The European CORDEX (EURO-CORDEX) initiative is a large voluntary effort that seeks to advance regional climate and Earth system science in Europe. As part of the World Climate Research Programme (WCRP) - Coordinated Regional Downscaling Experiment (CORDEX), it shares the broader goals of providing a model evaluation and climate projection framework and improving communication with both the General Circulation Model (GCM) and climate data user communities. EURO-CORDEX oversees the design and coordination of ongoing ensembles of regional climate projections of unprecedented size and resolution (0.11° EUR-11 and 0.44° EUR-44 domains). Additionally, the inclusion of empirical-statistical downscaling allows investigation of much larger multi-model ensembles. These complementary approaches provide a foundation for scientific studies within the climate research community and others. The value of the EURO-CORDEX ensemble is shown via numerous peer-reviewed studies and its use in the development of climate services. Evaluations of the EUR-44 and EUR-11 ensembles also show the benefits of higher resolution. However, significant challenges remain. To further advance scientific understanding, two flagship pilot studies (FPS) were initiated. The first investigates local-regional phenomena at convection-permitting scales over central Europe and the Mediterranean in collaboration with the Med-CORDEX community. The second investigates the impacts of land cover changes on European climate across spatial and temporal scales. Over the coming years, the EURO-CORDEX community looks forward to closer collaboration with other communities, new advances, supporting international initiatives such as the IPCC reports, and continuing to provide the basis for research on regional climate impacts and adaptation in Europe.

Surface air temperatures modelled by ERA‐40, ERA‐Interim and (NCEP)/(NCAR) reanalysis (NNRP‐1) have been compared with observations at 11 synoptic stations in Ireland over the period 1989–2001. The three reanalysis datasets show good agreement with the observed data and with each other. Slopes of the least‐squares line to scatter plots of reanalysis data versus observational data show small differences between the three reanalyses, with ERA‐40, ERA‐Interim and NNRP‐1 slopes ranging between (0.79–1.06) ± 0.01, (0.83–1.01) ± 0.01 and (0.76–0.98) ± 0.01, respectively. Summary statistics and the monthly mean temperatures over the 1989–2001 period showed that the reanalyses were significantly warmer in winter than the observations, which resulted in best fit lines with slopes consistently less than unity. ERA‐Interim was slightly better than both ERA‐40 and NNRP‐1 at modelling winter temperatures and it had higher correlation coefficients with the observations. All three reanalyses use different grid sizes and types. Subsequent regridding of the ERA‐Interim and NNRP‐1 data to the ERA‐40 grid showed that the grid difference had no significant influence on the results. Comparison of ERA‐Interim and NNRP‐1 data with the air temperatures at four marine buoys around the Irish coast for the period 2001–2005 showed that the reanalyses modelled colder winter temperatures than the observations; resulting in best fit lines with slopes consistently greater than unity. The slopes for NNRP‐1 and ERA‐Interim at the marine buoys, respectively, averaged 1.09 ± 0.04 and 1.10 ± 0.05 while the slopes at the four land stations over the same period averaged 0.87 ± 0.02 and 0.89 ± 0.02, respectively. We believe that this pattern results from the difference in the treatment of land and sea surfaces in the reanalysis datasets. Copyright © 2010 Royal Meteorological Society

