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At national and European levels development of climate services is seen as a bridge between climate research and decision makers, meant to mitigate and create a sound basis to adapt to Climate Change. To enhance the quality and relevance of climate services, several actors, namely users, providers, purveyors, and researchers participate to identify and provide through co-design, co-development, and co-delivery the improvements and innovations in climate services that are needed to better inform decision-making processes. Strengthening the two-way interaction between climate modelers and climate service providers will enhance the scientific basis for these services and the relevance of climate research and modelling outputs.The H2020 EUCP (European Climate Prediction System) project aimed to produce climate information to deliver to intermediate users, such as climate service providers and consultants, that ultimately should enter the decision domain. For this reason, one of the main objectives of the project was to produce prototypes to showcase how project’s resulting climate information could be used in the real world and how they can make a difference. One of the main goals of the engagement approach in the EUCP project is to reduce the gap between ‘top-down’ climate information driven by science and ‘bottom-up’ end-user requirements to increase the credibility and usability of climate information. This is a major barrier to the use of climate information in decision making at present. To overcome this barrier, it is widely recognized that prototyping is a key element that allows users to understand the “science behind” as well as how it could be applied in specific case studies providing valuable comments to improve the prototypes to close the gap with end users.Similarly, to what happens in producing operational climate services, EUCP prototype production was based on a cycle of prototyping through user trials following the 5Es approach: Explore, Exploit, Expose, Examine, and Expand. It is not a series of sequential steps but an iterative process where a step forward does not imply leaving that stage and not considering it anymore. For instance, understanding the users’ needs is a step that should be considered many times during the development; at the beginning understanding users’ needs should inform the scientific community about research areas of interests, then, user needs should affect how results are shown through an effective display.This presentation reviews how the 5Es approach was developed throughout the project, who were the actors involved and what instruments for users’ engagement were applied and used in this framework. Moreover, some examples of prototypes will be discussed in detail demonstrating how the 5Es approach is flexible enough to prototype different products. Finally, some lessons learnt in the project will be summarized as guidelines for future research.

In this work we use a regional atmosphere–ocean coupled model (RAOCM) and its stand-alone atmospheric component to gain insight into the impact of atmosphere–ocean coupling on the climate change signal over the Iberian Peninsula (IP). The IP climate is influenced by both the Atlantic Ocean and the Mediterranean sea. Complex interactions with the orography take place there and high-resolution models are required to realistically reproduce its current and future climate. We find that under the RCP8.5 scenario, the generalized 2-m air temperature (T2M) increase by the end of the twenty-first century (2070–2099) in the atmospheric-only simulation is tempered by the coupling. The impact of coupling is specially seen in summer, when the warming is stronger. Precipitation shows regionally-dependent changes in winter, whilst a drier climate is found in summer. The coupling generally reduces the magnitude of the changes. Differences in T2M and precipitation between the coupled and uncoupled simulations are caused by changes in the Atlantic large-scale circulation and in the Mediterranean Sea. Additionally, the differences in projected changes of T2M and precipitation with the RAOCM under the RCP8.5 and RCP4.5 scenarios are tackled. Results show that in winter and summer T2M increases less and precipitation changes are of a smaller magnitude with the RCP4.5. Whilst in summer changes present a similar regional distribution in both runs, in winter there are some differences in the NW of the IP due to differences in the North Atlantic circulation. The differences in the climate change signal from the RAOCM and the driving Global Coupled Model show that regionalization has an effect in terms of higher resolution over the land and ocean.

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.

City planners have to take multiple considerations and prospective issues into account when an urban area is to be developed. Especially in the cities, the heat island effect and the high population density combine to a health threat during heatwaves. Climate change exacerbates this heat stress and continues to do so for decades – a time scale relevant in urban planning. The increasing necessity to include urban climate adaption measures requires valid arguments for the decision-making process where they are in competition with other use of scarce urban space.Urban climate models are a tool for assessments of the heat stress, wind comfort, the dispersion of pollutants and others – be it already built or only a proposed plan. The high-performance LES model PALM allows for modelling the atmospheric boundary layer from a whole-city level to a block of houses in resolutions up to 2 m. The model system PALM-4U can be adapted to the assessment question of interest by activating modules like urban surfaces. This incorporates, for example, urban green infrastructure from trees to façade greenery in the simulation. In this presentation, we show an application case for the model PALM-4U to assess a common planning question taken from municipal practice. The simulations investigate the impact of a high degree of green and blue infrastructure compared to a low degree in the plans of a development area. Climate adaption measures like façade greening, replacement of pavement with grass and ponds are evaluated in their cumulative effect on thermal comfort indices PT, PET and UTCI.These simulations are part of the research project “ProPolis” that seeks to bridge the gap between science and practice in urban climate modelling by operationalizing PALM-4U into a practicable and user-friendly tool tailored towards the needs of municipalities and urban planners. ProPolis is part of the research and development program “Urban Climate Under Change [UC]²” funded by Germany’s Federal Ministry of Education and Research (BMBF).

