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Climate Dynamics

, Volume 29, Issue 7–8, pp 791–805 | Cite as

A European pattern climatology 1766–2000

  • Carlo CastyEmail author
  • Christoph C. Raible
  • Thomas F. Stocker
  • Heinz Wanner
  • Jürg Luterbacher
Article

Abstract

Using monthly independently reconstructed gridded European fields for the 500 hPa geopotential height, temperature, and precipitation covering the last 235 years we investigate the temporal and spatial evolution of these key climate variables and assess the leading combined patterns of climate variability. Seasonal European temperatures show a positive trend mainly over the last 40 years with absolute highest values since 1766. Precipitation indicates no clear trend. Spatial correlation technique reveals that winter, spring, and autumn covariability between European temperature and precipitation is mainly influenced by advective processes, whereas during summer convection plays the dominant role. Empirical Orthogonal Function analysis is applied to the combined fields of pressure, temperature, and precipitation. The dominant patterns of climate variability for winter, spring, and autumn resemble the North Atlantic Oscillation and show a distinct positive trend during the past 40 years for winter and spring. A positive trend is also detected for summer pattern 2, which reflects an increased influence of the Azores High towards central Europe and the Mediterranean coinciding with warm and dry conditions. The question to which extent these recent trends in European climate patterns can be explained by internal variability or are a result of radiative forcing is answered using cross wavelets on an annual basis. Natural radiative forcing (solar and volcanic) has no imprint on annual European climate patterns. Connections to CO2 forcing are only detected at the margins of the wavelets where edge effects are apparent and hence one has to be cautious in a further interpretation.

Keywords

Independent climate field reconstructions Europe Climate patterns Combined EOFs 

Notes

Acknowledgments

CC and TFS are funded by the European commission fifth framework programme, Contract EVRI-2002–000413, project PACLIVA. We acknowledge support by the Swiss National Science Foundation through its NCCR Climate (MONALISA & PALVAREX II). JL also acknowledges the European Environment and Sustainable Development programme, projects SO&P (EVK2-CT-2002-00160) and EMULATE (EVK2-CT-2002-00161). We kindly acknowledge Dr. Elena Xoplaki and Dr. Andreas Pauling for providing their data and thank the two anonymous reviewers for their comments, which helped to improve this article. The package for performing cross-wavelet and wavelet coherence analysis is available at: http://www.pol.ac.uk/home/research/waveletcoherence/.

Supplementary material

382_2007_257_MOESM1_ESM.pdf (331 kb)
Figure A a-c): Second Empirical Orthogonal Function (EOF2) winter (D,J,F) pattern of the 500 hPa geopotential height (Z500, a), the land surface temperatures (LST, b), and land surface precipitation (LSP, c) obtained from the described combined linear EOF analysis 1766-2000. Values are correlations. d) The corresponding normalised Principal Components (PC) 1766-2000 of the combined EOF1. Indicated by the red curve is the 31-year smoothing (Mann 2004). e-p) The same as for a-d) but for spring (e-h, M,A,M), summer (i-l, J,J,A), and autumn (m-p, S,O,N) respectively. In the top right corners of Figures a, e, i, and m the explained variance of the respective EOF is shown. (330 kB PDF)
382_2007_257_MOESM2_ESM.pdf (324 kb)
Figure B a-c): Third Empirical Orthogonal Function (EOF3) winter (D,J,F) pattern of the 500 hPa geopotential height (Z500, a), the land surface temperatures (LST, b), and land surface precipitation (LSP, c) obtained from the described combined linear EOF analysis 1766-2000. Values are correlations. d) The corresponding normalised Principal Components (PC) 1766-2000 of the combined EOF1. Indicated by the red curve is the 31-year smoothing (Mann 2004). e-p) The same as for a-d) but for spring (e-h, M,A,M), summer (i-l, J,J,A), and autumn (m-p, S,O,N) respectively. In the top right corners of Figures a, e, i, and m the explained variance of the respective EOF is shown. (324 kB PDF)
382_2007_257_MOESM3_ESM.pdf (304 kb)
Figure C a-c): Second Empirical Orthogonal Function (EOF2) winter (D,J,F) pattern of the modelled 500 hPa geopotential height (Z500, a), the land surface temperatures (LST, b), and land surface precipitation (LSP, c) obtained from the described combined linear EOF analysis 1766–1990. Values are correlations. d) The corresponding normalised Principal Components (PC) 1766–1990 of the combined EOF1. Indicated by the red curve is the 31-year smoothing (Mann 2004). e-p) The same as for a-d) but for spring (e-h, M,A,M), summer (i-l, J,J,A), and autumn (m-p, S,O,N) respectively. In the top right corners of Figures a, e, i, and m the explained variance of the respective EOF is shown. (304 kB PDF)
382_2007_257_MOESM4_ESM.pdf (302 kb)
Figure D a-c): Third Empirical Orthogonal Function (EOF3) winter (D,J,F) pattern of the modelled 500 hPa geopotential height (Z500, a), the land surface temperatures (LST, b), and land surface precipitation (LSP, c) obtained from the described combined linear EOF analysis 1766–1990. Values are correlations. d) The corresponding normalized Principal Components (PC) 1766–1990 of the combined EOF1. Indicated by the red curve is the 31-year smoothing (Mann 2004). e-p) The same as for a-d) but for spring (e-h, M,A,M), summer (i-l, J,J,A), and autumn (m-p, S,O,N) respectively. In the top right corners of Figures a, e, i, and m the explained variance of the respective EOF is shown. (302 kB PDF)

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Copyright information

© Springer-Verlag 2007

Authors and Affiliations

  • Carlo Casty
    • 1
    Email author
  • Christoph C. Raible
    • 1
    • 3
  • Thomas F. Stocker
    • 1
    • 3
  • Heinz Wanner
    • 2
    • 3
  • Jürg Luterbacher
    • 2
    • 3
  1. 1.Climate and Environmental Physics, Physics InstituteUniversity of BernBernSwitzerland
  2. 2.Climatology and Meteorology, Institute of GeographyUniversity of BernBernSwitzerland
  3. 3.NCCR ClimateUniversity of BernBernSwitzerland

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