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This work represents a first step in the definition of a framework aimed at finding, by means of efficient global optimization based on metamodels, an optimal configuration of physical parameters for the ICON (ICOsahedral Nonhydrostatic) Limited Area Mode at high resolution (about 1.1 km) over Southern Italy, to be used for operational runs. The objective of the optimization is to reduce the distance between observed meteorological variables and modeled data. This distance is measured by an opportunely designed objective function. This work represents a preparatory step, since the input parameters considered are only a reduced number with respect to the huge amount of parameters potentially involved. First, domain size sensitivity was performed to choose the optimal domain. Then, the optimization was conducted by means of an Efficient Global Optimization algorithm relying on a Gaussian-based metamodel. The four parameters considered control the heat transfer in the turbulent layer, the laminar resistance and the snow vertical velocity. They were optimized over a week in November 2018, a period characterized by extreme events in the region considered. The results demonstrated the effectiveness of the proposed approach, reducing the distance from observed data, and the method can be considered promising from the perspective taking into account a larger set of physical parameters, and validation over a wider time-window.

The objective calibration method originally performed on regional climate models is applied to a fine horizontal resolution Numerical Weather Prediction (NWP) model over a mainly continental domain covering the Alpine Arc. The method was implemented on the MeteoSwiss COSMO (consortium for a small-scale modeling) model with a resolution of 0.01° (approximately 1 km). For the model calibration, five tuning parameters of the parameterization schemes affecting turbulence, soil-surface exchange and radiation were chosen. A full year was simulated, with the history of the soil included (hindcast) to find the optimal parameter value. A different year has been used to give an independent assessment of the impact of the optimization process. Although the operational MeteoSwiss model is already a well-tuned configuration, the results showed that a slight model performance gain is obtained by using the Calibration of COSMO (CALMO) methodology.

Nowadays, cities are the preferred location for more than half of the human population and the places where major human-perceived climate change impacts occur. In an increasingly urbanized world, it is essential to represent such areas adequately in Numerical Weather Prediction (NWP) models, not only to correctly forecast air temperature, but also the human heat stress and the micro-climate phenomena induced by the cities. Among them, the best known is the Urban Heat Island (UHI) effect, which refers to the significantly higher temperatures experienced by a metropolitan area than its rural surroundings. Currently, the COSMO model employs a zero-order urban description, which is unable to correctly reproduce the UHI effect: cities are simply represented as natural lands with increased surface roughness length and reduced vegetation cover. However, the reproduction of the urban climate features in NWP and regional climate models is possible with the use of the so-called urban canopy models, that are able to parameterize the interaction between the urbanized surface and the overlying atmosphere. In this context, a new bulk parameterization scheme, TERRA_URB (TU), has been developed within the COSMO Consortium. TU offers an intrinsic representation of urban physics: the effect of buildings, streets and other man-made layers on the surface-atmosphere interaction is described by parameterizing the impervious water balance, translating the 3D urban-canopy parameters into bulk parameters with the Semi-empirical Urban canopy parameterization (SURY) and using the externally calculated anthropogenic heat flux as additional heat source. In this work, we present high-resolution simulations with the TU scheme, for different European cities, Turin, Naples and Moscow. An in-depth evaluation and verification of the performances of the recent COSMO version with TU scheme and new implemented physical parameterizations, such the ICON-like surface-layer turbulence scheme and the new formulation of the surface temperature, have been carried out. The validation concerned the 2-meter temperature and was performed for 1- or 2-week selected periods over the 3 European cities characterized by different environment and climate, namely the Moscow megacity in Russia and Turin and Naples in Italy. Even if the three domains are morphologically different, the results follow a common behavior. In particular, the activation of TERRA_URB provides a substantial improvement in capturing the UHI intensity and improving air temperature forecasts in urban areas. Potential benefits in the model performance also arise from a new turbulence scheme and the representation of skin-layer temperature (for vegetation). Our model framework provides promising perspectives for enhancing urban climate modelling, although further investigations are needed.

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.

