Climate Dynamics

, Volume 11, Issue 5, pp 307–320 | Cite as

Observed dependence of the water vapor and clear-sky greenhouse effect on sea surface temperature: comparison with climate warming experiments

  • Sandrine Bony
  • Jean-Philippe Duvel
  • Hervé Le Trent


This study presents a comparison of the water vapor and clear-sky greenhouse effect dependence on sea surface temperature for climate variations of different types. Firstly, coincident satellite observations and meteorological analyses are used to examine seasonal and interannual variations and to evaluate the performance of a general circulation model. Then, this model is used to compare the results inferred from the analysis of observed climate variability with those derived from global climate warming experiments. One part of the coupling between the surface temperature, the water vapor and the clear-sky greenhouse effect is explained by the dependence of the saturation water vapor pressure on the atmospheric temperature. However, the analysis of observed and simulated fields shows that the coupling is very different according to the type of region under consideration and the type of climate forcing that is applied to the Earth-atmosphere system. This difference, due to the variability of the vertical structure of the atmosphere, is analyzed in detail by considering the temperature lapse rate and the vertical profile of relative humidity. Our results suggest that extrapolating the feedbacks inferred from seasonal and short-term interannual climate variability to longer-term climate changes requires great caution. It is argued that our confidence in climate models' predictions would be increased significantly if the basic physical processes that govern the variability of the vertical structure of the atmosphere, and its relation to the large-scale circulation, were better understood and simulated. For this purpose, combined observational and numerical studies focusing on physical processes are needed.


Water Vapor Climate Variability General Circulation Model Interannual Variation Vertical Structure 
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.


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Copyright information

© Springer-Verlag 1995

Authors and Affiliations

  • Sandrine Bony
    • 1
  • Jean-Philippe Duvel
    • 2
  • Hervé Le Trent
    • 1
  1. 1.Laboratoire de Météorologie Dynamique du CNRS, Ecole Normale SupérieureParis cedex 05France
  2. 2.Ecole PolytechniquePalaiseau cedexFrance

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