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Coupled atmosphere-ocean general circulation models (GCMs) simulate different realizations of possible future climates at global scale under contrasting scenarios of land-use and greenhouse gas emissions. Such data require several additional processing steps before it can be used to drive impact models. Spatial downscaling, typically by regional climate models (RCM), and bias-correction are two such steps that have already been addressed for Europe. Yet, the errors in resulting daily meteorological variables may be too large for specific model applications. Crop simulation models are particularly sensitive to these inconsistencies and thus require further processing of GCM-RCM outputs. Moreover, crop models are often run in a stochastic manner by using various plausible weather time series (often generated using stochastic weather generators) to represent climate time scale for a period of interest (e.g. 2000 ± 15 years), while GCM simulations typically provide a single time series for a given emission scenario. To inform agricultural policy-making, data on near- and medium-term decadal time scale is mostly requested, e.g. 2020 or 2030. Taking a sample of multiple years from these unique time series to represent time horizons in the near future is particularly problematic because selecting overlapping years may lead to spurious trends, creating artefacts in the results of the impact model simulations. This paper presents a database of consolidated and coherent future daily weather data for Europe that addresses these problems. Input data consist of daily temperature and precipitation from three dynamically downscaled and bias-corrected regional climate simulations of the IPCC A1B emission scenario created within the ENSEMBLES project. Solar radiation is estimated from temperature based on an auto-calibration procedure. Wind speed and relative air humidity are collected from historical series. From these variables, reference evapotranspiration and vapour pressure deficit are estimated ensuring consistency within daily records. The weather generator ClimGen is then used to create 30 synthetic years of all variables to characterize the time horizons of 2000, 2020 and 2030, which can readily be used for crop modelling studies. [ABSTRACT FROM AUTHOR]

The projected climate change signals of a five-member high resolution ensemble, based on two global climate models (GCMs: ECHAM5 and CCCma3) and two regional climate models (RCMs: CLM and WRF) are analysed in this paper (Part II of a two part paper). In Part I the performance of the models for the control period are presented. The RCMs use a two nest procedure over Europe and Germany with a final spatial resolution of 7 km to downscale the GCM simulations for the present (1971-2000) and future A1B scenario (2021-2050) time periods. The ensemble was extended by earlier simulations with the RCM REMO (driven by ECHAM5, two realisations) at a slightly coarser resolution. The climate change signals are evaluated and tested for significance for mean values and the seasonal cycles of temperature and precipitation, as well as for the intensity distribution of precipitation and the numbers of dry days and dry periods. All GCMs project a significant warming over Europe on seasonal and annual scales and the projected warming of the GCMs is retained in both nests of the RCMs, however, with added small variations. The mean warming over Germany of all ensemble members for the fine nest is in the range of 0.8 and 1.3 K with an average of 1.1 K. For mean annual precipitation the climate change signal varies in the range of −2 to 9 % over Germany within the ensemble. Changes in the number of wet days are projected in the range of ±4 % on the annual scale for the future time period. For the probability distribution of precipitation intensity, a decrease of lower intensities and an increase of moderate and higher intensities is projected by most ensemble members. For the mean values, the results indicate that the projected temperature change signal is caused mainly by the GCM and its initial condition (realisation), with little impact from the RCM. For precipitation, in addition, the RCM affects the climate change signal significantly. [ABSTRACT FROM AUTHOR]

Summary This paper presents a review of trend analysis of extreme precipitation and hydrological floods in Europe based on observations and future climate projections. The review summaries methods and methodologies applied and key findings from a large number of studies. Reported analyses of observed extreme precipitation and flood records show that there is some evidence of a general increase in extreme precipitation, whereas there are no clear indications of significant trends at large-scale regional or national level of extreme streamflow. Several studies from regions dominated by snowmelt-induced peak flows report decreases in extreme streamflow and earlier spring snowmelt peak flows, likely caused by increasing temperature. The review of likely future changes based on climate projections indicates a general increase in extreme precipitation under a future climate, which is consistent with the observed trends. Hydrological projections of peak flows show large impacts in many areas with both positive and negative changes. A general decrease in flood magnitude and earlier spring floods are projected for catchments with snowmelt-dominated peak flows, which is consistent with the observed trends. Finally, existing guidelines in Europe on design flood and design rainfall estimation are reviewed. The review shows that only few countries have developed guidelines that incorporate a consideration of climate change impacts. [ABSTRACT FROM AUTHOR]

