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dc.contributor.authorDíaz Fernández, Javier
dc.contributor.authorBolgiani, Pedro
dc.contributor.authorSantos Muñoz, Daniel
dc.contributor.authorQuitián Hernández, Lara
dc.contributor.authorSastre Marugan, Maríano 
dc.contributor.authorValero, Francisco
dc.contributor.authorFarrán Martín, José Ignacio 
dc.contributor.authorGonzález Alemán, Juan Jesús
dc.contributor.authorMartín Pérez, María Luisa 
dc.date.accessioned2024-11-13T10:47:49Z
dc.date.available2024-11-13T10:47:49Z
dc.date.issued2022
dc.identifier.citationAtmospheric Research, 2022, vol. 265, 105890es
dc.identifier.issn0169-8095es
dc.identifier.urihttps://uvadoc.uva.es/handle/10324/71403
dc.descriptionProducción científicaes
dc.description.abstractMountain lee waves usually involve aircraft icing and turbulence events. These weather phenomena, in turn, are a threat to aviation safety. For this reason, mountain lee waves are an interesting subject of study for the scientific community. This paper analyses several mountain lee waves events in the south-east of the Guadarrama mountain range, near the Adolfo Suarez Madrid-Barajas airport (Spain), using the Weather Research and Forecasting (WRF) and the HARMONIE-AROME high-resolution numerical models. For this work, simulated brightness temperature from the optimum WRF parametrization schemes and from the HARMONIE are validated using satellite observations to evaluate the performance of the models in reproducing the lenticular clouds associated to mountain lee waves. The brightness temperature probability density shows interesting differences between both models. Following, a mountain wave characterization is performed simulating some atmospheric variables (wind direction, wind speed, atmospheric stability, liquid water content and temperature) in several grid points located in the leeward, windward and over the summit of the mountains. The characterization results are compared for both numerical models and a decision tree is developed for each to forecast and warn the mountain lee waves, lenticular clouds and icing events with a 24 to 48 h lead time. These warnings are validated using several skill scores, revealing similar results for both models.en
dc.format.mimetypeapplication/pdfes
dc.language.isoenges
dc.publisherElsevieres
dc.relation.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject.classificationMountain lee waves
dc.subject.classificationIcing
dc.subject.classificationLenticular clouds
dc.subject.classificationWRF
dc.subject.classificationHARMONIE
dc.subject.classificationWarning
dc.subject.classificationDecision tree
dc.titleComparison of the WRF and HARMONIE models ability for mountain wave warningses
dc.typeinfo:eu-repo/semantics/articlees
dc.rights.holder© 2021 The Authors
dc.identifier.doi10.1016/j.atmosres.2021.105890es
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S0169809521004464?via%3Dihub
dc.identifier.publicationfirstpage105890es
dc.identifier.publicationtitleAtmospheric Researches
dc.identifier.publicationvolume265es
dc.peerreviewedSIes
dc.description.projectMinisterio de Asuntos Económicos y Transformación Digital y Universidad Complutense de Madrid (PID2019-105306RB-I00 (IBER-CANES); CGL2016-78702-C2-1-R y (SAFEFLIGHT); FEI-EU-17-16)es
dc.description.projectECMWF Special Projects (SPESMART AND SPESVALE)es
dc.description.projectMinisterio de Economía y Competitividad-FPI (BES-2017)
dc.rightsAtribución/Reconocimiento-NoComercial-SinDerivados 4.0 Internacional
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones


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