Identifying a robust method to build RCMs ensemble as climate forcing for hydrological impact models
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Ingeniería HidráulicaPatrocinadores
This work has been developed in the framework of R&D Project CGL2012-39895-C02-01 HYDROCLIM, funded by the State Secretary of Research of the Spanish Ministry of Economy and Competitiveness (MINECO) and FEDER funds. The support received from Spanish Ministry of Education, Culture and Sport for Mobility Grant of Senior Professors and Researchers (Ref. PRX14/00748), and from grant no. 07.0329/2013/671258/SUB/C1 ASSET project funded by European Commission, is gratefully acknowledged.Fecha de publicación
2016-06Editorial
ElsevierCita bibliográfica
P. Olmos Giménez, S.G. García Galiano, J.D. Giraldo-Osorio, Identifying a robust method to build RCMs ensemble as climate forcing for hydrological impact models, Atmospheric Research, Volumes 174–175, 2016, Pages 31-40, ISSN 0169-8095, https://doi.org/10.1016/j.atmosres.2016.01.012Revisión por pares
siPalabras clave
Climate changeRCMs ensemble
Rainfall variability
Uncertainties reduction
Resumen
The regional climate models (RCMs) improve the understanding of the climate mechanism and are often used as climate forcing to hydrological impact models. Rainfall is the principal input to the water cycle, so special attention should be paid to its accurate estimation. However, climate change projections of rainfall events exhibit great divergence between RCMs. As a consequence, the rainfall projections, and the estimation of uncertainties, are better based in the combination of the information provided by an ensemble approach from different RCMs simulations. Taking into account the rainfall variability provided by different RCMs, the aims of this work are to evaluate the performance of two novel approaches based on the reliability ensemble averaging (REA) method for building RCMs ensembles of monthly precipitation over Spain. The proposed methodologies are based on probability density functions (PDFs) considering the variability of different levels of information, on the one hand of ...
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