Global climate projections suggest a significant intensification of summer heat extremes in the Middle East and North Africa (MENA). To assess regional impacts, and underpin mitigation and adaptation measures, robust information is required from climate downscaling studies, which has been lacking for the region. Here, we project future hot spells by using the Heat Wave Magnitude Index and a comprehensive ensemble of regional climate projections for MENA. Our results, for a business-as-usual pathway, indicate that in the second half of this century unprecedented super- and ultra-extreme heatwave conditions will emerge. These events involve excessively high temperatures (up to 56 degrees C and higher) and will be of extended duration (several weeks), being potentially life-threatening for humans. By the end of the century, about half of the MENA population (approximately 600 million) could be exposed to annually recurring super- and ultra-extreme heatwaves. It is expected that the vast majority of the exposed population (>90%) will live in urban centers, who would need to cope with these societally disruptive weather conditions. This research was supported by the EMME-CARE project that has received funding from the European Union's Horizon 2020 Research and Innovation Program, under Grant Agreement No. 856612, as well as matching co-funding by the Government of the Republic of Cyprus. It was co-funded by the European Regional Development Fund and the Republic of Cyprus through the Research Innovation Foundation CELSIUS Project EXCELLENCE/1216/0039. Publisher's Version

In this work, the results of a sensitivity study based on ICON-LAM simulations at 2.5 km of spatial resolution over the Italian area, driven by ECMWF IFS global data, are presented. The main aim is to provide a contribution to the selection of suitable parameterization schemes that result in more effective for a proper representation of the Italian climate features. Model evaluation was conducted in terms of the air temperature and precipitation for three subregions, comparing a set of 13 simulations against SCIA and E-OBS standard datasets. In addition, evaluation was also conducted against selected data stations scattered over the Italian area. We found that the ICON-LAM model was able to provide a good representation of the temperature over Italy, whereas non-negligible biases were observed for precipitation in certain regions. The model proved to be sensitive to changes in physical parameterization schemes. In particular, we found that the explicit treatment of deep convection and the “clouds as in turbulence” scheme for cloud cover allowed for a better representation of precipitation in the summer over the Alpine region. The single moment scheme is currently the best option for cloud microphysics.

It is often assumed that, as a consequence of global warming, a reduction of snow load on the ground should be expected. In reality, snow load is often depending on local orographic situations that can determine an increase of its height, even when the average snow height over the surrounding areas is reduced. Large snow loads on roofs during the winter season of 2005–2006 led to over 200 roof collapses in Central Europe. To proceed with the adaptation of the European standards for important buildings and infrastructures to the implications of climate change, the expected changes in the climatic loading shall be assessed in terms of the Eurocodes concept for characteristic values of variable climatic actions. The paper presents a procedure for derivation of snow load on ground from data on daily temperatures and precipitation. In addition, it allows to derive the characteristic snow loads from climate change projections and thus to evaluate the future trends in variation of snow loading. Analysis of these trends for the Italian territory is performed by comparing the results for several subsequent time periods of thirty years, with those obtained for the reference period 1951–1980. Results presented show a significant increase in the snow loading for the period 1981–2010 in many regions in north and east Italy in comparison with the reference period. It is suggested that a European project on snow load map shall be started, in order to help National Competent Authorities to redraft the national snow load maps for design with the Eurocodes. Keywords: Climate change, Snow load on structures, Adaptation of structural design, Climatic actions, Prediction of snow load, Design working life of structures, European snow load map

Wave climate projections at global scales are often of little direct use for local or regional coastal applications, where bathymetric gradients and coastal geometry dominate onshore wave propagation and transformation. In such systems, and even more in the case of semi-enclosed basins where coastal orography can play a major role in wind modulation, wave climate assessments require a specific effort, with particularly strict prescriptions in terms of model resolution and quality of the wind forcing. In this work, we provide a numerical modelling estimate of the expected variations of wave regime in the Adriatic Sea (a semi-enclosed basin of the Mediterranean Sea) under an IPCC RCP 8.5 climate change scenario at the end of the current century, focusing on the implications for energy modulation in the coastal regions. Results tend to confirm the evolution towards an overall decrease of wave storminess in the basin, as suggested by previous studies, but show that some regions might experience a local increase in the severity of the sea states impacting the coast. The model resolution and the unprecedented directional skills of the climatological wind forcings allow to ascribe this behaviour to a shift in the directional wind regime that can be related to a northward translation of the Mediterranean cyclones trajectory. Although in the absence of a quantitative assessment of the uncertainty associated with the choice of the climate model, our results give an account of the possible extent of the spatial variability of the response of coastal dynamics to mid-latitude storm tracks modification induced by climate change.

