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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]

Results from high resolution 7-km WRF regional climate model (RCM) simulations are used to analyse changes in the occurrence frequencies of heat waves, of precipitation extremes and of the duration of the winter time freezing period for highly populated urban areas in Central Europe. The projected climate change impact is assessed for 11 urban areas based on climate indices for a future period (2021-2050) compared to a reference period (1971-2000) using the IPCC AR4 A1B Scenario as boundary conditions. These climate indices are calculated from daily maximum, minimum and mean temperatures as well as precipitation amounts. By this, the vulnerability of these areas to future climate conditions is to be investigated. The number of heat waves, as well as the number of single hot days, tropical nights and heavy precipitation events is projected to increase in the near future. In addition, the number of frost days is significantly decreased. Probability density functions of monthly mean summer time temperatures show an increase of the 95th percentile of about 1-3 °C for the future compared with the reference period. The projected increase of cooling and decrease of heating degree days indicate the possible impact on urban energy consumption under future climate conditions. [ABSTRACT FROM AUTHOR]

Precipitation extremes affect various economic sectors and may result in substantial costs for societies. Future projections of such extreme occurrences are needed to successfully develop robust regional adaptation strategies. Model ensemble-based approaches provide a higher level of confidence since they compensate to some degree for the uncertainties of individual climate model projections. An ensemble of twelve regional climate projections from five regional climate models was used to evaluate the suitability of a modified version of the Rainfall Anomaly Index (mRAI) as an alternative to the Standardised Precipitation Index (SPI) in assessing future precipitation conditions. We compared frequency distributions and trends of the mRAI with the SPI for a test region that is climatologically representative of Central Eastern Europe. Both indices are highly correlated with each other at all tested timescales-both for stations and for regionally averaged data-with Pearson correlation coefficients >>0.9 and Spearman correlation coefficients >0.99. There are no significant differences in their frequency distributions, although the mRAI shows slightly higher frequencies in the classes of 'moderately dry' to 'very dry' conditions. The change signals revealed by SPI and mRAI are very similar for mean changes as well as for changes in the extremes. Considering the large bandwidth of change signals of individual regional climate projections, the mRAI provides sufficiently robust results for the evaluation of future precipitation anomaly trends. The notably more complex calculation of the SPI has no appreciable advantage for this application. [ABSTRACT FROM AUTHOR]

Mountain ecosystems are currently experiencing the strongest climatic warming and the largest changes in land-use during the last millennia. The impacts of these changes on soils and their roles in the cycling of carbon and nutrients are, however, largely unknown. Here, we define mountain soils as soils from mountainous areas with cool summers and cold winters and thus, soils from ecosystems that are influenced by snow and ice and where biogeochemical processes are limited by temperature. Because climatic conditions, soil properties, plant species and productivity vary at a small scale in mountains, they provide a unique natural but a seldom used laboratory to study soil processes. In this special issue, we compile different studies on soils from European mountains, reaching from the functioning of mountain soils along natural climatic gradients to responses of greenhouse gas fluxes from mountain soils to experimental warming, soil frost and changes in precipitation. [ABSTRACT FROM AUTHOR]

Extreme river floods have been a substantial natural hazard in Europe over the past centuries, and radiative effects of recent anthropogenic changes in atmospheric composition are expected to cause climate changes, especially enhancement of the hydrological cycle, leading to an increased flood risk. For the past few decades, however, observations from Europe do not show a clear increase in flood occurrence rate. Here we present longer-term records of winter and summer floods in two of the largest rivers in central Europe, the Elbe and Oder rivers. For the past 80 to 150?yr, we find a decrease in winter flood occurrence in both rivers, while summer floods show no trend, consistent with trends in extreme precipitation occurrence. The reduction in winter flood occurrence can partly be attributed to fewer events of strong freezing-following such events, breaking river ice at the end of the winter may function as a water barrier and enhance floods severely. Additionally, we detect significant long-term changes in flood occurrence rates in the sixteenth to nineteenth centuries, and conclude that reductions in river length, construction of reservoirs and deforestation have had minor effects on flood frequency. [ABSTRACT FROM AUTHOR]