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Studien und Literatur

Ausgewählte Studien und Arbeiten zu Extremniederschlägen der Schweiz sowie Publikationen bezüglich Methoden der Extremwertstatistik. Es besteht kein Anspruch auf Vollständigkeit.


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Analysen der MeteoSchweiz


Extreme value analyses of a large number of relatively short time series are in increasing demand in environmental sciences and design. Here, we present an automated procedure for the peaks-over-threshold (POT) approach to extreme value theory and use it to provide a climatology of extreme hourly precipitation in Switzerland. The POT approach fits the generalized Pareto distribution (GPD) to independent exceedances above some high threshold. To guarantee independence, the time series is pruned: exceedances separated by less than a fixed interval called the run parameter are considered a cluster, and all but the cluster maxima are discarded. We propose the automation of an existing graphical method for joint selection of threshold and run parameter. Hourly precipitation is analyzed at 59 stations of the MeteoSwiss observational network over the period 1981–2010. The four seasons are considered separately. When necessary, a simple detrending is applied. Results suggest that unnecessarily large run parameters have adverse effects on the estimation of the GPD parameters. The proposed method yields mean cluster sizes that reflect the seasonal and geographical variation of lag dependence of hourly precipitation. The climatology, as represented by the return level maps and Alpine cross-section, mirror known aspects of the Swiss climate. Unlike for daily precipitation, summer thunderstorm tracks are visible in the seasonal frequency of events, rather than in the amplitude of rare events.


Methoden und ihre Anwendung auf Schweizer Niederschlag

  • Blanchet et al. (2015), Regional Intensity – Duration – Frequency analysis in a GEV scale-invariant framework, Water Resources Research, submitted
  • Coles, S. (2001), Introduction to statistical modeling of extreme values. Springer series in Statistics, Springer-Verlag, London.
  • Katz, R. W., M. B. Parlange and P. Naveau (2002), Statistics of extremes in hydrology, Advances in Water Resources, 25, 1287-1304.
  • Leadbetter, M. R., G. Lindgren and H. Rootzen, (1983), Extremes and related properties of random sequences and processes, Springer series in statistics, Springer-Verlag, New York.
  • Naveau, P., A. Toreti, I. Smith and E. Xoplaki (2014), A fast nonparametric spatio-temporal regression scheme for Generalized Pareto distributed heavy precipitation, Water Resources Research, 50, 4011 – 4017.
  • Rust, H. W., D. Maraun and T. J. Osborn  (2009), Modelling seasonality in extreme precipitation, The European Physical Journal – Special Topics, 174(1), 99-111.