Forcing, feedbacks and climate sensitivity in CMIP5 coupled atmosphere-ocean climate models

We quantify forcing and feedbacks across available CMIP5 coupled atmosphere‐ocean general circulation models (AOGCMs) by analysing simulations forced by an abrupt quadrupling of atmospheric carbon dioxide concentration. This is the first application of the linear forcing‐feedback regression analysis...

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Bibliographic Details
Published in:Geophysical research letters 2012-05, Vol.39 (9), p.n/a
Main Authors: Andrews, Timothy, Gregory, Jonathan M., Webb, Mark J., Taylor, Karl E.
Format: Article
Language:English
Subjects:
AOGCMs
Atmosphere
Atmospheric sciences
Carbon dioxide
Climate change
climate feedbacks
Climate models
Climate science
climate sensitivity
Clouds
CMIP5
Earth
Earth sciences
Earth, ocean, space
ENVIRONMENTAL SCIENCES
Exact sciences and technology
GEOSCIENCES
Global temperatures
Ocean-atmosphere interaction
radiative forcing
Regression analysis
Sea surface temperature
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Summary:We quantify forcing and feedbacks across available CMIP5 coupled atmosphere‐ocean general circulation models (AOGCMs) by analysing simulations forced by an abrupt quadrupling of atmospheric carbon dioxide concentration. This is the first application of the linear forcing‐feedback regression analysis of Gregory et al. (2004) to an ensemble of AOGCMs. The range of equilibrium climate sensitivity is 2.1–4.7 K. Differences in cloud feedbacks continue to be important contributors to this range. Some models show small deviations from a linear dependence of top‐of‐atmosphere radiative fluxes on global surface temperature change. We show that this phenomenon largely arises from shortwave cloud radiative effects over the ocean and is consistent with independent estimates of forcing using fixed sea‐surface temperature methods. We suggest that future research should focus more on understanding transient climate change, including any time‐scale dependence of the forcing and/or feedback, rather than on the equilibrium response to large instantaneous forcing. Key Points Range of eqm climate sensitivity (2.1‐4.7K) is similar to that found in CMIP3 Differences in cloud feedbacks continue to be a large source of this uncertainty Some models show small deviations from linear behaviour
ISSN:0094-8276
1944-8007
DOI:10.1029/2012GL051607