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The added value of using regional climate models (RCMs) to downscale data from general circulation models (GCMs) has often been questioned and researched. Although several studies have used different methods to identify (and in some cases quantify) the added value, there is still a need to find a general metric that quantifies the added value of any variable. This paper builds on past studies to propose a new metric of added value in the simulation of present-day climate which measures the difference in the probability density functions (PDFs) at each grid-cell between a model and an observation source, and then compares the results of the RCM and GCM in order to spatially compute the added value index. The same method is also adapted to quantify the climate change downscaling signal in a way that is consistent with the present-day metric. These new metrics are tested on the daily precipitation output from the EURO-CORDEX and CORDEX-CORE projection ensembles and reveal an overall positive added value of RCMs, especially at the tail-end of the distribution. Higher added value is obtained in areas of complex topography and coast-lines, as well as in tropical regions. Areas with large added value in present-day climate are consistent with areas of significant climate change downscaling signal in the RCP 8.5 far future simulations, and when the analysis is repeated at a low-resolution. The use of different resolution observations shows that the added value tends to decrease when models are compared to low-resolution observation datasets.

We here present a climate study on Heavy Precipitation Events (HPEs). To this aim we use an ensemble of convection-permitting regional climate models on a domain that covers the alps and large parts of the Mediterranean. These HPEs are generally meso-scale convective systems, which often are related to a landfall or orographic blocking. For society they are of major interest as they may damage infrastructure and threaten lives through flash floods and strong winds. From the models' output of precipitation we identify HPEs by applying an well-established clustering and tracking algorithm (MET MTD).Our study is organized into an evaluation and a climate study part. We evaluate the models by comparison of the evaluation scenario, driven by reanalysis data, against observations. In order to evaluate the tracking algorithm we analyse three specific historic events, occurring in southern France, central Italy and Germany. Eventually we investigate the climate response by comparison of the far future projection (2090-2100) under the rcp85 forcing against the historical scenario (1996-2006).In regards of the model evaluation we find that the annual cycle is very well captured by model ensemble, although the models overestimate HPEs over orography and underestimated HPEs over flatter terrain.Concerning the climate response our main result highlights that precipitation associated with HPEs is increasing in the far future, even though total annual precipitation is decreasing. Overall more HPEs occur in the far future, but only for an extended winter season (October to April), while for months May to September the occurrence of HPEs is decreasing. This behaviour motivates us to investigate the annual cycle of HPEs in greater detail.

The CORDEX-CORE initiative was developed with the aim of producing homogeneous regional climate model (RCM) projections over domains world wide. In its first phase, two RCMs were run at 0.22° resolution downscaling 3 global climate models (GCMs) from the CMIP5 program for 9 CORDEX domains and two climate scenarios, the RCP2.6 and RCP8.5. The CORDEX-CORE simulations along with the CMIP5 GCM ensemble and the most recently produced CMIP6 GCM ensemble are analyzed, with focus on several temperature, heat, wet and dry hazard indicators for present day and mid-century and far future time slices. The CORDEX-CORE ensemble shows a better performance than the driving GCMs for several hazard indices due to its higher spatial resolution. For the far future time slice the 3 ensembles project an increase in all temperature and heat indices analyzed under the RCP8.5 scenario. The largest increases are always shown by the CMIP6 ensemble, except for Tx > 35 °C, for which the CORDEX-CORE projects higher warming. Extreme wet and flood prone maxima are projected to increase by the RCM ensemble over the la Plata basin in South America, the Congo basin in Africa, east North America, north east Europe, India and Indochina, regions where a better performance is obtained, whereas the GCM ensembles show small or negligible signals. Compound hazard hotspots based on heat, drought and wet indicators are detected in each continent worldwide in region like Central America, the Amazon, the Mediterranean, South Africa and Australia, where a linear relation is shown between the heatwave and drought change signal, and region like Arabian peninsula, the central and south east Africa region (SEAF), the north west America (NWN), south east Asia, India, China and central and northern European regions (WCE, NEU) where the same linear relation is found for extreme precipitation and HW increases. Although still limited, the CORDEX-CORE initiative was able to produce high resolution climate projections with almost global coverage and can provide an important resource for impact assessment and climate service activities.

