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dc.contributor.authorRicondo Cueva, Alba 
dc.contributor.authorCagigal Gil, Laura 
dc.contributor.authorRueda Zamora, Ana Cristina 
dc.contributor.authorHoeke, Ron
dc.contributor.authorStorlazzi, Curt D.
dc.contributor.authorMéndez Incera, Fernando Javier 
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2023-09-27T17:33:43Z
dc.date.available2023-09-27T17:33:43Z
dc.date.issued2023-08
dc.identifier.issn1463-5003
dc.identifier.issn1463-5011
dc.identifier.otherPID2019-107053RB-I00es_ES
dc.identifier.urihttps://hdl.handle.net/10902/30018
dc.description.abstractLong-term and accurate wave hindcast databases are often required in different coastal engineering projects. The assessment of the nearshore wave climate is often accomplished by using downscaling techniques to translate offshore waves to coastal areas. However, dynamical downscaling approaches may incur huge computational cost. Additionally, the common use of bulk parameterizations are often not accurate for multidimensional waves. To overcome these limitations, we present a hybrid downscaling approach that combines mathematical algorithms (statistical downscaling) and numerical modeling (dynamical downscaling) over the individual spectral partitions. Every wave partition is downscaled and aggregated afterward by using principles of wave linear theory. By assuming linearity in the propagation of the wave celerity, the application of the method is limited from offshore to intermediate water depths. In addition, the method proposed uses a technique to simplify the spectral boundary conditions in complex domains. The methodology has been applied and validated in the island states of Samoa, American Samoa, Majuro, and Kwajalein, showing good skill at reproducing the spectral hourly time series of significant wave height, peak period, and peak direction. Moreover, an accurate representation of the observed energy spectrum was achieved. This study provides insight into the numerical approximation of the combined sea-swell states while improving the quality of fast spectral forecasting and early warning systems.es_ES
dc.description.sponsorshipThis work would not have been possible without funding from the Spanish Ministry of Science and Innovation, project Beach4cast PID2019-107053RB-I00. The authors would like to acknowledge CSIRO, for making the spectral hindcast data publicly available, PacIOOS (www.pacioos.org), part of the U.S. Integrated Ocean Observing System (IOOS®), for providing the Kalo and Aunu’u wave buoy measurements, the U.S. Geological Survey (www.sciencebase.gov) for providing the Kwajalein and Roi-Namur field observations, and Oceanor-SOPAC (today Fugro-SPC) for the Apolima buoy data. LC acknowledges the funding from the Juan de la Cierva – Formación FJC2021-046933-I/ MCIN/ AEI/ 10.13039/501100011033 and the European Union ‘‘NextGenerationEU’’/ PRTR. ARu acknowledges the funding from the Juan de la Cierva-Incorporación IJC2020-043907-I/ MCIN/AEI/ 10.13039/5011 00011033 and the European Union ‘‘NextGenerationEU’’/PRTR. ARi is funded by a Concepción Arenal studentship from the Universidad de Cantabria. We thank Kai Parker for conducting a USGS internal review of this manuscript. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. I understand that any modifications made to a published article require careful consideration and adherence to the journal’s policies. Therefore, I kindly request your guidance on the appropriate procedure to follow for making this minor modification. I am more than willing to provide any necessary documentation or clarification to support this request.es_ES
dc.format.extent11 p.es_ES
dc.language.isoenges_ES
dc.publisherElsevier Ltdes_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internationales_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.sourceOcean Modelling, 2023, 184, 102210es_ES
dc.subject.otherHybrid downscalinges_ES
dc.subject.otherData mininges_ES
dc.subject.otherMultimodal wave climatees_ES
dc.subject.otherSpectral partitioninges_ES
dc.subject.otherDirectional wave spectraes_ES
dc.titleHyWaves: Hybrid downscaling of multimodal wave spectra to nearshore areases_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherVersionhttps://doi.org/10.1016/j.ocemod.2023.102210es_ES
dc.rights.accessRightsopenAccesses_ES
dc.identifier.DOI10.1016/j.ocemod.2023.102210
dc.type.versionpublishedVersiones_ES


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Attribution-NonCommercial-NoDerivatives 4.0 InternationalExcepto si se señala otra cosa, la licencia del ítem se describe como Attribution-NonCommercial-NoDerivatives 4.0 International