The Regional Climate Modeling system (RegCM) has undergone a significant evolution over the years, leading for example to the widely used versions RegCM4 and RegCM4-NH. In response to the demand for higher resolution, a new version of the system has been developed, RegCM5, incorporating the non-hydrostatic dynamical core of the MOLOCH weather prediction model. In this paper we assess the RegCM5's performance for 9 CORDEX-CORE domains, including a pan-European domain at convection-permitting resolution. We find temperature biases generally in the range of −2 to 2 °C, with a larger positive bias in the northernmost regions of North America and Asia during winter, linked to cloud water overestimation. There are cold biases over Central Asia and the Tibetan Plateau, possibly due to sparse station coverage. The model exhibits a prevailing cold bias in maximum temperature and warm bias in minimum temperature, associated with a systematic overestimation of lower-level cloud fraction, especially in winter. Taylor diagrams indicate a high spatial temperature pattern correlation with ERA5 and CRU data, except in South America and the Caribbean region. The precipitation evaluation shows an overestimation in South America, East Asia, and Africa. RegCM5 improves the daily precipitation distribution compared to RegCM4, particularly at high intensities. The analysis of wind fields confirms the model's ability to simulate monsoon circulations. The assessment of tropical cyclone tracks highlights a strong sensitivity to the tracking algorithms, thus necessitating a careful model interpretation. Over the European region, the convection permitting simulations especially improve the diurnal cycle of precipitation and the hourly precipitation intensities.

Similarly to weather forecasting techniques, climate projections also aim to achieve very high spatial and temporal resolutions, which are needed both as inputs to impact models and to perform reliable risk assessment studies. This is all the more true for the Mediterranean region and the Italian territory in particular, whose heterogeneous and complex morphology do affect the local climate (highly sensitive to global warming), making this area particularly vulnerable to hydrogeological risks, such as heavy rainfall, landslides and flooding with serious losses of both human lives and economic. We present the results of downscaling CMIP6 global climate projections to local scales for the Mediterranean and Italian regions, aiming to produce high-resolution climate information for assessing climate change signals, with a particular focus on small-scale phenomena and extreme events. We performed hindcast (i.e. ERA5-driven) and historical simulations (driven by the MPI-ESM1-2-HR model) to simulate the present (1980-2014) and future (2014-2100) climate under three different emission scenarios (SSP1-2.6, SSP2-4.5, SSP5-8.5). For each experiment, we used a double nesting approach to downscale global data first to a regional domain, covering the whole of Europe (EURO-CORDEX domain) with a spatial resolution of 15 km, and subsequently to a fine spatial scale domain centered over Italy and the north-western Mediterranean with a resolution of 5 km, (i.e. close to the convection permitting limit resolution). We explore the effects of pushing the resolution to km-scale while still falling within the so-called “gray zone” (5-10 km), where deep convection can still be insufficiently resolved and a parameterization of the deep convection is still needed to fully represent it. We present the analysis of the most relevant Essential Climate Variables (ECVs), and the statistics of extreme events for both the current climate and for end of the century scenarios. Results highlight that the gray-zone model in the configuration here implemented mimics the behavior of a convection permitting model and improves the representation of the mean precipitation field over the entire domain. This improvement is also detectable for heavy precipitation, represented through high percentile of daily precipitation (p95 – p99). We show the multi-scenario projection of the climate signal for both the simulations on the common domain.This study was carried out within: RETURN Extended Partnership and received funding from the European Union Next-GenerationEU (National Recovery and Resilience Plan – NRRP, Mission 4, Component 2, Investment 1.3 – D.D. 1243 2/8/2022, PE0000005);ICSC Italian Research Center on High-Performance Computing, Big Data and Quantum Computing and received funding from the European Union Next-GenerationEU (National Recovery and Resilience Plan – NRRP, Mission 4, Component 2, Investment 1.4 – D.D: 3138 16/12/2021, CN00000013)

