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The collaboration between the Coordinated Regional Climate Downscaling Experiment (CORDEX) and the Earth System Grid Federation (ESGF) provides open access to an unprecedented ensemble of regional climate model (RCM) simulations, across the 14 CORDEX continental-scale domains, with global coverage. These simulations have been used as a new line of evidence to assess regional climate projections in the latest contribution of the Working Group I (WGI) to the IPCC Sixth Assessment Report (AR6), particularly in the regional chapters and the Atlas. Here, we present the work done in the framework of the Copernicus Climate Change Service (C3S) to assemble a consistent worldwide CORDEX grand ensemble, aligned with the deadlines and activities of IPCC AR6. This work addressed the uneven and heterogeneous availability of CORDEX ESGF data by supporting publication in CORDEX domains with few archived simulations and performing quality control. It also addressed the lack of comprehensive documentation by compiling information from all contributing regional models, allowing for an informed use of data. In addition to presenting the worldwide CORDEX dataset, we assess here its consistency for precipitation and temperature by comparing climate change signals in regions with overlapping CORDEX domains, obtaining overall coincident regional climate change signals. The C3S CORDEX dataset has been used for the assessment of regional climate change in the IPCC AR6 (and for the interactive Atlas) and is available through the Copernicus Climate Data Store (CDS)., Bulletin of the American Meteorological Society, 103 (12), ISSN:0003-0007, ISSN:1520-0477

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.

Made available in DSpace on 2022-04-28T19:51:16Z (GMT). No. of bitstreams: 0 Previous issue date: 2022-02-01 Stichting Combined Ophthalmic Research Rotterdam Deutsche Kniegesellschaft European Society of Gastrointestinal Endoscopy 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 ~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. Abdus Salam International Centre for Theoretical Physics Climate Service Center Germany (GERICS) Oak Ridge National Laboratory University of Innsbruck National Center for Atmospheric Research, Boulder Centro de Investigación Científica y de Educación Superior de Ensenada National Institute of Oceanography and Applied Geophysics (INOGS) Abdus Salam International Centre for Theoretical Physics University of São Paulo Climate Change Research Centre School of Biological Earth and Environmental Science University of New South Wales Institute of Atmospheric Physics Chinese Academy of Sciences Hong Kong University of Science and Technology São Paulo State University Federal University of Itajuba University of Augsburg São Paulo State University

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.

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.

Global warming is likely to cause a progressive drought increase in some regions, but how population and natural resources will be affected is still underexplored. This study focuses on global population, forests, croplands and pastures exposure to meteorological drought hazard in the 21st century, expressed as frequency and severity of drought events. As input, we use a large ensemble of climate simulations from the Coordinated Regional Climate Downscaling Experiment (CORDEX), population projections from the NASA-SEDAC dataset and land-use projections from the Land-Use Harmonization 2 project for 1981–2100. The exposure to drought hazard is presented for five Shared Socioeconomic Pathways (SSP1-SSP5) at four Global Warming Levels (GWLs: 1.5°C to 4°C). Results show that considering only Standardized Precipitation Index (SPI; based on precipitation), the SSP3 at GWL4 projects the largest fraction of the global population (14%) to experience an increase in drought frequency and severity (versus 1981–2010), with this value increasing to 60% if temperature is considered (indirectly included in the Standardized Precipitation-Evapotranspiration Index, SPEI). With SPEI, considering the highest GWL for each SSP, 8 (for SSP2, SSP4, SSP5) and 11 (SSP3) billion people, that is, more than 90%, will be affected by at least one unprecedented drought. For SSP5 at GWL4, approximately 2 × 10$^{6}$ km$^{2}$ of forests and croplands (respectively, 6% and 11%) and 1.5 × 10$^{6}$ km$^{2}$ of pastures (19%) will be exposed to increased drought frequency and severity according to SPI, but for SPEI this extent will rise to 17 × 10$^{6}$ km$^{2}$ of forests (49%), 6 × 10$^{6}$ km$^{2}$ of pastures (78%) and 12 × 10$^{6}$ km$^{2}$ of croplands (67%), being mid-latitudes the most affected. The projected likely increase of drought frequency and severity significantly increases population and land-use exposure to drought, even at low GWLs, thus extensive mitigation and adaptation efforts are needed to avoid the most severe impacts of climate change.

