final_program_abstracts[1]

11 IMSC Session Program
Nonparametric testing for change in the frequency of extreme
events
Friday - Poster Session 7
Markus Neuhäuser
Department of Mathematics and Technique, RheinAhrCampus, Koblenz University of
Applied Sciences, Remagen, Germany
The detection of a change in the frequency of extreme events in a time series is of
particular interest in climatology. Lopez-Diaz (Journal of Climate 203; 16, 2602-
2614) proposed to apply the nonparametric Wilcoxon-Mann-Whitney test. Here it is
shown that, when the climate is becoming more extreme, the positions that the events
occupy in the series have a smaller variance than the positions without the event. In
addition, there are obviously more observations without than with an extreme event.
In such a scenario another rank-based test, the test introduced by Brunner and Munzel
(Biometrical Journal 2000; 42, 17-25) is much more powerful than the Wilcoxon-
Mann-Whitney test. This difference in power is demonstrated here using simulated
data and three real time series on climate change.
Abstracts 318