@misc{BoettleRybskiKropp2016, author = {Boettle, Markus and Rybski, Diego and Kropp, J{\"u}rgen}, title = {Quantifying the effect of sea level rise and flood defence}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {559}, issn = {1866-8372}, doi = {10.25932/publishup-41240}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-412405}, pages = {18}, year = {2016}, abstract = {In contrast to recent advances in projecting sea levels, estimations about the economic impact of sea level rise are vague. Nonetheless, they are of great importance for policy making with regard to adaptation and greenhouse-gas mitigation. Since the damage is mainly caused by extreme events, we propose a stochastic framework to estimate the monetary losses from coastal floods in a confined region. For this purpose, we follow a Peak-over-Threshold approach employing a Poisson point process and the Generalised Pareto Distribution. By considering the effect of sea level rise as well as potential adaptation scenarios on the involved parameters, we are able to study the development of the annual damage. An application to the city of Copenhagen shows that a doubling of losses can be expected from a mean sea level increase of only 11 cm. In general, we find that for varying parameters the expected losses can be well approximated by one of three analytical expressions depending on the extreme value parameters. These findings reveal the complex interplay of the involved parameters and allow conclusions of fundamental relevance. For instance, we show that the damage typically increases faster than the sea level rise itself. This in turn can be of great importance for the assessment of sea level rise impacts on the global scale. Our results are accompanied by an assessment of uncertainty, which reflects the stochastic nature of extreme events. While the absolute value of uncertainty about the flood damage increases with rising mean sea levels, we find that it decreases in relation to the expected damage.}, language = {en} } @article{PrahlRybskiBoettleetal.2016, author = {Prahl, Boris F. and Rybski, Diego and Boettle, Markus and Kropp, J{\"u}rgen}, title = {Damage functions for climate-related hazards: unification and uncertainty analysis}, series = {Natural hazards and earth system sciences}, volume = {16}, journal = {Natural hazards and earth system sciences}, publisher = {Copernicus}, address = {G{\"o}ttingen}, issn = {1561-8633}, doi = {10.5194/nhess-16-1189-2016}, pages = {1189 -- 1203}, year = {2016}, abstract = {Most climate change impacts manifest in the form of natural hazards. Damage assessment typically relies on damage functions that translate the magnitude of extreme events to a quantifiable damage. In practice, the availability of damage functions is limited due to a lack of data sources and a lack of understanding of damage processes. The study of the characteristics of damage functions for different hazards could strengthen the theoretical foundation of damage functions and support their development and validation. Accordingly, we investigate analogies of damage functions for coastal flooding and for wind storms and identify a unified approach. This approach has general applicability for granular portfolios and may also be applied, for example, to heat-related mortality. Moreover, the unification enables the transfer of methodology between hazards and a consistent treatment of uncertainty. This is demonstrated by a sensitivity analysis on the basis of two simple case studies (for coastal flood and storm damage). The analysis reveals the relevance of the various uncertainty sources at varying hazard magnitude and on both the microscale and the macroscale level. Main findings are the dominance of uncertainty from the hazard magnitude and the persistent behaviour of intrinsic uncertainties on both scale levels. Our results shed light on the general role of uncertainties and provide useful insight for the application of the unified approach.}, 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} } @article{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 = {Natural hazards and earth system sciences}, volume = {15}, journal = {Natural hazards and earth system sciences}, number = {4}, publisher = {Copernicus}, address = {G{\"o}ttingen}, issn = {1561-8633}, doi = {10.5194/nhess-15-769-2015}, pages = {769 -- 788}, 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} } @article{ZhouRybskiKropp2013, author = {Zhou, Bin and Rybski, Diego and Kropp, J{\"u}rgen}, title = {On the statistics of urban heat island intensity}, series = {Geophysical research letters}, volume = {40}, journal = {Geophysical research letters}, number = {20}, publisher = {American Geophysical Union}, address = {Washington}, issn = {0094-8276}, doi = {10.1002/2013GL057320}, pages = {5486 -- 5491}, year = {2013}, abstract = {We perform a systematic study of all cities in Europe to assess the Urban Heat Island (UHI) intensity by means of remotely sensed land surface temperature data. Defining cities as spatial clusters of urban land cover, we investigate the relationships of the UHI intensity, with the cluster size and the temperature of the surroundings. Our results show that in Europe, the UHI intensity in summer has a strong correlation with the cluster size, which can be well fitted by an empirical sigmoid model. Furthermore, we find a novel seasonality of the UHI intensity for individual clusters in the form of hysteresis-like curves. We characterize the shape and identify apparent regional patterns.