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The immense popularity of online communication services in the last decade has not only upended our lives (with news spreading like wildfire on the Web, presidents announcing their decisions on Twitter, and the outcome of political elections being determined on Facebook) but also dramatically increased the amount of data exchanged on these platforms. Therefore, if we wish to understand the needs of modern society better and want to protect it from new threats, we urgently need more robust, higher-quality natural language processing (NLP) applications that can recognize such necessities and menaces automatically, by analyzing uncensored texts. Unfortunately, most NLP programs today have been created for standard language, as we know it from newspapers, or, in the best case, adapted to the specifics of English social media.
This thesis reduces the existing deficit by entering the new frontier of German online communication and addressing one of its most prolific forms—users’ conversations on Twitter. In particular, it explores the ways and means by how people express their opinions on this service, examines current approaches to automatic mining of these feelings, and proposes novel methods, which outperform state-of-the-art techniques. For this purpose, I introduce a new corpus of German tweets that have been manually annotated with sentiments, their targets and holders, as well as lexical polarity items and their contextual modifiers. Using these data, I explore four major areas of sentiment research: (i) generation of sentiment lexicons, (ii) fine-grained opinion mining, (iii) message-level polarity classification, and (iv) discourse-aware sentiment analysis. In the first task, I compare three popular groups of lexicon generation methods: dictionary-, corpus-, and word-embedding–based ones, finding that dictionary-based systems generally yield better polarity lists than the last two groups. Apart from this, I propose a linear projection algorithm, whose results surpass many existing automatically-generated lexicons. Afterwords, in the second task, I examine two common approaches to automatic prediction of sentiment spans, their sources, and targets: conditional random fields (CRFs) and recurrent neural networks, obtaining higher scores with the former model and improving these results even further by redefining the structure of CRF graphs. When dealing with message-level polarity classification, I juxtapose three major sentiment paradigms: lexicon-, machine-learning–, and deep-learning–based systems, and try to unite the first and last of these method groups by introducing a bidirectional neural network with lexicon-based attention. Finally, in order to make the new classifier aware of microblogs' discourse structure, I let it separately analyze the elementary discourse units of each tweet and infer the overall polarity of a message from the scores of its EDUs with the help of two new approaches: latent-marginalized CRFs and Recursive Dirichlet Process.
In this work we investigated ultrafast demagnetization in a Heusler-alloy. This material belongs to the halfmetal and exists in a ferromagnetic phase. A special feature of investigated alloy is a structure of electronic bands. The last leads to the specific density of the states. Majority electrons form a metallic like structure while minority electrons form a gap near the Fermi-level, like in semiconductor. This particularity offers a good possibility to use this material as model-like structure and to make some proof of principles concerning demagnetization. Using pump-probe experiments we carried out time-resolved measurements to figure out the times of demagnetization. For the pumping we used ultrashort laser pulses with duration around 100 fs. Simultaneously we used two excitation regimes with two different wavelengths namely 400 nm and 1240 nm. Decreasing the energy of photons to the gap size of the minority electrons we explored the effect of the gap on the demagnetization dynamics. During this work we used for the first time OPA (Optical Parametrical Amplifier) for the generation of the laser irradiation in a long-wave regime. We tested it on the FETOSPEX-beamline in BASSYII electron storage ring. With this new technique we measured wavelength dependent demagnetization dynamics. We estimated that the demagnetization time is in a correlation with photon energy of the excitation pulse. Higher photon energy leads to the faster demagnetization in our material. We associate this result with the existence of the energy-gap for minority electrons and explained it with Elliot-Yaffet-scattering events. Additionally we applied new probe-method for magnetization state in this work and verified their effectivity. It is about the well-known XMCD (X-ray magnetic circular dichroism) which we adopted for the measurements in reflection geometry. Static experiments confirmed that the pure electronic dynamics can be separated from the magnetic one. We used photon energy fixed on the L3 of the corresponding elements with circular polarization. Appropriate incidence angel was estimated from static measurements. Using this probe method in dynamic measurements we explored electronic and magnetic dynamics in this alloy.
