Thomas NOEL, Harilaos Loukos, Dimitri Defrance , Mathieu Vrac , Guillaume Levavasseur

A high-resolution climate projections dataset is obtained by statistically downscaling climate projections from the CMIP5 experiment using the ERA5 reanalyses from the Copernicus Climate Change service. The dataset is global has a spatial resolution of 0.25°x 0.25°, comprises 21 climate models and includes 5 surface daily variables: air temperature (mean, minimum, and maximum), precipitation, and mean near-surface wind speed. Two greenhouse gas emissions scenarios are available: one with mitigation policy (RCP4.5) and one without mitigation (RCP8.5). The downscaling method is a Quantile mapping method (QM) called the Cumulative Distribution Function transform (CDF-t) method that was first used for wind values and is now referenced in dozens of peer-reviewed publications. The data processing includes quality control of meta data according to the climate modelling community standards and value checking for outlier detection.