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The methodological framework of a large-scale risk assessment for Austrian forests under scenarios of climatic change is presented. A recently developed 3D-patch model is initialized with ground-true soil and vegetation data from sample plots of the Austrian Forest Inventory (AFI). Temperature and precipitation data of the current climate are interpolated from a network of more than 600 weather stations to the sample plots of the AFI. Vegetation development is simulated under current climate (âcontrol runâ) and under climate change scenarios starting from today's forest composition and structure. Similarity of species composition and accumulated biomass between these two runs at various points in time were used as assessment criteria. An additive preference function which is based on Saatyâs AHP is employed to synthesize these criteria to an overall index of the adaptation potential of current forests to a changing climate. The presented methodology is demonstrated for a small sample from the Austrian Forest Inventory. The forest model successfully simulated equilibrium species composition under current climatic conditions spatially explicit in a heterogenous landscape based on ground-true data. At none of the simulated sites an abrupt forest dieback did occur due to climate change impacts. However, substantial changes occured with regard to species composition of the potential natural vegetation (PNV).

Our current knowledge on multi‐decadal to centennial changes of snow in different parts of the world is based largely on observations of snow depth and depth of snowfall from national weather and hydrographic services. Studies analysing these snow observations in the European Alps are predominantly based on national data and are therefore limited by their respective borders in the detection of robust, spatiotemporal snow trends. In order to overcome this limitation, data from Austria and Switzerland, which cover a substantial fraction of the Alps when taken together, are merged for this study (196 station‐records). Additionally, it is the first time that such an analysis is based on homogenized data. Our homogenization study shows that, although the detection of breaks in snow depth series works quite well with the existing methods, further research is needed to adequately correct snow depth series at a daily resolution. Roughly, 70% (139 station‐records) of the snow depth series could be homogenized and are used for further trend analysis. The findings concern seven climatologically different areas that are identified by a regionalization (using empirical orthogonal functions) using station records from 1961 to 2012. These regions share a high degree of inner similarity and outer separation, and the temporal trends detected are rather different across the Swiss‐Austrian domain. Regions in the south show a clear decrease in the snow depth of up to −12 cm/decade on average, while those in the northeast are characterized by almost no change. The declining trend in the southern regions intensifies as altitude increases. Comparisons of these variations in depth changes with concurrent changes in air temperature and precipitation totals reveal a clear dichotomy with respect to elevation. Snow depths in low elevated areas are highly sensitive to air temperature changes, whereas those at high elevations strongly depend on alterations in precipitation totals. Snow depth observations of the Swiss‐Austrian region for the past half century show strikingly different trends. Whereas in particular the South of Austria is characterized by strongly decreasing snow depths, in the northeastern part of Austria they are almost unchanged. Our analyses show, that snow depth changes to a greater extent are forced by air temperature for low elevation regions, whereas for high elevation regions changes are sensitive to precipitation. The figure shows the Mann Kendall trend over the period 1961‐2012 for mean snow depth (November to April) at 139 stations within the Swiss‐Austrian area. White: no significant trend; Orange: significantly negative at a 95% confidence level; Red: significantly negative at a 99% confidence level. [ABSTRACT FROM AUTHOR]

