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    Precipitation Climatology in an Ensemble of CORDEX-Africa Regional Climate Simulations

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    Identificadores
    URI: http://hdl.handle.net/10902/20684
    DOI: 10.1175/JCLI-D-11-00375.1
    ISSN: 0894-8755
    ISSN: 1520-0442
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    Autoría
    Nikulin, Grigory; Jones, Colin; Giorgi, Filippo; Asrar, Ghassem; Büchner, Matthias; Cerezo Mota, Ruth; Christensen, Ole Bossing; Dèqué, Michel; Fernández Fernández, Jesús (matemático)Autoridad Unican; Hänsler, Andreas; Meijgaard, Erik van; Samuelsson, Patrick; Sylla, Mouhamadou Bamba; Sushama, Laxmi
    Fecha
    2012-09
    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(18), 6057-6078
    Editorial
    American Meteorological Society
    Enlace a la publicación
    https://journals.ametsoc.org/view/journals/clim/25/18/jcli-d-11-00375.1.xml
    Palabras clave
    Africa
    Monsoons
    Precipitation
    Model evaluation/performance
    Regional models
    Diurnal effects
    Resumen/Abstract
    An ensemble of regional climate simulations is analyzed to evaluate the ability of 10 regional climate models (RCMs) and their ensemble average to simulate precipitation over Africa. All RCMs use a similar domain and spatial resolution of ~50 km and are driven by the ECMWF Interim Re-Analysis (ERA-Interim) (1989-2008). They constitute the first set of simulations in the Coordinated Regional Downscaling Experiment in Africa (CORDEX-Africa) project. Simulated precipitation is evaluated at a range of time scales, including seasonal means, and annual and diurnal cycles, against a number of detailed observational datasets. All RCMs simulate the seasonal mean and annual cycle quite accurately, although individual models can exhibit significant biases in some subregions and seasons. The multimodel average generally outperforms any individual simulation, showing biases of similar magnitude to differences across a number of observational datasets. Moreover, many of the RCMs significantly improve the precipitation climate compared to that from their boundary condition dataset, that is, ERA-Interim. A common problem in the majority of the RCMs is that precipitation is triggered too early during the diurnal cycle, although a small subset of models does have a reasonable representation of the phase of the diurnal cycle. The systematic bias in the diurnal cycle is not improved when the ensemble mean is considered. Based on this performance analysis, it is assessed that the present set of RCMs can be used to provide useful information on climate projections over Africa.
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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