A decrease in rockfall probability under climate change conditions in Germany

The effect of climate change on rockfalls in the German low mountain regions is investigated following two different approaches. The first approach uses a logistic regression model that describes the combined effect of precipitation, freeze–thaw cycles, and fissure water on rockfall probability. The climate change signal for the past 6 decades is analysed by applying the model to meteorological observations. The possible effect of climate change until the end of the century is explored by applying the statistical model to the output of a multi-model ensemble of 23 regional climate scenario simulations. It is found that the number of days per year exhibiting an above-average probability for rockfalls has mostly been decreasing during the last few decades. Statistical significance is, however, present at only a few sites. A robust and statistically significant decrease can be seen in the Representative Concentration Pathway (RCP) climate scenario 8.5 (RCP8.5) simulations for Germany and neighbouring regions, locally falling below −10 % when comparing the last 30 years of the 20th century to the last 30 years of the 21st century. The most important factor determining the projected decrease in rockfall probability is a reduction in the number of freeze–thaw cycles expected under future climate conditions. For the second approach four large-scale meteorological patterns that are associated with enhanced rockfall probability are identified from reanalysis data. The frequency of all four patterns exhibits a seasonal cycle that maximises in the cold half of the year (winter and spring). Trends in the number of days that can be assigned to these patterns are determined both in meteorological reanalysis data and in climate simulations. In the reanalysis no statistically significant trend is found. For the future scenario simulations all climate models show a statistically significant decrease in the number of rockfall-promoting weather situations

a consensus view among methods with different system identification and tracking criteria

The Mediterranean storm track constitutes a well-defined branch of the North Hemisphere storm track and is characterised by small but intense features and frequent cyclogenesis. The goal of this study is to assess the level of consensus among cyclone detection and tracking methods (CDTMs), to identify robust features and to explore sources of disagreement. A set of 14 CDTMs has been applied for computing the climatology of cyclones crossing the Mediterranean region using the ERA-Interim dataset for the period 1979–2008 as common testbed. Results show large differences in actual cyclone numbers identified by different methods, but a good level of consensus on the interpretation of results regarding location, annual cycle and trends of cyclone tracks. Cyclogenesis areas such as the north-western Mediterranean, North Africa, north shore of the Levantine basin, as well as the seasonality of their maxima are robust features on which methods show a substantial agreement. Differences among methods are greatly reduced if cyclone numbers are transformed to a dimensionless index, which, in spite of disagreement on mean values and interannual variances of cyclone numbers, reveals a consensus on variability, sign and significance of trends. Further, excluding ‘weak’ and ‘slow’ cyclones from the computation of cyclone statistics improves the agreement among CDTMs. Results show significant negative trends of cyclone frequency in spring and positive trends in summer, whose contrasting effects compensate each other at annual scale, so that there is no significant long- term trend in total cyclone numbers in the Mediterranean basin in the 1979–2008 period

Objective climatology of cyclones in the Mediterranean region: a consensus view among methods with different system identification and tracking criteria

The Mediterranean storm track constitutes a well-defined branch of the North Hemisphere storm track and is characterised by small but intense features and frequent cyclogenesis. The goal of this study is to assess the level of consensus among cyclone detection and tracking methods (CDTMs), to identify robust features and to explore sources of disagreement. A set of 14 CDTMs has been applied for computing the climatology of cyclones crossing the Mediterranean region using the ERA-Interim dataset for the period 1979–2008 as common testbed. Results show large differences in actual cyclone numbers identified by different methods, but a good level of consensus on the interpretation of results regarding location, annual cycle and trends of cyclone tracks. Cyclogenesis areas such as the north-western Mediterranean, North Africa, north shore of the Levantine basin, as well as the seasonality of their maxima are robust features on which methods show a substantial agreement. Differences among methods are greatly reduced if cyclone numbers are transformed to a dimensionless index, which, in spite of disagreement on mean values and interannual variances of cyclone numbers, reveals a consensus on variability, sign and significance of trends. Further, excluding ‘weak’ and ‘slow’ cyclones from the computation of cyclone statistics improves the agreement among CDTMs. Results show significant negative trends of cyclone frequency in spring and positive trends in summer, whose contrasting effects compensate each other at annual scale, so that there is no significant long-term trend in total cyclone numbers in the Mediterranean basin in the 1979–2008 period

Mediterranean cyclones and windstorms in a changing climate

Changes in the frequency and intensity of cyclones and associated windstorms affecting the Medi-terranean region simulated under enhanced Greenhouse Gas forcing conditions are investigated. The analysis is based on 7 climate model integrations performed with two coupled global models (ECHAM5 MPIOM and INGV CMCC), comparing the end of the twentieth century and at least the first half of the twenty-first century. As one of the models has a considerably enhanced resolution of the atmosphere and the ocean, it is also investigated whether the climate change signals are influenced by the model resolution. While the higher resolved simulation is closer to reanalysis climatology, both in terms of cyclones and windstorm distributions, there is no evidence for an influence of the resolution on the sign of the climate change signal. All model simulations show a reduction in the total number of cyclones crossing the Mediterranean region under climate change conditions. Exceptions are Morocco and the Levant region, where the models predict an increase in the number of cyclones. The reduction is especially strong for intense cyclones in terms of their Laplacian of pressure. The influence of the simulated positive shift in the NAO Index on the cyclone decrease is restricted to the Western Mediterranean region, where it explains 10–50 % of the simulated trend, depending on the individual simulation. With respect to windstorms, decreases are simulated over most of the Mediterranean basin. This overall reduction is due to a decrease in the number of events associated with local cyclones, while the number of events associated with cyclones outside of the Mediterranean region slightly increases. These systems are, however, less intense in terms of their integrated severity over the Mediterranean area, as they mostly affect the fringes of the region. In spite of the general reduction in total numbers, several cyclones and windstorms of intensity unknown under current climate conditions are identified for the scenario simulations. For these events, no common trend exists in the individual simulations. Thus, they may rather be attributed to long-term (e.g. decadal) variability than to the Greenhouse Gas forcing. Nevertheless, the result indicates that high-impact weather systems will remain an important risk in the Mediterranean Basin