The use of regional climate model‐based projections for providing regional climate information in a research and climate service contexts is currently expanding very fast. This has been possible thanks to a considerable effort in developing comprehensive ensembles of regional climate model (RCM) projections, especially for Europe, in the EURO‐CORDEX community (Jacob et al., 2014; Jacob et al., 2020). Currently, EURO‐CORDEX has developed a set of 55 historical and scenario projections (RCP8.5) using 8 driving global climate models (GCMs) and 11 RCMs. This article presents the ensemble including its design. We target the analysis to better characterize the quality of the regional climate models by providing an evaluation of these RCM simulations over a number of classical climate variables and extreme and impact‐oriented indices for the period 1981‐2010. For the main variables, the model simulations generally agree with observations and reanalyses. However, several systematic biases are found as well, with shared responsibilities among RCMs and GCMs: simulations are overall too cold, too wet and too windy compared to available observations or reanalyses. Some simulations show strong systematic biases on temperature, others on precipitation or dynamical variables but none of the models/simulations can be defined as the best or the worst on all criteria. The article aims at supporting a proper use of these simulations within a climate services context.

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.

International audience; This paper analyzes the ensemble of regional climate model (RCM) projections for Europe completed within the EURO CORDEX project. Projections are available for the two greenhouse gas concentration scenarios RCP2.6 (22 members) and RCP8.5 (55 members) at 0.11° resolution from 11 RCMs driven by eight global climate models (GCMs). The RCM ensemble results are compared with the driving CMIP5 global models but also with a subset of available last generation CMIP6 projections. Maximum warming is projected by all ensembles in Northern Europe in winter, along with a maximum precipitation increase there; in summer, maximum warming occurs in the Mediterranean and Southern European regions associated with a maximum precipitation decrease. The CMIP6 ensemble shows the largest signals, both for temperature and precipitation, along with the largest inter model spread. There is a high model consensus across the ensembles on an increase of extreme precipitation and drought frequency in the Mediterranean region. Extreme temperature indices show an increase of heat extremes and a decrease of cold extremes, with CMIP6 showing the highest values and EURO CORDEX the finest spatial details. This data set of unprecedented size and quality will provide the basis for impact assessment and climate service activities for the European region.

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.