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

This study aims to assess the capabilities of a weather forecasting system based on simulations performed with the COSMO (COnsortium for Small-scale Modeling) model over a domain located in southern Italy, employing a spatial resolution of about 1 km, driven by ECMWF-IFS global data. The model is run daily at the Italian Aerospace Research Center (CIRA), and the evaluation was performed from January to May 2018 using a combination of observational data, specifically data provided by the CIRA meteorological station, wind profiler and ceilometer. Moreover, data provided by radio sounding located at Pratica di Mare and ground stations at two other locations were also used. A model configuration optimized through a tuning procedure over the domain considered was employed, while the evaluation was performed by comparing daily values of several variables and using standard monitoring indices. The results highlight that the model has good capability in reproducing daily values of temperature, while precipitation intensity is generally underestimated, even if rain patterns are well captured (alternating rainy and dry days). Good agreement is also reported for wind speed, especially at 100 and 500 m altitude. Regarding radio sounding data, the COSMO model configuration selected can reproduce the vertical profile of temperature and dew point, with the exception of inversion points. Evaluation against ceilometer data is achieved in terms of cloud height and planetary boundary layer height.

The results of a sensitivity analysis based on COSMO-LM (COnsortium for Small-Scale MOdeling&mdash, Lokal Model) simulations driven by ECMWF-IFS (European Centre for Medium-Range Weather Forecasts &ndash, Integrated Forecasting System). global data over a domain located in southern Italy are presented. Simulations have been performed at very high resolution (about 1 km). The main aim of this study is to individuate the most sensitive physical and numerical parameters of the model configuration, comparing a set of 18 simulations in terms of temperature and precipitation against ground observations. The parameters that result in having more influence for a proper representation of temperature and precipitation fields are the heat resistance length of laminar layer (which accounts for the high complexity of the interaction of the atmosphere with the underlying surface) and the minimal diffusion coefficient for heat. Temperature values are strongly influenced also by the vertical variation of critical relative humidity. An optimized tuning of these parameters allows COSMO-LM to improve the representation of simulated main features of this area, with significant bias reductions.

This study aimed to assess the capabilities of the regional climate model (RCM) COSMO-CLM in reproducing the main climate features of the Middle East and Northern Africa (MENA) domain. Two ERA-Interim-driven simulations were performed at 0.44° and 0.22° spatial resolution for the period 1979–2011 with an optimized model configuration. Model response has been analysed in terms of low level circulation, 2-m temperature, precipitation and cloud cover. Evaluation was conducted with respect to a combination of available ground observations, satellite products and reanalysis. Results reveal a good accuracy of the model in reproducing the circulation and a satisfactory representation of temperature, compared with other state-of-art RCMs, confirming that the albedo and aerosol parameterization schemes adopted lead to a remarkable improvement in model performances. The effects of increasing spatial resolution on the quality of the results have also been investigated. A comparison between the two simulations revealed that improvements with the resolution increase have been achieved for the temperature interannual variability, for monthly precipitation mean values, for cloud cover and for the representation of extreme precipitation events.

The results of a sensitivity work based on ERA-Interim driven COSMO-CLM simulations over the Middle East-North Africa (CORDEX-MENA) domain are presented. All simulations were performed at 0.44° spatial resolution. The purpose of this study was to ascertain model performances with respect to changes in physical and tuning parameters which are mainly related to surface, convection, radiation and cloud parameterizations. Evaluation was performed for the whole CORDEX-MENA region and six sub-regions, comparing a set of 26 COSMO-CLM runs against a combination of available ground observations, satellite products and reanalysis data to assess temperature, precipitation, cloud cover and mean sea level pressure. The model proved to be very sensitive to changes in physical parameters. The optimized configuration allows COSMO-CLM to improve the simulated main climate features of this area. Its main characteristics consist in the new parameterization of albedo, based on Moderate Resolution Imaging Spectroradiometer data, and the new parameterization of aerosol, based on NASA-GISS AOD distributions. When applying this configuration, Mean Absolute Error values for the considered variables are as follows: about 1.2 °C for temperature, about 15 mm/month for precipitation, about 9 % for total cloud cover, and about 0.6 hPa for mean sea level pressure.

