Climate Dynamics

, Volume 20, Issue 5, pp 491–502 | Cite as

Simple indices of global climate variability and change: Part I – variability and correlation structure

  •  K. Braganza
  •  D. Karoly
  •  A. Hirst
  •  M. Mann
  •  P. Stott
  •  R. Stouffer
  •  S. Tett

Abstract.

Some simple indices are used to describe global climate variability in observational data and climate model simulations. The indices are surface temperature based and include the global-mean, the land–ocean contrast, the meridional gradient, the interhemispheric contrast, and the magnitude of the annual cycle. These indices contain information independent of the variations of the global-mean temperature for unforced climate variations. They also represent the main features of the modelled surface temperature response to increasing greenhouse gases in the atmosphere. Hence, they should have a coherent response for greenhouse climate change. On interannual and decadal time scales, the variability and correlation structure of the indices from long control climate model simulations compare well with those from detrended instrumental observations for the twentieth century and proxy based climate reconstructions for 1700–1900. The indices provide a simple but effective way to evaluate global-scale climate variability in control climate model simulations. On decadal time scales, the observed correlation structure between the indices during the twentieth century shows significant differences from the detrended observations and control model simulations. These changes are consistent with forced climate variations in greenhouse climate change simulations. This suggests that the changes in the correlation structure between these indices can be used as an indicator of climate change.

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Copyright information

© Springer-Verlag 2003

Authors and Affiliations

  •  K. Braganza
    • 1
  •  D. Karoly
    • 1
  •  A. Hirst
    • 2
  •  M. Mann
    • 3
  •  P. Stott
    • 4
  •  R. Stouffer
    • 5
  •  S. Tett
    • 4
  1. 1.School of Mathematical Sciences, Monash University, PO Box 28M Clayton, VIC 3800 Australia
  2. 2.CSIRO Atmospheric Research, Aspendale, VIC, Australia
  3. 3.Department of Environmental Sciences, University of Virginia, Charlottesville, VA, USA
  4. 4.Hadley Centre for Climate Prediction and Research, Meteorological Office, Bracknell, Berks., UK
  5. 5.Geophysical Fluid Dynamics Laboratory, Princeton, NJ, USA

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