This dissertation is concerned with the relation between qualitative phonological organization in the form of syllabic structure and continuous phonetics, that is, the spatial and temporal dimensions of vocal tract action that express syllabic structure. The main claim of the dissertation is twofold. First, we argue that syllabic organization exerts multiple effects on the spatio-temporal properties of the segments that partake in that organization. That is, there is no unique or privileged exponent of syllabic organization. Rather, syllabic organization is expressed in a pleiotropy of phonetic indices. Second, we claim that a better understanding of the relation between qualitative phonological organization and continuous phonetics is reached when one considers how the string of segments (over which the nature of the phonological organization is assessed) responds to perturbations (scaling of phonetic variables) of localized properties (such as durations) within that string. Specifically, variation in phonetic variables and more specifically prosodic variation is a crucial key to understanding the nature of the link between (phonological) syllabic organization and the phonetic spatio-temporal manifestation of that organization. The effects of prosodic variation on segmental properties and on the overlap between the segments, we argue, offer the right pathway to discover patterns related to syllabic organization. In our approach, to uncover evidence for global organization, the sequence of segments partaking in that organization as well as properties of these segments or their relations with one another must be somehow locally varied. The consequences of such variation on the rest of the sequence can then be used to unveil the span of organization. When local perturbations to segments or relations between adjacent segments have effects that ripple through the rest of the sequence, this is evidence that organization is global. If instead local perturbations stay local with no consequences for the rest of the whole, this indicates that organization is local.
On a planetary scale human populations need to adapt to both socio-economic and environmental problems amidst rapid global change. This holds true for coupled human-environment (socio-ecological) systems in rural and urban settings alike. Two examples are drylands and urban coasts. Such socio-ecological systems have a global distribution. Therefore, advancing the knowledge base for identifying socio-ecological adaptation needs with local vulnerability assessments alone is infeasible: The systems cover vast areas, while funding, time, and human resources for local assessments are limited. They are lacking in low an middle-income countries (LICs and MICs) in particular.
But places in a specific socio-ecological system are not only unique and complex – they also exhibit similarities. A global patchwork of local rural drylands vulnerability assessments of human populations to socio-ecological and environmental problems has already been reduced to a limited number of problem structures, which typically cause vulnerability. However, the question arises whether this is also possible in urban socio-ecological systems. The question also arises whether these typologies provide added value in research beyond global change. Finally, the methodology employed for drylands needs refining and standardizing to increase its uptake in the scientific community. In this dissertation, I set out to fill these three gaps in research.
The geographical focus in my dissertation is on LICs and MICs, which generally have lower capacities to adapt, and greater adaptation needs, regarding rapid global change. Using a spatially explicit indicator-based methodology, I combine geospatial and clustering methods to identify typical configurations of key factors in case studies causing vulnerability to human populations in two specific socio-ecological systems. Then I use statistical and analytical methods to interpret and appraise both the typical configurations and the global typologies they constitute.
First, I improve the indicator-based methodology and then reanalyze typical global problem structures of socio-ecological drylands vulnerability with seven indicator datasets. The reanalysis confirms the key tenets and produces a more realistic and nuanced typology of eight spatially explicit problem structures, or vulnerability profiles: Two new profiles with typically high natural resource endowment emerge, in which overpopulation has led to medium or high soil erosion. Second, I determine whether the new drylands typology and its socio-ecological vulnerability concept advance a thematically linked scientific debate in human security studies: what drives violent conflict in drylands? The typology is a much better predictor for conflict distribution and incidence in drylands than regression models typically used in peace research. Third, I analyze global problem structures typically causing vulnerability in an urban socio-ecological system - the rapidly urbanizing coastal fringe (RUCF) – with eleven indicator datasets. The RUCF also shows a robust typology, and its seven profiles show huge asymmetries in vulnerability and adaptive capacity. The fastest population increase, lowest income, most ineffective governments, most prevalent poverty, and lowest adaptive capacity are all typically stacked in two profiles in LICs. This shows that beyond local case studies tropical cyclones and/or coastal flooding are neither stalling rapid population growth, nor urban expansion, in the RUCF. I propose entry points for scaling up successful vulnerability reduction strategies in coastal cities within the same vulnerability profile.