Detection and attribution of anthropogenic influence on extreme events has always been one of the focuses of climate research. A number of studies have been undertaken that employed different approaches (such as the risk-based, Boulder, and circulation-based ones) for attributing individual extreme events of various types over the globe. While many of these extreme events are attributable to anthropogenic or natural factors, some still remain inconclusive. To this end, a super attribution framework is proposed, in which multiple extreme events occurring in one region within a predefined timeframe are considered as a whole instead of individually. The rationale is that climate change may influence large-scale circulation over a region, which subsequently alters the frequency of extreme events in multiple locations in this area. Specifically, the supervariable is proposed to characterize how severely a region is affected by extreme precipitation in terms of area. It is defined as the fraction of area in a region that experiences extreme precipitation of over 99.9th percentile in each day. The trends in the supervariable in the 20 Italian regions are examined. For regions with positive but not significant trends, there could be an anthropogenic signal present, but it could be too weak to be detected. Therefore, regions with positive trends are selected, and a super attribution is undertaken on them simultaneously. It is accomplished by calculating the combined supervariable, which is obtained by pooling the stations/grids of the selected regions together. Simultaneous events that occur in the autumn of each year are then considered. The results show that a statistically significant increasing trend can be identified in the combined supervariable for the selected regions, which suggests an increase in the area affected by extreme precipitation. In parallel to the statistical analysis, dynamical attribution is also carried out using the analog method, and the type of pattern that is both significantly influenced by climate change and associated with significant increases in precipitation is identified.

Northern Italy is an area located in the northern part of the Mediterranean region where several factors make the modeling of its climate dynamics particularly challenging. The area is characterized by significant environmental gradients due to the complexity and high orography of the Alpine arc surrounding the relatively flat area of the Po Valley, while strong air-sea interactions and deep water formation processes in the northern Adriatic Sea are associated with Bora wind episodes flowing over the basin. Moreover, the peculiar West-East oriented topography of the region drives the formation of a complex river network including the Po river, which is one of the major freshwater sources of the Mediterranean Sea. Here we assess the performances of a state-of-the-art convection-permitting configuration of the Regional Earth System Model RegCM-ES specifically developed for the northern Italy region. The modeling tool components are : (i) RegCM5 with an horizontal resolution of 3 km and 50 vertical levels for the atmosphere, (ii) MITgcm with an horizontal resolution of approximately 700 m and 59 vertical levels (non hydrostatic) for the ocean and (iii) CHyM with an horizontal resolution of approximately 1 km for the rivers.Model performances have been evaluated against observations and reanalysis datasets (available for the region) in a numerical experiment driven at the boundaries by ERA5 for the atmosphere and by the Copernicus Marine Service (CMS) reanalysis for the ocean. The model well captures the spatial gradients and mean values of land and seawater temperature, precipitation and sea surface salinity. Still some deficiencies are observed such as a warm bias in summer over the western part of the Po Valley and an overestimation of precipitation over the Alps, although the latter is likely linked to the poor coverage of high altitude measurement stations in the area. This configuration will be adopted in the future to produce high resolution climate projections for the region.

Abstract. We present the results of downscaling CMIP6 global climate projections to local scales for the Mediterranean and Italian regions, aiming to produce high-resolution climate information for the assessment of climate change signals, with a focus on precipitation extreme events. We performed hindcast (i.e. ERA5-driven) and historical simulations (driven by the MPI-ESM1-2-HR model) to simulate the present (1980–2014) and future (2015–2100) climate under three different emission scenarios (SSP1-2.6, SSP2-4.5, SSP5-8.5). For each experiment, a double nesting approach is adopted to dynamically downscale global data to the regional domain of interest, firstly over the Europe (EURO) CORDEX domain, at a spatial resolution of 15 km, and then further refined (second nesting) over Italy and north-western Mediterranean, at a resolution of 5 km, i.e. in the so-called gray-zone (5–10 km), close to the convection permitting (CP) limit. Besides validating the experimental protocol, this work potentially questions the need for climate simulations to always resort to deep-convection parameterizations when spatial refinement is increased up to the limit of the CP scale, yet convective processes are still not explicitly resolved. Analyses of the most relevant Essential Climate Variables (ECVs) are presented, with a focus on the spatial distribution of precipitation, its probability density function, and the statistics of extreme events, for both current climate and far-end scenarios. By the end of the century for all the scenarios and seasons there is a projected general warming along with an intensification of the hydrological cycle over most of the continental EU and mean precipitation reduction over the Mediterranean region accompanied, over Italian Peninsula, by a strong increase in the intensity of extreme precipitation events, particularly relevant for the SSP5-8.5 scenario during autumn.