This study presents a detailed analysis of the present and expected future extreme climate conditions over Italy through the use of some extreme indicators. Climate data for this analysis were provided by the regional climate model COSMO-CLM, using different grid spacing to ascertain the real importance of using higher resolution climate data, especially over such a complex topography as Italy. Four simulations were carried out at spatial resolutions of 0.125° and 0.0715°, driven by ERA-Interim Reanalysis and the CMCC-CM global model. We investigated the ability of the model to represent realistically the climatology of a subset of climate indicators defined by the Expert Team on Climate Change Detection and Indices (ETCCDI) for precipitation and temperature. Several high-resolution observational data sets available over some Italian regions were therefore used in order to offset the limited number of observations available over Italy in the E-OBS data set and its coarse grid. We found that the increase in resolution could have interesting benefits in representing such extreme indices, especially in the more orographically complex areas. Finally, we investigated future climate changes regarding extreme weather events expected under anthropogenic climate change scenarios, employing the IPCC RCP4.5 and RCP8.5 greenhouse gas concentrations, showing that such events are expected to increase over Italy.

This study presents the results of dynamically downscaled climate simulations over Italy produced with the COSMO-CLM model. Three simulations forced by ERA-Interim Reanalysis were conducted respectively at a spatial resolution of 0.22°, 0.125° and 0.0715° over the period 1979–2011. The results were analysed in terms of 2-m temperature and precipitation with the aim of assessing the model's ability to reproduce these important features of the Italian climate. The results were validated by comparing model output with different independent observational datasets. Values of temperature and precipitation show a general good agreement with observations, with a fair reduction of errors in all seasons as the resolution is increased. Two simulations at a spatial resolution of 0.0715°, driven by the global model CMCC-CM, were performed over the period 1971–2100, employing the IPCC RCP4.5 and RCP8.5 scenarios. Climate projections show a significant warming expected in Italy at the end of the 21st century, along with a general reduction in precipitation, particularly evident in spring and summer.

This study aimed to assess the capabilities of high-resolution simulations in reproducing the main features of the climate in the complex topography region of the Alps for the period 1971–2000. This is to provide a reliable tool for impact studies on local scale. Two simulations, driven by ERA-40 Reanalysis, have been carried out, respectively, at spatial resolutions of 0.125° and 0.0715° with the regional climate model COSMO-CLM. The model response has been analyzed in terms of 2 m temperature and precipitation, and comparisons with available observations have been carried out. A number of climate indices have also been analyzed, widely adopted to monitor changes in extreme climate events. Finally, the effects of increasing spatial resolution have also been investigated. The model at high spatial resolution (0.0715°) provides a satisfactory representation of temperature. The simulated precipitation patterns are also improved due to the high model resolution that allows reproducing localized precipitation phenomena with a medium-high error, especially where summer thunderstorms over the complex topography of the Alpine region occurs.

This work compares meteorological results from different regional climate model (RCM) implementations in the Mediterranean area, with a focus on the northern Adriatic Sea. The need to use these datasets as atmospheric forcings (wind and atmospheric pressure fields) for coastal hydrodynamic models to assess future changes in the coastal hydrodynamics, is the basis of the presented analysis. It would allow the assessment of uncertainties due to atmospheric forcings in providing coastal current, surge and wave climate changes from future implementations of hydrodynamic models. Two regional climate models, with different spatial resolutions, downscaled from two different global climate models (whose atmospheric components are, respectively, ECHAM4 and ECHAM5), were considered. In particular, the RCM delivered wind and atmospheric pressure fields were compared with measurements at four stations along the Italian Adriatic coast. The analyses were conducted using a past control period, 1960–1990, and the A1B IPCC future scenario (2070–2100). The chosen scenario corresponds to a world of very rapid economic and demographic growth that peaks in mid-century, with a rapid introduction of new efficient technologies, which balance fossil and non-fossil resources (IPCC, 2007). Consideration is given to the accuracy of each model at reproducing the basic statistics and the trends. The role of models' spatial resolution in reproducing global and local scale meteorological processes is also discussed. The Adriatic Sea climate is affected by the orography that produces a strengthening of north-eastern katabatic winds like bora. Therefore, spatial model resolution, both for orography and for a better resolution of coastline (Cavaleri et al., 2010), is one of the important factors in providing more realistic wind forcings for future hydrodynamic models implementations. However, also the characteristics in RCM setup and parameterization can explain differences between the datasets. The analysis from an ensemble of model implementation would provide more robust indications on climatic wind and atmospheric pressure variations. The scenario-control comparison shows a general increase in the mean atmospheric pressure values while a decrease in mean wind speed and in extreme wind events is seen, particularly for the datasets with higher spatial resolution.

