@phdthesis{Lehmann2016,
  author    = {Lehmann, Jascha In-su},
  title     = {Changes in extratropical storm track activity and their implications for extreme weather events},
  pages     = {221},
  year      = {2016},
  language  = {en}
}
@phdthesis{Kornhuber2017,
  author    = {Kornhuber, Kai},
  title     = {Rossby wave dynamics and changes in summertime weather extremes},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xii, 222},
  year      = {2017},
  abstract  = {Extreme weather events like heatwaves and floods severely affect societies with impacts ranging from economic damages to losses in human lifes. Global warming caused by anthropogenic greenhouse gas emissions is expected to increase their frequency and intensity, particularly in the warm season. Next to these thermodynamic changes, climate change might also impact the large scale atmospheric circulation.Such dynamic changes might additionally act on the occurence of extreme weather events, but involved mechanisms are often highly non-linear. Therefore, large uncertainty exists on the exact nature of these changes and the related risks to society. Particularly in the densely populated mid-latitudes weather patterns are governed by the large scale circulation like the jet-streams and storm tracks. Extreme weather in this region is often related to persistent weather systems associated with a strongly meandering jet-stream. Such meanders are called Rossby waves. Under specific conditions they can become slow moving, stretched around the entire hemisphere and generate simultaneaous heat- and rainfall extremes in far-away regions. This thesis aims at enhancing the understanding of synoptic-scale, circumglobal Rossby waves and the associated risks of dynamical changes to society. More specific, the analyses investigate their relation to extreme weather, regions at risk, under which conditions they are generated, and the influence of anthropogenic climate change on those conditions now, in the past and in the future. I find that circumglobal Rossby waves promoted simultaneous occuring weather extremes across the northern hemisphere in several recent summers. Further, I present evidence that they are often linked to quasiresonant-amplification of planetary waves. These events include the 2003 European heatwave and the Moscow heatwave of 2010. This non-linear mechanism acts on the upper level flow through trapping and amplification of stationary synoptic scale waves. I show that this resonance mechanism acts in both hemispheres and is related to extreme weather. A main finding is that circumglobal Rossby waves primarily occur as two specific teleconnection patterns associated with a wave 5 and wave 7 pattern in the northern hemisphere, likely due to the favourable longitudinal distance of prominent mountain ridges here. Furthermore, I identify those regions which are particularly at risk: The central United States, western Europe and the Ukraine/Russian region. Moreover, I present evidence that the wave 7 pattern has and extreme weather in these regions. My results suggest that the increase in frequency can be linked to favourable changes in large scale temperature gradients, which I show to be largely underestimated by model simulations. Using surface temperature fingerprint as proxy for investigating historic and future model ensembles, evidence is presented that anthropogenic warming has likely increased the probability for the occurence of circumglobal Rossby waves. Further it is shown that this might lead to a doubling of such events until the end of the century under a high-emission scenario. Overall, this thesis establishes several atmosphere-dynamical pathways by which changes in large scale temperature gradients might link to persistent boreal summer weather. It highlights the societal risks associated with the increasing occurence of a newly discovered Rossby wave teleconnection pattern, which has the potential to cause simultaneaous heat-extremes in the mid-latitudinal bread-basket regions. In addition, it provides further evidence that the traditional picture by which quasi-stationary Rossby waves occur only in the low wavenumber regime, should be reconsidered.},
  language  = {en}
}
@misc{Steiglechner2018,
  type      = {Master Thesis},
  author    = {Steiglechner, Peter},
  title     = {Estimating global warming from anthropogenic heat emissions},
  doi       = {10.25932/publishup-49886},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-498866},
  school      = {Universit{\"a}t Potsdam},
  year      = {2018},