Two questions motivated this study: 1) Will meteorological droughts become more frequent and severe during the twenty-first century? 2) Given the projected global temperature rise, to what extent does the inclusion of temperature (in addition to precipitation) in drought indicators play a role in future meteorological droughts? To answer, we analyzed the changes in drought frequency, severity, and historically undocumented extreme droughts over 1981–2100, using the standardized precipitation index (SPI; including precipitation only) and standardized precipitation-evapotranspiration index (SPEI; indirectly including temperature), and under two representative concentration pathways (RCP4.5 and RCP8.5). As input data, we employed 103 high-resolution (0.448) simulations from the Coordinated Regional Climate Downscaling Experiment (CORDEX), based on a combination of 16 global circulation models (GCMs) and 20 regional circulation models (RCMs). This is the first study on global drought projections including RCMs based on such a large ensemble of RCMs. Based on precipitation only,;15% of the global land is likely to experience more frequent and severe droughts during 2071–2100 versus 1981–2010 for both scenarios. This increase is larger (;47% under RCP4.5,;49% under RCP8.5) when precipitation and temperature are used. Both SPI and SPEI project more frequent and severe droughts, especially under RCP8.5, over southern South America, the Mediterranean region, southern Africa, southeastern China, Japan, and southern Australia. A decrease in drought is projected for high latitudes in Northern Hemisphere and Southeast Asia. If temperature is included, drought characteristics are projected to increase over North America, Amazonia, central Europe and Asia, the Horn of Africa, India, and central Australia; if only precipitation is considered, they are found to decrease over those areas. Fil: Spinoni, Jonathan. Joint Research Centre; Italia Fil: Barbosa, Paulo. Joint Research Centre; Italia Fil: Bucchignani, Edoardo. Centro Euro Mediterraneo Sui Cambiamenti Climatici.; Italia Fil: Cassano, John. State University of Colorado at Boulder; Estados Unidos Fil: Cavazos, Tereza. Centro de Investigacion Cientifica y de Educacion Super; México Fil: Christensen, Jens H.. Danish Meteorological Institute; Dinamarca Fil: Christensen, Ole B.. Danish Meteorological Institute; Dinamarca Fil: Coppola, Erika. The Abdus Salam. International Centre for Theoretical Physics; Italia Fil: Evans, Jason. University of New South Wales. Faculty of Science; Australia Fil: Geyer, Beate. Institute of Coastal Research; Alemania Fil: Giorgi, Filippo. The Abdus Salam. International Centre for Theoretical Physics; Italia Fil: Hadjinicolaou, Panos. Environment And Water Research Center; Chipre Fil: Jacob, Daniela. Climate Service Center; Alemania Fil: Katzfey, Jack. Commonwealth Scientific And Industrial Research Organis; Australia Fil: Koenigk, Torben. Swedish Meteorological And Hydrological; Suecia Fil: Laprise, René. Université du Québec a Montreal; Canadá Fil: Lennard, Christopher J.. University of Cape Town; Sudáfrica Fil: Kurnaz, M. Levent. Bogazici University; Turquía Fil: Delei, L.I.. Chinese Academy of Sciences; República de China Fil: Llopart, Marta. Universidade Estadual Paulista Julio de Mesquita Filho; Brasil Fil: McCormick, Niall. European Commission Joint Research Centre; España Fil: Naumann, Gustavo. European Commission Joint Research Centre; España Fil: Nikulin, Grigory. No especifíca; Fil: Ozturk, Tugba. No especifíca; Fil: Panitz, Hans Juergen. No especifíca; Fil: da Rocha, Rosmeri Porfirio. No especifíca; Fil: Rockel, Burkhardt. No especifíca; Fil: Solman, Silvina Alicia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina Fil: Syktus, Jozef. The University of Queensland; Australia. University of Queensland; Australia Fil: Tangang, Fredolin. No especifíca; Fil: Vautard, Robert. No especifíca; Fil: Vautard, Robert. Centre National de la Recherche Scientifique; Francia Fil: Vogt, Jürgen V.. European Commission Joint Research Centre; España Fil: Winger, Katja. Université du Québec a Montreal; Canadá Fil: Zittis, George. No especifíca; Fil: Dosio, Alessandro. No especifíca

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.

The need to restrict global mean temperature to avoid irreversible climate change is supported by scientific evidence. The need became political practice at the Conference of the Parties in 2015, where the participants decided to limit global warming to not more than +2.0 °C compared to pre-industrial times and to rather aim for a limit of +1.5 °C global warming. Nevertheless, a clear picture of what European climate would look like under +1.5 °C, +2.0 °C and +3.0 °C global warming level (GWL) is still missing. In this study, we will fill this gap by assessing selected climate indices related to temperature and precipitation extremes, based on state of the art regional climate information for Europe taken from the European branch of the World Climate Research Program Coordinated Regional Downscaling Experiment (EURO-CORDEX) ensemble. To assess the impact of these indices under climate change, we investigate the spatial extent of the area of the climate change signal in relation to the affected population. This allows us to demonstrate which climate extremes could be avoided when global warming is kept well below +2.0 °C or even +1.5 °C compared to higher GWLs. The European north–south gradient of tropical nights and hot days is projected to be intensified with an increasing global warming level. For precipitation-related indices, an overall increase in precipitation extremes is simulated, especially under +3.0 °C GWL, for mid- and northern Europe, whereas an increase in dry days is projected for many regions in southern Europe. The benefit of staying below +1.5 °C GWL compared to +2.0 °C GWL is the avoidance of an additional increase in tropical nights and hot days parallel to an increase in dry days in parts of southern Europe as well as an increase in heavy precipitation in parts of Scandinavia. Compared to +3.0 °C GWL, the benefit of staying at +1.5 °C GWL is to avoid a substantial increase (i.e., an increase of more than five dry days and ten tropical nights) in dry days and tropical nights in southern European regions, while, in several European regions and especially in northern Europe, a substantial increase (i.e., more than two heavy precipitation days) in heavy precipitation days could be avoided. This study shows that a statistically significant change in the investigated climate indices can be avoided under +1.5 °C GWL compared to the investigated higher GWLs +2.0 °C and +3.0 °C for the majority of the population in almost all regions. Future studies will investigate compound events where the severity of single extreme events is intensified.

