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Sub-daily precipitation extremes can have a huge impact on society as they cause hazards such as flooding, erosion and landslides. For example, the July floods in Germany, Belgium and nearby countries, were one of the costliest events in Europe, with insured losses up to USD 13 billion. Climate change is expected to intensify precipitation extremes as atmospheric water content increases by 6-7% per degree of warming, underscoring the need to predict future hydrological hazards. Regional Climate Models (RCMs) typically run at a spatial resolution of 12-25 km, but they insufficiently describe the small-scale features of observed sub-daily precipitation extremes. The past decade, convection-permitting RCMs were developed which run at high resolution (1-4 km), and explicitly resolve deep convection. Confidence in future projections requires that RCMs adequately simulate the statistical features of observed sub-daily extreme precipitation and also represent the physical processes associated with convective events. We propose a diagnostic framework for simulated 1h-24h rainfall extremes that summarizes the overall RCM performance. This includes the following metrics: the seasonal/diurnal cycle, temperature and humidity dependency, temporal scaling, and spatiotemporal clustering. A substantial part of the work is devoted to the statistical modelling of the metrics with Extreme Value Theory (EVT). We illustrate the evaluation tool with convection-permitting RCM simulations over Belgium against high-frequency observations and assess the benefit of the convection-permitting RCMs with respect to coarser scales. Finally, we give some guidelines for bias correction of simulated precipitation extremes.

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.

The CORDEX.be project created the foundations for Belgian climate services by producing high-resolution Belgian climate information that (a) incorporates the expertise of the different Belgian climate modeling groups and that (b) is consistent with the outcomes of the international CORDEX (“COordinated Regional Climate Downscaling Experiment”) project. The key practical tasks for the project were the coordination of activities among different Belgian climate groups, fostering the links to specific international initiatives and the creation of a stakeholder dialogue. Scientifically, the CORDEX.be project contributed to the EURO-CORDEX project, created a small ensemble of High-Resolution (H-Res) future projections over Belgium at convection-permitting resolutions and coupled these to seven Local Impact Models. Several impact studies have been carried out. The project also addressed some aspects of climate change uncertainties. The interactions and feedback from the stakeholder dialogue led to different practical applications at the Belgian national level. Keywords: Regional downscaling, Climate impact modeling, Statistical downscaling, Dynamical downscaling, Local Impact Models, Climate change, EURO-CORDEX, Uncertainty estimation, Regional Climate Model, Climate Belgium, Water vapour observations

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