@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}
}
@phdthesis{Siegmund2018,
  author    = {Siegmund, Jonatan Frederik},
  title     = {Quantifying impacts of climate extreme events on vegetation},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-407095},
  school      = {Universit{\"a}t Potsdam},
  pages     = {129},
  year      = {2018},
  abstract  = {Together with the gradual change of mean values, ongoing climate change is projected to increase frequency and amplitude of temperature and precipitation extremes in many regions of Europe. The impacts of such in most cases short term extraordinary climate situations on terrestrial ecosystems are a matter of central interest of recent climate change research, because it can not per se be assumed that known dependencies between climate variables and ecosystems are linearly scalable. So far, yet, there is a high demand for a method to quantify such impacts in terms of simultaneities of event time series. In the course of this manuscript the new statistical approach of Event Coincidence Analysis (ECA) as well as it's R implementation is introduced, a methodology that allows assessing whether or not two types of event time series exhibit similar sequences of occurrences. Applications of the method are presented, analyzing climate impacts on different temporal and spacial scales: the impact of extraordinary expressions of various climatic variables on tree stem variations (subdaily and local scale), the impact of extreme temperature and precipitation events on the owering time of European shrub species (weekly and country scale), the impact of extreme temperature events on ecosystem health in terms of NDVI (weekly and continental scale) and the impact of El Ni{\~n}o and La Ni{\~n}a events on precipitation anomalies (seasonal and global scale). The applications presented in this thesis refine already known relationships based on classical methods and also deliver substantial new findings to the scientific community: the widely known positive correlation between flowering time and temperature for example is confirmed to be valid for the tails of the distributions while the widely assumed positive dependency between stem diameter variation and temperature is shown to be not valid for very warm and very cold days. The larger scale investigations underline the sensitivity of anthrogenically shaped landscapes towards temperature extremes in Europe and provide a comprehensive global ENSO impact map for strong precipitation events. Finally, by publishing the R implementation of the method, this thesis shall enable other researcher to further investigate on similar research questions by using Event Coincidence Analysis.},
  language  = {en}
}