Projections of global warming-induced impacts on winter storm losses in the German private household sector

We present projections of winter storm-induced insured losses in the German residential building sector for the 21st century. With this aim, two structurally most independent downscaling methods and one hybrid downscaling method are applied to a 3-member ensemble of ECHAM5/MPI-OM1 A1B scenario simulations. One method uses dynamical downscaling of intense winter storm events in the global model, and a transfer function to relate regional wind speeds to losses. The second method is based on a reshuffling of present day weather situations and sequences taking into account the change of their frequencies according to the linear temperature trends of the global runs. The third method uses statistical-dynamical downscaling, considering frequency changes of the occurrence of storm-prone weather patterns, and translation into loss by using empirical statistical distributions. The A1B scenario ensemble was downscaled by all three methods until 2070, and by the (statistical-) dynamical methods until 2100. Furthermore, all methods assume a constant statistical relationship between meteorology and insured losses and no developments other than climate change, such as in constructions or claims management. The study utilizes data provided by the German Insurance Association encompassing 24 years and with district-scale resolution. Compared to 1971–2000, the downscaling methods indicate an increase of 10-year return values (i.e. loss ratios per return period) of 6–35 % for 2011–2040, of 20–30 % for 2041–2070, and of 40–55 % for 2071–2100, respectively. Convolving various sources of uncertainty in one confidence statement (data-, loss model-, storm realization-, and Pareto fit-uncertainty), the return-level confidence interval for a return period of 15 years expands by more than a factor of two. Finally, we suggest how practitioners can deal with alternative scenarios or possible natural excursions of observed losses

Compound events in Germany in 2018: drivers and case studies

The European continent is regularly affected by a wide range of extreme events and natural hazards including heatwaves, extreme precipitation, droughts, cold spells, windstorms, and storm surges. Many of these events do not occur as single extreme events, but rather show a multivariate character, the so-called compound events. Within the scope of the interdisciplinary project climXtreme (https://climxtreme.net/), we investigate the interplay of extreme weather events, their characteristics and changes, intensity, frequency and uncertainties in the past, present and future and associated impacts on various socio-economic sectors in Germany and Central Europe. This contribution presents several case studies with special emphasis on the calendar year of 2018, which is of particular interest given the exceptional sequence of different compound events across large parts of Europe, with devastating impacts on human lives, ecosystems and infrastructure. We provide new evidence on drivers of spatially and temporally compound events (heat and drought; heavy precipitation in combination with extreme winds) with adverse impacts on ecosystems and society using large-scale atmospheric patterns. We shed light on the interannual influence of droughts on surface water and the impact of water scarcity and heatwaves on agriculture and forests. We assessed projected changes in compound events at different current and future global surface temperature levels, demonstrating the importance of better quantifying the likelihood of future extreme events for adaptation planning. Finally, we addressed research needs and future pathways, emphasising the need to define composite events primarily in terms of their impacts prior to their statistical characterisation

Charakteristika des »normalen« Erdwetters und des Extremwetters

Charakteristika des normalen Erdwetters und des Extremwetters: Extremwetter ist Teil der »normalen« klimatischen Verhältnisse. Man kann es statistisch über Häufigkeitsverteilungen der Wetterparameter, das heißt über die Seltenheit des Auftretens der entsprechenden Zustände definieren. Die Definition bezieht sich somit auf die beobachteten Werte, und damit auf die betrachtete Datengrundlage. Letztere wirkt sich somit auf die berechneten Wiederkehrperioden und Wiederkehrwerte aus, nach denen sich die Vorsorge gegen Auswirkungen von Extremereignissen richtet. Das Auftreten von Extremereignissen kann anhand der spezifischen ursächlichen Prozesse kategorisiert werden. Quantitative Einschätzungen von Extremwetter-Ereignissen können sich auch an deren Auswirkungen orientieren. Neben den meteorologischen Faktoren bestimmen Exposition (Ausgesetztheit) und Verwundbarkeit (Vulnerabilität) das Schadensrisiko. Für Warnungen vor Extremwetter ist die Information über die Unsicherheiten wichtig, mit denen die Vorhersage von Extremwetter naturgemäß behaftet ist. Characteristics of normal earth weather and extreme weather: Extreme weather events are part of normal climate. They can be defined in terms of their rareness, quantified statistically from frequency distributions of the respective weather parameters. This definition is based on past observations, and thus on the underlying data basis. As a consequence, the data basis affects the return periods and return values used for establishing precautionary measures against the respective impacts. Events can be categorized according to specific generation processes. Their quantification may be based on their impacts, which arise from the combination of meteorological factors, exposure and vulnerability. Extreme weather warnings should take uncertainty into account, which is associated with the forecasting process