Models tend to show strong rainfall biases over Southern Africa, especially during the Summer (DJF) months. This study aims to explore and understand why these biases occur. The Angolan Low (AL) and ENSO are two important sources of Summer rainfall variability. Thus, the study explores whether the relationship between the AL, ENSO and rainfall is represented correctly in three different ensembles; the CORDEX-CORE ensemble (CCORE, 0.22 degrees resolution), the lower resolution (0.44 degrees) CORDEX-phase 1 ensemble (C44) and the driving CMIP5 models. From regression analysis and a self organizing map the results show that wetter (drier) than normal DJF seasons usually occur during a strong (weak) AL and a La Nina (El Nino) event. While the models show this to an extent, they also show some differences in these relationships compared to the observed. The study examines some key dynamical features to understand why these differences occur. These results can further the understanding and improvement of the simulated Southern African rainfall in models.

Die natürliche Schneedecke ist ein zentraler Indikator des fortschreitenden Klimawandels. Gleichzeitig ist sie eine für viele Sektoren höchst relevante Ressource. Bereits in den letzten Dekaden hat sie sich als Folge der globalen Erwärmung in vielen Regionen Europas merklich zurückgezogen. Mit dem projizierten zukünftigen Temperaturanstieg erwarten wir generell eine weitere Abnahme, aber welche Regionen zu welcher Jahreszeit in welcher Art und Weise und mit welchen Unsicherheiten betroffen sind, erfordert eine dedizierte europaweite Analyse der zukünftigen Entwicklung der natürlichen Schneedecke. Der vorliegende Beitrag wagt diesen Schritt, basierend auf einem umfassenden Ensemble hochaufgelöster regionaler Klimasimulationen aus der EURO-CORDEX Initiative. Die vorgeschaltete Evaluierung zeigt, dass die Landoberflächenmodule heutiger regionaler Klimamodelle prinzipiell in der Lage sind, die räumliche und zeitliche Variabilität der europäischen Schneedecke abzubilden. Jedoch zeigen sich insbesondere in Gebirgsregionen auch Modelldefizite, die es zu beachten und zu berücksichtigen gilt. Die zukünftigen Projektionen für das 21. Jahrhundert ergeben für alle drei betrachteten Emissionsszenarien einen weiteren Rückgang der natürlichen Schneedecke, dessen Ausmass mit steigenden Treibhausgasemissionen zunimmt. Der teilweise Anstieg der winterlichen Gesamtniederschlagsmengen kann dabei den Effekt steigender Temperaturen in der Regel nicht ausgleichen. Für ein hohes Emissionsszenario ist in tiefgelegenen Regionen Zentral- und Südeuropas bis zum Ende des Jahrhunderts mit einem weitgehenden Verschwinden der natürlichen Schneedecke zu rechnen. Der prozentuale Schwund ist in mittleren und hohen Lagen der Gebirgsregionen (Skandinavien, Alpen, Pyrenäen) jedoch deutlich schwächer ausgeprägt. Selbst unter pessimistischen Annahmen zu zukünftigen menschlichen Treibhausgasemissionen wird hier ein nicht zu vernachlässigender Teil der natürlichen Schneedecke verbleiben. Die Unterschiede der einzelnen Modellsimulationen können beträchtlich sein, jedoch besteht eine hohe Einigkeit hinsichtlich der prinzipiellen raum-zeitlichen Änderungssignale.

In the German regional climate modeling project ReKliEs-De the existing EURO-CORDEX simulations have been systematically complemented by new simulations to derive more robust ranges of possible future climate change. The focus of the project lay on user tailored results, which are required for the planning of measures to adapt to the changing climate. Changes in temperature and precipitation indices are calculated from a multi model ensemble for the end of the 21st century. The results for the mitigation scenario RCP2.6 are compared to the results of the “business as usual” scenario RCP8.5. Averaged over Germany the increase of mean annual temperature and of the number of summer days will be around 3 times higher for RCP8.5 than for RCP2.6. In summer, the increase of dry days could be twice as high in RCP8.5 compared to RCP2.6.

Regional climate model simulations have routinely been applied to assess changes in precipitation extremes at daily time steps. However, shorter sub-daily extremes have not received as much attention. This is likely because of the limited availability of high temporal resolution data, both for observations and for model outputs. Here, summertime depth duration frequencies of a subset of the EURO-CORDEX 0.11∘ ensemble are evaluated with observations for several European countries for durations of 1 to 12 h. Most of the model simulations strongly underestimate 10-year depths for durations up to a few hours but perform better at longer durations. The spatial patterns over Germany are reproduced at least partly at a 12 h duration, but all models fail at shorter durations. Projected changes are assessed by relating relative depth changes to mean temperature changes. A strong relationship with temperature is found across different subregions of Europe, emission scenarios and future time periods. However, the scaling varies considerably between different combinations of global and regional climate models, with a spread in scaling of around 1–10 % K−1 at a 12 h duration and generally higher values at shorter durations.