Abstract Taking advantage of a large ensemble of Convection Permitting‐Regional Climate Models on a pan‐Alpine domain and of an object‐oriented dedicated analysis, this study aims to investigate future changes in high‐impact fall Mediterranean Heavy Precipitation Events at high warming levels. We identify a robust multi‐model agreement for an increased frequency from central Italy to the northern Balkans combined with a substantial extension of the affected areas, for a dominant influence of the driving Global Climate Models for projecting changes in the frequency, and for an increase in intensity, area, volume and severity over the French Mediterranean. However, large quantitative uncertainties persist despite the use of convection‐permitting models, with no clear agreement in frequency changes over southeastern France and a large range of plausible changes in events' properties, including for the most intense events. Model diversity and international coordination are still needed to provide policy‐relevant climate information regarding precipitation extremes.

The Regional Climate Modeling system (RegCM) has undergone a significant evolution over the years, leading for example to the widely used versions RegCM4 and RegCM4-NH. In response to the demand for higher resolution, a new version of the system has been developed, RegCM5, incorporating the non-hydrostatic dynamical core of the MOLOCH weather prediction model. In this paper we assess the RegCM5’s performance for 5 CORDEX-CORE domains, including a pan-European domain at convection-permitting resolution.We find temperature biases generally in the range of -2 to 2 degrees Celsius, higher in the northernmost regions of North America and Asia during winter, linked to cloud water overestimation. Central Asia and the Tibetan Plateau show cold biases, possibly due to sparse station coverage. The model exhibits a prevailing cold bias in maximum temperature and warm bias in minimum temperature, associated with a systematic overestimation of lower-level cloud fraction, especially in winter.Taylor diagrams indicate a high spatial temperature pattern correlation with ERA5 and CRU data, except in South America and the Caribbean region. The precipitation evaluation shows an overestimation in South America, East Asia, and Africa. RegCM5 improves the daily precipitation distribution compared to RegCM4, particularly at high intensities. The analysis of wind fields confirms the model’s ability to simulate monsoon circulations. The assessment of tropical cyclone tracks highlights a strong sensitivity to the tracking algorithms, thus necessitating a careful model interpretation.Over the European region, the convection permitting simulations especially improve the diurnal cycle of precipitation and the hourly precipitation intensities.

Extreme precipitation events lead to dramatic impacts on society and the situation will worsen under climate change. Decision-makers need reliable estimates of future changes as a basis for effective adaptation strategies, but projections at local scale from regional climate models (RCMs) are highly uncertain. Here we exploit the km-scale convection-permitting multi-model (CPM) ensemble, generated within the FPS Convection project, to provide new understanding of the changes in local precipitation extremes and related uncertainties over the greater Alpine region. The CPM ensemble shows a stronger increase in the fractional contribution from extreme events than the driving RCM ensemble during the summer, when convection dominates. We find that the CPM ensemble substantially reduces the model uncertainties and their contribution to the total uncertainties by more than 50%. We conclude that the more realistic representation of local dynamical processes in the CPMs provides more reliable local estimates of change, which are essential for policymakers to plan adaptation measures.

