Publication Details
Hans Van De Vyver, Bert Van Schaeybroeck, Rozemien De Troch, Lesley De Cruz, Rafiq Hamdi, Cecille Villanueva-Birriel, Philippe Marbaix, Jean-Pascal van Ypersele, Hendrik Wouters, Sam Vanden Broucke, Nicole P.M. van Lipzig, Sébastien Doutreloup, Coraline Wyard, Chloé Scholzen, Xavier Fettweis, Steven Caluwaerts, Piet Termonia

Journal of Applied Meteorology and Climatology

Contribution To Journal


Subdaily 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 subdaily 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 spatiotemporal clustering. The aim of this paper is as follows: (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 microensemble 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 2 hourly), but not on 6–24-h 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 to be 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.

DOI scopus