Environmental modeling studies aim to infer the impacts on environmental variables that are caused by natural and human-induced changes in environmental systems. Changes in environmental systems are typically implemented as discrete scenarios in environmental models to simulate environmental variables under changing conditions. The scenario development of a model input usually involves several data sources and perhaps other models, which are potential sources of uncertainty. The setup and the parametrization of the implemented environmental model are additional sources of uncertainty for the simulation of environmental variables. Yet to draw well-informed conclusions from the model simulations it is essential to identify the dominant sources of uncertainty. In impact studies in two Austrian catchments the eco-hydrological model Soil and Water Assessment Tool (SWAT) was applied to simulate discharge and nitrate-nitrogen (NO3- - N) loads under future changing conditions. For both catchments the SWAT model was set up with different spatial aggregations. Non-unique model parameter sets were identified that adequately reproduced observations of discharge and NO3- - N loads. We developed scenarios of future changes for land use, point source emissions, and climate and implemented the scenario realizations in the different SWAT model setups with different model parametrizations, which resulted in 7000 combinations of scenarios and model setups for both catchments. With all model combinations we simulated daily discharge and NO3- - N loads at the catchment outlets. The analysis of the 7000 generated model combinations of both case studies had two main goals: (i) to identify the dominant controls on the simulation of discharge and NO3- - N loads in the two case studies and (ii) to assess how the considered inputs control the simulation of discharge and NO3- - N loads. To assess the impact of the input scenarios, the model setup, and the parametrization on the simulation of discharge and NO3- - N loads, we employed methods of global sensitivity analysis (GSA). The uncertainties in the simulation of discharge and NO3- - N loads that resulted from the 7000 SWAT model combinations were evaluated visually. We present approaches for the visualization of the simulation uncertainties that support the diagnosis of how the analyzed inputs affected the simulation of discharge and NO3- - N loads. Based on the GSA we identified climate change and the model parametrization as being the most influential model inputs for the simulation of discharge and NO3- - N loads in both case studies. In contrast, the impact of the model setup on the simulation of discharge and NO3- - N loads was low, and the changes in land use and point source emissions were found to have the lowest impact on the simulated discharge and NO3- - N loads. The visual analysis of the uncertainty bands illustrated that the deviations in precipitation of the different climate scenarios to historic records dominated the changes in simulation outputs, while the differences in air temperature showed no considerable impact. [ABSTRACT FROM AUTHOR]

Environmental modeling studies aim to infer the impacts on environmental variables that are caused by natural and human-induced changes in environmental systems. Changes in environmental systems are typically implemented as discrete scenarios in environmental models to simulate environmental variables under changing conditions. The scenario development of a model input usually involves several data sources and perhaps other models, that are potential sources of uncertainty. The setup and the parametrization of the implemented environmental model are additional sources of uncertainty for the simulation of environmental variables. Yet, to draw well-informed conclusions from the model simulations it is essential to identify the dominant sources of uncertainty. In two Austrian impact studies the eco-hydrological model Soil and Water Assessment Tool (SWAT) was applied to simulate discharge and nitrate-nitrogen (NO3--N) loads under future changing conditions. For both catchments the SWAT model was set up with different spatial aggregations and non-unique model parameter sets were identified that adequately reproduced observations of discharge and NO3--N loads. We developed scenarios of future changes for land use, point source emissions, and climate and implemented the scenario realizations in the different SWAT model setups with different model parametrizations, which resulted in 7000 combinations of scenarios and model setups for both catchments. With all model combinations we simulated daily discharge and NO3--N loads at the catchment outlets. In both case studies we employed global sensitivity analysis (GSA) to identify the impact of the scenario inputs, the model setup and the parametrization on the simulation of discharge and NO3--N loads. We accompanied the GSA with a visual analysis of the simulation outputs and their associated uncertainties that resulted from the simulations of the 7000 SWAT model combinations. We present visualizations of the results of the GSA and the simulation uncertainty bands that proved to be powerful diagnostic tools in this study. Based on the GSA we identified climate change and the model parametrization to be the most sensitive model inputs for the simulation of discharge and NO3--N loads in both case studies. In contrast, the impact of the model setup on the simulation of discharge and NO3--N loads was low and the changes in land use and point source emissions were found to have the least impact on the simulated discharge and NO3--N loads. Additionally, the visual analysis of the uncertainty bands illustrated that the precipitation of the climate scenarios dominated the changes in simulation outputs, rather than changes in air temperature in both case studies. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Identifying populations within tree species potentially adapted to future climatic conditions is an important requirement for reforestation and assisted migration programmes. Such populations can be identified either by empirical response functions based on correlations of quantitative traits with climate variables or by climate envelope models that compare the climate of seed sources and potential growing areas. In the present study, we analyzed the intraspecific variation in climate growth response of Douglas-fir planted within the non-analogous climate conditions of Central and continental Europe. With data from 50 common garden trials, we developed Universal Response Functions (URF) for tree height and mean basal area and compared the growth performance of the selected best performing populations with that of populations identified through a climate envelope approach. Climate variables of the trial location were found to be stronger predictors of growth performance than climate variables of the population origin. Although the precipitation regime of the population sources varied strongly none of the precipitation related climate variables of population origin was found to be significant within the models. Overall, the URFs explained more than 88% of variation in growth performance. Populations identified by the URF models originate from western Cascades and coastal areas of Washington and Oregon and show significantly higher growth performance than populations identified by the climate envelope approach under both current and climate change scenarios. The URFs predict decreasing growth performance at low and middle elevations of the case study area, but increasing growth performance on high elevation sites. Our analysis suggests that population recommendations based on empirical approaches should be preferred and population selections by climate envelope models without considering climatic constrains of growth performance should be carefully appraised before transferring populations to planting locations with novel or dissimilar climate. [ABSTRACT FROM AUTHOR]

