Global warming may exacerbate soil moisture droughts. However, evaluations of future droughts are not conclusive because of the uncertainty in estimates of future warming. Here, we estimate the impacts of differential climate change at 1-3 K on the largest soil moisture droughts across Europe to understand the implications of the goal of the 2015 Paris climate change agreement to constrain global warming to below 1.5 degrees. The results show that under an increase of 3 K compared to 1.5 K, drought area will increase by 40% (± 24%) and will potentially affect 42% more people. Similarly, an event like the 2003 drought will become two times more frequent. Adapting to a temperature increase of 3 K implies adjusting to an increase

Abstract. There is growing evidence that climate change will alter water availability in Europe. Here, we investigate how hydrological low flows are affected under different levels of future global warming (i.e. 1.5, 2, and 3 K with respect to the pre-industrial period) in rivers with a contributing area of more than 1000 km 2 . The analysis is based on a multi-model ensemble of 45 hydrological simulations based on three representative concentration pathways (RCP2.6, RCP6.0, RCP8.5), five Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation models (GCMs: GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, MIROC-ESM-CHEM, NorESM1-M) and three state-of-theart hydrological models (HMs: mHM, Noah-MP, and PCR-GLOBWB). High-resolution model results are available at a spatial resolution of 5 km across the pan-European domain at a daily temporal resolution. Low river flow is described as the percentile of daily streamflow that is exceeded 90 % of the time. It is determined separately for each GCM/HM combination and warming scenario. The results show that the low-flow change signal amplifies with increasing warming levels. Low flows decrease in the Mediterranean region, while they increase in the Alpine and Northern regions. In the Mediterranean, the level of warming amplifies the signal from −12 % under 1.5 K, compared to the baseline period 1971-2000, to −35 % under global warming of 3 K, largely due to the projected decreases in annual precipitation. In contrast, the signal is amplified from +22 (1.5 K) to +45 % (3 K) in the Alpine region due to changes in snow accumulation. The changes in low flows are significant for regions with relatively large change signals and under higher levels of warming. However, it is not possible to distinguish climate-induced differences in low flows between 1.5 and 2 K warming because of (1) the large inter-annual variability which prevents distinguishing statistical estimates of periodaveraged changes for a given GCM/HM combination, and (2) the uncertainty in the multi-model ensemble expressed by the signal-to-noise ratio. The contribution by the GCMs to the uncertainty in the model results is generally higher than the one by the HMs. However, the uncertainty due to HMs cannot be neglected. In the Alpine, Northern, and Mediterranean regions, the uncertainty contribution by the HMs is partly higher than those by the GCMs due to different representations of processes such as snow, soil moisture and evapotranspiration. Based on the analysis results, it is recommended (1) to use multiple HMs in climate impact studies and (2) to embrace uncertainty information on the multimodel ensemble as well as its single members in the adaptation process.

Severe river floods often result in huge economic losses and fatalities. Since 1980, almost 1500 such events have been reported in Europe. This study investigates climate change impacts on European floods under 1.5, 2, and 3 K global warming. The impacts are assessed employing a multi-model ensemble containing three hydrologic models (HMs: mHM, Noah-MP, PCR-GLOBWB) forced by five CMIP5 general circulation models (GCMs) under three Representative Concentration Pathways (RCPs 2.6, 6.0, and 8.5). This multi-model ensemble is unprecedented with respect to the combination of its size (45 realisations) and its spatial resolution, which is 5 km over the entirety of Europe. Climate change impacts are quantified for high flows and flood events, represented by 10% exceedance probability and annual maxima of daily streamflow, respectively. The multi-model ensemble points to the Mediterranean region as a hotspot of changes with significant decrements in high flows from −11% at 1.5 K up to −30% at 3 K global warming mainly resulting from reduced precipitation. Small changes (< ±10%) are observed for river basins in Central Europe and the British Isles under different levels of warming. Projected higher annual precipitation increases high flows in Scandinavia, but reduced snow melt equivalent decreases flood events in this region. Neglecting uncertainties originating from internal climate variability, downscaling technique, and hydrologic model parameters, the contribution by the GCMs to the overall uncertainties of the ensemble is in general higher than that by the HMs. The latter, however, have a substantial share in the Mediterranean and Scandinavia. Adaptation measures for limiting the impacts of global warming could be similar under 1.5 K and 2 K global warming, but have to account for significantly higher changes under 3 K global warming.

