Storm surge modelling along European coastlines: The effect of the spatio-temporal resolution of the atmospheric forcing

The spatio-temporal resolution of atmospheric forcing plays a key role in the accuracy of simulated storm surges with hydrodynamic numerical models. Here, we generate five hydrodynamic hindcasts of coastal storm surges along the European Atlantic and the Mediterranean Sea coasts, forced with atmosph...

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Detalhes bibliográficos
Autores: Agulles, Miguel, Marcos, Marta, Amores, Ángel, Toomey, Tim
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2024
País:España
Recursos:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/379984
Acesso em linha:http://hdl.handle.net/10261/379984
https://api.elsevier.com/content/abstract/scopus_id/85204077293
Access Level:acceso abierto
Palavra-chave:Storm surges
Extreme sea level
Spatio-temporal resolution
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spelling Storm surge modelling along European coastlines: The effect of the spatio-temporal resolution of the atmospheric forcingAgulles, MiguelMarcos, MartaAmores, ÁngelToomey, TimStorm surgesExtreme sea levelSpatio-temporal resolutionThe spatio-temporal resolution of atmospheric forcing plays a key role in the accuracy of simulated storm surges with hydrodynamic numerical models. Here, we generate five hydrodynamic hindcasts of coastal storm surges along the European Atlantic and the Mediterranean Sea coasts, forced with atmospheric fields of varying temporal (hourly and daily) and spatial (0.25° to 2°) resolution since 1940. Our results, that are validated with insitu tide gauge observations, show that storm surges obtained with daily forcing underestimate the magnitude of coastal extreme sea level events by up to 50% compared to hourly simulations and observations. Nevertheless, low-resolution simulations capture the temporal variability of storm surges, including strong episodes. Furthermore, taking advantage of the consistent set of coastal storm surge hindcasts, we demonstrate that storm surges forced with daily mean atmospheric fields, when bias corrected via quantile mapping, provide accurate values of daily maxima as calculated by a high-resolution hindcast. This transformation paves the way to obtain daily maxima storm surge estimates from low-resolution atmospheric fields, as those typically provided by large-scale and global climate models, at a lower computational cost.This study was funded by DRICOEX project, grant number CNS2022-135532, funded by MCIN/AEI/10.13039/501100011033 and by “European Union NextGenerationEU/PRTR”. It was also partially funded by DETECT project (reference PID2021-124085OB-I00 MCIN/AEI/10.13039/501100011033/FEDER,UE). M.M acknowledges a grant from the Spanish Ministry of Universities through the European Union - Next Generation EU programme, and from “Pla de recuperació, transformació i resiliència” and the University of the Balearic Islands. This research has been financially supported by the agreement between the Spanish Ministry for Ecological Transition and Demographic Challenge and CSIC, funded by the European Union-Next Generation EU Program. T.T acknowledges an FPI grant associated with the MOCCA project (grant number PRE2019-088046).Peer reviewedElsevierMinisterio de Ciencia e Innovación (España)Agencia Estatal de Investigación (España)European CommissionMinisterio de Universidades (España)Universidad de Las Islas BalearesMinisterio para la Transición Ecológica y el Reto Demográfico (España)Agulles, Miguel [0000-0003-3501-2899]Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]202520252024info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10261/379984https://api.elsevier.com/content/abstract/scopus_id/85204077293reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglés#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#info:eu-repo/grantAgreement/AEI//PRE2019-088046info:eu-repo/grantAgreement/AEI//CNS2022-135532info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-124085OB-I00The underlying dataset has been published as supplementary material of the article in the publisher platform at DOI https://doi.org/10.1016/j.ocemod.2024.102432https://doi.org/10.1016/j.ocemod.2024.102432Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/3799842026-05-22T06:33:51Z
dc.title.none.fl_str_mv Storm surge modelling along European coastlines: The effect of the spatio-temporal resolution of the atmospheric forcing
title Storm surge modelling along European coastlines: The effect of the spatio-temporal resolution of the atmospheric forcing
spellingShingle Storm surge modelling along European coastlines: The effect of the spatio-temporal resolution of the atmospheric forcing
Agulles, Miguel
Storm surges
Extreme sea level
Spatio-temporal resolution
title_short Storm surge modelling along European coastlines: The effect of the spatio-temporal resolution of the atmospheric forcing
title_full Storm surge modelling along European coastlines: The effect of the spatio-temporal resolution of the atmospheric forcing
title_fullStr Storm surge modelling along European coastlines: The effect of the spatio-temporal resolution of the atmospheric forcing
title_full_unstemmed Storm surge modelling along European coastlines: The effect of the spatio-temporal resolution of the atmospheric forcing
title_sort Storm surge modelling along European coastlines: The effect of the spatio-temporal resolution of the atmospheric forcing
dc.creator.none.fl_str_mv Agulles, Miguel
Marcos, Marta
Amores, Ángel
Toomey, Tim
author Agulles, Miguel
author_facet Agulles, Miguel
Marcos, Marta
Amores, Ángel
Toomey, Tim
author_role author
author2 Marcos, Marta
Amores, Ángel
Toomey, Tim
author2_role author
author
author
dc.contributor.none.fl_str_mv Ministerio de Ciencia e Innovación (España)
Agencia Estatal de Investigación (España)
European Commission
Ministerio de Universidades (España)
Universidad de Las Islas Baleares
Ministerio para la Transición Ecológica y el Reto Demográfico (España)
Agulles, Miguel [0000-0003-3501-2899]
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Storm surges
Extreme sea level
Spatio-temporal resolution
topic Storm surges
Extreme sea level
Spatio-temporal resolution
description The spatio-temporal resolution of atmospheric forcing plays a key role in the accuracy of simulated storm surges with hydrodynamic numerical models. Here, we generate five hydrodynamic hindcasts of coastal storm surges along the European Atlantic and the Mediterranean Sea coasts, forced with atmospheric fields of varying temporal (hourly and daily) and spatial (0.25° to 2°) resolution since 1940. Our results, that are validated with insitu tide gauge observations, show that storm surges obtained with daily forcing underestimate the magnitude of coastal extreme sea level events by up to 50% compared to hourly simulations and observations. Nevertheless, low-resolution simulations capture the temporal variability of storm surges, including strong episodes. Furthermore, taking advantage of the consistent set of coastal storm surge hindcasts, we demonstrate that storm surges forced with daily mean atmospheric fields, when bias corrected via quantile mapping, provide accurate values of daily maxima as calculated by a high-resolution hindcast. This transformation paves the way to obtain daily maxima storm surge estimates from low-resolution atmospheric fields, as those typically provided by large-scale and global climate models, at a lower computational cost.
publishDate 2024
dc.date.none.fl_str_mv 2024
2025
2025
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Publisher's version
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/379984
https://api.elsevier.com/content/abstract/scopus_id/85204077293
url http://hdl.handle.net/10261/379984
https://api.elsevier.com/content/abstract/scopus_id/85204077293
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv #PLACEHOLDER_PARENT_METADATA_VALUE#
#PLACEHOLDER_PARENT_METADATA_VALUE#
#PLACEHOLDER_PARENT_METADATA_VALUE#
info:eu-repo/grantAgreement/AEI//PRE2019-088046
info:eu-repo/grantAgreement/AEI//CNS2022-135532
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-124085OB-I00
The underlying dataset has been published as supplementary material of the article in the publisher platform at DOI https://doi.org/10.1016/j.ocemod.2024.102432
https://doi.org/10.1016/j.ocemod.2024.102432
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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