This paper addresses the current knowledge on climate change impacts on mass movement activity in mountain environments by illustrating characteristic cases of debris flows, rock slope failures and landslides from the French, Italian, and Swiss Alps. It is expected that events are likely to occur less frequently during summer, whereas the anticipated increase of rainfall in spring and fall could likely alter debris-flow activity during the shoulder seasons (March, April, November, and December). The magnitude of debris flows could become larger due to larger amounts of sediment delivered to the channels and as a result of the predicted increase in heavy precipitation events. At the same time, however, debris-flow volumes in high-mountain areas will depend chiefly on the stability and/or movement rates of permafrost bodies, and destabilized rock glaciers could lead to debris flows without historic precedents in the future. The frequency of rock slope failures is likely to increase, as excessively warm air temperatures, glacier shrinkage, as well as permafrost warming and thawing will affect and reduce rock slope stability in the direction that adversely affects rock slope stability. Changes in landslide activity in the French and Western Italian Alps will likely depend on differences in elevation. Above 1500 m asl, the projected decrease in snow season duration in future winters and springs will likely affect the frequency, number and seasonality of landslide reactivations. In Piemonte, for instance, 21st century landslides have been demonstrated to occur more frequently in early spring and to be triggered by moderate rainfalls, but also to occur in smaller numbers. On the contrary, and in line with recent observations, events in autumn, characterized by a large spatial density of landslide occurrences might become more scarce in the Piemonte region. [ABSTRACT FROM AUTHOR]

In a changing climate, it is likely that precipitation patterns will experience shifts in amount and seasonality, with a tendency towards increased drought in many parts of Europe. In order to investigate what could be some of the feedbacks of dry conditions on temperature, this paper has investigated close to 30 European locations to assess the influence of observed dry summer days on daily maximum temperature ( Tmax) as well as a clustering of rainless days, and finally the temperature impact related to drought conditions as defined by the Standardized Precipitation Index. The results show that for the three main European climatic regions investigated ('Mediterranean', 'Maritime', 'Continental'), the influence of rainless days is discernible, with an average difference between mean summer Tmax and Tmax during rainless days only of up to 1.5 °C. A further aim of the study is to determine whether recent shifts in the occurrence of rainless days during the summer have a bearing on temperature trends. Results show that shifts in rainless days explain only a fraction of the observed temperature change at the locations studied, thereby hinting that the enhanced greenhouse effect remains the dominant mechanism for temperature change. Finally, using a regional climate model, very preliminary insight into a 'greenhouse climate' highlights the fact that changes in dry conditions seem to confirm the findings for current climate, i.e. they account for only a fraction of the increase in temperatures. Copyright © 2012 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

This paper proposes an optimal method for estimating time-dependent climate change signals from general circulation models. The basic idea is to identify vectors that maximize the mean-square detection statistic derived from optimal fingerprinting techniques. The method also provides an objective and systematic procedure for identifying the limit to which a signal can be restricted in space and time without losing detectability. As an illustration, the method is applied to the Coupled Model Intercomparison Project, phase 3 multimodel dataset to determine the continental seasonal-mean anomaly in surface air temperature and precipitation that is most detectable, on average, in these models. Anomalies in seasonal-mean surface air temperature are detectable in all seasons by almost all models on all continents but Europe; seasonal-mean anomalies over Europe are undetectable for some models, though this does not preclude other expressions of the signal, such as those that include longer time averages or time-lag information, from being detectable. Detectability in seasonal-mean temperature is found not only for multidecadal warming trends but also for cooling after major volcanic eruptions. In contrast, seasonal-mean precipitation anomalies are detectable in only a few models for averages over 5 yr or more, suggesting that the signal should include more spatiotemporal detail to be detectable across more models. Nevertheless, of the precipitation anomalies that are detectable, the signal appears to be of two characters: a systematic trend and enhanced frequency of extreme values. These results derived from twentieth-century simulations appear to be consistent with previous studies based on twenty-first-century simulations with larger signal-to-noise ratios. [ABSTRACT FROM AUTHOR]

Satellite-derived high-resolution precipitation products (HRPP) have been developed to address the needs of the user community and are now available with 0.25° × 0.25° (or less) subdaily resolutions. This paper evaluates a number of commonly available satellite-derived HRPPs covering northwest Europe over a 6-yr period. Precipitation products include the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA), the Climate Prediction Center (CPC) morphing (CMORPH) technique, the CPC merged microwave technique, the Naval Research Laboratory (NRL) blended technique, and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) technique. In addition, the Geosynchronous Operational Environmental Satellite (GOES) precipitation index (GPI) and the European Centre for Medium-Range Weather Forecasting (ECMWF) operational forecast model products are included for comparison. Surface reference data from the European radar network is used as ground truth, supported by the Global Precipitation Climatology Centre (GPCC) precipitation gauge analysis and gauge data over the United Kingdom. Measures of correlation, bias ratio, probability of detection, and false alarm ratio are used to evaluate the products. Results show that satellite products generally exhibit a seasonal cycle in correlation, bias ratio, probability of detection, and false alarm ratio, with poorer statistics during the winter. The ECMWF model also shows a seasonal cycle in the correlation, although the results are poorer during the summer, while the bias ratio, probability of detection, and false alarm ratio are consistent through all seasons. Importantly, all the satellite HRPPs underestimate precipitation over northwest Europe in all seasons. [ABSTRACT FROM AUTHOR]