In this work we use a regional ocean-atmosphere coupled model (RAOCM) and its stand-alone atmospheric component to gain insight into the impact of atmosphere-ocean coupling on the climate change signal over the Iberian Peninsula (IP). The IP is a well suited location for this study as high-resolution models are required to realistically reproduce its current and future climate. We find that under the RCP8.5 scenario, the generalized 2-m air temperature (T2M) increase by the end of the 21st century (2070-2099) in the atmospheric-only simulation is tempered by the coupling. The impact of coupling is specially seen in summer, when the warming is stronger. Precipitation shows regionally-dependent changes in winter, whilst a drier climate is found in summer. The coupling generally reduces the magnitude of the changes. Differences in T2M and precipitation between coupled and uncoupled simulations are caused by changes in the Atlantic large-scale circulation and in the Mediterranean Sea. Additionally, the differences in projected changes of T2M and precipitation with the RAOCM under the RCP8.5 and RCP4.5 scenarios are tackled. Results show that in winter and summer T2M increases less and precipitation changes are of a smaller magnitude with the RCP4.5. Whilst in summer changes present a similar regional distribution in both runs, in winter there are some differences in the NW of the IP due to differences in the North Atlantic circulation. The differences in the climate change signal from the RAOCM and the driving Global Coupled Model shows the added value of regionalization in terms of higher resolution over the land and ocean.

The impact of climate change on precipitation over Southern Africa is of particular interest due to its possible devastating societal impacts. To add to this, simulating precipitation is challenging and models tend to show strong biases over this region, especially during the Austral Summer (DJF) months. One of the reasons for this is the mis-representation of the Angolan Low (AL) and its influence on Southern Africa’s Summer precipitation in the models. Therefore, this study aims to explore and compare different models’ ability to capture the AL and its link to precipitation variability as well as consider the impact climate change may have on this link. We also explore how the interaction between ENSO, another important mode of variability for precipitation, and the Angolan Low, impact precipitation, how the models simulate this and whether this could change in the future under climate change. We computed the position and strength of the AL in reanalysis data and compared these results to three different model ensembles with varying resolutions. Namely, the CORDEX-CORE ensemble (CCORE), a new phase of CORDEX simulations with higher resolutions (0.22 degrees), the lower resolution (0.44 degrees) CORDEX-phase 1 ensemble (C44) and the CMIP5 models that drive the two RCM ensembles. We also used Self Organizing Maps to group DJF yearly anomaly patterns and identify which combination of ENSO and AL strength scenarios are responsible for particularly wet or dry conditions. Regression analysis was performed to analyze the relationships between precipitation and the AL and ENSO. This analysis was repeated for near (2041-2060) and far (2080-2099) future climate and compared with the present to understand how the strength of the AL, and its connection to precipitation variability and ENSO, changes in the future. We found that, in line with previous studies, models with stronger AL tend to produce more rainfall. CCORE tends to simulate a stronger AL than C44 and therefore, higher precipitation biases. However, the regression analysis shows us that CCORE is able to capture the relationship between precipitation and the AL strength variability as well as ENSO better than the other ensembles. We found that generally dry rainfall patterns over Southern Africa are associated with a weak AL and El Nino event whereas wet rainfall patterns occur during a strong AL and La Nina year. While the models are able to capture this, they also tend to show more neutral ENSO conditions associated with these wet and dry patterns which possibly indicates less of a connection between AL strength and ENSO than seen in the observed results. Analysis of the future results indicates that the AL weakens, this is shown across all the ensembles and could be a contributing factor to some of the drying seen. These results have applications in understanding and improving model representation of precipitation over Southern Africa as well as providing some insight into the impact of climate change on precipitation and some of its associated dynamics over this region.

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.

Die regionalen Klimasimulationen des EURO-CORDEX-Ensembles leisten einen grundlegen Beitrag zur Abschätzung des Klimawandels und seiner Folgen. Diese regionalen Klimasimulationen verwenden als Antrieb die Daten von 13 Globalmodellsimulationen aus CMIP5 (Coupled Model Intercomparison Project Phase 5). Für die Nutzer des EURO-CORDEX-Ensembles ist es wichtig zu wissen, wie die Ergebnisse der antreibenden Globalmodellsimulationen in das gesamte CMIP5 und in das neue CMIP6 Ensemble einzuordnen sind. Diese Analyse wird für Europa durchgeführt. Die Ergebnisse aller Globalmodellsimulationen aus CMIP5 und CMIP6 werden für den historischen Zeitraum 1981-2010 mit Beobachtungen und Reanalysen verglichen. Dies gibt Aufschluss darüber, welches Globalmodel ein historisches Klima simuliert, das dem Beobachteten entspricht. Des Weiteren wird die zukünftige Klimaänderung jeder Globalmodellsimulation (CMIP5 und CMIP6) für die unterschiedlichen Klimaszenarien berechnet. Diese Untersuchungen werden an Hand der Variablen Temperatur, Niederschlag, Windgeschwindigkeit, Strahlung, Meeresoberflächentemperatur und Druck sowie ausgewählter Klimaindizes und statistischer Kenngrößen durchgeführt.

