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

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A Correction to this article was published on 03 February 2021

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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.

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Change history

Notes

  1. Averaging over a longer time period (e.g., years 2–11 after initialization) does not impact our results.

  2. For the MPI-ESM-LR and HadGEM-A models, turbulence and condensation are not separated and are combined in the “turbulence” tendencies.

  3. Surface buoyancy fluxes B are related to surface fluxes through the relation \(B \propto (\mathrm{SHF}+ 0.61 \, ((c_p \bar{T})/L_v)\,\mathrm{LHF})\) where \(\mathrm{LHF}\) is the surface latent heat flux. In the tropics, the coefficient multiplying \(\mathrm{LHF}\) is close to 0.07 (Cuijpers and Bechtold 1995). We thus use the approximation \(B \propto (\mathrm{SHF} + 0.07\mathrm{LHF})\).

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Acknowledgments

This work was supported by the Department of Energy’s Regional and Global Climate Modeling Program under the project “Identifying Robust Cloud Feedbacks in Observations and Model”. We thank Bjorn Stevens, Louise Nuijens, Steve Klein and Peter Caldwell for useful discussions on this topic and two anonymous reviewers for their insightful comments on the manuscript. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups (listed in Table 1) for producing and making available their model output.

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Authors and Affiliations

  1. Department of Earth Sciences, ETH Zurich, Zurich, Switzerland

    Florent Brient, Tapio Schneider & Zhihong Tan

  2. California Institute of Technology, Pasadena, CA, USA

    Tapio Schneider & Zhihong Tan

  3. Laboratoire de Météorologie Dynamique (LMD/IPSL), Université Pierre et Marie Curie, CNRS, Paris, France

    Sandrine Bony

  4. Department of Atmospheric and Oceanic Sciences, University of California, PO Box 951565, Los Angeles, CA, 90095-1565, USA

    Xin Qu & Alex Hall

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  1. Florent Brient
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Correspondence to Florent Brient.

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Brient, F., Schneider, T., Tan, Z. et al. Shallowness of tropical low clouds as a predictor of climate models’ response to warming. Clim Dyn 47, 433–449 (2016). https://doi.org/10.1007/s00382-015-2846-0

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