@misc{EgholmAndersenFaurschouKnudsenetal.2015,
  author    = {Egholm, David L. and Andersen, Jane Lund and Faurschou Knudsen, Mads and Jansen, John D. and Nielsen, S. B.},
  title     = {The periglacial engine of mountain erosion},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {552},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-40971},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-409718},
  pages     = {20},
  year      = {2015},
  abstract  = {There is growing recognition of strong periglacial control on bedrock erosion in mountain landscapes, including the shaping of low-relief surfaces at high elevations (summit flats). But, as yet, the hypothesis that frost action was crucial to the assumed Late Cenozoic rise in erosion rates remains compelling and untested. Here we present a landscape evolution model incorporating two key periglacial processes - regolith production via frost cracking and sediment transport via frost creep - which together are harnessed to variations in temperature and the evolving thickness of sediment cover. Our computational experiments time-integrate the contribution of frost action to shaping mountain topography over million-year timescales, with the primary and highly reproducible outcome being the development of flattish or gently convex summit flats. A simple scaling of temperature to marine delta O-18 records spanning the past 14 Myr indicates that the highest summit flats in mid-to high-latitude mountains may have formed via frost action prior to the Quaternary. We suggest that deep cooling in the Quaternary accelerated mechanical weathering globally by significantly expanding the area subject to frost. Further, the inclusion of subglacial erosion alongside periglacial processes in our computational experiments points to alpine glaciers increasing the long-term efficiency of frost-driven erosion by steepening hillslopes.},
  language  = {en}
}
@misc{PrahlRybskiBurghoffetal.2015,
  author    = {Prahl, Boris F. and Rybski, Diego and Burghoff, Olaf and Kropp, J{\"u}rgen},
  title     = {Comparison of storm damage functions and their performance},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {492},
  issn      = {1866-8372},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-408119},
  pages     = {20},
  year      = {2015},
  abstract  = {Winter storms are the most costly natural hazard for European residential property. We compare four distinct storm damage functions with respect to their forecast accuracy and variability, with particular regard to the most severe winter storms. The analysis focuses on daily loss estimates under differing spatial aggregation, ranging from district to country level. We discuss the broad and heavily skewed distribution of insured losses posing difficulties for both the calibration and the evaluation of damage functions. From theoretical considerations, we provide a synthesis between the frequently discussed cubic wind-damage relationship and recent studies that report much steeper damage functions for European winter storms. The performance of the storm loss models is evaluated for two sources of wind gust data, direct observations by the German Weather Service and ERA-Interim reanalysis data. While the choice of gust data has little impact on the evaluation of German storm loss, spatially resolved coefficients of variation reveal dependence between model and data choice. The comparison shows that the probabilistic models by Heneka et al. (2006) and Prahl et al. (2012) both provide accurate loss predictions for moderate to extreme losses, with generally small coefficients of variation. We favour the latter model in terms of model applicability. Application of the versatile deterministic model by Klawa and Ulbrich (2003) should be restricted to extreme loss, for which it shows the least bias and errors comparable to the probabilistic model by Prahl et al. (2012).},
  language  = {en}
}