Identifying added value in high-resolution climate simulations over Scandinavia

Abstract

A B S T R A C T High-resolution data are needed in order to assess potential impacts of extreme events on infrastructure in the mid-latitudes. Dynamical downscaling offers one way to obtain this information. However, prior to implementation in any impacts assessment scheme, model output must be validated and determined fitfor-purpose. This study presents the results from two 8-km resolution perfect boundary experiments over Scandinavia. Two different regional climate models were initialised and driven with ERA interim reanalysis from 1990 to 2010. Reference data come from both gridded products and point-based station observations. In addition to the canonical variables of daily precipitation and temperature, winds were also investigated. The models exhibit systematic cold and wet biases on seasonal time scales ( (1 K and '50Á100%, respectively). However, frequency-based skill scores for daily precipitation and temperature are high, indicating that the distributions of these variables are generally well captured. Wind speeds over the North and Norwegian Seas were simulated more realistically in the models than in the ERA interim reanalysis. However, most importantly, for impacts assessments, the models should be capable of capturing the timing, intensity and location of short-duration extreme events, in particular precipitation. In this respect, both models outperform the reanalysis over the city of Copenhagen, where recent pluvial floods led to costly damages to infrastructure.

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

“…and more complex description of atmospheric processes compared to GCMs. This often results in more realistic representation of precipitation variability and of climate feedback mechanisms (IPCC, 2001;Mearns et al, 2004;Christensen and Christensen, 2007;Mayer et al, 2015). Whatever climate models are used, verification of their results under the current climate is needed, because some high-resolution RCMs fail to adequately describe local-scale surface processes (especially in inhomogeneous regions with complex topography) due to the convective parameterization scheme or the characteristics of the GCM they are nested in (Hohenegger et al, 2008, andWillems et al, 2012).…”

Downscaling future precipitation extremes to urban hydrology scales using a spatio-temporal Neyman–Scott weather generator

“…Even though the overall qualitative features of precipitation are reproduced realistically by regional climate models (RCMs) they are not able to capture the very finescale spatio-temporal features of precipitation satisfactorily and yield output that is too spatially correlated (Tebaldi and Knutti, 2007;Gregersen et al, 2013). To overcome this, either dynamic downscaling with climate models has to operate at much finer scales in order to properly describe convective precipitation dynamics (Kendon et al, 2014;Mayer et al, 2015) or further statistical downscaling of the climate model output has to be performed (Olsson and Burlando, 2002;Wood et al, 2004;Cowpertwait, 2006;Molnar and Burlando, 2008;Willems et al, 2012;Sunyer et al, 2012;Arnbjerg-Nielsen et al, 2013). Fine-scale dynamic downscaling is computationally extremely expensive and statistical downscaling is therefore often favoured (Maraun et al, 2010).…”

Evaluating adaptation options for urban flooding based on new high-end emission scenario regional climate model simulations

“…A key input to the revised recommendation is the use of a multi-model ensemble of regional climate projections in Europe from the ENSEMBLES project (van der Linden & Mitchell 2009) and application of 3 different downscaling methods (Sunyer et al 2015). In addition, results based on a high-end scenario are included using a projection of the RCP8.5 scenario (Mayer et al 2015) downscaled by means of a stochastic weather generator (Sørup et al 2015). Based on this ensemble of information, 'mean' and 'high' changes are suggested as a function of the projection horizon and re turn period.…”

“…The focus will be on assessing changes in impacts that can be attributed to differences between a moderate climate change scenario such as an A1B scenario (van der Linden & Mitchell 2009) and high-end scenarios, in cluding a 6°C global warming scenario (Christensen et al 2015, this Special) and the most intense Representative Concentration Pathway (RCP8.5) scenario (Mayer et al 2015).…”