  abstract  = {The forcing from the anthropogenic heat flux (AHF), i.e. the dissipation of primary energy consumed by the human civilisation, produces a direct climate warming. Today, the globally averaged AHF is negligibly small compared to the indirect forcing from greenhouse gas emissions. Locally or regionally, though, it has a significant impact. Historical observations show a constant exponential growth of worldwide energy production. A continuation of this trend might be fueled or even amplified by the exploration of new carbon-free energy sources like fusion power. In such a scenario, the impacts of the AHF become a relevant factor for anthropogenic post-greenhouse gas climate change on the global scale, as well. This master thesis aims at estimating the climate impacts of such a growing AHF forcing. In the first part of this work, the AHF is built into simple and conceptual, zero- and one-dimensional Energy Balance Models (EBMs), providing quick order of magnitude estimations of the temperature impact. In the one-dimensional EBM, the ice-albedo feedback from enhanced ice melting due to the AHF increases the temperature impact significantly compared to the zero-dimensional EBM. Additionally, the forcing is built into a climate model of intermediate complexity, CLIMBER-3α. This allows for the investigation of the effect of localised AHF and gives further insights into the impact of the AHF on processes like the ocean heat uptake, sea ice and snow pattern changes and the ocean circulation. The global mean temperature response from the AHF today is of the order of 0.010 - 0.016 K in all reasonable model configurations tested. A transient tenfold increase of this forcing heats up the Earth System additionally by roughly 0.1 - 0.2 K in the presented models. Further growth can also affect the tipping probability of certain climate elements. Most renewable energy sources do not or only partially contribute to the AHF forcing as the energy from these sources dissipates anyway. Hence, the transition to a (carbon-free) renewable energy mix, which, in particular, does not rely on nuclear power, eliminates the local and global climate impacts from the increasing AHF forcing, independent of the growth of energy production.},
  language  = {en}
}
@phdthesis{Reese2018,
  author    = {Reese, Ronja},
  title     = {The far reach of ice-shelf thinning in Antarctica},
  school      = {Universit{\"a}t Potsdam},
  pages     = {227},
  year      = {2018},
  language  = {en}
}
@phdthesis{Hesse2018,
  author    = {Hesse, Cornelia},
  title     = {Integrated water quality modelling in meso- to large-scale catchments of the Elbe river basin under climate and land use change},
  doi       = {10.25932/publishup-42295},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-422957},
  school      = {Universit{\"a}t Potsdam},
  pages     = {ix, 217},
  year      = {2018},
  abstract  = {In einer sich {\"a}ndernden Umwelt sind Fließgew{\"a}sser{\"o}kosysteme vielf{\"a}ltigen direkten und indirekten anthropogenen Belastungen ausgesetzt, die die Gew{\"a}sser sowohl in ihrer Menge als auch in ihrer G{\"u}te beeintr{\"a}chtigen k{\"o}nnen. Ein {\"u}berm{\"a}ßiger Eintrag von N{\"a}hrstoffen verursacht etwa Massenentwicklungen von Algen und Sauerstoffdefizite in den Gew{\"a}ssern, was zum Verfehlen der Ziele der Wasserrahmenrichtlinie (WRRL) f{\"u}hren kann. In vielen europ{\"a}ischen Einzugsgebieten und auch dem der Elbe sind solche Probleme zu beobachten. W{\"a}hrend der letzten Jahrzehnte entstanden diverse computergest{\"u}tzte Modelle, die zum Schutz und Management von Wasserressourcen genutzt werden k{\"o}nnen. Sie helfen beim Verstehen der N{\"a}hrstoffprozesse und Belastungspfade in Einzugsgebieten, bei der Absch{\"a}tzung m{\"o}glicher Folgen von Klima- und Landnutzungs{\"a}nderungen f{\"u}r die Wasserk{\"o}rper, sowie bei der Entwicklung eventueller Kompensationsmaßnahmen. Aufgrund der Vielzahl an sich gegenseitig beeinflussenden Prozessen ist die Modellierung der Wasserqualit{\"a}t komplexer und aufw{\"a}ndiger als eine reine hydrologische Modellierung. {\"O}kohydrologische Modelle zur Simulation der Gew{\"a}sserg{\"u}te, einschließlich des Modells SWIM (Soil and Water Integrated Model), bed{\"u}rfen auch h{\"a}ufig noch einer Weiterentwicklung und Verbesserung der Prozessbeschreibungen. Aus diesen {\"U}berlegungen entstand die vorliegende Dissertation, die sich zwei Hauptanliegen widmet: 1) einer Weiterentwicklung des N{\"a}hrstoffmoduls des {\"o}kohydrologischen Modells SWIM f{\"u}r Stickstoff- und Phosphorprozesse, und 2) der Anwendung des Modells SWIM im Elbegebiet zur Unterst{\"u}tzung eines anpassungsf{\"a}higen Wassermanagements im Hinblick auf m{\"o}gliche zuk{\"u}nftige {\"A}nderungen der Umweltbedingungen. Die kumulative Dissertation basiert auf f{\"u}nf wissenschaftlichen Artikeln, die in internationalen Zeitschriften ver{\"o}ffentlicht wurden. Im Zuge der Arbeit wurden verschiedene Modellanpassungen in SWIM vorgenommen, wie etwa ein einfacher Ansatz zur Verbesserung der Simulation der Wasser- und N{\"a}hrstoffverh{\"a}ltnisse in Feuchtgebieten, ein um Ammonium erweiterter Stickstoffkreislauf im Boden, sowie ein Flussprozessmodul, das Umwandlungsprozesse, Sauerstoffverh{\"a}ltnisse und Algenwachstum im Fließgew{\"a}sser simuliert, haupts{\"a}chlich angetrieben von Temperatur und Licht. Auch wenn dieser neue Modellansatz ein sehr komplexes Modell mit einer Vielzahl an neuen Kalibrierungsparametern und steigender Unsicherheit erzeugte, konnten gute Ergebnisse in den Teileinzugsgebieten und dem gesamten