The new Coordinated Output for Regional Evaluations (CORDEX-CORE) ensemble provides high-resolution, consistent regional climate change projections for the major inhabited areas of the world. It serves as a solid scientific basis for further research related to vulnerability, impact, adaptation and climate services in addition to existing CORDEX simulations. The aim of this study is to investigate and document the climate change information provided by the CORDEX-CORE simulation ensemble, as a part of the World Climate Research Programme (WCRP) CORDEX community. An overview of the annual and monthly mean climate change information in selected regions in different CORDEX domains is presented for temperature and precipitation, providing the foundation for detailed follow-up studies and applications. Initially, two regional climate models (RCMs), REMO and RegCM were used to downscale global climate model output. The driving simulations by AR5 global climate models (AR5-GCMs) were selected to cover the spread of high, medium, and low equilibrium climate sensitivity at a global scale. The CORDEX-CORE ensemble has doubled the spatial resolution compared to the previously existing CORDEX simulations in most of the regions (25$$\,\mathrm {km}$$km(0.22$$^{\circ }$$∘) versus 50$$\,\mathrm {km}$$km(0.44$$^{\circ }$$∘)) leading to a potentially improved representation of, e.g., physical processes in the RCMs. The analysis focuses on changes in the IPCC physical climate reference regions. The results show a general reasonable representation of the spread of the temperature and precipitation climate change signals of the AR5-GCMs by the CORDEX-CORE simulations in the investigated regions in all CORDEX domains by mostly covering the AR5 interquartile range of climate change signals. The simulated CORDEX-CORE monthly climate change signals mostly follow the AR5-GCMs, although for specific regions they show a different change in the course of the year compared to the AR5-GCMs, especially for RCP8.5, which needs to be investigated further in region specific process studies.

N. Ban et al., 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 ∼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 (∼ 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 ∼ −40% at 12 km to ∼ −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., Open access funding provided by University of Innsbruck and Medical University of Innsbruck., The ETH team, MZ, CNRM IPSL, ICTP, SMHI, Met-Office, DMI, CMCC, HZG, KNMI acknowledge funding from the HORIZON 2020 EUCP (European Climate Prediction System) project (https://www.eucp-project.eu, grant agreement No. 776613). AL-G acknowledges support by the Spanish government through grant BES-2016-078158 and MINECO/FEDER co-funded project MULTI-SDM (CGL2015-66583-R).

We present a multi-model ensemble of regional climate model scenario simulations run at scales allowing for explicit treatment of convective processes (2-3km) over historical and end of century time slices, providing an overview of future precipitation changes over the Alpine domain within the convection-permitting CORDEX-FPS initiative. The 12 simulations of the ensemble have been performed by different research groups around Europe. The simulations are compared with high resolution observations to assess the performance over the historical period and the ensemble of 12 to 25 km resolution driving models is used as a benchmark.An improvement of the representation of fine scale details of the analyzed fields on a seasonal scale is found, as well as of the onset and peak of the summer diurnal convection. An enhancement of the projected patterns of change and modifications of its sign for the daily precipitation intensity and heavy precipitation over some regions are found with respect to coarse resolution ensemble. A change of the amplitude of the diurnal cycle for precipitation intensity and frequency is also shown, as well also a larger positive change for high to extreme events for daily and hourly precipitation distributions. The results are challenging and promising for further assessment of the local impacts of climate change.

This 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., 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-of-its-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., IG and LS have been supported by the Croatian Science Foundation (HrZZ) project CARE (no. 2831). JF acknowledges support by the Spanish R + D programme through MINECO/FEDER co-funded project INSIGNIA (CGL2016-79210-R). AL-G is supported by the Spanish government though grant BES-2016-078158 and MINECO/FEDER co-funded project MULTI-SDM (CGL2015-66583-R). JM and KW-S gratefully acknowledge the support by the German Science Foundation (DFG) through project FOR 1695. DM, MP, and HT gratefully acknowledge the support received via the Austrian Science Fund (FWF) project NHCM-2 (no. P24758-N29) and the projects HighEnd:Extremes and EASICLIM, funded by the Austrian Climate Research Programme (ACRP) of the Klima- und Energiefonds (nos. KR13AC6K10981 and KR16AC0K13160, respectively). SS and TL acknowledge the support of NOTUR project no. NN9280K and the Research Council of Norway and its basic institute support of their strategic project on Climate Services. RMC and PMMS gratefully acknowledge the support of the SOLAR project (PTDC/GEOMET/7078/2014) financed by the Portuguese Foundation for Science and Technology. EJ Kendon gratefully acknowledges funding from the Joint Department of Energy and Climate Change (DECC) and Department for Environment Food and Rural Affairs (Defra) Met Office Hadley Centre Climate Programme (GA01101). S. Khodayar research is supported by the Bundesministerium für Bildung und Forschung (BMBF; German Federal Ministry of Education and Research). Support of Ministry of Education, Youth and Sports of the Czech Republic for funding the participation in Euro-CORDEX activities via the scheme INTER-TRANSFER under the Grant no. LTT17007. Funding from the Research Council of Norway through the SUPER (Grant no. 250573) and HYPRE (Grant no. 243942) projects.

