NPG Nonlinear Processes in Geophysics NPG Nonlin. Processes Geophys. 1607-7946 Copernicus Publications Göttingen, Germany 10.5194/npg-17-651-2010 Markov chain analysis of regional climates Mieruch S. 1 Noël S. 1 Bovensmann H. 1 Burrows J. P. 1 Freund J. A. 2 Institute of Environmental Physics (IUP), University of Bremen, Otto-Hahn Allee 1, 28359 Bremen, Germany Institute for Chemistry and Biology of the Marine Environment (ICBM), University of Oldenburg, Carl-von-Ossietzky Str. 9-11, 26111 Oldenburg, Germany 19 11 2010 17 6 651 661 Copyright: © 2010 S. Mieruch et al. 2010 This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/3.0/ This article is available from https://npg.copernicus.org/articles/17/651/2010/npg-17-651-2010.html The full text article is available as a PDF file from https://npg.copernicus.org/articles/17/651/2010/npg-17-651-2010.pdf

We present a novel method for regional climate classification that is based on coarse-grained categorical representations of multivariate climate anomalies and a subsequent Markov chain analysis. From the estimated transition matrix several descriptors, such as <i>persistence, recurrence time</i> and <i>entropy</i>, are derived. These descriptors characterise dynamic properties of regional climate anomalies and are connected with fundamental concepts from nonlinear physics like residence times, relaxation process and predictability. Such characteristics are useful for a comparative analysis of different climate regions and, in the context of global climate change, for a regime shift analysis. <br><br> We apply the method to the bivariate set of water vapour and temperature anomalies of two regional climates, the Iberian Peninsula and the islands of Hawaii in the central Pacific Ocean. Through the Markov chain analysis and via the derived descriptors we find significant differences between the two climate regions. Since anomalies are departures from seasonal and long term components, these differences relate to differences in the short term stability of both regional climates.

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