The Coordinated Output for Regional Evaluations (CORE) simulation ensemble is an effort of the WCRP CORDEX community to provide high resolution regional climate change information for the major inhabited areas of the world and thus to generate the solid scientific basis for further research related to vulnerability, impact, adaptation and climate services (VIACS). This is especially important in those areas in which so far only few high-resolution simulations or only global comparatively coarse simulations were available. The driving simulations were selected to cover the spread of high, medium and low climate sensitivity at a global scale. Initially, the two RCMs REMO and RegCM4 were used to downscale these data global climate model output to a resolution of 0.22° (about 25km) while it is intended that the CORDEX CORE ensemble can then be extended by additional regional simulations to further increase the ensemble size and thus the representation of possible future climate change pathways. The aim of this study is to investigate and document the climate change information provided by the current CORDEX CORE ensemble with respect to mean climate change in different regions and in comparison to previously existing global climate information, especially those global climate simulations used as boundary forcing for CORDEX CORE, but also in comparison to the entire AR5-GCM ensemble. The analysis focuses on the representation of the AR5-GCM range of climate change signals by the CORDEX CORE ensemble with respect to mean temperature and precipitation changes and corresponding shifts in the annual cycles in the new AR6 IPCC physical reference regions. This also provides an indication for CORDEX CORE suitability for VIACS applications in each region.

It is well established that Africa is particularly exposed to climate extremes including heat waves, droughts, and intense rainfall events. How exposed Africa is to the co‐occurrence of these events is however virtually unknown. This study provides the first analysis of projected changes in the co‐occurrence of five such compound climate extremes in Africa, under a low (RCP2.6) and high (RCP8.5) emissions scenario. These changes are combined with population projections for a low (SSP1) and high (SSP3) population growth scenario, in order to provide estimates of the number of people that may be exposed to such events at the end of the 21st century. We make use of an ensemble of regional climate projections from the Coordinated Output for Regional Evaluations (CORE) project embedded in the Coordinated Regional Climate Downscaling Experiment (CORDEX) framework. This ensemble comprises five different Earth System Model/Regional Climate Model (ESM/RCM) combinations with three different ESMs and two RCMs. We show that all five compound climate extremes will increase in frequency, with changes being greater under RCP8.5 than RCP2.6. Moreover, populations exposed to these changes are greater under RCP8.5/SSP3, than RCP2.6/SSP1, increasing by 47‐ and 12‐fold, respectively, compared to the present‐day. Regions of Africa that are particularly exposed are West Africa, Central‐East Africa, and Northeast and Southeast Africa. Increased exposure is mainly driven by the interaction between climate and population growth, and the effect of population alone. This has important policy implications in relation to climate mitigation and adaptation.

Moving towards convection permitting simulations up to few kilometers scale are emerging solutions to the challenge and complexities in simulating different convective phenomena especially over mountainous regions. In this study we execute sensitivity experiments with the non-hydrostatic regional climate model REMO-NH at convection permitting resolution (~3km). We use this model in three setups where different parameterization schemes for horizontal diffusion are tested. In the first setup “DIFF2” we utilize the standard 2nd order diffusion while the second setup “DIFF4” applies 4th order diffusion. The higher order has a smaller impact on larger scales so that the atmospheric fields exhibit more details, especially in regions with high convective activity. In the third setup “TURB3D”, REMO-NH runs with a new 3D Smagorinsky-type turbulence scheme instead of the artificial diffusion schemes. Though turbulent horizontal diffusion is of second order in this setup, it incorporates a spatially and temporally varying exchange coefficient so that flows with little deformation remain unaffected. The domain of the simulations driven with EURO-CORDEX boundary data covers Germany and the time integration spans the year 2006. Selected cases reveal a better representation of convective elements in DIFF4 and TURB3D when compared with DIFF2. We cannot compare these individual cases directly to observations since REMO-NH is not a reanalysis but a climate model. However, the spatial precipitation fields deduced from DWD radar data have characteristics which are more similar to DIFF4 and TURB3D than to DIFF2. More details are resolved in DIFF4 and TURB3D since the diffusion mainly act at the smallest spatial scales resolved by the model. DIFF2 smoothes convective activity drastically so that it appears in the form of unrealistically wide convective cells. On the other hand, the statistics of precipitation (seasonal average, standard deviation and 95th percentile) show a better agreement with observations in the simulation DIFF2 and TURB3D. TURB3D appears to be the best compromise regarding the simulation of precipitations fields. However, TURB3D exhibits a warm bias in the 2m temperature field in autumn and winter. Further model development may help to overcome this issue.

CORDEX-CORE is a new phase of CORDEX simulations with higher resolutions (0.22 degrees) consisting of two RCMs forced by three GCMs. This higher resolution ensemble could provide added value to regional climate change information, however, since the data has just recently been released, more studies are required to validate and report on its climate change signal. With this in mind, we computed the mean climate and extreme indices over Africa using the CORDEX-CORE ensemble. These results are compared to the results of the driving models as well as to the lower resolution CORDEX-phase 1 ensemble. We found that for most of the extreme indices the CORDEX-CORE shows lower biases over Africa owing to its higher spatial resolution. We also found that the mean climate change signal over Africa was broadly consistent across the three different ensembles. Indicating that the new CORDEX-CORE ensemble is able to capture the uncertainty spread well. We report the projected changes in extreme indices over Africa found in the new higher resolution CORDEX-CORE ensemble. We also examine and compare the representation of some key dynamical features over Africa in the different ensembles. Africa is especially vulnerable to extreme events, due to its limited capacity for disaster management. Thus, this study adds important, higher resolution information to the existing climate change impact knowledge for Africa.

