In the face of climate change, the assessment of land transport infrastructure exposure towards adverse climate events is of major importance for Europe's economic prosperity and social wellbeing. In this study, a climate index estimating rainfall patterns which trigger landslides in central Europe is analysed until the end of this century and compared to present-day conditions. The analysis of the potential future development of landslide risk is based on an ensemble of dynamically downscaled climate projections which are driven by the SRES A1B socio-economic scenario. Resulting regional-scale climate change projections across central Europe are concatenated with Europe's road and railway network. Results indicate overall increases of landslide occurrence. While flat terrain at low altitudes exhibits an increase of about 1 more potentially landslide-inducing rainfall period per year until the end of this century, higher elevated regions are more affected and show increases of up to 14 additional periods. This general spatial distribution emerges in the near future (2021–2050) but becomes more pronounced in the remote future (2071–2100). Since largest increases are to be found in Alsace, potential impacts of an increasing amount of landslides are discussed using the example of a case study covering the Black Forest mountain range in Baden-Württemberg by further enriching the climate information with additional geodata. The findings derived are suitable to support political decision makers and European authorities in transport, freight and logistics by offering detailed information on which parts of Europe's ground transport network are at particularly high risk concerning landslide activity.

Lake surface temperature (LST) is a key characteristic of lakes, shaping the ecological properties of these inland water bodies and their environment. This study aims at establishing a long-term, high-quality, monthly LST dataset within the European Alps reaching back to 1880, which is provided to the scientific community for further research. Therefore monthly temperature records from Austrian lakes covering a period of about six decades are digitized from hydrological yearbooks. Clustering techniques (rotated empirical orthogonal functions and hierarchical cluster analysis) are used to identify groups of lakes signified by inner similarity and outer separation. These are not only used for an overall quality assessment, but also provide optimal starting conditions for the application of a homogenization procedure, warranting homogeneous LST data from 1950 onwards. LST reconstructions back to 1880 are derived from atmospheric covariates (provided by HISTALP) via sets of transfer-functions. Applied transfer-functions have passed a selection process ensuring mathematical, physical and quality requirements. They are selected from about 160 million candidates according to skill, which is determined through a comprehensive assessment based on validation experiments and several performance measures. Results show overall high skill following a seasonal cycle. From 1880 to 1950 LSTs feature generally slight increases accompanied by a succession of climate states. These are in alignment with outstanding climate periods and sustained, far-reaching repercussions triggered by significant events, which are known from historical documents. LST developments throughout the second half of the twentieth century up to date are characterized by a decline until the mid-1980s, indicating the impact of industrial aerosols. This behaviour is superseded by a steep increase, revealing the gradual unmasking of the anthropogenic greenhouse effect by the continuous reduction of aerosol loads in the atmosphere. The latter substantiates man-made climate change, whose prove is based on atmospheric variables by different data pertaining to the hydrosphere. Potential research hypotheses corresponding to various fields of science that may be investigated by using the here established LST dataset are considered. We hope that these data sets and associated findings will make a contribution to the broader research community.

We apply a direct downscaling approach to generate ensembles of local-scale glacier mass balance projections from coarse-scale general circulation model (GCM) data. The general modes of the atmospheric circulation over a large geographical region are linked statistically to Peyto Glacier's winter and summer balance separately. Our study focuses on the generation of ensemble projections derived from simulations with ECHAM5-MPIOM forced with Intergovernmental Panel on Climate Change - Special Report on Emission Scenarios (IPCC-SRES) A1B and B1. The resulting ensembles of mass balance projections show a moderate increase in winter balance and a steep decrease in summer balance. Together these results suggest continued frontal recession and downwasting of Peyto Glacier and a shift of the equilibrium line altitude by at least 100 m above that estimated for the 1966–2001 period suggesting that very little of the glacier will remain by 2100. Copyright © 2008 Crown in the right of Canada. Published by John Wiley & Sons, Ltd.

In the face of climate change, the assessment of land transport infrastructure exposure towards adverse climate events is of major importance for Europe's economic prosperity and social wellbeing. Robust and reliable information on the extent of climate change and its projected future impacts on roads and railways are of prime importance for proactive planning and the implementation of targeted adaptation strategies. Among various menacing natural hazards, landslides stand out as most destructive hazards to the functional effectivity and structural integrity of land-bound transport systems, since they cause long-lasting downtimes and exceedingly expensive repair works. Periods of heavy precipitation persisting over several days are known to be a major trigger for increased landslide activity. Along with climate change such events can be expected to increase in frequency, duration and intensity over the decades to come. In this study, a Climate Index (CI) picturing rainfall patterns which trigger landslides in Central Europe is analyzed until the end of this century and compared to present day conditions. The analysis of potential future developments is based on an ensemble of dynamically downscaled climate projections which are driven by the SRES A1B socio-economic scenario. Resulting regional scale climate change projections across Central Europe are concatenated with Europe's road and railway network. Results indicate overall increases of landslide occurrences. While flat terrain at low altitudes exhibits increases of about two more landslide events per year until the end of this century, higher elevated regions are more affected and show increases of up to eight additional events. This general spatial distribution emerges already in the near future (2021–2050) but gets more pronounced in the remote future (2071–2100). Largest increases are to be found in the Alsace. Consequently, potential impacts of increasing landslide events are discussed using the example of a case study covering the Black Forest mountain range in Baden-Württemberg by further enriching the climate information with and additional geodata. Derived findings are suitable to support political decision-makers and European authorities in transport, freight and logistics by offering detailed information on which parts of Europe's land-bound transport network are at particularly high risk concerning landslide activity. This study supports proactive development of adaption strategies and the realization of cost-efficient and effective protection programmes as well as the generation of guidelines for climate proofing. This refers to the design of transport networks, intermodal logistics as well as the setting up of maintenance and reinforcement strategies in order to safeguard one of the most essential backbones of Europe's economic prosperity.