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    Seasonal predictability of wintertime precipitation in Europe using the snow advance index

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    Identificadores
    URI: http://hdl.handle.net/10902/17403
    DOI: 10.1175/JCLI-D-12-00083.1
    ISSN: 0894-8755
    ISSN: 1520-0442
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    Autoría
    Brands, Swen FranzAutoridad Unican; García Manzanas, RodrigoAutoridad Unican; Gutiérrez Llorente, José Manuel; Cohen, Judah L.
    Fecha
    2012-06-15
    Derechos
    © 2012 American Meteorological Society. AMS´s Full Copyright Notice: https://www.ametsoc.org/ams/index.cfm/publications/authors/journal-and-bams-authors/author-resources/copyright-information/copyright-policy/
    Publicado en
    Journal of Climate, 2012, 25(12), 4023-4028
    Editorial
    American Meteorological Society
    Enlace a la publicación
    https://doi.org/10.1175/JCLI-D-12-00083.1
    Palabras clave
    Europe
    Teleconnections
    Hydrology
    Snow cover
    Seasonal forecasting
    Statistical forecasting
    Resumen/Abstract
    This study tests the applicability of Eurasian snow cover increase in October, as described by the recently published snow advance index (SAI), for forecasting December–February precipitation totals in Europe. On the basis of a classical correlation analysis, global significance was obtained and locally significant correlation coefficients of up to 0.89 and 20.78 were found for the Iberian Peninsula and southern Norway, respectively. For a more robust assessment of these results, a linear regression approach is followed to hindcast the precipitation sums in a 1-yr-out cross-validation framework, using the SAI as the only predictor variable. With this simple empirical approach, local-scale precipitation could be reproduced with a correlation of up to 0.84 and 0.71 for the Iberian Peninsula and southern Norway, respectively, while catchment aggregations on the Iberian Peninsula could be hindcast with a correlation of up to 0.73. These findings are confirmed when repeating the hindcast approach to a degraded but much longer version of the SAI. With the recommendation to monitor the robustness of these results as the sample size of the SAI increases, the authors encourage its use for the purpose of seasonal forecasting in southern Norway and the Iberian Peninsula, where general circulation models are known to perform poorly for the variable in question.
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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