A recently launched project under the auspices of the World Climate Research Program's (WCRP) Coordinated Regional Downscaling Experiments Flagship Pilot Studies program (CORDEX-FPS) is presented. This initiative aims to build first-ofits-kind ensemble climate experiments of convection permitting models to investigate present and future convective processes and related extremes over Europe and the Mediterranean. In this manuscript the rationale, scientific aims and approaches are presented along with some preliminary results from the testing phase of the project. Three test cases were selected in order to obtain a first look at the ensemble performance. The test cases covered a summertime extreme precipitation event over Austria, a fall Foehn event over the Swiss Alps and an intensively documented fall event along the Mediterranean coast. The test cases were run in both "weather-like" (WL, initialized just before the event in question) and "climate" (CM, initialized 1 month before the event) modes. Ensembles of 18-21 members, representing six different modeling systems with different physics and modelling chain options, was generated for the test cases (27 modeling teams have committed to perform the longer climate simulations). Results indicate that, when run in WL mode, the ensemble captures all three events quite well with ensemble correlation skill scores of 0.67, 0.82 and 0.91. They suggest that the more the event is driven by large-scale conditions, the closer the agreement between the ensemble members. Even in climate mode the large-scale driven events over the Swiss Alps and the Mediterranean coasts are still captured (ensemble correlation skill scores of 0.90 and 0.62, respectively), but the inter-model spread increases as expected. In the case over Mediterranean the effects of local-scale interactions between flow and orography and land-ocean contrasts are readily apparent. However, there is a much larger, though not surprising, increase in the spread for the Austrian event, which was weakly forced by the large-scale flow. Though the ensemble correlation skill score is still quite high (0.80). The preliminary results illustrate both the promise and the challenges that convection permitting modeling faces and make a strong argument for an ensemble-based approach to investigating high impact convective processes. Keywords Convection-permitting • Ensemble models • Climate applicationsThis paper is a contribution to the special issue on Advances in Convection-Permitting Climate Modeling, consisting of papers that focus on the evaluation, climate change assessment, and feedback processes in kilometer-scale simulations and observations. The special issue is coordinated by

Here we present the first multi-model ensemble of regional climate simulations at kilometer-scale horizontal grid spacing over a decade long period. A total of 23 simulations run with a horizontal grid spacing of $$\sim $$ ∼ 3 km, driven by ERA-Interim reanalysis, and performed by 22 European research groups are analysed. Six different regional climate models (RCMs) are represented in the ensemble. The simulations are compared against available high-resolution precipitation observations and coarse resolution ($$\sim $$ ∼ 12 km) RCMs with parameterized convection. The model simulations and observations are compared with respect to mean precipitation, precipitation intensity and frequency, and heavy precipitation on daily and hourly timescales in different seasons. The results show that kilometer-scale models produce a more realistic representation of precipitation than the coarse resolution RCMs. The most significant improvements are found for heavy precipitation and precipitation frequency on both daily and hourly time scales in the summer season. In general, kilometer-scale models tend to produce more intense precipitation and reduced wet-hour frequency compared to coarse resolution models. On average, the multi-model mean shows a reduction of bias from $$\sim \,$$ ∼  −40% at 12 km to $$\sim \,$$ ∼  −3% at 3 km for heavy hourly precipitation in summer. Furthermore, the uncertainty ranges i.e. the variability between the models for wet hour frequency is reduced by half with the use of kilometer-scale models. Although differences between the model simulations at the kilometer-scale and observations still exist, it is evident that these simulations are superior to the coarse-resolution RCM simulations in the representing precipitation in the present-day climate, and thus offer a promising way forward for investigations of climate and climate change at local to regional scales.

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.

The accurate prediction of Mediterranean tropical-like cyclones, or medicanes, is an important challenge for numerical weather prediction models due to their significant adverse impact on the environment, life, and property. The aim of this study is to investigate the sensitivity of an intense medicane, which formed south of Sicily on 7 November 2014, to the microphysical, cumulus, and boundary/surface layer schemes. The non-hydrostatic Weather Research and Forecasting model (version 3.7.1) is employed. A symmetric cyclone with a deep warm core, corresponding to a medicane, develops in all of the experiments, except for the one with the Thompson microphysics. There is a significant sensitivity of different aspects of the simulated medicane to the physical parameterizations. Its intensity is mainly influenced by the boundary/surface layer scheme, while its track is mainly influenced by the representation of cumulus convection, and its duration is mainly influenced by microphysical parameterization. The modification of the drag coefficient and the roughness lengths of heat and moisture seems to improve its intensity, track, and duration. The parameterization of shallow convection, with explicitly resolved deep convection, results in a weaker medicane with a shorter lifetime. An optimum combination of physical parameterizations in order to simulate all of the characteristics of the medicane does not seem to exist.

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