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Evaluation and projection of daily temperature percentiles from statistical and dynamical downscaling methods

Journal: Natural Hazards and Earth System Sciences
Year: 2013   Volume: 13
Initial page: 2089   Last page: 2099
Status: Published
In this status since: 22 Aug 2013
PDF file: 2013_Casanueva_NHESS.pdf
Link to PDF: http://www.nat-hazards-earth-syst-sci.net/13/2089/2013/
DOI: 10.5194/nhess-13-2089-2013

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 in 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 analyze high (95th) and low (5th) percentiles in daily maximum and minimum temperatures, respectively, derived from different downscaling methods (statistical and dynamical) in the Iberian Peninsula. First, we analyze the performance of reanalysis-driven 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 analyze 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.

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