Highlights: [•] Modelling probability and intensity of bark beetle disturbances at stand scale. [•] Stand, site and climate data provided at large spatial scale and high resolution. [•] Temporal and spatial autocorrelation taken into account in a mixed model framework. [•] Bark beetle phenology included in the models. [•] Models can be used for risk analysis outside of the study area. [ABSTRACT FROM AUTHOR]

ABSTRACT This study presents a new gridded dataset providing absolute monthly mean temperatures across the Greater Alpine Region (GAR) of Europe at a spatial resolution of 5 arcmin (6 × 9 km in the region) from 1780 to 2008. The starting point was a set of long-term homogenized station time series. To assure the quality of the analyses back in time, when the station density decreases, missing measurements were reconstructed by an Empirical Orthogonal Function analysis that can deal with gappy data. It is shown that the reconstructed values comprise similar statistical features to the observations and that the method produces no breaks between the reconstructions and the observations. The compound anomaly dataset was then interpolated separately for two different altitude ranges to preserve anomaly gradients between high and low elevations. This allowed for the derivation of individual anomalies at each grid point in GAR. Finally, these smooth anomalies were blended with the highly resolved monthly mean absolute temperature fields, provided by a project of the European Climate Support Network. The added value of this new high resolution and long-term temperature dataset is shown and discussed using the examples of the height of the 0 °C altitude and vertical lapse rates. For the first time, these and other features are now available for more than two centuries in a topographically complex region like GAR. [ABSTRACT FROM AUTHOR]

This study is based on the study from Matulla et al. (2009) where the glacier under estimation has been Peyto Glacier in Canada. The same methods have been used for five Austrian glaciers; projections of glacier mass balance are generated from ensembles of general circulation model (GCM) simulations by the use of direct statistical downscaling. Thereby, the general features of the atmospheric circulation over an expanded geographical region covering the European Alps are linked empirically to winter and summer mass balance records measured at five glaciers in Austria. The projections are taken from an ensemble of ECHAM5-MPIOM simulations forced with the IPCC-SRES scenarios A1B and B1. Results based on the statistical downscaling indicate decreasing balances for both winter and summer. These results suggest continued frontal recession and downwasting of the alpine glaciers in this region until 2100. For Jamtalferner, these suggestions reach reductions of about 1000 mm water equivalent in summer. Copyright © 2012 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

The article discusses the application of a direct downscaling approach from coarse-scale general circulation model (GCM) data to yield ensembles of local-scale glacier mass balance projections for Peyto Glacier, Alberta. It concentrates on the propagation of ensemble projections obtained from ECHAM5-MPIOM. It notes that ensemble simulations yield a moderate rise in winter balance.

The article describes the historical instrumental climatological surface time series of the Greater Alpine Region (HISTALP) database which consists of monthly homogenized records of temperature, pressure, precipitation, sunshine and cloudiness for the Greater Alpine Region. Among the key findings of the trend analysis is the parallel centennial decrease of both temperature and air pressure in the 19th century. The 20th century increase evolved stepwise with a first peak near 1950. A long-term increase of the high-elevation series relative to the low-elevation series is given for sunshine and air pressure.