The occurrence of environmental conditions favorable for severe convective storms was assessed in an ensemble of 14 regional climate models covering Europe and the Mediterranean with a horizontal grid spacing of 0.44°. These conditions included the collocated presence of latent instability and strong deep-layer (surface to 500 hPa) wind shear, which is conducive to the severe and well-organized convective storms. The occurrence of precipitation in the models was used as a proxy for convective initiation. Two climate scenarios (RCP4.5 and RCP8.5) were investigated by comparing two future periods (2021–50 and 2071–2100) to a historical period (1971–2000) for each of these scenarios. The ensemble simulates a robust increase (change larger than twice the ensemble sample standard deviation) in the frequency of occurrence of unstable environments (lifted index ≤ −2) across central and south-central Europe in the RCP8.5 scenario in the late twenty-first century. This increase coincides with the increase in lower-tropospheric moisture. Smaller, less robust changes were found until midcentury in the RCP8.5 scenario and in the RCP4.5 scenario. Changes in the frequency of situations with strong (≥15 m s⁻¹) deep-layer shear were found to be small and not robust, except across far northern Europe, where a decrease in shear is projected. By the end of the century, the simultaneous occurrence of latent instability, strong deep-layer shear, and model precipitation is simulated to increase by up to 100% across central and eastern Europe in the RCP8.5 and by 30%–50% in the RCP4.5 scenario. Until midcentury, increases in the 10%–25% range are forecast for most regions. A large intermodel variability is present in the ensemble and is primarily due to the uncertainties in the frequency of the occurrence of unstable environments.

The Weather Research and Forecasting model (WRF) is used to downscale interim ECMWF Re-Analysis (ERA-Interim) data for the climate over Europe for the period 1990–95 with grid spacing of 0.44° for 12 combinations of physical parameterizations. Two longwave radiation schemes, two land surface models (LSMs), two microphysics schemes, and two planetary boundary layer (PBL) schemes have been investigated while the remaining physics schemes were unchanged. WRF simulations are compared with Ensemble-Based Predictions of Climate Changes and their Impacts (ENSEMBLES) observations gridded dataset (E-OBS) for surface air temperatures (T2), precipitation, and mean sea level pressure (MSLP) in eight subregions within the model domain to assess the performance of the different parameterizations on widely varying regional climates. This work shows that T2 is modeled well by WRF with high correlation coefficients (0.8 < R < 0.95) and biases less than 4°C. T2 shows greatest sensitivity to land surface models, some sensitivity to longwave radiation schemes, and less sensitivity to microphysics and PBL schemes. Precipitation is not well modeled by WRF with low correlation coefficients (0.1 < R < 0.3) and high root-mean-square differences (RMSDs; 8–9 mm day−1). Precipitation shows sensitivity to LSMs in summer. No significant bias has been observed in the MSLP modeled by WRF. Correlation coefficients are typically in the range 0.7 < R < 0.8 while RMSDs are in the range 6–10 hPa. MSLP output is sensitive to longwave radiation scheme in summer but is relatively insensitive to either microphysics or the choice of LSM. The optimum combination of parameterizations for all three state variables examined is strongly dependent on subregion and demonstrates the need to carefully select parameterization combinations when attempting to use WRF as a regional climate model.

Interactions between the land surface and the atmosphere play a fundamental role in the weather and climate system. Here we present a comparison of summertime land‐atmosphere coupling strength found in a subset of the ERA‐Interim‐driven European domain Coordinated Regional Climate Downscaling Experiment (EURO‐CORDEX) model ensemble (1989–2008). Most of the regional climate models (RCMs) reproduce the overall soil moisture interannual variability, spatial patterns, and annual cycles of surface exchange fluxes for the different European climate zones suggested by the observational Global Land Evaporation Amsterdam Model (GLEAM) and FLUXNET data sets. However, some RCMs differ substantially from FLUXNET observations for some regions. The coupling strength is quantified by the correlation between the surface sensible and the latent heat flux, and by the correlation between the latent heat flux and 2 m temperature. The first correlation is compared to its estimate from the few available long‐term European high‐quality FLUXNET observations, and the latter to results from gridded GLEAM data. The RCM simulations agree with both observational datasets in the large‐scale pattern characterized by strong coupling in southern Europe and weak coupling in northern Europe. However, in the transition zone from strong to weak coupling covering large parts of central Europe many of the RCMs tend to overestimate the coupling strength in comparison to both FLUXNET and GLEAM. The RCM ensemble spread is caused primarily by the different land surface models applied, and by the model‐specific weather conditions resulting from different atmospheric parameterizations.