The effects of climate change on freezing rain in Europe under medium (RCP4.5) and strong (RCP8.5) future emission scenarios were assessed using seven regional climate model simulations conducted within the World Climate Research Project\'s COordinated Regional climate Downscaling Experiment over the European Domain (EURO‐CORDEX). A precipitation‐typing algorithm was applied to modeled three‐dimensional subdaily time series of key meteorological variables to estimate the occurrence and amounts of freezing rain above selected intensity thresholds. The annual probabilities of freezing rain during the baseline (1971–2000) and future (2071–2100) periods were calculated. The models agree that under the RCP8.5 scenario, the frequencies of freezing rain decrease in western, central, and southeastern Europe by 20–55% and increase in the northern and northeastern parts of the continent by 0–50% toward the end of the century. In the northern regions, the peaks in spring and fall with freezing rain amounts during the baseline period tend to merge to a single peak in winter during the future period. Under the RCP4.5 scenario, the changes are qualitatively similar but smaller.

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.

The impact of a +2 °C global warming on temperature and precipitation over tropical Africa is examined, based on an ensemble of 12 regional climate model scenario simulations. These 12 scenarios are re-phased so that they all correspond to the same global warming of 2 °C with respect to pre-industrial conditions. The continental temperature increase is above the global average. If heat waves are defined with the same temperature threshold in the reference climate and in the scenario, their frequency increases by a factor of 10. When the temperature threshold is adapted to future conditions, there is still a slight increase in frequency. The average precipitation does not show a significant response, due to model-to-model spread. However two compensating phenomena occur, which are robust among the models: (a) the number of rain days decreases whereas the precipitation intensity increases, and (b) the rain season occurs later during the year with less precipitation in early summer and more precipitation in late summer. Simulated daily temperature and precipitation data are combined in two impact models, one for the hydrology of the Nile and Niger basins, one for the food security of the different countries. They show that the main feature of the climate change is not a continuous trend signal, but an alternation of dry and wet decadal to multidecadal episodes.

The transferability of the regional climate model REMO with a standard setup over different regions of the world has been evaluated. The study is based on the idea that the modeling parameters and parameterizations in a regional climate model should be robust to adequately simulate the major climatic characteristic of different regions around the globe. If a model is not able to do that, there might be a chance of an “overtuning” to the “home-region”, which means that the model physics are tuned in a way that it might cover some more fundamental errors, e.g., in the dynamics. All simulations carried out in this study contribute to the joint effort by the international regional downscaling community called COordinated Regional climate Downscaling EXperiment (CORDEX). REMO has been integrated over six CORDEX domains forced with the so-called perfect boundary conditions obtained from the global reanalysis dataset ERA-Interim for the period 1989 to 2008. These six domains include Africa, Europe, North America, South America, West Asia and the Mediterranean region. Each of the six simulations was conducted with the identical model setup which allows investigating the transferability of a single model to regions with substantially different climate characteristics. For the consistent evaluation over the different domains, a new evaluation framework is presented by combining the Köppen-Trewartha climate classification with temperature-precipitation relationship plots and a probability density function (PDF) skill score method. The evaluation of the spatial and temporal characteristics of simulated precipitation and temperature, in comparison to observational datasets, shows that REMO is able to simulate the mean annual climatic features over all the domains quite reasonably, but still some biases remain. The regions over the Amazon and near the coast of major upwelling regions have a significant warm bias. Wet and dry biases appear over the mountainous regions and East Africa, respectively. The temperature over South America and precipitation over the tundra and highland climate of West Asia are misrepresented. The probable causes leading to these biases are discussed and ideas for improvements are suggested. The annual cycle of precipitation and temperature of major catchments in each domain are also well represented by REMO. The model has performed well in simulating the inter- and intra-seasonal characteristics of different climate types in different regions. Moreover, the model has a high ability in representing the general characteristics of different climate types as measured by the probability density function (PDF) skill score method. Although REMO seems to perform best over its home domain in Europe (domain of development and testing), the model has simulated quite well the climate characteristics of other regions with the same set of parameterization options. Therefore, these results lead us to the conclusion that REMO is well suited for long-term climate change simulations to examine projected future changes in all these regions.

