Mostrar el registro sencillo del ítem

Empirical Estimation of Nearshore Waves From a Global Deep-Water Wave Model

dc.contributor.authorBROWNE, Matthew
dc.contributor.authorSTRAUSS, Darrell
hal.structure.identifierEnvironnements et Paléoenvironnements OCéaniques [EPOC]
hal.structure.identifierGriffith University [Brisbane]
hal.structure.identifierUniversité de Bordeaux [UB]
hal.structure.identifierCentre National de la Recherche Scientifique [CNRS]
dc.contributor.authorCASTELLE, Bruno
IDREF: 087596520
hal.structure.identifierUniversität Heidelberg [Heidelberg] = Heidelberg University
dc.contributor.authorBLUMENSTEIN, Michael
dc.contributor.authorTOMLINSON, Rodger
dc.contributor.authorLANE, Chris
dc.date.accessioned2022-05-05T09:35:51Z
dc.date.available2022-05-05T09:35:51Z
dc.date.issued2006-10-01
dc.identifier.issn1545-598X
dc.identifier.urihttps://www.researchgate.net/publication/3449769_Empirical_Estimation_of_Nearshore_Waves_From_a_Global_Deep-Water_Wave_Model
dc.identifier.uriorcid:0000-0003-1740-7395:10.1109/lgrs.2006.876225
dc.identifier.urioai:researchgate.net:3449769
dc.identifier.uriorcid:0000-0002-2668-6229:10.1109/lgrs.2006.876225
dc.identifier.urioai:crossref.org:10.1109/lgrs.2006.876225
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/139983
dc.description.abstractEnGlobal wind-wave models such as the National Oceanic and Atmospheric Administration WaveWatch 3 (NWW3) play an important role in monitoring the world's oceans. However, untransformed data at grid points in deep water provide a poor estimate of swell characteristics at nearshore locations, which are often of significant scientific, engineering, and public interest. Explicit wave modeling, such as the Simulating Waves Nearshore (SWAN), is one method for resolving the complex wave transformations affected by bathymetry, winds, and other local factors. However, obtaining accurate bathymetry and determining parameters for such models is often difficult. When target data is available (i.e., from in situ buoys or human observers), empirical alternatives such as artificial neural networks (ANNs) and linear regression may be considered for inferring nearshore conditions from offshore model output. Using a sixfold cross-validation scheme, significant wave height Hs and period were estimated at one onshore and two nearshore locations. In estimating Hs at the shoreline, the validation performance of the best ANN was r=0.91, as compared to those of linear regression (0.82), SWAN (0.78), and the NWW3 Hs baseline (0.54)
dc.publisherInstitute of Electrical & Electronics Engineers (IEEE)
dc.sourceorcid
dc.sourceresearchgate
dc.sourcecrossref
dc.title.enEmpirical Estimation of Nearshore Waves From a Global Deep-Water Wave Model
dc.typeArticle de revueen_US
dc.identifier.doi10.1109/lgrs.2006.876225
dc.subject.halSciences de l'environnement
bordeaux.journalIEEE Geoscience and Remote Sensing Lettersen_US
bordeaux.page462-466
bordeaux.volume3
bordeaux.hal.laboratoriesEnvironnements et Paléoenvironnements Océaniques et Continentaux (EPOC) - UMR 5805en_US
bordeaux.issue4
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionCNRS
bordeaux.import.sourcedissemin
hal.identifierhal-03770204
hal.version1
hal.date.transferred2022-09-06T09:26:37Z
hal.exporttrue
workflow.import.sourcedissemin
dc.rights.ccPas de Licence CCen_US
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=IEEE%20Geoscience%20and%20Remote%20Sensing%20Letters&rft.date=2006-10-01&rft.volume=3&rft.issue=4&rft.spage=462-466&rft.epage=462-466&rft.eissn=1545-598X&rft.issn=1545-598X&rft.au=BROWNE,%20Matthew&STRAUSS,%20Darrell&CASTELLE,%20Bruno&BLUMENSTEIN,%20Michael&TOMLINSON,%20Rodger&rft.genre=article


Archivos en el ítem

Thumbnail
Nombre:
2006 Browne et al IEEE Letters.pdf
Tamaño:
346.1Kb
Formato:
PDF
Ver/Abrir

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem