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dc.contributor.authorMoeini, Mohammad Hadien_US
dc.contributor.authorEtemad Shahidi, Amiren_US
dc.contributor.authorChegini, Vahiden_US
dc.contributor.authorRahmani, Irajen_US
dc.date.accessioned2017-05-03T16:06:43Z
dc.date.available2017-05-03T16:06:43Z
dc.date.issued2012en_US
dc.date.modified2013-06-27T00:42:35Z
dc.identifier.issn16167341en_US
dc.identifier.doi10.1007/s10236-012-0529-5en_US
dc.identifier.urihttp://hdl.handle.net/10072/46756
dc.description.abstractThe main goal of this study is to develop an efficient approach for the assimilation of the hindcasted wave parameters in the Persian Gulf. Hence, the third generation SWAN model was employed for wave modeling forced by the 6-h ECMWF wind data with a resolution of 0.5஠In situ wave measurements at two stations were utilized to evaluate the assimilation approaches. It was found that since the model errors are not the same for wave height and period, adaptation of model parameter does not result in simultaneous and comprehensive improvement of them. Therefore, an approach based on the error prediction and updating of output variables was employed to modify wave height and period. In this approach, artificial neural networks (ANNs) were used to estimate the deviations between the simulated and measured wave parameters. The results showed that updating of output variables leads to significant improvement in a wide range of the predicted wave characteristics. It was revealed that the best input parameters for error prediction networks are mean wind speed, mean wind direction, wind duration, and the wave parameters. In addition, combination of the ANN estimated error with numerically modeled wave parameters leads to further improvement in the predicted wave parameters in contrast to direct estimation of the parameters by ANN.en_US
dc.description.peerreviewedYesen_US
dc.description.publicationstatusYesen_US
dc.format.extent649598 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglishen_US
dc.language.isoen_US
dc.publisherSpringeren_US
dc.publisher.placeGermanyen_US
dc.relation.ispartofstudentpublicationNen_US
dc.relation.ispartofpagefrom785en_US
dc.relation.ispartofpageto797en_US
dc.relation.ispartofissue5en_US
dc.relation.ispartofjournalOcean Dynamicsen_US
dc.relation.ispartofvolume62en_US
dc.rights.retentionYen_US
dc.subject.fieldofresearchGeology not elsewhere classifieden_US
dc.subject.fieldofresearchcode040399en_US
dc.titleWave data assimilation using a hybrid approach in the Persian Gulfen_US
dc.typeJournal articleen_US
dc.type.descriptionC1 - Peer Reviewed (HERDC)en_US
dc.type.codeC - Journal Articlesen_US
gro.rights.copyrightCopyright 2012 Springer Berlin / Heidelberg. This is an electronic version of an article published in Ocean Dynamics, May 2012, Volume 62, Issue 5, pp 785-797. Ocean Dynamics is available online at: http://www.springerlink.com/ with the open URL of your article.en_US
gro.date.issued2012
gro.hasfulltextFull Text


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