Regional Climate Models (RCMs) have undergone substantial development, resulting in increasingly reliable high-resolution simulations. Despite this, the added value of these simulations compared to their driving General Circulation Models (GCMs) has been a recurring issue. Past studies have used different techniques to quantify the added value of a RCM. A new method is now being presented, based on these past studies, that quantifies the added value and presents it spatially. The method was also adapted to assess the Downscaling Signal (DS) in climate change simulations and compare this to the added value.This new method has been used to assess the daily precipitation of the 55-model EURO-CORDEX ensemble and the CORDEX-CORE ensemble, focusing especially on the higher-end of the PDFs. This revealed an overall positive added value across all domains, especially in areas of complex topography, cost-lines, and tropical regions. This DS was similar to that of the added value when looking at RCP 8.5 far-future simulations.

Snow cover is a crucial part of the climate system due to its distinctive alteration of surface reflectance (snow-albedo-feedback) and its influence on further physical surface properties (e.g. heat conduction and water storage). These effects are particularly relevant in alpine areas and high latitude regions, where snow coverage prevails for a significant part of the season. In addition, various human activities rely on snow cover duration and/or snow amounts, such as winter tourism, agriculture and hydropower production.The EURO-CORDEX project provides an RCM ensemble with a horizontal resolution of ~50 and ~12 km for both present-day and future climates assuming different emission scenarios. These simulations present a potentially valuable information source for the future snow cover evolution. Prerequisite, however, is the ability of RCMs to reproduce historical snow cover conditions. These issues are addressed in the present work on a European scale. A horizontal resolution of ~12 km allows for an improved representation of topography and is thus particularly interesting for snow cover studies, as snow in alpine regions strongly correlates with elevation. We therefore only consider the high-resolution EURO-CORDEX RCMs and, for the climate projection part, simulations for RCP2.6, RCP4.5 and RCP8.5.To assess the RCMs’ ability of reproducing current snow cover conditions in Europe, we evaluate simulated snow water equivalent and snow cover duration/extent by comparison against different reanalysis data (e.g. ERA5, UERRA MESCAN-SURFEX) and snow products derived from remote sensing. Regarding the spatial domain, we consider entire Europe with a focus on four mountainous regions (Alps, Norway, Pyrenees and Carpathians). The evaluation reveals that, on an European scale, mean yearly snow cover duration is well captured by the ensemble mean of the models. However, the majority of the RCMs underestimates snow cover extent throughout the season. This bias is more pronounced in the reanalysis (ERA-Interim) driven set of simulations than in the GCM-driven runs. In regions with complex topography, winter snow water equivalent is distinctively overestimated in some simulations - whereas certain grid cells reveal glaciation (i.e. year-round snow coverage). A comparison with E-OBS data indicates that biases in snow cover duration and amount are, besides arising from inaccurate snow schemes, linked to mismatches in simulated air temperature and precipitation patterns. Scenarios for the 21st century show a distinctive reduction in snow cover duration for low-elevation regions, whereas the magnitude of this decrease depends, amongst other factors, on the climate scenario. Projected decreases in the snow cover are less pronounced for medium to high-elevation regions.

The African population is already exposed to climate extremes such as droughts, heat waves and extreme precipitation, which cause damage to agriculture and infrastructure, and affect people's well-being. However, the simultaneous or sequential occurrence of two single climate extremes (compound event) has a more severe impact on the population and economy than single climate extremes. This circumstance is exacerbated by the increase in the African population, which is expected to double by the middle of this century according to the UN Department of Economic and Social Affairs (DESA). Currently, little is known about the potential future change in the occurrence of compound climate extremes and population exposed to these events in Africa. This knowledge is however needed by stakeholder and decision makers to develop measures for adaptation.This research analyzes the occurrence of compound climate extremes such as droughts, heat waves and extreme precipitation in Africa under two different emission scenarios for the end of the century. For the analysis, we applied regional climate projections from the newly performed Coordinated Output for Regional Evaluations (CORE) embedded in the WCRP Coordinated Regional Climate Downscaling Experiment (CORDEX) Framework for Africa at a grid spacing of 25 km, and spatial maps of population projections derived from two different Shared Socioeconomic Pathways (SSPs). In order to take into account a low and a high emission scenario, the Representative Concentration Pathways (RCPs) 2.6 and 8.5 were used in the regional climate projections.We will show that compound climate extremes are projected to be more frequent in Africa under the high emission scenario at the end of the century, and an increase in total exposure is primarily expected for West Africa, Central-East Africa and South-East Africa. Furthermore, combined impacts of population growth and increase in frequencies of compound extremes play an important role in the change of total exposure.