The advancement of computational resources has allowed researchers to run convection-permitting regional climate model (CPRCM) simulations. A pioneering effort promoting a multimodel ensemble of such simulations is the CORDEX Flagship Pilot Studies (FPS) on “Convective Phenomena over Europe and the Mediterranean” over an extended Alps region. In this study, the Distribution Added Value metric is used to determine the improvement of the representation of all available FPS hindcast simulations for the daily mean near-surface wind speed. The analysis is performed on normalized empirical probability distributions and considers station observation data as the reference. The use of a normalized metric allows for spatial comparison among the different regions (coast and inland), altitudes and seasons. This approach permits a direct assessment of the added value between the CPRCM simulations against their global driving reanalysis (ERA-Interim) and respective coarser resolution regional model counterparts. In general, the results show that CPRCMs add value to their global driving reanalysis or forcing regional model, due to better-resolved topography or through better representation of ocean-land contrasts. However, the nature and magnitude of the improvement in the wind speed representation vary depending on the model, the season, the altitude, or the region. Among seasons, the improvement is usually larger in summer than winter. CPRCMs generally display gains at low and medium-range altitudes. In addition, despite some shortcomings in comparison to ERA-Interim, which can be attributed to the assimilation of wind observations on the coast, the CPRCMs outperform the coarser regional climate models, both along the coast and inland.

Heatwaves (HWs) are high-impact phenomena stressing both societies and ecosystems. Their intensity and frequency are expected to increase in a warmer climate over many regions of the world. While these impacts can be wide-ranging, they are potentially influenced by local to regional features such as topography, land cover, and urbanization. Here, we leverage recent advances in the very high-resolution modelling required to elucidate the impacts of heatwaves at these fine scales. Further, we aim to understand how the new generation of km-scale regional climate models (RCMs) modulates the representation of heatwaves over a well-known climate change hot spot. We analyze an ensemble of 15 convection-permitting regional climate model (CPRCM, ~ 2–4 km grid spacing) simulations and their driving, convection-parameterized regional climate model (RCM, ~ 12–15 km grid spacing) simulations from the CORDEX Flagship Pilot Study on Convection. The focus is on the evaluation experiments (2000–2009) and three subdomains with a range of climatic characteristics. During HWs, and generally in the summer season, CPRCMs exhibit warmer and drier conditions than their driving RCMs. Higher maximum temperatures arise due to an altered heat flux partitioning, with daily peaks up to ~ 150 W/m 2 larger latent heat in RCMs compared to the CPRCMs. This is driven by a 5–25% lower soil moisture content in the CPRCMs, which is in turn related to longer dry spell length (up to double). It is challenging to ascertain whether these differences represent an improvement. However, a point-scale distribution-based maximum temperature evaluation, suggests that this CPRCMs warmer/drier tendency is likely more realistic compared to the RCMs, with ~ 70% of reference sites indicating an added value compared to the driving RCMs, increasing to 95% when only the distribution right tail is considered. Conversely, a CPRCMs slight detrimental effect is found according to the upscaled grid-to-grid approach over flat areas. Certainly, CPRCMs enhance dry conditions, with knock-on implications for summer season temperature overestimation. Whether this improved physical representation of HWs also has implications for future changes is under investigation.

We introduce the latest version of the RegCM regional climate modeling system, RegCM5. Compared to the previous model version (RegCM4) the main new development is the inclusion of the non‐hydrostatic dynamical core from the weather prediction model MOLOCH, which is more accurate and much more computationally stable and efficient than the previous one. In particular, the new dynamical core is best designed for use at convection‐permitting resolutions of a few km. Several physics schemes and coupled model components have also been upgraded compared to the previous version of the model. A set of test simulations for present day climate conditions at parameterized convection and convection permitting resolutions over different European domains is presented for illustrative purposes. Overall, for these simulations RegCM5 exhibits a better performance than RegCM4 for the majority of statistics analyzed, especially at convection‐permitting resolutions. However, this performance depends on the physics schemes used, and further optimization work is under way to fully test the model in different climate settings and reduce current biases. RegCM5 is a freely available, computationally efficient, flexible, and portable Regional Earth System model designed for community use, so that prospective model users are welcome to access its code and use it for different applications.