This dissertation shows that patchworks of local vulnerability assessments can be generalized to structure global socio-ecological vulnerabilities in both rural and urban socio-ecological systems according to typical problems. In terms of climate-related extreme events in the RUCF, conflicting problem structures and means to deal with them are threatening to widen the development gap between LICs and high-income countries unless successful vulnerability reduction measures are comprehensively scaled up. The explanatory power for human security in drylands warrants further applications of the methodology beyond global environmental change research in the future. Thus, analyzing spatially explicit global typologies of socio-ecological vulnerability is a useful complement to local assessments: The typologies provide entry points for where to consider which generic measures to reduce typical problem structures – including the countless places without local assessments. This can save limited time and financial resources for adaptation under rapid global change.
This thesis investigates whether multilingual speakers’ use of grammatical constraints in an additional language (La) is affected by the native (L1) and non-native grammars (L2) of their linguistic repertoire.
Previous studies have used untimed measures of grammatical performance to show that L1 and L2 grammars affect the initial stages of La acquisition. This thesis extends this work by examining whether speakers at intermediate levels of La proficiency, who demonstrate mature untimed/offline knowledge of the target La constraints, are differentially affected by their L1 and L2 knowledge when they comprehend sentences under processing pressure. With this purpose, several groups of La German speakers were tested on word order and agreement phenomena using online/timed measures of grammatical knowledge. Participants had mirror distributions of their prior languages and they were either L1English/L2Spanish speakers or L1Spanish/L2English speakers. Crucially, in half of the phenomena the target La constraint aligned with English but not with Spanish, while in the other half it aligned with Spanish but not with English. Results show that the L1 grammar plays a major role in the use of La constraints under processing pressure, as participants displayed increased sensitivity to La constraints when they aligned with their L1, and reduced sensitivity when they did not. Further, in specific phenomena in which the L2 and La constraints aligned, increased L2 proficiency resulted in an enhanced sensitivity to the La constraint. These findings suggest that both native and non-native grammars affect how speakers use La grammatical constraints under processing pressure. However, L1 and L2 grammars differentially influence on participants’ performance: While L1 constraints seem to be reliably recruited to cope with the processing demands of real-time La use, proficiency in an L2 can enhance sensitivity to La constraints only in specific circumstances, namely when L2 and La constraints align.
Predators can have numerical and behavioral effects on prey animals. While numerical effects are well explored, the impact of behavioral effects is unclear. Furthermore, behavioral effects are generally either analyzed with a focus on single individuals or with a focus on consequences for other trophic levels. Thereby, the impact of fear on the level of prey communities is overlooked, despite potential consequences for conservation and nature management. In order to improve our understanding of predator-prey interactions, an assessment of the consequences of fear in shaping prey community structures is crucial.
In this thesis, I evaluated how fear alters prey space use, community structure and composition, focusing on terrestrial mammals. By integrating landscapes of fear in an existing individual-based and spatially-explicit model, I simulated community assembly of prey animals via individual home range formation. The model comprises multiple hierarchical levels from individual home range behavior to patterns of prey community structure and composition. The mechanistic approach of the model allowed for the identification of underlying mechanism driving prey community responses under fear.
My results show that fear modified prey space use and community patterns. Under fear, prey animals shifted their home ranges towards safer areas of the landscape. Furthermore, fear decreased the total biomass and the diversity of the prey community and reinforced shifts in community composition towards smaller animals. These effects could be mediated by an increasing availability of refuges in the landscape. Under landscape changes, such as habitat loss and fragmentation, fear intensified negative effects on prey communities. Prey communities in risky environments were subject to a non-proportional diversity loss of up to 30% if fear was taken into account. Regarding habitat properties, I found that well-connected, large safe patches can reduce the negative consequences of habitat loss and fragmentation on prey communities. Including variation in risk perception between prey animals had consequences on prey space use. Animals with a high risk perception predominantly used safe areas of the landscape, while animals with a low risk perception preferred areas with a high food availability. On the community level, prey diversity was higher in heterogeneous landscapes of fear if individuals varied in their risk perception compared to scenarios in which all individuals had the same risk perception.
Overall, my findings give a first, comprehensive assessment of the role of fear in shaping prey communities. The linkage between individual home range behavior and patterns at the community level allows for a mechanistic understanding of the underlying processes. My results underline the importance of the structure of the landscape of fear as a key driver of prey community responses, especially if the habitat is threatened by landscape changes. Furthermore, I show that individual landscapes of fear can improve our understanding of the consequences of trait variation on community structures. Regarding conservation and nature management, my results support calls for modern conservation approaches that go beyond single species and address the protection of biotic interactions.