}, language = {en} } @article{BoettleRybskiKropp2013, author = {B{\"o}ttle, Markus and Rybski, Diego and Kropp, J{\"u}rgen}, title = {How changing sea level extremes and protection measures alter coastal flood damages}, series = {Water resources research}, volume = {49}, journal = {Water resources research}, number = {3}, publisher = {American Geophysical Union}, address = {Washington}, issn = {0043-1397}, doi = {10.1002/wrcr.20108}, pages = {1199 -- 1210}, year = {2013}, abstract = {While sea level rise is one of the most likely consequences of climate change, the provoked costs remain highly uncertain. Based on a block-maxima approach, we provide a stochastic framework to estimate the increase of expected damages with sea level rise as well as with meteorological changes and demonstrate the application to two case studies. In addition, the uncertainty of the damage estimations due to the stochastic nature of extreme events is studied. Starting with the probability distribution of extreme flood levels, we calculate the distribution of implied damages in a specific region employing stage-damage functions. Universal relations of the expected damages and their standard deviation, which demonstrate the importance of the shape of the damage function, are provided. We also calculate how flood protection reduces the damages leading to a more complex picture, where the extreme value behavior plays a fundamental role. Citation: Boettle, M., D. Rybski, and J. P. Kropp (2013), How changing sea level extremes and protection measures alter coastal flood damages, Water Resour. Res., 49, 1199-1210, doi: 10.1002/wrcr.20108.}, language = {en} } @article{RybskiRosKropp2013, author = {Rybski, Diego and Ros, Anselmo Garcia Cantu and Kropp, J{\"u}rgen}, title = {Distance-weighted city growth}, series = {PHYSICAL REVIEW E}, volume = {87}, journal = {PHYSICAL REVIEW E}, number = {4}, publisher = {AMER PHYSICAL SOC}, address = {COLLEGE PK}, issn = {1539-3755}, doi = {10.1103/PhysRevE.87.042114}, pages = {6}, year = {2013}, abstract = {Urban agglomerations exhibit complex emergent features of which Zipf\’s law, i.e., a power-law size distribution, and fractality may be regarded as the most prominent ones. We propose a simplistic model for the generation of citylike structures which is solely based on the assumption that growth is more likely to take place close to inhabited space. The model involves one parameter which is an exponent determining how strongly the attraction decays with the distance. In addition, the model is run iteratively so that existing clusters can grow (together) and new ones can emerge. The model is capable of reproducing the size distribution and the fractality of the boundary of the largest cluster. Although the power-law distribution depends on both, the imposed exponent and the iteration, the fractality seems to be independent of the former and only depends on the latter. Analyzing land-cover data, we estimate the parameter-value gamma approximate to 2.5 for Paris and its surroundings. DOI: 10.1103/PhysRevE.87.042114}, language = {en} } @article{PrahlRybskiKroppetal.2012, author = {Prahl, Boris F. and Rybski, Diego and Kropp, J{\"u}rgen and Burghoff, Olaf and Held, Hermann}, title = {Applying stochastic small-scale damage functions to German winter storms}, series = {Geophysical research letters}, volume = {39}, journal = {Geophysical research letters}, number = {12}, publisher = {American Geophysical Union}, address = {Washington}, issn = {0094-8276}, doi = {10.1029/2012GL050961}, pages = {6}, year = {2012}, abstract = {Analyzing insurance-loss data we derive stochastic storm-damage functions for residential buildings. On district level we fit power-law relations between daily loss and maximum wind speed, typically spanning more than 4 orders of magnitude. The estimated exponents for 439 German districts roughly range from 8 to 12. In addition, we find correlations among the parameters and socio-demographic data, which we employ in a simplified parametrization of the damage function with just 3 independent parameters for each district. A Monte Carlo method is used to generate loss estimates and confidence bounds of daily and annual storm damages in Germany. Our approach reproduces the annual progression of winter storm losses and enables to estimate daily losses over a wide range of magnitudes. Citation: Prahl, B. F., D. Rybski, J. P. Kropp, O. Burghoff, and H. Held (2012), Applying stochastic small-scale damage functions to German winter storms, Geophys. Res. Lett., 39, L06806, doi: 10.1029/2012GL050961.}, language = {en} }