Gebiet der Elbe erzielt werden, so dass das Modell zur Absch{\"a}tzung m{\"o}glicher Folgen von Klimavariabilit{\"a}ten und ver{\"a}nderten anthropogenen Einfl{\"u}ssen f{\"u}r die Gew{\"a}sserg{\"u}te genutzt werden konnte. Das neue Fließgew{\"a}ssermodul ist ein wichtiger Beitrag zur Verbesserung der N{\"a}hrstoffmodellierung in SWIM, vor allem f{\"u}r Stoffe, die haupts{\"a}chlich aus Punktquellen in die Gew{\"a}sser gelangen (wie z.B. Phosphat). Der neue Modellansatz verbessert zudem die Anwendbarkeit von SWIM f{\"u}r Fragestellungen im Zusammenhang mit der WRRL, bei der biologische Qualit{\"a}tskomponenten (wie etwa Phytoplankton) eine zentrale Rolle spielen. Die dargestellten Ergebnisse der Wirkungsstudien k{\"o}nnen bei Entscheidungstr{\"a}gern und anderen Akteuren das Verst{\"a}ndnis f{\"u}r zuk{\"u}nftige Herausforderungen im Gew{\"a}ssermanagement erh{\"o}hen und dazu beitragen, ein angepasstes Management f{\"u}r das Elbeeinzugsgebiet zu entwickeln.},
  language  = {en}
}
@phdthesis{Willner2018,
  author    = {Willner, Sven N.},
  title     = {Global economic response to flood damages under climate change},
  school      = {Universit{\"a}t Potsdam},
  pages     = {v, 247},
  year      = {2018},
  abstract  = {Climate change affects societies across the globe in various ways. In addition to gradual changes in temperature and other climatic variables, global warming is likely to increase intensity and frequency of extreme weather events. Beyond biophysical impacts, these also directly affect societal and economic activity. Additionally, indirect effects can occur; spatially, economic losses can spread along global supply-chains; temporally, climate impacts can change the economic development trajectory of countries. This thesis first examines how climate change alters river flood risk and its local socio-economic implications. Then, it studies the global economic response to river floods in particular, and to climate change in general. Changes in high-end river flood risk are calculated for the next three decades on a global scale with high spatial resolution. In order to account for uncertainties, this assessment makes use of an ensemble of climate and hydrological models as well as a river routing model, that is found to perform well regarding peak river discharge. The results show an increase in high-end flood risk in many parts of the world, which require profound adaptation efforts. This pressure to adapt is measured as the enhancement in protection level necessary to stay at historical high-end risk. In developing countries as well as in industrialized regions, a high pressure to adapt is observed - the former to increase low protection levels, the latter to maintain the low risk levels perceived in the past. Further in this thesis, the global agent-based dynamic supply-chain model acclimate is developed. It models the cascading of indirect losses in the global supply network. As an anomaly model its agents - firms and consumers - maximize their profit locally to respond optimally to local perturbations. Incorporating quantities as well as prices on a daily basis, it is suitable to dynamically resolve the impacts of unanticipated climate extremes. The model is further complemented by a static measure, which captures the inter-dependencies between sectors across regions that are only connected indirectly. These higher-order dependencies are shown to be important for a comprehensive assessment of loss-propagation and overall costs of local disasters. In order to study the economic response to river floods, the acclimate model is driven by flood simulations. Within the next two decades, the increase in direct losses can only partially be compensated by market adjustments, and total losses are projected to increase by 17\% without further adaptation efforts. The US and the EU are both shown to receive indirect losses from China, which is strongly affected directly. However, recent trends in the trade relations leave the EU in a better position to compensate for these losses. Finally, this thesis takes a broader perspective when determining the investment response to the climate change damages employing the integrated assessment model DICE. On an optimal economic development path, the increase in damages is anticipated as emissions and consequently temperatures increase. This leads to a significant devaluation of investment returns and the income losses from climate damages almost double. Overall, the results highlight the need to adapt to extreme weather events - local physical adaptation measures have to be combined with regional and global policy measures to prepare the global supply-chain network to climate change.},
  language  = {en}
}
@article{LadeiraMarwanDestroFilhoetal.2020,
  author    = {Ladeira, Guenia and Marwan, Norbert and Destro-Filho, Joao-Batista and Ramos, Camila Davi and Lima, Gabriela},
  title     = {Frequency spectrum recurrence analysis},
  series = {Scientific reports},
  volume    = {10},
  journal   = {Scientific reports},
  number    = {1},