The purpose of this work is the analysis of the capabilities of the Limited Area Model COSMO-CLM in simulating the main features of the observed climate over an area characterized by complex orography. Two sets of simulations of the XX century climate have been carried out, at a spatial resolution of 14 km, in order to provide a detailed description of the climate variability on local scale, useful for impact studies. A first experimental set-up consists of a set of simulations driven by the boundary conditions provided by the global model SINTEX-G. Our aim is to test the capability of this experimental set in realistically reproducing the main characteristics of the Alpine region climate under present climate conditions in order to provide a reliable tool for future climate scenario investigations. A second set of simulations has been carried out, driven by ERA40 reanalysis, in order to test the influence of the global model boundary conditions. Results are shown in terms of 2-m temperature and total precipitation and they are compared with two observational datasets: CRU and ARPA Piedmont. A good capability of the model in reproducing both the mean field and the seasonal cycle of temperature is observed, while the precipitation is affected by accuracy problems, related to the resolution. Though the model resolution is fine enough to reproduce fairly well the intensity of winter precipitation, it often fails in its localization. As far as summer precipitation is concerned, the model resolution appears too coarse to simulate the localized convection, which characterizes summer precipitation over Alps.

In this paper we have put forward a Bayesian framework for the analysis and testing of possible non-stationarities in extreme events. We use the extreme value theory to model temperature and precipitation data in the Dar es Salaam region, Tanzania. Temporal trends are modeled writing the location parameter of the generalized extreme value distribution in terms of deterministic functions of explanatory covariates. The analyses are performed using synthetic time series derived from a Regional Climate Model. The simulations, performed in an area around the Dar es Salaam city, Tanzania, take into account two Representative Concentration Pathways scenarios from the Intergovernmental Panel on Climate Change. Our main interest is to analyze extremes with high spatial and temporal resolution and to pursue this requirement we have adopted an individual grid box analysis approach. The approach presented in this paper is composed of the following key elements: (1) an advanced Bayesian method for the estimation of model parameters, (2) a rigorous procedure for model selection, and (3) uncertainty assessment and propagation. The results of our analyses are intended to be used for quantitative hazard and risk assessment and are presented in terms of hazard curves and probabilistic hazard maps. In the case study we found that for both the temperature and precipitation data, a linear trend in the location parameter was the only model performing better than the stationary one in the areas where evidence against the stationary model exists. © 2014, Springer Science+Business Media Dordrecht.

International audience; Future climate evolution is of primary importance for the societal, economical, political orientations and decision-making. It explains the increasing use of climate projections as input for quantitative impact studies, assessing vulnerability and defining adaptation strategies in different sectors. Here we analyse 17 national and representative use cases so as to identify the diversity of the demand for climate information depending on user profiles as well as the best practices, methods and tools that are needed to answer the different requests. A particular emphasis is put on the workflow that allows to translate climate data into suitable impact data, the way to deal with the different sources of uncertainty and to provide a suited product to users. We identified three complementary tools to close the gap between climate scientists and user needs: an efficient interface between users and providers; an optimized methodology to handle user requests and a portal to facilitate access to data and elaborated products. We detail in the paper how these three tools can limit the intervention of experts, educate users, and lead to the production of useful information. This work provides the basis on which the ENES (European Network for Earth System Modelling) Portal Interface for the Climate Impact Communities is built.

This study presents the results of high-resolution (0.125°) climate simulations over a Chinese area performed with an optimized configuration of the regional climate model COSMO-CLM, driven by ERA-Interim Reanalysis over the period 1979–2011 and by the output of the global model CMCC-CM (resolution 0.75°) over the period 1979–2100. The main aim of this work was to analyze the capabilities of COSMO-CLM to describe the climate of China in the recent past; validation revealed a good improvement in reproducing the precipitation and a reasonable improvement in 2 m temperature representation compared to results reported elsewhere. Climate projections, under the new IPCC RCP4.5 and RCP8.5 emission scenarios, show a significant warming expected in China over the 21st century, while precipitation changes are expected only on a regional scale: increases in precipitation are projected for both scenarios in the northern part of the domain, while the southern area will be affected by a reduction in winter.