.handle.net/2117/166401
https://dx.doi.org/10.1007/s00382-018-4592-6
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv European Commission http://doi.org/10.13039/100010661 Horizon 2020 Framework Programme 727862 Advanced Prediction in Polar regions and beyond: Modelling, observing system design and LInkages associated with ArctiC ClimATE change
European Commission http://doi.org/10.13039/100010661 Horizon 2020 Framework Programme 727890 Integrated Arctic observation system
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869410031657549824
score 15,300724

Similares en LA Referencia