Within the framework of WCRP CORDEX, the CORE (CORDEX Coordinated Output for Regional Evaluations) experiment provides a homogeneous ensemble of regional climate projections for 9 domains covering all land areas of the globe with the exception of the Arctic and Antarctic regions (http://www.cordex.org/experiment-guidelines/cordex-core/). CORDEX-CORE provides data from two regional climate models (REMO2015 and RegCM), driven by 3 GCMs and under 2 RCP scenario conditions at a resolution of about 25 km. In addition, within the same framework, simulations of the current climate, driven by ERA-Interim, were carried out for all areas with REMO2015 at a grid resolution of approx. 25 km.Within the German Project ViWA (Virtual Water Values, https://viwa.geographie-muenchen.de), simulations with the regional climate model REMO2015, driven by ERA-INTERIM analyses were carried out for the same regions globally, but on a significantly higher spatial resolution of approx. 12.5 km. These simulations cover the time period from 2015 to 2018. Comparing these highly resolved simulations to the coarsely resolved CORDEX-CORE simulations, can give indications, in which regions and for which processes the CORDEX-CORE resolution of 25 km is sufficient and where a higher resolution brings a clear added value.We will show first results of this comparison, focusing on selected regions and processes which potentially benefit from higher spatial resolution of the simulations.

The Coordinated Output for Regional Evaluations (CORE) simulation ensemble is an effort of the WCRP CORDEX community to provide high-resolution regional climate change information for the major inhabited areas of the world and thus generate a solid scientific basis for further research related vulnerability, impact, adaptation and climate services. This is especially important in those areas in which only a few high-resolution simulations or only comparatively coarse simulations from global models were available. The driving global climate model (GCM) simulations were selected to cover the spread of high, medium, and low equilibrium climate sensitivity at a global scale. Initially, two regional climate models (RCMs) REMO and RegCM4 were used to downscale GCM output to a spatial resolution of 0.22°. It is intended that the CORDEX-CORE ensemble can then be extended by additional regional simulations to further increase the ensemble size and thus the representation of possible future climate change pathways. The aim of this study is to investigate and document the climate change information provided by the current CORDEX-CORE ensemble with respect to the mean climate change in different regions of the world and in comparison to previously existing global climate information, especially those global climate simulations used as boundary forcing for CORDEX-CORE RCMs. First, the regional biases of the RCMs simulations and its driving GCMs simulations were quantified compared to the CRU TS 4.02 observational dataset during the reference period from 1971 to 2000. Second, the near future (2036 to 2065) and far future (2071 to 2099) climate change signals were quantified from the new CORDEX-CORE ensemble. The analysis focuses on the mean temperature and precipitation changes based on the new IPCC physical climate reference regions. For selected regions, the differences of the climate change information at different resolutions are documented. Using this selected regions, the climate change signals from the CORDEX-CORE ensemble were compared to other existing CORDEX simulations and the CMIP5 GCM ensemble. First results of this comparison will be presented.

In this study, we perform an evaluation of PRIMAVERA high-resolution (25–50 km) Global Climate Models (GCMs) relative to CORDEX Regional Climate Models (RCMs) over Europe (12–50 km resolutions). It is the first time such assessment is performed for regional climate information using ensembles of GCMs and RCMs at similar horizontal resolutions. We perform this exercise for the distribution of daily precipitation contributions to rainfall bins over Europe under current climate conditions. Both ensembles are evaluated against high quality national gridded observations in terms of resolution and station density. We show that PRIMAVERA GCMs simulate very similar distribution to CORDEX RCMs that CMIP5 cannot because of their coarse resolutions. PRIMAVERA and CORDEX ensembles generally show similar strengths and weaknesses. They are of good quality in summer and autumn in most European regions, but tend to overestimate precipitation in winter and spring. PRIMAVERA show improvements in the latter bias by reducing mid-rain rate biases in Central and Eastern Europe. Moreover, CORDEX simulate less light rainfall than PRIMAVERA in most regions and seasons, which improves this common GCM bias. Finally, PRIMAVERA simulate less heavy precipitation than CORDEX in most regions and seasons, especially in summer. PRIMAVERA appear to be closer to observations. However, when we apply an averaged precipitation undercatch error of 20 %, CORDEX become closer to these synthetic datasets. Considering 50 km resolution GCM or RCM datasets over Europe results in large benefits compared to CMIP5 models for impact studies at the regional scale. The effect of increasing resolution from 50 km to 12 km in CORDEX simulations is, in comparison, small in most regions and seasons outside mountainous regions (due to the importance of orography) and coastal regions (mostly depending on the resolution of the land-sea contrast). Now that GCMs are able to reach the level of information provided by CORDEX RCMs run at similar resolutions, there is an opportunity to better coordinate GCM and RCM simulations for future model intercomparison projects.

