Articles | Volume 18, issue 5
Hydrol. Earth Syst. Sci., 18, 1561–1573, 2014
Hydrol. Earth Syst. Sci., 18, 1561–1573, 2014

Research article 06 May 2014

Research article | 06 May 2014

Selection of intense rainfall events based on intensity thresholds and lightning data in Switzerland

L. Gaál1,2,*, P. Molnar1, and J. Szolgay2 L. Gaál et al.
  • 1Institute of Environmental Engineering, ETH Zurich, Zurich, Switzerland
  • 2Slovak University of Technology, Bratislava, Slovakia
  • *now at: Technical University of Vienna, Vienna, Austria

Abstract. This paper presents a method to identify intense warm season storms with convective character based on intensity thresholds and the presence of lightning, and analyzes their statistical properties. Long records of precipitation and lightning data at 4 stations and 10 min resolution in different climatological regions in Switzerland are used. Our premise is that thunderstorms associated with lightning generate bursts of high rainfall intensity. We divided all recorded storms into those accompanied by lightning and those without lightning and found the threshold I* that separates intense events based on peak 10 min intensity IpI* for a chosen misclassification rate α. The performance and robustness of the selection method was tested by investigating the inter-annual variability of I* and its relation to the frequency of lightning strikes. The probability distributions of the main storm properties (rainfall depth R, event duration D, average storm intensity Ia and peak 10 min intensity Ip) for the intense storm subsets show that the event average and peak intensities are significantly different between the stations. Non-parametric correlations between the main storm properties were estimated for intense storms and all storms including stratiform rain. The differences in the correlations between storm subsets are greater than those between stations, which indicates that care must be exercised not to mix events of different origin when they are sampled for multivariate analysis, for example, copula fitting to rainfall data.