  publisher = {Nature portfolio},
  address   = {Berlin},
  issn      = {2045-2322},
  doi       = {10.1038/s41598-020-77903-4},
  pages     = {9},
  year      = {2020},
  abstract  = {In this paper, we present the new frequency spectrum recurrence analysis technique by means of electro-encephalon signals (EES) analyses. The technique is suitable for time series analysis with noise and disturbances. EES were collected, and alpha waves of the occipital region were analysed by comparing the signals from participants in two states, eyes open and eyes closed. Firstly, EES were characterized and analysed by means of techniques already known to compare with the results of the innovative technique that we present here. We verified that, standard recurrence quantification analysis by means of EES time series cannot statistically distinguish the two states. However, the new frequency spectrum recurrence quantification exhibit quantitatively whether the participants have their eyes open or closed. In sequence, new quantifiers are created for analysing the recurrence concentration on frequency bands. These analyses show that EES with similar frequency spectrum have different recurrence levels revealing different behaviours of the nervous system. The technique can be used to deepen the study on depression, stress, concentration level and other neurological issues and also can be used in any complex system.},
  language  = {en}
}
@misc{OttoPiontekKalkuhletal.2020,
  author    = {Otto, Christian and Piontek, Franziska and Kalkuhl, Matthias and Frieler, Katja},
  title     = {Event-based models to understand the scale of the impact of extremes},
  series = {Nature energy},
  volume    = {5},
  journal   = {Nature energy},
  number    = {2},
  publisher = {Nature Publishing Group},
  address   = {London},
  issn      = {2058-7546},
  doi       = {10.1038/s41560-020-0562-4},
  pages     = {111 -- 114},
  year      = {2020},
  abstract  = {Climate change entails an intensification of extreme weather events that can potentially trigger socioeconomic and energy system disruptions. As we approach 1 degrees C of global warming we should start learning from historical extremes and explicitly incorporate such events in integrated climate-economy and energy systems models.},
  language  = {en}
}
@article{PradhanKropp2020,
  author    = {Pradhan, Prajal and Kropp, J{\"u}rgen},
  title     = {Interplay between diets, health, and climate change},
  series = {Sustainability},
  volume    = {12},
  journal   = {Sustainability},
  number    = {9},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {2071-1050},
  doi       = {10.3390/su12093878},
  pages     = {14},
  year      = {2020},
  abstract  = {The world is facing a triple burden of undernourishment, obesity, and environmental impacts from agriculture while nourishing its population. This burden makes sustainable nourishment of the growing population a global challenge. Addressing this challenge requires an understanding of the interplay between diets, health, and associated environmental impacts (e.g., climate change). For this, we identify 11 typical diets that represent dietary habits worldwide for the last five decades. Plant-source foods provide most of all three macronutrients (carbohydrates, protein, and fat) in developing countries. In contrast, animal-source foods provide a majority of protein and fat in developed ones. The identified diets deviate from the recommended healthy diet with either too much (e.g., red meat) or too little (e.g., fruits and vegetables) food and nutrition supply. The total calorie supplies are lower than required for two diets. Sugar consumption is higher than recommended for five diets. Three and five diets consist of larger-than-recommended carbohydrate and fat shares, respectively. Four diets with a large share of animal-source foods exceed the recommended value of red meat. Only two diets consist of at least 400 gm/cap/day of fruits and vegetables while accounting for food waste. Prevalence of undernourishment and underweight dominates in the diets with lower calories. In comparison, a higher prevalence of obesity is observed for diets with higher calories with high shares of sugar, fat, and animal-source foods. However, embodied emissions in the diets do not show a clear relation with calorie supplies and compositions. Two high-calorie diets embody more than 1.5 t CO<mml:semantics>2</mml:semantics>eq/cap/yr, and two low-calorie diets embody around 1 t CO<mml:semantics>2</mml:semantics>eq/cap/yr. Our analysis highlights that sustainable and healthy diets can serve the purposes of both nourishing the population and, at the same time, reducing the environmental impacts of agriculture.},
  language  = {en}
}
@phdthesis{Kraemer2021,
  author    = {Kr{\"a}mer, Kai Hauke},
  title     = {Towards a robust framework for recurrence analysis},
  doi       = {10.25932/publishup-53874},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-538743},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xlii, 217},
  year      = {2021},
