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Recent winter seasons have evidenced that global warming does not exclude the occurrence of exceptionally cold and/or snowy episodes in the Northern mid-latitudes. The expected rarefaction of such events is likely to exacerbate both their societal and environmental impacts. This paper therefore aims to evaluate model uncertainties underlying the fate of wintertime cold extremes over Europe. Understanding why climate models (1) still show deficiencies in simulating present-day features and (2) differ in their responses under future scenarios for the twentyfirst century indeed constitutes a crucial challenge. Here we propose a weather-regime approach in order to separate the contributions of large-scale circulation and non-dynamical processes to biases or changes in the simulated mean and extreme temperatures. We illustrate our methodology from the wintertime occurrence of extremely cold days in idealized atmosphere-only experiments performed with two of the CMIP5 climate models (CNRM-CM5 and IPSL-CM5A-LR). First we find that most of the present-day temperature biases are due to systematic errors in non-dynamical processes, while the main features of the large-scale dynamics are well captured in such experiments driven by observed sea-surface temperatures, with the exception of a generalized underestimation of blocking episodes. Then we show that uncertainties associated with changes in large-scale circulation modulate the depletion in cold extremes under an idealized scenario for the late twentyfirst century. These preliminary results suggest that the original methodology proposed in this paper can be helpful for understanding spreads of larger model-ensembles when simulating the response of temperature extremes to climate change.