[en] Sub-daily precipitation extremes are high-impact events that can result in flash floods, sewer system overload, or landslides. Several studies have reported an intensification of projected short-duration extreme rainfall in a warmer future climate. Traditionally, regional climate models (RCMs) are run at a coarse resolution using deep-convection parameterization for these extreme events. As computational resources are continuously ramping up, these models are run at convection-permitting resolution, thereby partly resolving the small-scale precipitation events explicitly. To date, a comprehensive evaluation of convection-permitting models is still missing. We propose an evaluation strategy for simulated sub-daily rainfall extremes that summarizes the overall RCM performance. More specifically, the following metrics are addressed: the seasonal/diurnal cycle, temperature and humidity dependency, temporal scaling and spatio-temporal clustering. The aim of this paper is: (i) to provide a statistical modeling framework for some of the metrics, based on extreme value analysis, (ii) to apply the evaluation metrics to a micro-ensemble of convection-permitting RCM simulations over Belgium, against high-frequency observations, and (iii) to investigate the added value of convection-permitting scales with respect to coarser 12-km resolution. We find that convection-permitting models improved precipitation extremes on shorter time scales (i.e, hourly or two-hourly), but not on 6h-24h time scales. Some metrics such as the diurnal cycle or the Clausius-Clapeyron rate are improved by convection-permitting models, whereas the seasonal cycle appears robust across spatial scales. On the other hand, the spatial dependence is poorly represented at both convection-permitting scales and coarser scales. Our framework provides perspectives for improving high-resolution atmospheric numerical modeling and datasets for hydrological applications.
Disciplines :
Earth sciences & physical geography
Author, co-author :
Van de Vyver, Hans
Van Schaeybroeck, Bert; Royal Meteorological Institute, Brussels, Belgium
De Troch, Rozemien; Royal Meteorological Institute, Brussels, Belgium
De Cruz, Lesley; Royal Meteorological Institute, Brussels, Belgium
Hamdi, Rafiq; Royal Meteorological Institute, Brussels, Belgium
Villanueva-Birriel, Cecille; Earth and Life Institute, Georges Lemaître Centre for Earth and Climate Research, Université catholique de Louvain, Louvain-la-Neuve, Belgium
Marbaix, Philippe; Earth and Life Institute, Georges Lemaître Centre for Earth and Climate Research, Université catholique de Louvain, Louvain-la-Neuve, Belgium
Van Ypersele, Jean-Pascal; Earth and Life Institute, Georges Lemaître Centre for Earth and Climate Research, Université catholique de Louvain, Louvain-la-Neuve, Belgium
Wouters, Hendrick; Department of Earth and Environmental Sciences, KU Leuven, Leuven, Belgium
Vanden Broucke, Sam; Department of Earth and Environmental Sciences, KU Leuven, Leuven, Belgium
van Lipzig, Nicole P.M.; Department of Earth and Environmental Sciences, KU Leuven, Leuven, Belgium
Doutreloup, Sébastien ; Université de Liège - ULiège > Département de géographie > Climatologie et Topoclimatologie
Wyard, Coraline ; Université de Liège - ULiège > Département de géographie > Climatologie et Topoclimatologie
Scholtzen, Chloé; Department of Geosciences University of Oslo, Oslo, Norway
Fettweis, Xavier ; Université de Liège - ULiège > Département de géographie > Climatologie et Topoclimatologie
Caluwaerts, Steven; Royal Meteorological Institute, Brussels, and Department of Physics and Astronomy, Ghent University, Ghent, Belgium
Termonia, Piet; Royal Meteorological Institute, Brussels, and Department of Physics and Astronomy, Ghent University, Ghent, Belgium
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