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Climate Dynamics

, Volume 20, Issue 7–8, pp 843–854 | Cite as

A comparison of climate response to different radiative forcings in three general circulation models: towards an improved metric of climate change

  • M. Joshi
  • K. Shine
  • M. Ponater
  • N. Stuber
  • R. Sausen
  • L. Li
Article

Abstract.

In order to review, and possibly refine, the concept of radiative forcing as a suitable metric for climate change, the responses of three general circulation models to distinct forcing scenarios are compared. CO2, solar radiation, and O3 are added in different locations, whilst keeping the globally averaged radiative forcing constant at 1 Wm–2. The three models react differently to the forcings, as feedback mechanisms such as sea-ice albedo and clouds behave differently in each model. However, we find that their climate sensitivities λ (defined as the ratio of the globally averaged surface temperature change to the radiative forcing), normalised by the climate sensitivity for a control case (e.g. CO2 added globally), match each other to within 30% in most experiments. Moreover, the models indicate generic deviations of λ from the case of global CO2 perturbations: upper tropospheric O3 increases generally produce lower values of λ, while lower stratospheric O3 perturbations lead to higher values of λ, as found in some previous work. λ tends to be higher for extratropical forcings than tropical forcings; a phenomenon which can be partially accounted for by a new explanation based on the variation of the outgoing longwave radiation with latitude. Our results suggest that if the radiative forcing associated with some perturbation is multiplied by some factor accounting for the efficiency of that mechanism, then such modified forcings can be compared more robustly than the forcings themselves.

Keywords

Ozone Climate Sensitivity Stratospheric Ozone Tropospheric Ozone Lower Stratosphere 
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.

Notes

Acknowledgements.

This study is part of the METRIC project, which has been funded by the European Commission through the Fifth Framework Programme (project number EV2K-CT-1999-000021). We thank the referees for their many useful comments.

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Copyright information

© Springer-Verlag 2003

Authors and Affiliations

  • M. Joshi
    • 1
  • K. Shine
    • 1
  • M. Ponater
    • 2
  • N. Stuber
    • 2
  • R. Sausen
    • 2
  • L. Li
    • 3
  1. 1.Department of Meteorology, University of Reading, Earley Gate, PO Box 243, Reading RG6 6BB, UK
  2. 2.DLR, Oberpfaffenhofen, Germany
  3. 3.Laboratoire de Météorologie Dynamique du C.N.R.S., France

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