@article{MiddelanisWillnerOttoetal.2021,
  author    = {Middelanis, Robin and Willner, Sven N. and Otto, Christian and Kuhla, Kilian and Quante, Lennart and Levermann, Anders},
  title     = {Wave-like global economic ripple response to Hurricane Sandy},
  series = {Environmental research letters : ERL / Institute of Physics},
  volume    = {16},
  journal   = {Environmental research letters : ERL / Institute of Physics},
  number    = {12},
  publisher = {IOP Publ. Ltd.},
  address   = {Bristol},
  issn      = {1748-9326},
  doi       = {10.1088/1748-9326/ac39c0},
  pages     = {11},
  year      = {2021},
  abstract  = {Tropical cyclones range among the costliest disasters on Earth. Their economic repercussions along the supply and trade network also affect remote economies that are not directly affected. We here simulate possible global repercussions on consumption for the example case of Hurricane Sandy in the US (2012) using the shock-propagation model Acclimate. The modeled shock yields a global three-phase ripple: an initial production demand reduction and associated consumption price decrease, followed by a supply shortage with increasing prices, and finally a recovery phase. Regions with strong trade relations to the US experience strong magnitudes of the ripple. A dominating demand reduction or supply shortage leads to overall consumption gains or losses of a region, respectively. While finding these repercussions in historic data is challenging due to strong volatility of economic interactions, numerical models like ours can help to identify them by approaching the problem from an exploratory angle, isolating the effect of interest. For this, our model simulates the economic interactions of over 7000 regional economic sectors, interlinked through about 1.8 million trade relations. Under global warming, the wave-like structures of the economic response to major hurricanes like the one simulated here are likely to intensify and potentially overlap with other weather extremes.},
  language  = {en}
}
@article{KormannFranckeRenneretal.2015,
  author    = {Kormann, C. and Francke, Till and Renner, M. and Bronstert, Axel},
  title     = {Attribution of high resolution streamflow trends in Western Austria},
  series = {Hydrology and earth system sciences},
  volume    = {19},
  journal   = {Hydrology and earth system sciences},
  publisher = {EGU},
  address   = {Katlenburg-Lindau},
  issn      = {1607-7938},
  doi       = {10.5194/hess-19-1225-2015},
  pages     = {1225 -- 1245},
  year      = {2015},
  abstract  = {The results of streamflow trend studies are often characterized by mostly insignificant trends and inexplicable spatial patterns. In our study region, Western Austria, this applies especially for trends of annually averaged runoff. However, analysing the altitudinal aspect, we found that there is a trend gradient from higher-altitude to lower-altitude stations, i.e. a pattern of mostly positive annual trends at higher stations and negative ones at lower stations. At midaltitudes, the trends are mostly insignificant. Here we hypothesize that the streamflow trends are caused by the following two main processes: on the one hand, melting glaciers produce excess runoff at higher-altitude watersheds. On the other hand, rising temperatures potentially alter hydrological conditions in terms of less snowfall, higher infiltration, enhanced evapotranspiration, etc., which in turn results in decreasing streamflow trends at lower-altitude watersheds. However, these patterns are masked at mid-altitudes because the resulting positive and negative trends balance each other. To support these hypotheses, we attempted to attribute the detected trends to specific causes. For this purpose, we analysed trends of filtered daily streamflow data, as the causes for these changes might be restricted to a smaller temporal scale than the annual one. This allowed for the explicit determination of the exact days of year (DOYs) when certain streamflow trends emerge, which were then linked with the corresponding DOYs of the trends and characteristic dates of other observed variables, e.g. the average DOY when temperature crosses the freezing point in spring. Based on these analyses, an empirical statistical model was derived that was able to simulate daily streamflow trends sufficiently well. Analyses of subdaily streamflow changes provided additional insights. Finally, the present study supports many modelling approaches in the literature which found out that the main drivers of alpine streamflow changes are increased glacial melt, earlier snowmelt and lower snow accumulation in wintertime.},
  language  = {en}
}