Supermassive black holes reside in the hearts of almost all massive galaxies. Their evolutionary path seems to be strongly linked to the evolution of their host galaxies, as implied by several empirical relations between the black hole mass (M BH ) and different host galaxy properties. The physical driver of this co-evolution is, however, still not understood. More mass measurements over homogeneous samples and a detailed understanding of systematic uncertainties are required to fathom the origin of the scaling relations.
In this thesis, I present the mass estimations of supermassive black holes in the nuclei of one late-type and thirteen early-type galaxies. Our SMASHING sample extends from the intermediate to the massive galaxy mass regime and was selected to fill in gaps in number of galaxies along the scaling relations. All galaxies were observed at high spatial resolution, making use of the adaptive-optics mode of integral field unit (IFU) instruments on state-of-the-art telescopes (SINFONI, NIFS, MUSE). I extracted the stellar kinematics from these observations and constructed dynamical Jeans and Schwarzschild models to estimate the mass of the central black holes robustly. My new mass estimates increase the number of early-type galaxies with measured black hole masses by 15%. The seven measured galaxies with nuclear light deficits (’cores’) augment the sample of cored galaxies with measured black holes by 40%. Next to determining massive black hole masses, evaluating the accuracy of black hole masses is crucial for understanding the intrinsic scatter of the black hole- host galaxy scaling relations. I tested various sources of systematic uncertainty on my derived mass estimates.
The M BH estimate of the single late-type galaxy of the sample yielded an upper limit, which I could constrain very robustly. I tested the effects of dust, mass-to-light ratio (M/L) variation, and dark matter on my measured M BH . Based on these tests, the typically assumed constant M/L ratio can be an adequate assumption to account for the small amounts of dark matter in the center of that galaxy. I also tested the effect of a variable M/L variation on the M BH measurement on a second galaxy. By considering stellar M/L variations in the dynamical modeling, the measured M BH decreased by 30%. In the future, this test should be performed on additional galaxies to learn how an as constant assumed M/L flaws the estimated black hole masses.
Based on our upper limit mass measurement, I confirm previous suggestions that resolving the predicted BH sphere-of-influence is not a strict condition to measure black hole masses. Instead, it is only a rough guide for the detection of the black hole if high-quality, and high signal-to-noise IFU data are used for the measurement. About half of our sample consists of massive early-type galaxies which show nuclear surface brightness cores and signs of triaxiality. While these types of galaxies are typically modeled with axisymmetric modeling methods, the effects on M BH are not well studied yet. The massive galaxies of our presented galaxy sample are well suited to test the effect of different stellar dynamical models on the measured black hole mass in evidently triaxial galaxies. I have compared spherical Jeans and axisymmetric Schwarzschild models and will add triaxial Schwarzschild models to this comparison in the future. The constructed Jeans and Schwarzschild models mostly disagree with each other and cannot reproduce many of the triaxial features of the galaxies (e.g., nuclear sub-components, prolate rotation). The consequence of the axisymmetric-triaxial assumption on the accuracy of M BH and its impact on the black hole - host galaxy relation needs to be carefully examined in the future.
In the sample of galaxies with published M BH , we find measurements based on different dynamical tracers, requiring different observations, assumptions, and methods. Crucially, different tracers do not always give consistent results. I have used two independent tracers (cold molecular gas and stars) to estimate M BH in a regular galaxy of our sample. While the two estimates are consistent within their errors, the stellar-based measurement is twice as high as the gas-based. Similar trends have also been found in the literature. Therefore, a rigorous test of the systematics associated with the different modeling methods is required in the future. I caution to take the effects of different tracers (and methods) into account when discussing the scaling relations.
I conclude this thesis by comparing my galaxy sample with the compilation of galaxies with measured black holes from the literature, also adding six SMASHING galaxies, which were published outside of this thesis. None of the SMASHING galaxies deviates significantly from the literature measurements. Their inclusion to the published early-type galaxies causes a change towards a shallower slope for the M BH - effective velocity dispersion relation, which is mainly driven by the massive galaxies of our sample. More unbiased and homogenous measurements are needed in the future to determine the shape of the relation and understand its physical origin.