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.

Daily precipitation statistics as simulated by the ERA-Interim-driven EURO-CORDEX regional climate model (RCM) ensemble are evaluated over two distinct regions of the European continent, namely the European Alps and Spain. The potential added value of the high-resolution 12 km experiments with respect to their 50 km resolution counterparts is investigated. The statistics considered consist of wet-day intensity and precipitation frequency as a measure of mean precipitation, and three precipitation-derived indicators (90th percentile on wet days—90pWET, contribution of the very wet days to total precipitation—R95pTOT and number of consecutive dry days—CDD)., This work is supported by CORWES (CGL2010-22158-C02) and EXTREMBLES (CGL2010-21869) projects funded by the Spanish R&D programme and the European COST ACTION VALUE (ES1102). A. C. thanks the Spanish Ministry of Economy and Competitiveness for the funding provided within the FPI programme (BES-2011-047612 and EEBB-I-13-06354).

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.

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.

The ability of a large ensemble of regional climate models to accurately simulate heat waves at the regional scale of Europe was evaluated. Within the EURO-CORDEX project, several state-of-the art models, including non-hydrostatic meso-scale models, were run for an extended time period (20 years) at high resolution (12 km), over a large domain allowing for the first time the simultaneous representation of atmospheric phenomena over a large range of spatial scales. Eight models were run in this configuration, and thirteen models were run at a classical resolution of 50 km. The models were driven with the same boundary conditions, the ERA-Interim re-analysis, and except for one simulation, no observations were assimilated in the inner domain. Results, which are compared with daily temperature and precipitation observations (ECA&D and E-OBS data sets) show that, even forced by the same re-analysis, the ensemble exhibits a large spread. A preliminary analysis of the sources of spread, using in particular simulations of the same model with different parameterizations, shows that the simulation of hot temperature is primarily sensitive to the convection and the microphysics schemes, which affect incoming energy and the Bowen ratio. Further, most models exhibit an overestimation of summertime temperature extremes in Mediterranean regions and an underestimation over Scandinavia. Even after bias removal, the simulated heat wave events were found to be too persistent, but a higher resolution reduced this deficiency. The amplitude of events as well as the variability beyond the 90th percentile threshold were found to be too strong in almost all simulations and increasing resolution did not generally improve this deficiency. Resolution increase was also shown to induce large-scale 90th percentile warming or cooling for some models, with beneficial or detrimental effects on the overall biases. Even though full causality cannot be established on the basis of this evaluation work, the drivers of such regional differences were shown to be linked to changes in precipitation due to resolution changes, affecting the energy partitioning. Finally, the inter-annual sequence of hot summers over central/southern Europe was found to be fairly well simulated in most experiments despite an overestimation of the number of hot days and of the variability. The accurate simulation of inter-annual variability for a few models is independent of the model bias. This indicates that internal variability of high summer temperatures should not play a major role in controlling inter-annual variability. Despite some improvements, especially along coastlines, the analyses conducted here did not allow us to generally conclude that a higher resolution is clearly beneficial for a correct representation of heat waves by regional climate models. Even though local-scale feedbacks should be better represented at high resolution, combinations of parameterizations have to be improved or adapted accordingly. © 2013 Springer-Verlag Berlin Heidelberg., The EURO-CORDEX simulations and analysis were carried out in several groups within the framework of the IMPACT2C FP7 project (Grant FP7-ENV.2011.1.1.6-1). The BTU Cottbus offered an exchange ftp site for sharing all model simulation files. The contribution from CRP-GL was funded by the Luxembourg National Research Fund (FNR) through Grant FNR C09/SR/16 (CLIMPACT). We acknowledge financial support from the Spanish R&D program through Grants CGL2010-21869 (EXTREMBLES) and CGL2010-22158-C02-01 (CORWES). Charles University runs were supported partially in framework of the Research Plan of MSMT (No. MSM 0021620860) and GACR project No. P209/11/2405. The contribution from UHOH was funded by the German Science Foundation (DFG) through project FOR 1695. The REMO simulations were supported by CSC, MPI, as well as BMBF and performed under the ‘‘Konsortial’’ share at the German Climate Computing Centre (DKRZ), as well as the CCLM simulations carried out by BTU, which we are further thankful for their various support. We are thankful to the French CCRT/TGCC supercomputing center support and the CEA and GENCI computing resource allocation agency for the WRF-IPSL-INERIS runs. The development of the modeling chain at INERIS and IPSL was carried out in part within the French national project SALUT’AIR (PRIMEQUAL research program). Part of SMHI contribution was done in the ECLISE projects that receive funding from the European Union Seventh Framework Programme (FP7/2007–2013) under Grant agreement 265240 and in the Swedish Mistra-SWECIA programme founded by Mistra (the Foundation for Strategic Environmental Research). DHMZ contribution was partially supported by the Croatian Ministry of Science, Education and Sports (Grant No. 004-1193086-3035).

