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Climate Dynamics

, Volume 46, Issue 9–10, pp 3025–3039 | Cite as

Robustness, uncertainties, and emergent constraints in the radiative responses of stratocumulus cloud regimes to future warming

  • Yoko TsushimaEmail author
  • Mark A. Ringer
  • Tsuyoshi Koshiro
  • Hideaki Kawai
  • Romain Roehrig
  • Jason Cole
  • Masahiro Watanabe
  • Tokuta Yokohata
  • Alejandro Bodas-Salcedo
  • Keith D. Williams
  • Mark J. Webb
Article

Abstract

Future responses of cloud regimes are analyzed for five CMIP5 models forced with observed SSTs and subject to a patterned SST perturbation. Correlations between cloud properties in the control climate and changes in the warmer climate are investigated for each of a set of cloud regimes defined using a clustering methodology. The only significant (negative) correlation found is in the in-regime net cloud radiative effect for the stratocumulus regime. All models overestimate the in-regime albedo of the stratocumulus regime. Reasons for this bias and its relevance to the future response are investigated. A detailed evaluation of the models’ daily-mean contributions to the albedo from stratocumulus clouds with different cloud cover fractions reveals that all models systematically underestimate the relative occurrence of overcast cases but overestimate those of broken clouds. In the warmer climate the relative occurrence of overcast cases tends to decrease while that of broken clouds increases. This suggests a decrease in the climatological in-regime albedo with increasing temperature (a positive feedback); this is opposite to the feedback suggested by the analysis of the bulk in-regime albedo. Furthermore we find that the inter-model difference in the sign of the in-cloud albedo feedback is consistent with the difference in sign of the in-cloud liquid water path response, and there is a strong positive correlation between the in-regime liquid water path in the control climate and its response to warming. We therefore conclude that further breakdown of the in-regime properties into cloud cover and in-cloud properties is necessary to better understand the behavior of the stratocumulus regime. Since cloud water is a physical property and is independent of a model’s radiative assumptions, it could potentially provide a useful emergent constraint on cloud feedback.

Keywords

Stratocumulus Liquid water path Cloud feedback Cloud radiative effect Climate model 

Notes

Acknowledgments

We are very grateful to Drs. Gill Martin, Adrian Lock, William Ingram, and Malcolm Roberts who gave useful comments. We thank the international climate modeling groups (listed in Sect. 2.3 of this paper), the WCRP’s Working Group on Coupled Modeling for making available the multi-model data set obtained from the Phase 5 of the Coupled Model Intercomparison Project (CMIP5). The data set has been indispensable for the study conducted here. For CMIP5 the U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. The research leading to these results has received funding from the European Union, Seventh Framework Programme (FP7/2007–2013) under grant agreement no 244067 via the EU Cloud Intercomparison and Process Study Evaluation Project (EUCLIPSE) and the Joint DECC/Defra Met Office Hadley Centre Climate Programme (GA01101).

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Copyright information

© © Crown Copyright as represented by the Met Office 2015 2015

Authors and Affiliations

  • Yoko Tsushima
    • 1
    Email author
  • Mark A. Ringer
    • 1
  • Tsuyoshi Koshiro
    • 2
  • Hideaki Kawai
    • 2
  • Romain Roehrig
    • 3
  • Jason Cole
    • 4
  • Masahiro Watanabe
    • 5
  • Tokuta Yokohata
    • 6
  • Alejandro Bodas-Salcedo
    • 1
  • Keith D. Williams
    • 1
  • Mark J. Webb
    • 1
  1. 1.Met Office Hadley CentreExeterUK
  2. 2.Meteorological Research Institute (MRI)JMATsukubaJapan
  3. 3.Centre National de Recherches MétéorologiquesToulouseFrance
  4. 4.Canadian Centre for Climate Modelling and AnalysisTorontoCanada
  5. 5.Atmosphere and Ocean Research Institute (AORI)University of TokyoKashiwaJapan
  6. 6.National Institute for Environmental StudiesTsukubaJapan

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