  abstract  = {In our daily life, recurrence plays an important role on many spatial and temporal scales and in different contexts. It is the foundation of learning, be it in an evolutionary or in a neural context. It therefore seems natural that recurrence is also a fundamental concept in theoretical dynamical systems science. The way in which states of a system recur or develop in a similar way from similar initial states makes it possible to infer information about the underlying dynamics of the system. The mathematical space in which we define the state of a system (state space) is often high dimensional, especially in complex systems that can also exhibit chaotic dynamics. The recurrence plot (RP) enables us to visualize the recurrences of any high-dimensional systems in a two-dimensional, binary representation. Certain patterns in RPs can be related to physical properties of the underlying system, making the qualitative and quantitative analysis of RPs an integral part of nonlinear systems science. The presented work has a methodological focus and further develops recurrence analysis (RA) by addressing current research questions related to an increasing amount of available data and advances in machine learning techniques. By automatizing a central step in RA, namely the reconstruction of the state space from measured experimental time series, and by investigating the impact of important free parameters this thesis aims to make RA more accessible to researchers outside of physics. The first part of this dissertation is concerned with the reconstruction of the state space from time series. To this end, a novel idea is proposed which automates the reconstruction problem in the sense that there is no need to preprocesse the data or estimate parameters a priori. The key idea is that the goodness of a reconstruction can be evaluated by a suitable objective function and that this function is minimized in the embedding process. In addition, the new method can process multivariate time series input data. This is particularly important because multi-channel sensor-based observations are ubiquitous in many research areas and continue to increase. Building on this, the described minimization problem of the objective function is then processed using a machine learning approach. In the second part technical and methodological aspects of RA are discussed. First, we mathematically justify the idea of setting the most influential free parameter in RA, the recurrence threshold ε, in relation to the distribution of all pairwise distances in the data. This is especially important when comparing different RPs and their quantification statistics and is fundamental to any comparative study. Second, some aspects of recurrence quantification analysis (RQA) are examined. As correction schemes for biased RQA statistics, which are based on diagonal lines, we propose a simple method for dealing with border effects of an RP in RQA and a skeletonization algorithm for RPs. This results in less biased (diagonal line based) RQA statistics for flow-like data. Third, a novel type of RQA characteristic is developed, which can be viewed as a generalized non-linear powerspectrum of high dimensional systems. The spike powerspectrum transforms a spike-train like signal into its frequency domain. When transforming the diagonal line-dependent recurrence rate (τ-RR) of a RP in this way, characteristic periods, which can be seen in the state space representation of the system can be unraveled. This is not the case, when Fourier transforming τ-RR. Finally, RA and RQA are applied to climate science in the third part and neuroscience in the fourth part. To the best of our knowledge, this is the first time RPs and RQA have been used to analyze lake sediment data in a paleoclimate context. Therefore, we first elaborate on the basic formalism and the interpretation of visually visible patterns in RPs in relation to the underlying proxy data. We show that these patterns can be used to classify certain types of variability and transitions in the Potassium record from six short (< 17m) sediment cores collected during the Chew Bahir Drilling Project. Building on this, the long core (∼ m composite) from the same site is analyzed and two types of variability and transitions are identified and compared with ODP Site  wetness index from the eastern Mediterranean. Type  variability likely reflects the influence of precessional forcing in the lower latitudes at times of maximum values of the long eccentricity cycle ( kyr) of the earth's orbit around the sun, with a tendency towards extreme events. Type  variability appears to be related to the minimum values of this cycle and corresponds to fairly rapid transitions between relatively dry and relatively wet conditions. In contrast, RQA has been applied in the neuroscientific context for almost two decades. In the final part, RQA statistics are used to quantify the complexity in a specific frequency band of multivariate EEG (electroencephalography) data. By analyzing experimental data, it can be shown that the complexity of the signal measured in this way across the sensorimotor cortex decreases as motor tasks are performed. The results are consistent with and comple- ment the well known concepts of motor-related brain processes. We assume that the thus discovered features of neuronal dynamics in the sensorimotor cortex together with the robust RQA methods for identifying and classifying these contribute to the non-invasive EEG-based development of brain-computer interfaces (BCI) for motor control and rehabilitation. The present work is an important step towards a robust analysis of complex systems based on recurrence.},