New evaluation simulations with the ERA5 boundary conditions have been completed with the new model RegCM5 for all CORDEX-CORE domains at 25 km resolution. Model performances are satisfactory for all evaluation metrics for both the mean climate and extreme climate and for temperature, precipitation and cloud variables. For some of the domains the new model is able to remove some well know biases like the dry bias in the Amazon region in the CAM domain or the warm bias in the La Plata basin for the SAM domain. In other domains the RegCM5 performs consistently with the previous model version. One simulation at convection permitting resolution (CP) has been completed for the first time for the whole Euro-CORDEX domain thanks to the new semi implicit dynamical core implemented in the RegCM5 that allow the model to remain stable at such resolution even with time steps of 30 seconds at 3 km resolution. The evaluation of the CP simulation is comparable with the previous model evaluation over the ALPS domain with a tendency to improve both the dry and wet bias in summer and winter respectively. Over the whole Euro-CORDEX domain validation of the sub daily statistic for the precipitation frequency, intensity and diurnal cycle confirm the fitness for purposes of this new model version to run at such resolution for such extended region. A further CP configuration is also tested with two overlapping longitudinal stripe domains covering the Euro-CORDEX domain and the comparison is shown between the two CP simulations.

Abstract The advancement of computational resources has allowed researchers to conduct convection-permitting regional climate model (CPRCM) simulations. A pioneering effort promoting a multimodel ensemble of such simulations is the CORDEX Flagship Pilot Studies (FPS) on "Convective Phenomena over Europe and the Mediterranean" over an extended Alps region. In this study, the Distribution Added Value metric is used to determine the improvement of the representation of all available FPS hindcast simulations for the daily mean wind speed. The analysis is performed on normalized empirical probability distributions and considers station observation data as the reference. The use of a normalized metric allows for spatial comparison among the different regions (coast and inland), altitudes and seasons. This approach permits a direct assessment of the added value between the CPRCM simulations against their global driving reanalysis (ERA-Interim) and respective coarser resolution regional model counterparts. In general, the results show that CPRCMs add value to their global driving reanalysis or forcing regional model, due to better-resolved topography or through better representation of ocean-land contrasts. However, the nature and magnitude of the improvement in the wind speed representation vary depending on the model, the season, the altitude, or the region. Among seasons, the improvement is usually larger in summer than winter. CPRCMs generally display gains at low and medium range altitudes. In addition, despite some shortcomings in comparison to ERA-Interim, which can be attributed to the assimilation of wind observations on the coast, the CPRCMs outperform the coarser regional climate models, both along the coast and inland.

The present study analyses the climate change response of Alpine-Mediterranean heavy precipitation events (HPEs), often associated with hazardous flooding. We investigate HPE properties describing their propagation, scale and intensity, by applying a storm tracking algorithm in an ensemble of convection permitting regional climate models (cpRCMs) under the CMIP5-RCP85 forcing scenario. The climate change response of HPE properties we derive by comparing their mean values for periods nearfuture [2040, 2050] and farfuture [2090, 2100] against those of a present-day period historical [1996, 2005]. By the end of the 21st century the model ensemble projects the region’s surface temperatures to increase by 4.0 ^∘ C. In this warmer climate HPEs are found to propagate farther and faster. They last longer by 5

We present the first evaluation of the wind field from the ensemble of kilometer-scale simulations from the CORDEX-Flagship Pilot Study on convection, with focus on the Adriatic region. Kilometer-scale climate models, also known as convection-permitting models (CPMs), produce a good representation of small-scale topographic features and consequently a more detailed depiction of dynamical and thermal circulations. These enable a reliable view of climate characteristics of the wind field, especially in coastal regions and over complex terrain, such as the Adriatic region. We investigate the (potential) added value introduced by CPMs compared to classical "cumulus-parametrized" regional climate models (RCMs), reanalysis and station observations. For this purpose, wind components at 10 m level are used at 3-hourly frequency. All simulations cover a 10-year period, extending from 2000 to 2009. In terms of the standard statistical parameters such as correlation coefficient and temporal standard deviation, CPMs are very dependent on their parent RCM performance. However, the orographic forcing emphasizes the potential added value and CPMs contain some fine spatial scale variability (i.e., stronger extremes by 25% and more accurate wind direction) that is absent in coarser RCMs and reanalysis. The potential added value is higher in the cold season compared to the warm season due to the proportion of severe wind events. CPMs reproduce well the typical wind regimes along the Adriatic coast, namely Bora and Sirocco. The benefit of using CPMs is especially pronounced in simulating Bora maximum wind speeds in northern Adriatic and Sirocco frequencies in southern Adriatic. Based on our overall analysis, we conclude that CPMs provide added value compared to coarser models, especially in the complex coastal terrain.