Key message: Autumn and spring frost events caused wide variation in the survival of juvenile Douglas-fir in Austrian forest sites located in the transition zone from Atlantic to continental climate. Survival rate can be optimized by planting provenances originating from an altitudinal belt of 500–1400 m in North America. Neither the variety nor the climate of origin of planted Douglas-fir provenances influence its response to frost events. Context: Understanding the risks of frost during late spring and early autumn is crucial for planting non-native Douglas-fir (Pseudotsuga menziesii [Mirbel] Franco) as an alternative tree species under climate change in Europe. Aims: We investigate the role of early and late frost events on the survival of juvenile Douglas-fir and tested whether survival depends on seed origin. Methods: With data from 19 provenance trials across Austria, we modeled the effects of early and late frost events on juvenile survival rate, accounting for random variations due to site condition and provenance origin. Results: Wide variations (37–93%) in the juvenile survival rate of Douglas-fir were mainly driven by early and late frost events (daily Tmin < 0 °C), summer drought, and continentality. Juvenile survival declined with an increasing number of frost events within the observation period and prevailing warm spells preceding the frost events. The seed origin of the tested provenances had a minor effect and was related to the altitude, but not to the variety or the climate of provenance origin. Conclusion: For planting Douglas-fir in the transition zone from Atlantic to continental climates, typical in Austrian forests, the local site conditions and the probability of the occurrence of early and late frosts should be considered, while provenance selection should rather focus on productivity. [ABSTRACT FROM AUTHOR]

An important consequence of climate change is the impact on phenological spring timing events. Although it is generally understood that anthropogenic mechanisms play a major role in the warming trend of the climate and that the timing of phenological phases depends largely on the temperature, the link has yet to be quantitatively shown for different kind of areas. In this study the goal is to show this for a Central European region. In order to do this a multistep attribution to external forcings is carried out, linking the earlier timing of phenological spring events to changed climate conditions (increasing temperature) and this change in the environment to external (anthropogenic) forcing.The goal is to apply the ‚optimal fingerprint' technique to detect and attribute anthropogenic causes to the earlier timing of phenological events (Hasselmann, 1997). In order to achieve this, one has to use data from different models. First, to assess the variability of the climate without any kind of forcing (neither natural, nor anthropogenic), pre-industrial control (piControl) simulations from Global Circulation Models (GCMs) are needed. Second, one needs different historical GCM runs, some forced by natural forcings only and others with anthropogenic forcing included. To be able to compare the large Scale Information from the GCMs with the local scale information in the form of phenological observations, an empirical-statistical downscaling model is used, to overcome the scale differences. Afterwards, a phenological model is fed with the downscaled temperature data to obtain distinctly forced, simulated phenological data.The study is successful if and only if a discrepancy between naturally forced climate conditions and observations is found, so that the estimated statistical significance level of the detection of a net climate change satisfies the requirements (rejection of the null hypothesis that the change can be explained by natural variability only or naturally forced climate conditions). And if it can only be explained when factoring in anthropogenic forcings, meaning the observations are only consistent when incorporating them. This attribution part in using the aforementioned technique is a consistency check and yields confidence values to quantitatively assess the anthropogenic impact.HASSELMANN, Klaus. Multi-pattern fingerprint method for detection and attribution of climate change. Climate Dynamics, 1997, 13. Jg., Nr. 9, S. 601-611. [ABSTRACT FROM AUTHOR]

