Climate Dynamics

, Volume 44, Issue 7–8, pp 2301–2325 | Cite as

The cloud radiative effect on the atmospheric energy budget and global mean precipitation

  • F. Hugo LambertEmail author
  • Mark J. Webb
  • Masakazu Yoshimori
  • Tokuta Yokohata


This study seeks to explain the effects of cloud on changes in atmospheric radiative absorption that largely balance changes in global mean precipitation under climate change. The partial radiative perturbations (PRPs) due to changes in cloud and due to the effects of the pre-existing climatological cloud distribution on non-cloud changes, known as “cloud masking”, are calculated when atmospheric CO2 concentration is doubled for the HadSM3 and MIROC models and for a large ensemble of parameter perturbed models based on HadSM3. Because the effect of cloud on changes in atmospheric shortwave absorption is almost negligible, longwave fluxes are analysed alone. We find that the net effects of cloud masking and cloud PRP on atmospheric absorption are both substantial. For the tropics, our results are reviewed in light of hypotheses put forward to explain cloud and radiative flux changes. We find that the major effects of clouds on radiation change are linked to known physical processes that are quite consistently simulated by models. Cloud top height changes are quite well described by the fixed anvil temperature hypothesis of Hartmann and Larson; cloud base heights change little, remaining near the same pressure. Changes in cloud geographical location and cloud amount are significant, but play a smaller role in driving radiative flux changes. Finally, because clouds are a large source of modelling uncertainty, we consider whether resolving errors in cloud simulation could reconcile modelled global mean precipitation trends of about 1–3 %\(\hbox {K}^{-1}\) with some estimates of observed trends of 7 %\(\hbox {K}^{-1}\) or more. This would require the radiative effect of clouds to change from one that increases atmospheric radiative absorption by about \(0.5\,\hbox {Wm}^{-2}\,\hbox {K}^{-1}\) to one that decreases it by \(-3.5\,\hbox {Wm}^{-2}\,\hbox {K}^{-1}\). Based on our results, this seems difficult to achieve within our current rationale for the tropics at least.


Cloud Amount Cloud Feedback Cloud Radiative Effect Feedback Component Cloud Masking 
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.



We are very grateful to James Manners and William Ingram for help with running the Edwards–Slingo radiation code and to Rob Chadwick, Joe Osborne and Jon Petch for helpful discussions. We thank two reviewers for thorough reviews. Mark Webb was supported by the Joint DECC/Defra Met Office Hadley Centre Climate Programme (GA01101) and by funding from the European Union, Seventh Framework Programme (FP7/2007-2013) under grant agreement number 244067 via the EU Cloud Intercomparison and Process Study Evaluation project (EUCLIPSE).

Supplementary material

382_2014_2174_MOESM1_ESM.pdf (134 kb)
Supplementary material 1 (pdf 134 KB)


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • F. Hugo Lambert
    • 1
    Email author
  • Mark J. Webb
    • 2
  • Masakazu Yoshimori
    • 3
    • 5
  • Tokuta Yokohata
    • 4
  1. 1.College of Engineering, Mathematics and Physical SciencesUniversity of ExeterExeterUK
  2. 2.Met Office Hadley CentreExeterUK
  3. 3.Atmosphere and Ocean Research InstituteThe University of TokyoKashiwaJapan
  4. 4.National Institute for Environmental StudiesTsukubaJapan
  5. 5.Faculty of Environmental Earth ScienceHokkaido UniversitySapporoJapan

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