The 2003 drought event in Europe had major implications on many societal sectors, including energy production, health, forestry and agriculture. The reduced availability of water accompanied by high temperatures led to substantial economic losses on the order of 1.5 Billion Euros, in agriculture alone.

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[1] In this study, high-resolution climate change data from the regional climate models COSMO-CLM, HIRHAM, RegCM, and REMO were evaluated in the Greater Alpine Region (GAR; 4°W-19°W and 43°N-49°N) and three additional subareas of 1.5°by 1°i n size. Evaluation statistics include mean temperature and precipitation, frequency of days with precipitation over 1 mm and over 15 mm, 90% quantile of the frequency distribution, and maximum number of consecutive dry days. The evaluation for the period indicates that the models reproduce spatial precipitation patterns and the annual cycle. The mean precipitation domain bias varies between 11% and 40% in winter season and between À14.5% and 11% in summer. Larger errors are found for other statistics and in the various regions. No single best model could be identified comparing modeled precipitation characteristics with observational reference. The study shows that there is still high uncertainty in the expected climate change. Furthermore, future temperature and precipitation changes simulated with different SRES scenarios and calculated by different RCMs overlap. The temperature calculations for the period 2071-2100 related to the period 1961-1990 in the GAR area show an increase in the monthly mean 2m temperature of up to 4.8 K in summer. In the GAR area, a precipitation decrease of up to 29% in summer and precipitation increase of approximately 20% in the winter season is simulated. Summer and autumn temperatures are expected to increase more than winter and spring temperatures. Detailed analysis reveals that the different regional climate model runs based on different regional models, different driving global models and different emission scenarios show similar trends, but differ in the magnitude of the expected climate change signal. All models seem to agree on the increased frequency of high-precipitation events in the winter season.Citation: Smiatek, G., H. Kunstmann, R. Knoche, and A. Marx (2009), Precipitation and temperature statistics in high-resolution regional climate models: Evaluation for the European Alps,

Simulations of water fluxes at high spatial resolution that consistently cover historical observations, seasonal forecasts, and future climate projections are key to providing climate services aimed at supporting operational and strategic planning, and developing mitigation and adaptation policies. The End-to-end Demonstrator for improved decision-making in the water sector in Europe (EDgE) is a proof-of-concept project funded by the Copernicus Climate Change Service program that addresses these requirements by combining a multimodel ensemble of state-of-the-art climate model outputs and hydrological models to deliver sectoral climate impact indicators (SCIIs) codesigned with private and public water sector stakeholders from three contrasting European countries. The final product of EDgE is a water-oriented information system implemented through a web application. Here, we present the underlying structure of the EDgE modeling chain, which is composed of four phases: 1) climate data processing, 2) hydrological modeling, 3) stakeholder codesign and SCII estimation, and 4) uncertainty and skill assessments. Daily temperature and precipitation from observational datasets, four climate models for seasonal forecasts, and five climate models under two emission scenarios are consistently downscaled to 5-km spatial resolution to ensure locally relevant simulations based on four hydrological models. The consistency of the hydrological models is guaranteed by using identical input data for land surface parameterizations. The multimodel outputs are composed of 65 years of historical observations, a 19-yr ensemble of seasonal hindcasts, and a century-long ensemble of climate impact projections. These unique, high-resolution hydroclimatic simulations and SCIIs provide an unprecedented information system for decision-making over Europe and can serve as a template for water-related climate services in other regions.

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