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 authors like to thank the coordination and the participating institutes of the EURO‐CORDEX initiative for making this study possible. The contribution from Centre de Recherche Public‐Gabriel Lippmann (labeled here as “MIUB”) (now Luxembourg Institute of Science and Technology, LIST) was funded by the Luxembourg National Research Fund (FNR) through grant FNR C09/SR/16 (CLIMPACT). The John von Neumann Institute for Computing and the Forschungszentrum Julich provided the required compute time for the project JJSC15. Work is furthermore sponsored through a research and development cooperation on hydrometeorology between the Federal Institute of Hydrology, Koblenz, Germany, and the Meteorological Institute, University of Bonn, Bonn, Germany. The KNMI‐RACMO simulation was supported by the Dutch Ministry of Infrastructure and the Environment. The simulations of the Universidad de Cantabria were supported by the CORWES project (CGL2010‐22158‐C02), funded by the Spanish R&D Programme and by the FP7 grant 308291 (EUPORIAS). We acknowledge Santander Supercomputacion support group at the University of Cantabria, who provided access to the Altamira Supercomputer at the Institute of Physics of Cantabria (IFCA‐CSIC), member of the Spanish Supercomputing Network. Rowan Fealy acknowledges the financial support provided by the Irish Environmental Protection Agency and the use of Maynooth University's high‐performance computer and the Irish Centre for High End Computing (ICHEC) Stokes facility. The work done by Rita M. Cardoso and Pedro M.M. Soares was financed the Portuguese Science Foundation (FCT) under Project SOLAR‐PTDC/GEOMET/7078/2014. The work of University of Hohenheim as part of the Project RU 1695 was funded by German Science Foundation (DFG). WRF‐UHOH simulations were carried out at the supercomputing center HLRS in Stuttgart (Germany). The CLMcom‐CCLM simulation was supported by the German Federal Ministry of Education and Research (BMBF) and the German Climate Computing Centre (DKRZ). AUTH‐DMC acknowledges the technical support of AUTH‐Scientific Computing Center, the HellasGrid/EGI infrastructure, and the financial support of AUTH‐Research Committee (Pr.Nr. 91376 and 87783). This work used eddy covariance data acquired by the FLUXNET community. We acknowledge the financial support to the eddy covariance data harmonization (www.fluxdata.org). The ERA‐Interim data were accessed from http://apps.ecmwf.int/datasets/. The GLEAM data were accessed from www.gleam.eu/#downloads. The analysis results and the underlying RCM data base are available upon request (sknist@uni‐bonn.de). The data are archived at the Julich Supercomputing Centre, Research Centre Julich, Julich, Germany. We thank the anonymous reviewers for their detailed and constructive comments.

A new ensemble of climate and climate change simulations covering all major inhabited regions with a spatial resolution of about 25 km, from the WCRP CORDEX COmmon Regional Experiment (CORE) Framework, has been established in support of the growing demands for climate services. The main objective of this study is to assess the quality of the simulated climate and its fitness for climate change projections by REMO (REMO2015), a regional climate model of Climate Service Center Germany (GERICS) and one of the RCMs used in the CORDEX-CORE Framework. The CORDEX-CORE REMO2015 simulations were driven by the ECMWF ERA-Interim reanalysis and the simulations were evaluated in terms of biases and skill scores over ten CORDEX Domains against the Climatic Research Unit (CRU) TS version 4.02, from 1981 to 2010, according to the regions defined by the K&ouml, ppen&ndash, Trewartha (K&ndash, T) Climate Classification types. The REMO simulations have a relatively low mean annual temperature bias (about &plusmn, 0.5 K) with low spatial standard deviation (about &plusmn, 1.5 K) in the European, African, North and Central American, and Southeast Asian domains. The relative mean annual precipitation biases of REMO are below &plusmn, 50 % in most domains, however, spatial standard deviation varies from &plusmn, 30 % to &plusmn, 200 %. The REMO results simulated most climate types relatively well with lowest biases and highest skill score found in the boreal, temperate, and subtropical regions. In dry and polar regions, the REMO results simulated a relatively high annual biases of precipitation and temperature and low skill. Biases were traced to: missing or misrepresented processes, observational uncertainty, and uncertainties due to input boundary forcing.

An evaluation of the present-day climate in South America simulated by the MPI atmospheric limited area model, REMO, is made. The model dataset was generated by dynamical downscaling from the ECMWF-ERA40 reanalysis and compared to in-situ observations. The model is able to reproduce the low-level summer monsoon circulation but it has some deficiencies in representing the South American Low-Level Jet structure. At upper levels, summer circulation features like the Bolivian High and the associated subtropical jet are well simulated by the model. Sea-level pressure fields are in general well represented by REMO. The model exhibits reasonable skill in representing the general features of the mean seasonal cycle of precipitation. Nevertheless, there is a systematic overestimation of precipitation in both tropical and subtropical regions. Differences between observed and modeled temperature are smaller than 1.5A degrees C over most of the continent, excepting during spring when those differences are quite large. Results also show that the dynamical downscaling performed using REMO introduces some enhancement of the global reanalysis especially in temperature at the tropical regions during the warm season and in precipitation in both the subtropics and extratropics. It is then concluded that REMO can be a useful tool for regional downscaling of global simulations of present and future climates.

