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    Observational uncertainty and regional climate model evaluation: A pan-European perspective

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    ObservationalUncerta ... (5.865Mb)
    Identificadores
    URI: http://hdl.handle.net/10902/12975
    DOI: 10.1002/joc.5249
    ISSN: 0899-8418
    ISSN: 1097-0088
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    Autoría
    Herrera García, SixtoAutoridad Unican; Gutiérrez Llorente, José Manuel
    Fecha
    2017-09
    Derechos
    ©John Wiley & Sons. "This is the peer reviewed version of the following article: Kotlarski, S., Szabó, P., Herrera, S., Räty, O., Keuler, K., Soares, P. M., Cardoso, R. M., Bosshard, T., Pagé, C., Boberg, F., Gutiérrez, J. M., Isotta, F. A., Jaczewski, A., Kreienkamp, F., Liniger, M. A., Lussana, C. and Pianko-Kluczy?ska, K. (2017), Observational uncertainty and regional climate model evaluation: a pan-European perspective. Int. J. Climatol. doi:10.1002/joc.5249, which has been published in final form at http://dx.doi.org/10.1002/joc.5249. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving."
    Publicado en
    International Journal of Climatology
    Editorial
    John Wiley and Sons Ltd
    Enlace a la publicación
    http://onlinelibrary.wiley.com/doi/10.1002/joc.5249/abstract#publication-history
    Resumen/Abstract
    The influence of uncertainties in gridded observational reference data on regional climate model (RCM) evaluation is quantified on a pan-European scale. Three different reference data sets are considered: the coarse-resolved E-OBS data set, a compilation of regional high-resolution gridded products (HR) and the European-scale MESAN reanalysis. Five high-resolution ERA-Interim-driven RCM experiments of the EURO-CORDEX initiative are evaluated against each of these references over eight European sub-regions and considering a range of performance metrics for mean daily temperature and daily precipitation. The spatial scale of the evaluation is 0.22°, i.e. the grid spacing of the coarsest data set in the exercise (E-OBS). While the three reference grids agree on the overall mean climatology, differences can be pronounced over individual regions. These differences partly translate into RCM evaluation uncertainty. For most cases observational uncertainty is smaller than RCM uncertainty. Nevertheless, for individual sub-regions and performance metrics observational uncertainty can dominate. This is especially true for precipitation and for metrics targeting the wet-day frequency, the pattern correlation and the distributional similarity. In some cases the spatially averaged mean bias can also be considerably affected. An illustrative ranking exercise highlights the overall effect of observational uncertainty on RCM ranking. Over individual sub-domains, the choice of a specific reference can modify RCM ranks by up to four levels (out of five RCMs). For most cases, however, RCM ranks are stable irrespective of the reference. These results provide a twofold picture: model uncertainty dominates for most regions and for most performance metrics considered, and observational uncertainty plays a minor role. For individual cases, however, observational uncertainty can be pronounced and needs to be definitely taken into account. Results can, to some extent, also depend on the treatment of precipitation undercatch in the observational reference.
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    UNIVERSIDAD DE CANTABRIA

    Repositorio realizado por la Biblioteca Universitaria utilizando DSpace software
    Contacto | Sugerencias
    Metadatos sujetos a:licencia de Creative Commons Reconocimiento 4.0 España