Contents of this contribution sketch the derivation of this procedure and its successful application to the (so-far) largest and most complex civil-protection project implemented in Austria after WWII. Results, rely largely on three master theses carried out within a cooperation of the Climate Impact Team (CIT) at ZAMG, the BMNT and the Institute of Meteorology and Geophysics at the University of Vienna. Apart therefrom findings profit greatly from a close cooperation of CIT and the European Freight and Logistics Leaders' Forum (F&L). The goal is to support decision makers in designing and implementing efficient and sustainable protection against changing threats. This necessitates extensive preparatory work: (i) the generation of ensembles comprising regional-scale climate-change scenarios until 2100, driven by different pathways of mankind (RCPs: 2.6, 4.5 and 8.5, RCPs - Representative Concentration Pathways); (ii) facilitated under the umbrella of the BMNT: first-time integration of the three most comprehensive national cadasters of extreme-weather induced hazard-events; the outstanding scope and quality of these cadasters enable the compilation of the so-called 'event space', which is now Austria's most extensive database of weather driven hazard-processes (well above 20.000 records from 1948 onwards); this wealth of observations (we focus here on landslides and floodings) allows for (iii) in depth analyses (von Storch and Zwiers, 1999) of linkages between extreme weather and potential damage events, distinguishing at the same time (iv) amongst process-categories as well as sub-regions within Austria's share of the European Alps: 'Alpine Territory', 'Northern Lowlands' and the 'Southern Basin Chain'; blending (v) the 'event space' with spatial high-resolved, daily observations of precipitation totals and temperature values (SPARTACUS, Hiebl and Frei 2015, 2017) sets the frame required for the (vi) identification-procedure of region- and category-sensitive weather sequences triggering potential damage-events (so-called Climate Indices, CIs); step (vii) derives future CIs occurrences from previously downgescaled ensembles within 'near' (2036-2065) and 'remote' periods (2071-2100) and assesses results in terms of current levels; sustainable protection structures must withstand these 'near' (and 'remote') threat levels;Step (viii) finally demonstrates the successful application of the procedure calibrated by the expertise of our partners in charge of public protection protection, to Austria's (so far) largest project in public protection since WWII, in which methods currently available have not provided guidance. Presently BMNT surveys adjustments required for the integration of the procedure. Aside therefrom, its application to critical transport infrastructure is in discussion with the Forum of European Freight and Logistics Leaders (F\&L), because members are experiencing rises of supply-chain disruptions due to climate-change driven hazard events. [ABSTRACT FROM AUTHOR]

Extreme events, such as heat waves and floodings, constitute major challenges for all organizations and institutions responsible for protection, support and medical assistance of civilians. Therefore the ongoing enhancement of alert and warning systems is highly desirable. In particular the investigation of climate change driven effects on extreme events will help agencies to plan their medium to long term resources. We thus investigate the relationship between large scale synoptic weather patterns and extreme events on the regional scale in Austria and thereby focus on studying how the frequency, duration and intensity of weather patterns change under global warming by performing nonstationary regression. Furthermore the impact of these trends in the large scale weather patterns on extreme precipitation and temperature events in Austria is analyzed. Achieved results shall significantly support disaster protection and relief organizations' anticipatory medium to long term planning of resources. [ABSTRACT FROM AUTHOR]

In order to allow anticipatory planning achieving statistically robust strategies, all necessary calculations involvedin setting them up have to draw on well occupied ensembles of losc projections. If, aside from that, such ensemblesare also available for different pathways of mankind, resulting strategies are not only statistically robust but referon top of that to corridors, which jointly encompass sufficient parts of potential future developments (e.g. of futurethreat-occurrences).Both features enhance the validity and significance of in such way established strategies, which are - in case of civil protection and the defense of critical infrastructure against damaging events - evidently worth striving for. Therefore, the goal we present here is the generation of - statistically as well as in terms of mankind's evolution - robust ensembles in the European Alps, where they are much required.This goal is achieved by an ESD technique termed Analog Method, which rests on capturing synoptic dynamics and the grading of similarity between observed and projected patterns ('analogs') whereby physically consistent losc weather conditions are assigned to GCM patterns. In order to ensure optimal quality of the derived ensembles as well as coherence amongst weather conditions in all considered losc regions, we have to solve two optimization problems. One of these refers to the dimensions of the atmospheric window used for analog-detection and is a problem under two boundary conditions imposed by von Storch et al. (1993) and van den Dool (1994). The first pertains to GCMs' skillful scale and, hence, sets an infimum to the space dimensions to be considered, whilst the latter claim corresponds to a supremum stating it's outstandingly unlikely to identify proper analogs at high dimensions.The other optimization problem is associated with the determination of the most suitable geographical position within a large sector over the North Atlantic, the continent and the Mediterranean, on which the atmospheric window best has to be centered. Findings are presented, discussed and put into context. [ABSTRACT FROM AUTHOR]

