ACP Atmospheric Chemistry and Physics ACP 1680-7324 Copernicus GmbH Göttingen, Germany 10.5194/acp-10-10021-2010 Extreme events in total ozone over Arosa – Part 1: Application of extreme value theory Rieder H. E. 1 Staehelin J. 1 Maeder J. A. 1 Peter T. 1 Ribatet M. 2 Davison A. C. 2 Stübi R. 3 Weihs P. 4 Holawe F. 5 Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland Institute of Mathematics, EPF Lausanne, Lausanne, Switzerland Federal Institute of Meteorology and Climatology (MeteoSwiss), Payerne, Switzerland Institute for Meteorology, University of Natural Resources and Applied Life Sciences (BOKU), Vienna, Austria Institute for Geography and Regional Research, University of Vienna, Vienna, Austria 25 10 2010 10 20 10021 10031 This is an open-access article ditributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. This article is available from http://www.atmos-chem-phys.net/10/10021/2010/acp-10-10021-2010.html The full text article is available as a PDF file from http://www.atmos-chem-phys.net/10/10021/2010/acp-10-10021-2010.pdf

In this study ideas from extreme value theory are for the first time applied in the field of stratospheric ozone research, because statistical analysis showed that previously used concepts assuming a Gaussian distribution (e.g. fixed deviations from mean values) of total ozone data do not adequately address the structure of the extremes. We show that statistical extreme value methods are appropriate to identify ozone extremes and to describe the tails of the Arosa (Switzerland) total ozone time series. In order to accommodate the seasonal cycle in total ozone, a daily moving threshold was determined and used, with tools from extreme value theory, to analyse the frequency of days with extreme low (termed ELOs) and high (termed EHOs) total ozone at Arosa. The analysis shows that the Generalized Pareto Distribution (GPD) provides an appropriate model for the frequency distribution of total ozone above or below a mathematically well-defined threshold, thus providing a statistical description of ELOs and EHOs. The results show an increase in ELOs and a decrease in EHOs during the last decades. The fitted model represents the tails of the total ozone data set with high accuracy over the entire range (including absolute monthly minima and maxima), and enables a precise computation of the frequency distribution of ozone mini-holes (using constant thresholds). Analyzing the tails instead of a small fraction of days below constant thresholds provides deeper insight into the time series properties. Fingerprints of dynamical (e.g. ENSO, NAO) and chemical features (e.g. strong polar vortex ozone loss), and major volcanic eruptions, can be identified in the observed frequency of extreme events throughout the time series. Overall the new approach to analysis of extremes provides more information on time series properties and variability than previous approaches that use only monthly averages and/or mini-holes and mini-highs.

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