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dc.contributor.authorCasanueva Vicente, Ana 
dc.contributor.authorHerrera García, Sixto 
dc.contributor.authorFernández Fernández, Jesús 
dc.contributor.authorFrías Domínguez, María Dolores 
dc.contributor.authorGutiérrez Llorente, José Manuel
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.description.abstractABSTRACT. The study of extreme events has become of great interest in recent years due to their direct impact on society. Extremes are usually evaluated by using extreme indicators, based on order statistics on the tail of the probability distribution function (typically percentiles). In this study, we focus on the tail of the distribution of daily maximum and minimum temperatures. For this purpose, we analyse high (95th) and low (5th) percentiles in daily maximum and minimum temperatures on the Iberian Peninsula, respectively, derived from different downscaling methods (statistical and dynamical). First, we analyse the performance of reanalysisdriven downscaling methods in present climate conditions. The comparison among the different methods is performed in terms of the bias of seasonal percentiles, considering as observations the public gridded data sets E-OBS and Spain02, and obtaining an estimation of both the mean and spatial percentile errors. Secondly, we analyse the increments of future percentile projections under the SRES A1B scenario and compare them with those corresponding to the mean temperature, showing that their relative importance depends on the method, and stressing the need to consider an ensemble of methodologies.es_ES
dc.format.extent10 p.es_ES
dc.publisherCopernicus Publicationses_ES
dc.rightsAtribución 3.0 Españaes_ES
dc.sourceNatural Hazards and Earth System Sciences, 2013, 13, 2089-2099es_ES
dc.titleEvaluation and projection of daily temperature percentiles from statistical and dynamical downscaling methodses_ES

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Atribución 3.0 EspañaExcept where otherwise noted, this item's license is described as Atribución 3.0 España