We here inter-compare four different tracking algorithms by applying them onto the precipitation fields of an ensemble of convection-permitting regional climate models (cpRCMs) and on high-resolution observational datasets of precipitation. The domain covers the Alps and the northern Mediterranean and thus we here analyse heavy precipitation events, that are renowned for causing hydrological hazards. In this way, this study is both, an inter-comparison of tracking algorithms as well as an evaluation study of cpRCMs in the Lagrangian frame of reference. The tracker inter-comparison is performed by comparison of two case studies as well as of climatologies of cpRCMs and observations. We find that that all of the trackers produce qualitatively equal results concerning characteristic track properties. This means that, despite of quantitative differences, equivalent scientific conclusions would be drawn. This result suggests that all trackers investigated are reliable analysis tools of atmospheric research. With respect to the model ensemble evaluation, we find an encouraging performance of cpRCMs in comparison to radar-based observations. In particular prominent hotspots of heavy precipitation events are well-reproduced by the models. In general most characteristic properties of precipitation events have positive biases. Assuming the under-catchment of precipitation in observations in a domain of such complex orography, this result is to be expected. Only the mean area of tracks is underestimated, while their duration is overestimated. Mean precipitation rate is estimated well, while maximum precipitation rate is overestimated. Furthermore, geometrical and rain volume are overestimated. We find that models overestimate the occurrence of precipitation events over all mountain chains, whereas over plain terrain in summer precipitation events are seen underestimated. This suggests that, despite the convection-permitting resolution, thermally driven thunderstorms are either not triggered or their dynamics still under-resolved. Eventually we find that biases in the spatio-temporal properties of precipitation events appear reduced when evaluating cpRCMs against Doppler radar-based and rain gauge-adjusted observational datasets of comparable spatial resolution, strengthening their role in evaluation studies.

We describe the first effort within the Coordinated Regional Climate Downscaling Experiment- Coordinated Output for Regional Evaluation, or CORDEX-CORE EXP-I. It consists of a set of twenty-first-century projections with two regional climate models (RCMs) downscaling three global climate model (GCM) simulations from the CMIP5 program, for two greenhouse gas concentration pathways (RCP8.5 and RCP2.6), over nine CORDEX domains at similar to 25-km grid spacing. Illustrative examples from the initial analysis of this ensemble are presented, covering a wide range of topics, such as added value of RCM nesting, extreme indices, tropical and extratropical storms, monsoons, ENSO, severe storm environments, emergence of change signals, and energy production. They show that the CORDEX- CORE EXP-I ensemble can provide downscaled information of unprecedented comprehensiveness to increase understanding of processes relevant for regional climate change and impacts, and to assess the added value of RCMs. The CORDEX- CORE EXP-I dataset, which will be incrementally augmented with new simulations, is intended to be a public resource available to the scientific and end-user communities for application to process studies, impacts on different socioeconomic sectors, and climate service activities. The future of the CORDEX-CORE initiative is also discussed.