Additive Manufacturing (AM) in terms of laser powder-bed fusion (L-PBF) offers new prospects regarding the design of parts and enables therefore the production of lattice structures. These lattice structures shall be implemented in various industrial applications (e.g. gas turbines) for reasons of material savings or cooling channels. However, internal defects, residual stress, and structural deviations from the nominal geometry are unavoidable.
In this work, the structural integrity of lattice structures manufactured by means of L-PBF was non-destructively investigated on a multiscale approach.
A workflow for quantitative 3D powder analysis in terms of particle size, particle shape, particle porosity, inter-particle distance and packing density was established. Synchrotron computed tomography (CT) was used to correlate the packing density with the particle size and particle shape. It was also observed that at least about 50% of the powder porosity was released during production of the struts.
Struts are the component of lattice structures and were investigated by means of laboratory CT. The focus was on the influence of the build angle on part porosity and surface quality. The surface topography analysis was advanced by the quantitative characterisation of re-entrant surface features. This characterisation was compared with conventional surface parameters showing their complementary information, but also the need for AM specific surface parameters.
The mechanical behaviour of the lattice structure was investigated with in-situ CT under compression and successive digital volume correlation (DVC). The deformation was found to be knot-dominated, and therefore the lattice folds unit cell layer wise.
The residual stress was determined experimentally for the first time in such lattice structures. Neutron diffraction was used for the non-destructive 3D stress investigation. The principal stress directions and values were determined in dependence of the number of measured directions. While a significant uni-axial stress state was found in the strut, a more hydrostatic stress state was found in the knot. In both cases, strut and knot, seven directions were at least needed to find reliable principal stress directions.
The individual’s mental lexicon comprises all known words as well related infor-mation on semantics, orthography and phonology. Moreover, entries connect due to simi-larities in these language domains building a large network structure. The access to lexical information is crucial for processing of words and sentences. Thus, a lack of information in-hibits the retrieval and can cause language processing difficulties. Hence, the composition of the mental lexicon is essential for language skills and its assessment is a central topic of lin-guistic and educational research.
In early childhood, measurement of the mental lexicon is uncomplicated, for example through parental questionnaires or the analysis of speech samples. However, with growing content the measurement becomes more challenging: With more and more words in the mental lexicon, the inclusion of all possible known words into a test or questionnaire be-comes impossible. That is why there is a lack of methods to assess the mental lexicon for school children and adults. For the same reason, there are only few findings on the courses of lexical development during school years as well as its specific effect on other language skills. This dissertation is supposed to close this gap by pursuing two major goals: First, I wanted to develop a method to assess lexical features, namely lexicon size and lexical struc-ture, for children of different age groups. Second, I aimed to describe the results of this method in terms of lexical development of size and structure. Findings were intended to help understanding mechanisms of lexical acquisition and inform theories on vocabulary growth.
The approach is based on the dictionary method where a sample of words out of a dictionary is tested and results are projected on the whole dictionary to determine an indi-vidual’s lexicon size. In the present study, the childLex corpus, a written language corpus for children in German, served as the basis for lexicon size estimation. The corpus is assumed to comprise all words children attending primary school could know. Testing a sample of words out of the corpus enables projection of the results on the whole corpus. For this purpose, a vocabulary test based on the corpus was developed. Afterwards, test performance of virtual participants was simulated by drawing different lexicon sizes from the corpus and comparing whether the test items were included in the lexicon or not. This allowed determination of the relation between test performance and total lexicon size and thus could be transferred to a sample of real participants. Besides lexicon size, lexical content could be approximated with this approach and analyzed in terms of lexical structure.
To pursue the presented aims and establish the sampling method, I conducted three consecutive studies. Study 1 includes the development of a vocabulary test based on the childLex corpus. The testing was based on the yes/no format and included three versions for different age groups. The validation grounded on the Rasch Model shows that it is a valid instrument to measure vocabulary for primary school children in German. In Study 2, I estab-lished the method to estimate lexicon sizes and present results on lexical development dur-ing primary school. Plausible results demonstrate that lexical growth follows a quadratic function starting with about 6,000 words at the beginning of school and about 73,000 words on average for young adults. Moreover, the study revealed large interindividual differences. Study 3 focused on the analysis of network structures and their development in the mental lexicon due to orthographic similarities. It demonstrates that networks possess small-word characteristics and decrease in interconnectivity with age.