All over the world, an increasing number of weather-induced damage events can be observed. They are due to enhanced frequencies and intensities of previously scarce weather patterns. This development raises consciousness among federal officials and industry executives responsible for public protection as it increases the risk of casualties and losses to society, ecosystems, socio-economics, infrastructure and therefore poses the question of how the actual level of protection can be sustained in the decades to come. This study investigates the use of decision theory techniques to support decision-making processes actually used by the authorities responsible for civil protection. In order to accomplish these tasks, we apply the Bernoulli Principle in conjunction with a set of rules to a very comprehensive and complex case study in which the standard decision-making procedures of the authorities have not yielded a clear result. By employing protection-strategies used by the authorities (retention strategies, linear as well as retention measures) under coherently compiled assumptions concerning their potential future evolution, we employ decision theory methods to address the challenge of how to sustain present-day protection-levels under enhanced flooding-occurrences derived from ensembles of downscaled climate-change projections associated with different future pathways of mankind. Achieved results highlight the significance of this approach in forward-planning sustainable public protection-strategies and safeguarding critical infrastructure. This is of far-reaching importance because presented approaches allow for the consistent integration of decisive future threat-levels. Anticipatory planning is in fact urgently needed in this context because by now the maintenance of structures in place already makes up a substantial part of the total budget available for public measures. The achived findings of this study have already caused discussions by authorities in charge of civil protection on so far utilized decision-making processes. In addition, the intense cooperation with European transport, freight and logistics leaders has allowed us to estimate the implementation of presented strategies with regard to their future cost development. Apart from that results correspond to the recommendations of the Federal Ministry for Sustainability and Tourism (BMNT) regarding the Flood Directive and the publications of the European Union on flood protection. [ABSTRACT FROM AUTHOR]

Floodings and landslides are amongst the most devastating damage-processes worldwide. Associated risk levels are particularly high in topographically complex terrain. Along with the increase in climate-change induced extreme-events, research devoted to the identification of so-called Climate Indices (CIs) describing weather phenomena triggering hazard-occurrences and intensities gain rising emphasis.In this study we accomplish the first-time unification of the three most comprehensive cadastres on weather-induced hazard-processes, compiled and maintained by federal authorities. The therefrom resulting 'event space' stretches seven decades from 1950 onwards and contains 20.000 hazard occurrences, classified into six different process-categories. Event data are analyzed together with a high-quality, daily-based dataset providing temperatures and precipitation totals on a 1 km grid across the Austrian part of the European Alps. On the resulting unprecedented extent of extreme-weather triggered hazard-processes and gridded weather observations, we are able to examine the hypothesis that daily sequences of precipitation-totals preceding damage-events allow for detecting temporal weather-sequences uniquely allocatable to various hazard-categories in three orographically distinct regions in the European Alps. We pursue this research aim by analyzing for each hazard-category its quadratic form representing the physics contained in the observations. Resulting eigen-directions, invariant under its inherent second order tensor, are the sought-for total-sequences (CIs) and hence reject the alternative hypothesis. Therefore, precipitation total-sequences can be uniquely assigned to every hazard category within each region, giving an overall of 18 CIs. It is important to note that findings based on this novel, objective approach do not contradict, but rather add to attained research achievements by introducing this new perspective on the subject. Obtained CIs have substantial potential in research and applications. In civil defense, safeguarding critical infrastructure, early warning systems and the development of sustainable protection strategies, findings are in implementation by responsible decision-makers and in intense discussion with the European Freight Leaders Forum. [ABSTRACT FROM AUTHOR]