Although sulphur emissions (mainly as SO2) have been continuously decreasing over the last 20 years in most western industrialized countries, localized SO2 problems still exist in conjunction with strong local emission, meteorological, and topographical factors. In this study, the effect of supplementary installed flue gas desulphurization (FGD) units at high-capacity power plants on regional air pollution in the Carpathian Basin is investigated. The dispersion and accumulation of the SO2 air pollutant are studied with the regional three-dimensional on-line atmosphere-chemistry model REMOTE. The changes in the SO2 air pollution are investigated by parallel simulations in a case study, where the single modified parameter is the SO2 emission rate. The results show that FGD units significantly reduce the horizontal and the vertical dispersion of the emitted SO2, and its transboundary transport, too. Beside the SO2 removal efficiency, the dispersion and accumulation also depend on the seasonal weather conditions. During winter, the dispersion and accumulation are higher than in other seasons. Due to this phenomenon, higher SO2 removal efficiency is needed to guarantee similar air quality features like in the other seasons.

Ambitious climate change mitigation plans call for a significant increase in the use of renewables, which could, however, make the supply system more vulnerable to climate variability and changes. Here we evaluate climate change impacts on solar photovoltaic (PV) power in Europe using the recent EURO-CORDEX ensemble of high-resolution climate projections together with a PV power production model and assuming a well-developed European PV power fleet. Results indicate that the alteration of solar PV supply by the end of this century compared with the estimations made under current climate conditions should be in the range (−14%;+2%), with the largest decreases in Northern countries. Temporal stability of power generation does not appear as strongly affected in future climate scenarios either, even showing a slight positive trend in Southern countries. Therefore, despite small decreases in production expected in some parts of Europe, climate change is unlikely to threaten the European PV sector., Renewables are key for abating climate change, but also potentially vulnerable to it. Here, the authors show that the power supply from a well-developed European fleet of photovoltaic installations may undergo decreases during the 21st century, but with limited changes in amplitude and temporal stability.

Climate signal maps can be used to identify regions where robust climate changes can be derived from an ensemble of climate change simulations. Here, robustness is defined as a combination of model agreement and the significance of the individual model projections. Climate signal maps do not show all information available from the model ensemble, but give a condensed view in order to be useful for non-climate scientists who have to assess climate change impact during the course of their work. Three different ensembles of regional climate projections have been analyzed regarding changes of seasonal mean and extreme precipitation (defined as the number of days exceeding the 95th percentile threshold of daily precipitation) for Germany, using climate signal maps. Although the models used and the scenario assumptions differ for the three ensembles (representative concentration pathway (RCP) 4.5 vs. RCP8.5 vs. A1B), some similarities in the projections of future seasonal and extreme precipitation can be seen. For the winter season, both mean and extreme precipitation are projected to increase. The strength, robustness and regional pattern of this increase, however, depends on the ensemble. For summer, a robust decrease of mean precipitation can be detected only for small regions in southwestern Germany and only from two of the three ensembles, whereas none of them projects a robust increase of summer extreme precipitation.

REMO-HAM is a new regional aerosol-climate model. It is based on the REMO regional climate model and includes most of the major aerosol processes. The structure for aerosol is similar to the global aerosol-climate model ECHAM5-HAM, for example the aerosol module HAM is coupled with a two-moment stratiform cloud scheme. On the other hand, REMO-HAM does not include an online coupled aerosol-radiation nor a secondary organic aerosol module. In this work, we evaluate the model and compare the results against ECHAM5-HAM and measurements. Four different measurement sites were chosen for the comparison of total number concentrations, size distributions and gas phase sulfur dioxide concentrations: Hyytiälä in Finland, Melpitz in Germany, Mace Head in Ireland and Jungfraujoch in Switzerland. REMO-HAM is run with two different resolutions: 50 × 50 km2 and 10 × 10 km2. Based on our simulations, REMO-HAM is in reasonable agreement with the measured values. The differences in the total number concentrations between REMO-HAM and ECHAM5-HAM can be mainly explained by the difference in the nucleation mode. Since we did not use activation nor kinetic nucleation for the boundary layer, the total number concentrations are somewhat underestimated. From the meteorological point of view, REMO-HAM represents the precipitation fields and 2 m temperature profile very well compared to measurement. Overall, we show that REMO-HAM is a functional aerosol-climate model, which will be used in further studies.

This article describes one of the scattering algorithms of the three-dimensional polarized radiative transfer model ARTS (Atmospheric Radiative Transfer Simulator) which has been implemented to study for example the influence of cirrus clouds on microwave limb sounding. The model uses the DOIT (Discrete Ordinate Iterative) method to solve the vector radiative transfer equation. The implementation of a discrete ordinate method is challenging due to the spherical geometry of the model atmosphere which is required for the simulation of limb radiances. The involved numerical issues, which are grid optimization and interpolation methods, are discussed in this paper. Scattering simulations are presented for limb- and down-looking geometries, for one-dimensional and three-dimensional spherical atmospheres. They show the impact of cloud particle size, shape, and orientation on the brightness temperatures and on the polarization of microwave radiation in the atmosphere. The cloud effect is much larger for limb radiances than for nadir radiances. Particle size is a very important parameter in all simulations. The polarization signal is negligible for simulations with completely randomly oriented particles, whereas for horizontally aligned particles with random azimuthal orientation the polarization signal is significant. Moreover, the effect of particle shape is only relevant for oriented cloud particles. The simulations show that it is essential to use a three-dimensional scattering model for inhomogeneous cloud layers. Upprättat; 2004; 20070502 (pafi)