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Skill of raw and downscaled seasonal predictions of monsoonal precipitation from the ENSEMBLES multimodel over Senegal and Ghana

AutorManzanas, R. ; Gutiérrez, José M.
Fecha de publicación2012
Citación4th AMMA: (2012)
ResumenThe aim of this work is to compare the skill of raw and downscaled seasonal predictions of precipitation during the monsoon season (July-August-September) over Senegal and Ghana. For such purpose, the state-of-the-art ENSEMBLES seasonal multimodel, which covers the period of study 1961-2000, is used. In a first step, the model’s ability to reproduce monsoonal rain two months in advance is evaluated by using a robust probabilistic validation based on terciles. The poor performance found (especially for Senegal) might be related to the GCM coarse resolution, which is not able to capture small-scale processes triggering monsoonal rains. Therefore, downscaling approaches need to be undertaken. In this context, a meticulous search for identifying the most adequate downscaling configurations (predictors-domain) in Perfect Prognosis is conducted. Then, various methodologies are followed to statistically downscale the GCM outputs to the local stations where observational data of good quality are available. Apart from probabilistic scores, comparison between raw and downscaled predictions is given in terms of other indicators such as the frequency of wet days or the mean length of wet spells.
DescripciónTrabajo presentado a la 4th AMMA International Conference celebrada en Francia del 2 al 6 de julio de 2012.
Versión del editorhttp://amma-conf2012.ipsl.fr/home/
URIhttp://hdl.handle.net/10261/94474
Aparece en las colecciones: (IFCA) Comunicaciones congresos
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