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Climate Dynamics

, Volume 36, Issue 11–12, pp 2371–2397 | Cite as

Extremes and predictability in the European pre-industrial climate of a regional climate model

  • L. TomassiniEmail author
  • S. Hagemann
  • Ch. Moseley
  • A. Haumann
  • R. Podzun
  • D. Jacob
Article

Abstract

A high-resolution pre-industrial control simulation with the regional climate model REMO is analyzed in detail for different European subregions. To our knowledge, this is the first long pre-industrial control simulation by a regional climate model as well as at comparable resolution. We assess the ability of the climate model to reproduce the observed climate variability in various parts of the continent. In order to investigate the representation of extreme events in the model under pre-industrial greenhouse gas concentrations, selected seasons are examined with regard to the atmospheric circulation and other climatic characteristics that have contributed to the occurrences. A special focus is dedicated to land-atmosphere interactions. Extreme seasons are simulated by the model under various circumstances, some of them strongly resemble observed periods of extraordinary conditions like the summer 2003 or autumn 2006 in parts of Europe. The regional perspective turns out to be of importance when analyzing events that are constituted by meso-scale atmospheric dynamics. Moreover, the predictability of the European climate on seasonal to decadal time scales is examined by relating the statistics of surface variables to large-scale modes of variability impacting the North Atlantic sector like the Meridional Overturning Circulation, the El Niño Southern Oscillation, and the North Atlantic Oscillation. For this purpose, we introduce a measure of tail dependence that quantifies the correlation between extreme values in two variables that describe the state of the climate system. Significant dependence of extreme events can be detected in various situations.

Keywords

Pre-industrial climate Regional climate modeling Extremes predictability 

Notes

Acknowledgments

We would like to thank Bjorn Stevens, Monika Esch, Michael Botzet, Wolfgang Müller, Johann Jungclaus, Philip Lorenz and Alberto Elizalde for support and helpful discussions.

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Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • L. Tomassini
    • 1
    Email author
  • S. Hagemann
    • 1
  • Ch. Moseley
    • 1
  • A. Haumann
    • 1
  • R. Podzun
    • 1
  • D. Jacob
    • 1
  1. 1.Max Planck Institute for MeteorologyHamburgGermany

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