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Abstract: The study examines climate change scenarios of precipitation extremes over the western, central and part of the eastern Mediterranean region for the late 21st century (2070–99) in an ensemble of high-resolution regional climate model (RCM) simulations from the ENSEMBLES project. Precipitation extremes are considered at a wide range of time scales from hourly to multi-day amounts and in individual seasons (DJF, MAM, JJA, SON). We focus on (1) the dependence of the results on the time scale of precipitation aggregation, (2) seasonal differences, (3) uncertainties of the scenarios related to differences amongst the RCM simulations, and (iv) identification of regions and seasons in which the projected changes in precipitation extremes are particularly large and/or robust in the RCM ensemble. The examined ensemble of RCM simulations captures basic precipitation patterns for the recent climate (1961–90), including seasonal changes. Climate change scenarios for the late 21st century differ substantially for short-term (hourly) and multi-day (5-day and 15-day) precipitation extremes, mainly in the western Mediterranean. Projected increases in short-term extremes exceed those of daily and multi-day extremes, and occur even in regions and seasons in which mean precipitation is projected to decline. This change in the patterns of extreme precipitation may have important hydrological consequences, with increases in the severity of flash floods in a warmer climate in spite of the overall drying projected for the region. However, uncertainty of the scenarios of precipitation extremes related to within-ensemble variability is large. Consistency of the projected changes amongst the RCMs is highest in winter and lowest in summer, and generally it is higher for short-term than multi-day extremes. [Copyright &y& Elsevier]

Abstract: The paper presents a methodology for estimating high quantiles of distributions of daily temperature in a non-stationary context, based on peaks-over-threshold analysis with a time-dependent threshold expressed in terms of regression quantiles. The extreme value models are applied to estimate 20-yr return values of maximum daily temperature over Europe in transient global climate model (GCM) simulations for the 21st century. A comparison of scenarios of changes in the 20-yr return temperatures based on the non-stationary peaks-over-threshold models with conventional stationary models is performed. It is demonstrated that the application of the stationary extreme value models in temperature data from GCM scenarios yields results that may be to a large extent biased, while the non-stationary models lead to spatial patterns that are robust and enable one to detect areas where the projected warming in the tail of the distribution of daily temperatures is largest. The method also allows splitting the projected warming of extremely high quantiles into two parts that reflect change in the location and scale of the distribution of extremes, respectively. Spatial patterns of the two components differ significantly in the examined climate change projections over Europe. [Copyright &y& Elsevier]