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| Titel |
Evaluation and projection of daily temperature percentiles from statistical and dynamical downscaling methods |
| VerfasserIn |
A. Casanueva, S. Herrera, J. Fernandez, M. D. Frias, J. M. Gutiérrez |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1561-8633
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| Digitales Dokument |
URL |
| Erschienen |
In: Natural Hazards and Earth System Science ; 13, no. 8 ; Nr. 13, no. 8 (2013-08-22), S.2089-2099 |
| Datensatznummer |
250085502
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| Publikation (Nr.) |
 copernicus.org/nhess-13-2089-2013.pdf |
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| Zusammenfassung |
| 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 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 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. |
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