Taken together, this dissertation provides an innovative approach for the assessment and description of the development of the mental lexicon from primary school onwards. The studies determine recent results on lexical acquisition in different age groups that were miss-ing before. They impressively show the importance of this period and display the existence of extensive interindividual differences in lexical development. One central aim of future research needs to address the causes and prevention of these differences. In addition, the application of the method for further research (e.g. the adaptation for other target groups) and teaching purposes (e.g. adaptation of texts for different target groups) appears to be promising.
The Himalayas are a region that is most dependent, but also frequently prone to hazards from changing meltwater resources. This mountain belt hosts the highest mountain peaks on earth, has the largest reserve of ice outside the polar regions, and is home to a rapidly growing population in recent decades. One source of hazard has attracted scientific research in particular in the past two decades: glacial lake outburst floods (GLOFs) occurred rarely, but mostly with fatal and catastrophic consequences for downstream communities and infrastructure. Such GLOFs can suddenly release several million cubic meters of water from naturally impounded meltwater lakes. Glacial lakes have grown in number and size by ongoing glacial mass losses in the Himalayas. Theory holds that enhanced meltwater production may increase GLOF frequency, but has never been tested so far. The key challenge to test this notion are the high altitudes of >4000 m, at which lakes occur, making field work impractical. Moreover, flood waves can attenuate rapidly in mountain channels downstream, so that many GLOFs have likely gone unnoticed in past decades. Our knowledge on GLOFs is hence likely biased towards larger, destructive cases, which challenges a detailed quantification of their frequency and their response to atmospheric warming. Robustly quantifying the magnitude and frequency of GLOFs is essential for risk assessment and management along mountain rivers, not least to implement their return periods in building design codes.
Motivated by this limited knowledge of GLOF frequency and hazard, I developed an algorithm that efficiently detects GLOFs from satellite images. In essence, this algorithm classifies land cover in 30 years (~1988–2017) of continuously recorded Landsat images over the Himalayas, and calculates likelihoods for rapidly shrinking water bodies in the stack of land cover images. I visually assessed such detected tell-tale sites for sediment fans in the river channel downstream, a second key diagnostic of GLOFs. Rigorous tests and validation with known cases from roughly 10% of the Himalayas suggested that this algorithm is robust against frequent image noise, and hence capable to identify previously unknown GLOFs. Extending the search radius to the entire Himalayan mountain range revealed some 22 newly detected GLOFs. I thus more than doubled the existing GLOF count from 16 previously known cases since 1988, and found a dominant cluster of GLOFs in the Central and Eastern Himalayas (Bhutan and Eastern Nepal), compared to the rarer affected ranges in the North. Yet, the total of 38 GLOFs showed no change in the annual frequency, so that the activity of GLOFs per unit glacial lake area has decreased in the past 30 years. I discussed possible drivers for this finding, but left a further attribution to distinct GLOF-triggering mechanisms open to future research.
This updated GLOF frequency was the key input for assessing GLOF hazard for the entire Himalayan mountain belt and several subregions. I used standard definitions in flood hydrology, describing hazard as the annual exceedance probability of a given flood peak discharge [m3 s-1] or larger at the breach location. I coupled the empirical frequency of GLOFs per region to simulations of physically plausible peak discharges from all existing ~5,000 lakes in the Himalayas. Using an extreme-value model, I could hence calculate flood return periods. I found that the contemporary 100-year GLOF discharge (the flood level that is reached or exceeded on average once in 100 years) is 20,600+2,200/–2,300 m3 s-1 for the entire Himalayas. Given the spatial and temporal distribution of historic GLOFs, contemporary GLOF hazard is highest in the Eastern Himalayas, and lower for regions with rarer GLOF abundance. I also calculated GLOF hazard for some 9,500 overdeepenings, which could expose and fill with water, if all Himalayan glaciers have melted eventually. Assuming that the current GLOF rate remains unchanged, the 100-year GLOF discharge could double (41,700+5,500/–4,700 m3 s-1), while the regional GLOF hazard may increase largest in the Karakoram.
To conclude, these three stages–from GLOF detection, to analysing their frequency and estimating regional GLOF hazard–provide a framework for modern GLOF hazard assessment. Given the rapidly growing population, infrastructure, and hydropower projects in the Himalayas, this thesis assists in quantifying the purely climate-driven contribution to hazard and risk from GLOFs.