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

Abstract. Studies on recent climate trends from the Himalayan range are limited, and even completely absent at high elevation (> 5000 m a.s.l.). This study specifically explores the southern slopes of Mt. Everest, analyzing the time series of temperature and precipitation reconstructed from seven stations located between 2660 and 5600 m a.s.l. during 1994–2013, complemented with the data from all existing ground weather stations located on both sides of the mountain range (Koshi Basin) over the same period. Overall we find that the main and most significant increase in temperature is concentrated outside of the monsoon period. Above 5000 m a.s.l. the increasing trend in the time series of minimum temperature (+0.072 °C yr−1) is much stronger than of maximum temperature (+0.009 °C yr−1), while the mean temperature increased by +0.044 °C yr−1. Moreover, we note a substantial liquid precipitation weakening (−9.3 mm yr−1) during the monsoon season. The annual rate of decrease in precipitation at higher elevations is similar to the one at lower elevations on the southern side of the Koshi Basin, but the drier conditions of this remote environment make the fractional loss much more consistent (−47% during the monsoon period). Our results challenge the assumptions on whether temperature or precipitation is the main driver of recent glacier mass changes in the region. The main implications are the following: (1) the negative mass balances of glaciers observed in this region can be more ascribed to a decrease in accumulation (snowfall) than to an increase in surface melting; (2) the melting has only been favoured during winter and spring months and close to the glaciers terminus; (3) a decrease in the probability of snowfall (−10%) has made a significant impact only at glacier ablation zone, but the magnitude of this decrease is distinctly lower than the observed decrease in precipitation; (4) the decrease in accumulation could have caused the observed decrease in glacier flow velocity and the current stagnation of glacier termini, which in turn could have produced more melting under the debris glacier cover, leading to the formation of numerous supraglacial and proglacial lakes that have characterized the region in the last decades.

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.