  language  = {en}
}
@article{FeldmannReeseWinkelmannetal.2022,
  author    = {Feldmann, Johannes and Reese, Ronja and Winkelmann, Ricarda and Levermann, Anders},
  title     = {Shear-margin melting causes stronger transient ice discharge than ice-stream melting in idealized simulations},
  series = {The Cryosphere : TC ; an interactive open access journal of the European Geosciences Union},
  volume    = {16},
  journal   = {The Cryosphere : TC ; an interactive open access journal of the European Geosciences Union},
  number    = {5},
  publisher = {Copernicus},
  address   = {G{\"o}ttingen},
  issn      = {1994-0416},
  doi       = {10.5194/tc-16-1927-2022},
  pages     = {1927 -- 1940},
  year      = {2022},
  abstract  = {Basal ice-shelf melting is the key driver of Antarctica's increasing sea-level contribution. In diminishing the buttressing force of the ice shelves that fringe the ice sheet, the melting increases the ice discharge into the ocean. Here we contrast the influence of basal melting in two different ice-shelf regions on the time-dependent response of an isothermal, inherently buttressed ice-sheet-shelf system. In the idealized numerical simulations, the basal-melt perturbations are applied close to the grounding line in the ice-shelf's (1) ice-stream region, where the ice shelf is fed by the fastest ice masses that stream through the upstream bed trough and (2) shear margins, where the ice flow is slower. The results show that melting below one or both of the shear margins can cause a decadal to centennial increase in ice discharge that is more than twice as large compared to a similar perturbation in the ice-stream region. We attribute this to the fact that melt-induced ice-shelf thinning in the central grounding-line region is attenuated very effectively by the fast flow of the central ice stream. In contrast, the much slower ice dynamics in the lateral shear margins of the ice shelf facilitate sustained ice-shelf thinning and thereby foster buttressing reduction. Regardless of the melt location, a higher melt concentration toward the grounding line generally goes along with a stronger response. Our results highlight the vulnerability of outlet glaciers to basal melting in stagnant, buttressing-relevant ice-shelf regions, a mechanism that may gain importance under future global warming.},
  language  = {en}
}
@phdthesis{Middelanis2023,
  author    = {Middelanis, Robin},
  title     = {Global response to local extremes—a storyline approach on economic loss propagation from weather extremes},
  doi       = {10.25932/publishup-61112},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-611127},
  school      = {Universit{\"a}t Potsdam},
  pages     = {vii, 237},
  year      = {2023},
  abstract  = {Due to anthropogenic greenhouse gas emissions, Earth's average surface temperature is steadily increasing. As a consequence, many weather extremes are likely to become more frequent and intense. This poses a threat to natural and human systems, with local impacts capable of destroying exposed assets and infrastructure, and disrupting economic and societal activity. Yet, these effects are not locally confined to the directly affected regions, as they can trigger indirect economic repercussions through loss propagation along supply chains. As a result, local extremes yield a potentially global economic response. To build economic resilience and design effective adaptation measures that mitigate adverse socio-economic impacts of ongoing climate change, it is crucial to gain a comprehensive understanding of indirect impacts and the underlying economic mechanisms. Presenting six articles in this thesis, I contribute towards this understanding. To this end, I expand on local impacts under current and future climate, the resulting global economic response, as well as the methods and tools to analyze this response. Starting with a traditional assessment of weather extremes under climate change, the first article investigates extreme snowfall in the Northern Hemisphere until the end of the century. Analyzing an ensemble of global climate model projections reveals an increase of the most extreme snowfall, while mean snowfall decreases. Assessing repercussions beyond local impacts, I employ numerical simulations to compute indirect economic effects from weather extremes with the numerical agent-based shock propagation model Acclimate. This model is used in conjunction with the recently