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Local impact analysis of climate change on precipitation extremes: are high-resolution climate models needed for realistic simulations?

This study explores whether climate models with higher spatial resolutions provide higher accuracy for precipitation simulations and/or different climate change signals. The outputs from two convection-permitting climate models (ALARO and CCLM) with a spatial resolution of 3–4 km are compared with t...

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Bibliographic Details
Published in:Hydrology and earth system sciences 2016-09, Vol.20 (9), p.3843-3857
Main Authors: Tabari, Hossein, De Troch, Rozemien, Giot, Olivier, Hamdi, Rafiq, Termonia, Piet, Saeed, Sajjad, Brisson, Erwan, Van Lipzig, Nicole, Willems, Patrick
Format: Article
Language:English
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Summary:This study explores whether climate models with higher spatial resolutions provide higher accuracy for precipitation simulations and/or different climate change signals. The outputs from two convection-permitting climate models (ALARO and CCLM) with a spatial resolution of 3–4 km are compared with those from the coarse-scale driving models or reanalysis data for simulating/projecting daily and sub-daily precipitation quantiles. Validation of historical design precipitation statistics derived from intensity–duration–frequency (IDF) curves shows a better match of the convection-permitting model results with the observations-based IDF statistics compared to the driving GCMs and reanalysis data. This is the case for simulation of local sub-daily precipitation extremes during the summer season, while the convection-permitting models do not appear to bring added value to simulation of daily precipitation extremes. Results moreover indicate that one has to be careful in assuming spatial-scale independency of climate change signals for the delta change downscaling method, as high-resolution models may show larger changes in extreme precipitation. These larger changes appear to be dependent on the timescale, since such intensification is not observed for daily timescales for both the ALARO and CCLM models.
ISSN:1607-7938
1027-5606
1607-7938
DOI:10.5194/hess-20-3843-2016