Climate Dynamics

, Volume 47, Issue 1–2, pp 433–449 | Cite as

Shallowness of tropical low clouds as a predictor of climate models’ response to warming

  • Florent Brient
  • Tapio Schneider
  • Zhihong Tan
  • Sandrine Bony
  • Xin Qu
  • Alex Hall
Article

Abstract

How tropical low clouds change with climate remains the dominant source of uncertainty in global warming projections. An analysis of an ensemble of CMIP5 climate models reveals that a significant part of the spread in the models’ climate sensitivity can be accounted by differences in the climatological shallowness of tropical low clouds in weak-subsidence regimes: models with shallower low clouds in weak-subsidence regimes tend to have a higher climate sensitivity than models with deeper low clouds. The dynamical mechanisms responsible for the model differences are analyzed. Competing effects of parameterized boundary-layer turbulence and shallow convection are found to be essential. Boundary-layer turbulence and shallow convection are typically represented by distinct parameterization schemes in current models—parameterization schemes that often produce opposing effects on low clouds. Convective drying of the boundary layer tends to deepen low clouds and reduce the cloud fraction at the lowest levels; turbulent moistening tends to make low clouds more shallow but affects the low-cloud fraction less. The relative importance different models assign to these opposing mechanisms contributes to the spread of the climatological shallowness of low clouds and thus to the spread of low-cloud changes under global warming.

Keywords

Low-clouds Climate sensitivity Tropics Convection Turbulence 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Florent Brient
    • 1
  • Tapio Schneider
    • 1
    • 2
  • Zhihong Tan
    • 1
    • 2
  • Sandrine Bony
    • 3
  • Xin Qu
    • 4
  • Alex Hall
    • 4
  1. 1.Department of Earth SciencesETH ZurichZurichSwitzerland
  2. 2.California Institute of TechnologyPasadenaUSA
  3. 3.Laboratoire de Météorologie Dynamique (LMD/IPSL)Université Pierre et Marie Curie, CNRSParisFrance
  4. 4.Department of Atmospheric and Oceanic SciencesUniversity of CaliforniaLos AngelesUSA

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