emerged storyline framework, which involves analyzing the impacts of a particular reference extreme event and comparing them to impacts in plausible counterfactual scenarios under various climate or socio-economic conditions. Using this approach, I introduce three primary storylines that shed light on the complex mechanisms underlying economic loss propagation. In the second and third articles of this thesis, I analyze storylines for the historical Hurricanes Sandy (2012) and Harvey (2017) in the USA. For this, I first estimate local economic output losses and then simulate the resulting global economic response with Acclimate. The storyline for Hurricane Sandy thereby focuses on global consumption price anomalies and the resulting changes in consumption. I find that the local economic disruption leads to a global wave-like economic price ripple, with upstream effects propagating in the supplier direction and downstream effects in the buyer direction. Initially, an upstream demand reduction causes consumption price decreases, followed by a downstream supply shortage and increasing prices, before the anomalies decay in a normalization phase. A dominant upstream or downstream effect leads to net consumption gains or losses of a region, respectively. Moreover, I demonstrate that a longer direct economic shock intensifies the downstream effect for many regions, leading to an overall consumption loss. The third article of my thesis builds upon the developed loss estimation method by incorporating projections to future global warming levels. I use these projections to explore how the global production response to Hurricane Harvey would change under further increased global warming. The results show that, while the USA is able to nationally offset direct losses in the reference configuration, other countries have to compensate for increasing shares of counterfactual future losses. This compensation is mainly achieved by large exporting countries, but gradually shifts towards smaller regions. These findings not only highlight the economy's ability to flexibly mitigate disaster losses to a certain extent, but also reveal the vulnerability and economic disadvantage of regions that are exposed to extreme weather events. The storyline in the fourth article of my thesis investigates the interaction between global economic stress and the propagation of losses from weather extremes. I examine indirect impacts of weather extremes — tropical cyclones, heat stress, and river floods — worldwide under two different economic conditions: an unstressed economy and a globally stressed economy, as seen during the Covid-19 pandemic. I demonstrate that the adverse effects of weather extremes on global consumption are strongly amplified when the economy is under stress. Specifically, consumption losses in the USA and China double and triple, respectively, due to the global economy's decreased capacity for disaster loss compensation. An aggravated scarcity intensifies the price response, causing consumption losses to increase. Advancing on the methods and tools used here, the final two articles in my thesis extend the agent-based model Acclimate and formalize the storyline approach. With the model extension described in the fifth article, regional consumers make rational choices on the goods bought such that their utility is maximized under a constrained budget. In an out-of-equilibrium economy, these rational consumers are shown to temporarily increase consumption of certain goods in spite of rising prices. The sixth article of my thesis proposes a formalization of the storyline framework, drawing on multiple studies including storylines presented in this thesis. The proposed guideline defines eight central elements that can be used to construct a storyline. Overall, this thesis contributes towards a better understanding of economic repercussions of weather extremes. It achieves this by providing assessments of local direct impacts, highlighting mechanisms and impacts of loss propagation, and advancing on methods and tools used.},
  language  = {en}
}
@article{Marwan2023,
  author    = {Marwan, Norbert},
  title     = {Challenges and perspectives in recurrence analyses of event time series},
  series = {Frontiers in applied mathematics and statistics},
  volume    = {9},
  journal   = {Frontiers in applied mathematics and statistics},
  publisher = {Frontiers Media},
  address   = {Lausanne},
  issn      = {2297-4687},
  doi       = {10.3389/fams.2023.1129105},
  pages     = {7},
  year      = {2023},
  abstract  = {The analysis of event time series is in general challenging. Most time series analysis tools are limited for the analysis of this kind of data. Recurrence analysis, a powerful concept from nonlinear time series analysis, provides several opportunities to work with event data and even for the most challenging task of comparing event time series with continuous time series. Here, the basic concept is introduced, the challenges are discussed, and the future perspectives are summarized.},
  language  = {en}
}