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APPMAR 1.0: A Python application for downloading and analyzing of WAVEWATCH III® wave and wind data

dc.contributor.authorRivillas-Ospina, German
dc.contributor.authorCasas, Diego
dc.contributor.authorMaza, Mauro
dc.contributor.authorBolivar, Marianella
dc.contributor.authorRuiz, Gabriel
dc.contributor.authorGuerrero, Roberto
dc.contributor.authorHorrillo-Caraballo, José M.
dc.contributor.authorGuerrero, Milton
dc.contributor.authorDiaz Martinez, Karina SOFIA
dc.contributor.authorDel Rio, Roberto
dc.contributor.authorCampos, Erick
dc.date.accessioned2022-04-18T19:34:27Z
dc.date.available2022-04-18T19:34:27Z
dc.date.issued2022-03-10
dc.date.submitted2022-04-08
dc.identifier.citationGerman Rivillas-Ospina, Diego Casas, Mauro Antonio Maza-Chamorro, Marianella Bolívar, Gabriel Ruiz, Roberto Guerrero, José M. Horrillo-Caraballo, Milton Guerrero, Karina Díaz, Roberto del Rio, Erick Campos, APPMAR 1.0: A Python application for downloading and analyzing of WAVEWATCH III® wave and wind data, Computers & Geosciences, Volume 162, 2022, 105098, ISSN 0098-3004, https://doi.org/10.1016/j.cageo.2022.105098.spa
dc.identifier.urihttps://hdl.handle.net/20.500.12585/10674
dc.description.abstractThis work presents APPMAR 1.0, an application written in the Python programming language that downloads, processes, and analyzes wind and wave data. This application is composed of a graphical user interface (GUI) that contains two main modules: the first module downloads data from WAVEWATCH III® (WW3) production hindcasts by the National Oceanic and Atmospheric Administration (NOAA); the second module applies statis tical mathematics for processing and analyzing wave and wind data. This application provides useful graphical results that describe mean and extreme wave and wind climate. APPMAR generates plots of exceedance prob ability, joint probability distribution, wave direction, Weibull distribution, and storm frequency analysis. Currently, APPMAR only downloads and analyzes wave and wind data from WW3 hindcasts, but it is under development to other datasets and marine climate parameters. This application has been tested in the Magdalena River mouth, Colombia, and Cancún, M´exico, where observational wave and wind data are scarce.spa
dc.format.extent14 Páginas
dc.format.mimetypeapplication/pdfspa
dc.language.isoengspa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.sourceComputers & Geosciences Vol. 162 (2022)spa
dc.titleAPPMAR 1.0: A Python application for downloading and analyzing of WAVEWATCH III® wave and wind dataspa
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datacite.rightshttp://purl.org/coar/access_right/c_abf2spa
oaire.versionhttp://purl.org/coar/version/c_ab4af688f83e57aaspa
dc.type.driverinfo:eu-repo/semantics/articlespa
dc.type.hasVersioninfo:eu-repo/semantics/restrictedAccessspa
dc.identifier.doihttps://doi.org/10.1016/j.cageo.2022.105098.
dc.subject.keywordsWAVEWATCH IIIspa
dc.subject.keywordsWave and wind climatespa
dc.subject.keywordsData accessspa
dc.subject.keywordsVisualizationspa
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessspa
dc.rights.ccAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.identifier.instnameUniversidad Tecnológica de Bolívarspa
dc.identifier.reponameRepositorio Universidad Tecnológica de Bolívarspa
dc.publisher.placeCartagena de Indiasspa
dc.subject.armarcLEMB
dc.type.spahttp://purl.org/coar/resource_type/c_2df8fbb1spa
oaire.resourcetypehttp://purl.org/coar/resource_type/c_2df8fbb1spa


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