The CMIP project has reached the end of its sixth phase, with a large set of simulations that represent a very large volume of data. The exploitation of all the simulations in impact studies would be extremely costly in computing time and storage. Moreover, these models suffer from several sources of uncertainties (coarse spatial resolution, physical parameterizations, ...) which produce large systematic biases.This study details an approach developed for the selection of a subset of simulations from the CMIP6 multi-model ensemble to assess the impact of climate change on the energy demand in Europe. At a climatic time scale, besides socio-economic factors, energy demand variability and evolution depend mainly on air temperature. The developed process of selection combines two main criteria applied to the daily mean, maximum, and minimum air temperature from all CMIP6 simulations where these variables are available. The first one consists of choosing a subset of models that represents the whole range of possible temperature changes in the future compared to the historical climate. The second criterion considers the skills of the CMIP6 historical simulations over Europe with respect to ERA5 climatology in order to discard the climate simulations with the poorest representation of the present climate. The methodology of selection allows the maximization of the diversity of climate projections among the best-performing models.
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