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Cloud Adjustment and its Role in CO2 Radiative Forcing and Climate Sensitivity: A Review

期刊

SURVEYS IN GEOPHYSICS
卷 33, 期 3-4, 页码 619-635

出版社

SPRINGER
DOI: 10.1007/s10712-011-9152-0

关键词

Climate sensitivity; Radiative forcing; Cloud feedback; Tropospheric adjustment

资金

  1. NERC open CASE award
  2. University of Leeds
  3. Met Office
  4. Joint DECC/Defra Met Office Hadley Centre Climate Programme [GA01101]
  5. ESRC [ES/G021694/1] Funding Source: UKRI
  6. NERC [NE/E016189/1] Funding Source: UKRI
  7. Economic and Social Research Council [ES/G021694/1] Funding Source: researchfish
  8. Natural Environment Research Council [ncas10009, NE/E016189/1] Funding Source: researchfish

向作者/读者索取更多资源

Understanding the role of clouds in climate change remains a considerable challenge. Traditionally, this challenge has been framed in terms of understanding cloud feedback. However, recent work suggests that under increasing levels of atmospheric carbon dioxide, clouds not only amplify or dampen climate change through global feedback processes, but also through rapid (days to weeks) tropospheric temperature and land surface adjustments. In this article, we use the Met Office Hadley Centre climate model HadGSM1 to review these recent developments and assess their impact on radiative forcing and equilibrium climate sensitivity. We estimate that cloud adjustment contributes similar to 0.8 K to the 4.4 K equilibrium climate sensitivity of this particular model. We discuss the methods used to evaluate cloud adjustments, highlight the mechanisms and processes involved and identify low level cloudiness as a key cloud type. Looking forward, we discuss the outstanding issues, such as the application to transient forcing scenarios. We suggest that the upcoming CMIP5 multi-model database will allow a comprehensive assessment of the significance of cloud adjustments in fully coupled atmosphere-ocean-general-circulation models for the first time, and that future research should exploit this opportunity to understand cloud adjustments/feedbacks in non-idealised transient climate change scenarios.

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