Thirteen regional climate model (RCM) integrations from the Prediction of Regional Scenarios and Uncertainties for Defining European Climate change risks and Effects (PRUDENCE) ensemble are used together with extreme value analysis to assess changes to seasonal precipitation extremes in nine UK rainfall regions by 2070-2100 under the SRES A2 emissions scenario. Model weights are based on similarities between observed and modelled UK extreme precipitation calculated for a combination of (1) spatial characteristics: the semi-variogram parameters sill and range, and (2) the discrepancy in the regional median seasonal maxima. These weights are used to combine individual RCM bootstrap samples to provide multi-model ensemble estimates of percent change in the return value magnitudes of regional extremes. The contribution of global climate model (GCM) and RCM combinations to model structural uncertainty is also investigated. The multi-model ensembles project increases across the UK in winter, spring and autumn extreme precipitation; although there is uncertainty in the absolute magnitude of increases, these range from 5 to 30% depending upon region and season. In summer, model predictions span the zero change line, although there is low confidence due to poor model performance. RCM performance is shown to be highly variable; extremes are well simulated in winter and very poorly simulated in summer. The ensemble distributions are wider (projections are more uncertain) for shorter duration extremes (e.g. 1 day) and higher return periods (e.g. 25 year). There are rather limited differences in the weighted and unweighted multi-model ensembles, perhaps a consequence of the lack of model independence between ensemble members. The largest contribution to uncertainty in the multi-model ensembles comes from the lateral boundary conditions used by RCMs included in the ensemble. Therefore, the uncertainty bounds shown here are conservative despite the relatively large number of RCMs contributing to the multi-model ensemble distribution.

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[1] Using the results from multimodel ensembles enables the assessment of model uncertainty in present and future estimates of extremes and the production of probabilities for regional or local-scale change. Six regional climate model (RCM) integrations from the PRUDENCE ensemble are used together with extreme value analysis to assess changes to precipitation extremes over Europe by 2070-2100 under the SRES A2 emissions scenario, investigating the contribution of the formulations of global (GCM) and regional climate models to scenario uncertainty. RCM ability to simulate precipitation extremes is evaluated for a UK case study. RCMs are shown to underestimate 1 day return values but reasonably simulate longer-duration (5 or 10 day) extremes. A multimodel approach by which probabilities can be produced for regional or local-scale change in extremes is then developed. A key result is that all RCMs project increases in the magnitude of short-and long-duration extreme precipitation for most of Europe. Individual model projections vary considerably but are independent of changes in mean precipitation. The magnitude of change is strongly influenced by the driving GCM but moderated by the RCM, which also influences spatial pattern. Therefore, when designing future ensemble experiments (1) the number of GCMs should at least equal the number of RCMs and (2) if spatial pattern is important then integrations from different RCMs should be incorporated. For impact studies, both the resolution and number of models in the ensemble will influence projections of change. The use of a multimodel approach therefore provides more robust estimates.

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