Summary: The European Alps are one region of the world where climate-driven changes are already perceptible, as exemplified by the general retreat of mountain glaciers over past decades. Temperatures have risen by up to 2°C since 1900 particularly at high elevations, a rate that is roughly three times the global-average 20th century warming. Regional climate models suggest that by 2100, winters in Switzerland may warm by 3–5°C and summers by 6–7°C according to greenhouse-gas emissions scenarios, while precipitation is projected to increase in winter and sharply decrease in summer. The impacts of these levels of climatic change will affect both the natural environment and a number of economic activities. Alpine glaciers may lose between 50% and 90% of their current volume and the average snowline will rise by 150m for each degree of warming. Hydrological systems will respond in quantity and seasonality to changing precipitation patterns and to the timing of snow-melt in the Alps, with a greater risk of flooding during the spring and droughts in summer and fall. The direct and indirect impacts of a warming climate will affect key economic sectors such as tourism, hydropower, agriculture and the insurance industry that will be confronted to more frequent natural disasters. This paper will thus provide an overview of the current state of knowledge on climatic change and its impacts on the Alpine world. [ABSTRACT FROM AUTHOR]

Abstract: Understanding climate patterns, with their decisive influence on plant distribution and development, is crucial to understanding the history of vegetation patterns in Europe during the Miocene. This paper presents the detailed analyses of several precipitation parameters, including monthly precipitation of the wettest, driest and warmest months, for five Miocene stages. In conjunction with seasonality of temperature, those parameters provide a meaningful measure of continentality and can help to document Miocene climate changes and patterns and their possible influence on vegetation. Climate reconstructions provided here are entirely based on palaeobotanical material. In total, 169 Miocene floras were selected, including 14 Burdigalian, 41 Langhian, 40 Serravallian, 36 Tortonian, and 38 Messinian localities. All floras were analysed using the Coexistence Approach. The analysis of several precipitation parameters, the statistical inter-correlation of results, and the comparison with modern patterns provides a comprehensive account on Miocene precipitation. Miocene climatic changes after the Mid Miocene Climatic Optimum (MMCO) are evidenced in our data set by three major factors, i.e. (1) increasing seasonality of temperature, (2) changes in the annual distribution of precipitation towards a precipitation peak in summer, and (3) a late increase of longitudinal gradients of precipitation parameters. Evidence of continental climate in Eastern Europe first appears during the Messinian. In addition to changes in temperature, shifts in the annual distribution of precipitation may have played a major role in post-Langhian climate changes. However, the most significant climatic transformations occurred later, from the end of Miocene through to the present. Several authors have described patterns of vegetation development in Europe that are in good agreement with our finding of the first evidence for continental climate in Eastern Europe during the Messinian. Our data do not support an onset of opening of vegetation during the Tortonian or even earlier, as has been described for some parts of Eastern and Southern Europe. Possibly either non climatic parameters influenced such an early development, or our data lack the required resolution and/or spatial coverage to fully decipher the influence of continentality on vegetation and to correlate climate and vegetation statistically. Nevertheless, climatic data that quantify continentality can provide a sound basis for explaining the expansion of grassland in Eurasia. [Copyright &y& Elsevier]

This paper analyzes the soil–atmosphere feedbacks and uncertainties under current (1960–1990) and plausible future climate conditions (2070–2100, using the A2 greenhouse gases emission scenario). For this purpose, two vegetation descriptions differing only in the grassland and grass-with-trees proportion in some parts of the domain have been created. The combination of these two different climate scenarios and two vegetation descriptions defines four different 30-year experiments, which have been completed using a regional climate model. The domain is centered around the Mediterranean basin and covers most of Europe. The study focuses on the summer season when there are major differences between the two vegetation descriptions and when the impact of land–surface processes on precipitation is largest. Present climate experiments show large evapotranspiration differences over areas where vegetation changes have taken place. Precipitation increases (up to 3 mm day−1 in some regions) follow evapotranspiration increases, although with a more complex spatial structure. These results indicate a high sensitivity at regional scales of summer precipitation processes to vegetation changes. Future climate simulations show very similar changes to those observed in the current climate experiments. This indicates that the impacts of climate change are relatively independent to the land-cover descriptions used in this study. [ABSTRACT FROM AUTHOR]