Abstract
To date, the assessment of hydrological climate change impacts, not least on pluvial flooding, has been severely limited by i) the insufficient spatial resolution of regional climate models (RCMs) as well as ii) the simplified description of key processes, e.g., convective rainfall generation. Therefore, expectations have been high on the recent generation of high-resolution convection-permitting regional climate models (CPRCMs), to reproduce the small-scale features of observed (extreme) rainfall that are driving small-scale hydrological hazards. Are they living up to these expectations? In this study, we zoom in on southern Sweden and investigate to which extent two climate models, a 3-km resolution CPRCM (HCLIM3) and a 12-km non-convection permitting RCM (HCLIM12), are able to reproduce the rainfall climate with focus on short-duration extremes. We use three types of evaluation–intensity-based, time-based and event-based–which have been designed to provide an added value to users of high-intensity rainfall information, as compared with the ways climate models are generally evaluated. In particular, in the event-based evaluation we explore the prospect of bringing climate model evaluation closer to the user by investigating whether the models are able to reproduce a well-known historical high-intensity rainfall event in the city of Malmö 2014. The results very clearly point at a substantially reduced bias in HCLIM3 as compared with HCLIM12, especially for short-duration extremes, as well as an overall better reproduction of the diurnal cycles. Furthermore, the HCLIM3 model proved able to generate events similar to the one in Malmö 2014. The results imply that CPRCMs offer a clear potential for increased confidence in future projections of small-scale hydrological climate change impacts, which is crucial for climate-proofing, e.g., our cities, as well as climate modeling in general.
Highlights
In August 2014, the city of Malmö in southern Sweden was hit by a severe cloudburst which flooded parts of the city and caused damages estimated at ∼60 MEUR, in this respect making it the worst urban flooding Sweden has experienced (Hernebring et al, 2015; SOU, 2017)
To assess the ability of HCLIM3 and HCLIM12 to represent extreme rainfall intensities, we examine the reproduction of average annual maximum intensities
HCLIM12 performs slightly better with mean absolute error (MAE) 6% for the monthly fractions, compared with 9% for HCLIM3
Summary
In August 2014, the city of Malmö in southern Sweden was hit by a severe cloudburst which flooded parts of the city and caused damages estimated at ∼60 MEUR, in this respect making it the worst urban flooding Sweden has experienced (Hernebring et al, 2015; SOU, 2017). This was only three years after Copenhagen, just across the Öresund strait, was hit even harder (e.g., ArnbjergNielsen et al, 2015). Still, taking all other uncertainties and limitations included in infrastructural design into account, the statistical uncertainty in the design rainfall is generally considered manageable
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