Climate Dynamics

, Volume 28, Issue 2–3, pp 181–197 | Cite as

ENSO influence on Europe during the last centuries

  • S. BrönnimannEmail author
  • E. Xoplaki
  • C. Casty
  • A. Pauling
  • J. Luterbacher


El Niño/Southern Oscillation (ENSO) affects climate not only in the Pacific region and the tropics, but also in the North Atlantic-European area. Studies based on twentieth-century data have found that El Niño events tend to be accompanied in late winter by a negative North Atlantic Oscillation index, low temperatures in northeastern Europe and a change in precipitation patterns. However, many questions are open, for example, concerning the stationarity of this relation. Here we study the relation between ENSO and European climate during the past 500 years based on statistically reconstructed ENSO indices, early instrumental station series, and reconstructed fields of surface air temperature, sea-level pressure, precipitation, and 500 hPa geopotential height. After removing years following tropical volcanic eruptions (which systematically mask the ENSO signal), we find a consistent and statistically significant ENSO signal in late winter and spring. The responses to El Niño and La Niña are close to symmetric. In agreement with studies using twentieth-century data only, the ENSO signal in precipitation is different in fall than in late winter. Moving correlation analyses confirm a stationary relationship between ENSO and late winter climate in Europe during the past 300 years. However, the ENSO signal is modulated significantly by the North Pacific climate. A multi-field cluster analysis for strong ENSO events during the past 300 years yields a dominant pair of clusters that is symmetric and represents the ‘classical’ ENSO effects on Europe.


North Atlantic Oscillation Index Principal Component Time Series NINO3 Index Climate Field Reconstruction Tropical Volcanic Eruption 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



S.B. was funded by the Swiss National Science Foundation. J.L. and E.X. were funded by the Swiss National Competence Center for Research in Climate. C.C. is funded by the Fifth European framework programme, project PACLIVA (EVRI-2002-000413). E.X. and A.P. were also financially supported through the European Environment and Sustainable Development programme project SOAP (EVK2-CT-2002-00160). Additionally, E.X. was supported through the European Environment and Sustainable Development programme, project EMULATE (EVK2-CT-2002-00161).


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Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  • S. Brönnimann
    • 1
    Email author
  • E. Xoplaki
    • 2
    • 3
  • C. Casty
    • 4
  • A. Pauling
    • 5
  • J. Luterbacher
    • 2
    • 3
  1. 1.Institute for Atmospheric and Climate Science, ETH ZürichZürichSwitzerland
  2. 2.NCCR ClimateUniversity of BernBernSwitzerland
  3. 3.Institute of Geography, Climatology and MeteorologyUniversity of BernBernSwitzerland
  4. 4.Physics InstituteUniversity of BernBernSwitzerland
  5. 5.MeteoSwissZürichSwitzerland

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