dc.contributor.author | Lobeto Alonso, Hector | |
dc.contributor.author | Semedo, Álvaro | |
dc.contributor.author | Menéndez García, Melisa | |
dc.contributor.author | Lemos, Gil | |
dc.contributor.author | Kumar, Rajesh | |
dc.contributor.author | Akpinar, Adem | |
dc.contributor.author | Dobrynin, Mikhail | |
dc.contributor.author | Kamranzad, Bahareh | |
dc.contributor.other | Universidad de Cantabria | es_ES |
dc.date.accessioned | 2025-02-13T12:51:50Z | |
dc.date.available | 2025-02-13T12:51:50Z | |
dc.date.issued | 2023-12 | |
dc.identifier.issn | 1748-9326 | |
dc.identifier.uri | https://hdl.handle.net/10902/35529 | |
dc.description.abstract | This study investigates the epistemic uncertainty associated with the wave propagation modeling in wave climate projections. A single-forcing, single-scenario, seven-member global wave climate projection ensemble is used, developed using three wave models with a consistent numerical domain. The uncertainty is assessed through projected changes in wave height, wave period, and wave direction. The relative importance of the wave model used and its internal parameterization are examined. The former is the dominant source of uncertainty in approximately two-thirds of the global ocean. The study reveals divergences in projected changes from runs of different models and runs of the same model with different parameterizations over 75% of the ensemble mean change in several ocean regions. Projected changes in the wave period shows the most significant uncertainties, particularly in the Pacific Ocean basin, while the wave height shows the least. Over 30% of global coastlines exhibit significant uncertainties in at least two out of the three wave climate variables analyzed. The coasts of western North America, the Maritime Continent and the Arabian Sea show the most significant wave modeling uncertainties. | es_ES |
dc.description.sponsorship | HL and MM acknowledge financial support by CoCliCo project, which received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No. 101003598, and the ThinkInAzul programme, with funding from European Union NextGenerationEU/PRTR-C17.I1 and the Comunidad de Cantabria. GL acknowledges financial support of Portuguese Fundação para a Ciência e a Tecnologia I.P./MCTES through national funds (PIDDAC)—UIDB/50019/2020—Instituto Dom Luiz. | es_ES |
dc.format.extent | 12 p. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | IOP | es_ES |
dc.rights | Attribution 4.0 International | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
dc.source | Environmental Research Letters, 2023, 18(12), 124006 | es_ES |
dc.subject.other | Wave climate | es_ES |
dc.subject.other | Climate change | es_ES |
dc.subject.other | Uncertainty | es_ES |
dc.subject.other | Wave modeling | es_ES |
dc.title | On the assessment of the wave modeling uncertainty in wave climate projections | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.relation.publisherVersion | https://doi.org/10.1088/1748-9326/ad0137 | es_ES |
dc.rights.accessRights | openAccess | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/H2020/101003598/EU/COASTAL CLIMATE CORE SERVICES/CoCliCo/ | es_ES |
dc.identifier.DOI | 10.1088/1748-9326/ad0137 | |
dc.type.version | publishedVersion | es_ES |