High Impact Weather (HIW), particularly Heavy Precipitation Events (HPE), are common phenomena affecting the Western Mediterranean (WMED) especially in the fall period. Understanding and evaluating the capability to adequately represent such events in model simulations is one of the main goals of the Hydrological cycle in the Mediterranean Experiment (HyMeX) and the main motivation of this investigation. In order to gain a better knowledge of the model representation of HPE and related processes we perform a seamless multi-model intercomparison at the event scale. Limited area model runs (grid spacing from 2 to 20 km) at weather and climate timescales are considered, four with parameterized and five with explicit convection. The performance of the nine models is compared by analysing precipitation, as well as convection-relevant parameters. An Intensive Observation Period (IOP12) from the HyMeX-SOP1 (Special Observation Period) is used to illustrate the results. During IOP12, HPE affected the north-western Mediterranean region, from Spain to Italy, as a consequence of Mesoscale Convective Systems (MCSs) which initiated and intensified in the area of investigation. Results show that: (i) the timing of the maximum precipitation seems to be linked with the representation of large-scale conditions rather than differences among models, (ii) Convection Permitting Models (CPMs) exhibit differences among each other, but better represent the short-intense convective events. All four convection-parameterised models produce a large number of weak and long-lasting events. Regional Climate Models (RCMs) capture the occurrence of the event but produce notably lower precipitation amount and hourly intensities than CPMs and Numerical Weather Prediction (NWP) models with parameterized convection. (iii) These differences do not seem to come from mean moisture or Convective Available Potential Energy (CAPE) which are in the same range for all models, but rather from differences in the variability and vertical distribution of moisture and the triggering of deep convection.

The Special Observation Period (SOP1), part of the HyMeX campaign (Hydrological cycle in the Mediterranean Experiments, 5 September–6 November 2012), was dedicated to heavy precipitation events and flash floods in the western Mediterranean, and three Italian hydro-meteorological monitoring sites were identified: Liguria–Tuscany, northeastern Italy and central Italy. The extraordinary deployment of advanced instrumentation, including instrumented aircrafts, and the use of several different operational weather forecast models, including hydrological models and marine models, allowed an unprecedented monitoring and analysis of high-impact weather events around the Italian hydro-meteorological sites. This activity has seen strong collaboration between the Italian scientific and operational communities. In this paper an overview of the Italian organization during SOP1 is provided, and selected Intensive Observation Periods (IOPs) are described. A significant event for each Italian target area is chosen for this analysis: IOP2 (12–13 September 2012) in northeastern Italy, IOP13 (15–16 October 2012) in central Italy and IOP19 (3–5 November 2012) in Liguria and Tuscany. For each IOP the meteorological characteristics, together with special observations and weather forecasts, are analyzed with the aim of highlighting strengths and weaknesses of the forecast modeling systems, including the hydrological impacts. The usefulness of having different weather forecast operational chains characterized by different numerical weather prediction models and/or different model set up or initial conditions is finally shown for one of the events (IOP19).

This paper presents the first multi-model ensemble of 10-year, “convection-permitting” kilometer- scale regional climate model (RCM) scenario simulations downscaled from selected CMIP5 GCM projections for historical and end of century time slices. The technique is to first downscale the CMIP5 GCM projections to an intermediate 12–15 km resolution grid using RCMs, and then use these fields to downscale further to the kilometer scale. The aim of the paper is to provide an overview of the representation of the precipitation characteristics and their projected changes over the greater Alpine domain within a Coordinated Regional Climate Downscaling Experiment Flagship Pilot Study and the European Climate Prediction system project, tasked with investigating convective processes at the kilometer scale. An ensemble of 12 simulations performed by different research groups around Europe is analyzed. The simulations are evaluated through comparison with high resolution observations while the complementary ensemble of 12 km resolution driving models is used as a benchmark to evaluate the added value of the convection-permitting ensemble. The results show that the kilometer-scale ensemble is able to improve the representation of fine scale details of mean daily, wet-day/hour frequency, wet- day/hour intensity and heavy precipitation on a seasonal scale, reducing uncertainty over some regions. It also improves the representation of the summer diurnal cycle, showing more realistic onset and peak of convection. The kilometer-scale ensemble refines and enhances the projected patterns of change from the coarser resolution simulations and even modifies the sign of the precipitation intensity change and heavy precipitation over some regions. The convection permitting simulations also show larger changes for all indices over the diurnal cycle, also suggesting a change in the duration of convection over some regions. A larger positive change of frequency of heavy to severe precipitation is found. The results are encouraging towards the use of convection-permitting model ensembles to produce robust assessments of the local impacts of future climate change.