<p>Climate change exhibits one of its strongest and shocking effects through extreme precipitation events. Extreme convective precipitation events are getting more intense and more frequent and their attribution to global warming is confirmed by recent studies in many regions of the world. During October the 4<sup>th</sup> and 5<sup>th</sup> a Nord-Atlantic trough entering the western Mediterranean favored the formation of deep convective systems feeded by the wet and warm prefrontal flow. One of them built up over the Ligurian Gulf on the 4<sup>th</sup>. Sustained by long-lasting interaction of large scale conditions and local forcings, the V-shape storm persisted over 24 hours locally accumulating more than 900 mm of rain. The event exceeded local and European precipitation records and caused landslides and flash-floods. In this study we try to objectively link the event to climate change through an extreme value theory analysis. This has been carried out through rain-gauge observations over Liguria, available continuously from 1960 for the fall season. The climate conditions of the event are compared to a pre-industrial period 1.2°C cooler than the present days. The Euro-CORDEX 12km resolution ensemble has been also used to confirm the event attribution to global warming. </p>

A new metric that quantifies Added Value (AV) was developed that compares the difference within the entire probability distribution functions (PDFs) of the Regional Climate Model (RCM) and its driving General Circulation Model (GCM) with a high-resolution observation source, at every grid point, to obtain a spatial distribution of AV. This is important to assess the validity of the computationally expensive process of downscaling, especially for Convection Permitting Models (CPMs). The method can be adapted to focus on the tail-end of the distribution, since GCMs struggle to resolve precipitation extremes. To achieve this, the threshold value of the percentile of interest (for example, the 95th percentile) is obtained from the observation source and then applied to the PDF data as a filter, after which the corresponding AV can be obtained. This metric can also be adapted to assess the Climate Change Downscaling Signal (CCDS) of climate projections, by comparing to the corresponding historical data-set instead of an observation source. This method is now being adapted to CPM simulations using a multi-model approach. The analysis is focused on both daily and hourly data from a 14-model ensemble of the ALP-3 domain using 5 high-resolution observation sources (GRIPHO for Italy; EURO4M for large alpine area; COMEPHORE for France; RADKLIM for Germany; and RdisaggH for Switzerland). The primary objective is to assess the added value of the CPM with the driving RCM, but a comparison to the GCM is also included. Preliminary results show that the CPM runs add value over the RCM, with possible emphasis in models/regions of lower RCM AV (requires confirmation by comparing RCMs to the driving GCMs). The analysis is will also focus on the CCDS metric of the near- and far-future simulations of the CPM, and the historical analysis is being replicated using hourly precipitation instead of daily.

Flash floods rank among the most dangerous and costliest hazards of the alpine and mediterranean region. The severe convective storms causing them are influenced by both, the presence of a large body of sea water and a complex orography. These storms are the main subject of the present study and in the following referred to as heavy precipitation events (HPEs). We here study heavy precipitation events by using an ensemble of convection permitting regional climate models and applying a tracking algorithm, and focus on their charateristic properties. The domain covers the Alps and the central part of the Mediterranean, and we investigate and compare three 10-year periods under the rcp85 forcing scenario: historical [2000-2009], near-future [2040-2049] and far-future [2090-2099]. Our analysis reproduces a most important message: even though in the future the mediterranean climate is drying, precipitation associated with heavy precipitation events is increasing. Further, HPEs will be more frequent in the future. In particular, their occurrence frequency will increases in wintertime, whereas it will decrease in summertime. We investigate the climate change signal of characteristic properties describing the propagation, the spatial and temporal scales and the intensity of HPEs: on average HPEs travel by 10% farther [8km], they last longer by 5% [20 min], their area increases by 16% and their total rain volume by 34%. Regarding metrics of intensity the changes of the highest percentiles are greatest: the 90th percentiles of a HPE's precipitation field increases by 5.6%, the 99th percentile by 9.4% and the maximum increases by 12.7%. Eventually we unravel the characterics for specific regions and seasons: changes are more dramatical for HPEs that cross the coastline and in wintertime. In summary, this study confirms important messages of climate research in an ensemble of state-of-the-art regional climate models, demonstrates the capabilities of convection-permitting spatial resolution and explores the possibilities that come with applying a tracking algorithm and by looking into precipitation extremes in the Lagrangion framework of reference.