We investigate the performance of one stretched-grid atmospheric global model, five different regional climate models and a statistical downscaling technique in simulating 3 months (January 1971, November 1986, July 1996) characterized by anomalous climate conditions in the southern La Plata Basin. Models were driven by reanalysis (ERA-40). The analysis has emphasized on the simulation of the precipitation over land and has provided a quantification of the biases of and scatter between the different regional simulations. Most but not all dynamical models underpredict precipitation amounts in south eastern South America during the three periods. Results suggest that models have regime dependence, performing better for some conditions than others. The models' ensemble and the statistical technique succeed in reproducing the overall observed frequency of daily precipitation for all periods. But most models tend to underestimate the frequency of dry days and overestimate the amount of light rainfall days. The number of events with strong or heavy precipitation tends to be under simulated by the models. Fil: Menendez, Claudio Guillermo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina Fil: de Castro, M.. Universidad de Castilla-La Mancha; España Fil: Boulanger, J. P.. Universite de Bretagne Occidentale. Departamento Umr 6538; Francia. Centre National de la Recherche Scientifique; Francia Fil: D'Onofrio, A.. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina Fil: Sanchez, E.. Universidad de Castilla-La Mancha; España Fil: Sörensson, Anna. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina Fil: Blazquez, Josefina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina Fil: Elizalde, A.. Universidad de Castilla-La Mancha; España Fil: Jacob, D.. Max Planck Institute for Meteorology; Alemania Fil: Le Treut, H.. Centre National de la Recherche Scientifique; Francia Fil: Li, Z. X.. Centre National de la Recherche Scientifique; Francia Fil: Nuñez, Mario Nestor. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina Fil: Pessacg, Natalia Liz. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina Fil: Pfeiffer, S.. Max Planck Institute for Meteorology; Alemania Fil: Rojas, M.. Universidad de Chile; Chile Fil: Rolla, Alfredo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina Fil: Samuelsson, P.. Swedish Meteorological and Hydrological Institute; Suecia Fil: Solman, Silvina Alicia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina Fil: Teichmann, C.. Max Planck Institute for Meteorology; Alemania

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)