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Published May 27, 2014 | Published
Journal Article Open

Weakening and strengthening structures in the Hadley Circulation change under global warming and implications for cloud response and climate sensitivity

Abstract

It has long been recognized that differences in climate model-simulated cloud feedbacks are a primary source of uncertainties for the model-predicted surface temperature change induced by increasing greenhouse gases such as CO_2. Large-scale circulation broadly determines when and where clouds form and how they evolve. However, the linkage between large-scale circulation change and cloud radiative effect (CRE) change under global warming has not been thoroughly studied. By analyzing 15 climate models, we show that the change of the Hadley Circulation exhibits meridionally varying weakening and strengthening structures, physically consistent with the cloud changes in distinct cloud regimes. The regions that experience a weakening (strengthening) of the zonal-mean circulation account for 54% (46%) of the multimodel-mean top-of-atmosphere (TOA) CRE change integrated over 45°S–40°N. The simulated Hadley Circulation structure changes per degree of surface warming differ greatly between the models, and the intermodel spread in the Hadley Circulation change is well correlated with the intermodel spread in the TOA CRE change. This correlation underscores the close interactions between large-scale circulation and clouds and suggests that the uncertainties of cloud feedbacks and climate sensitivity reside in the intimate coupling between large-scale circulation and clouds. New model performance metrics proposed in this work, which emphasize how models reproduce satellite-observed spatial variations of zonal-mean cloud fraction and relative humidity associated with the Hadley Circulation, indicate that the models closer to the satellite observations tend to have equilibrium climate sensitivity higher than the multimodel mean.

Additional Information

© 2014 American Geophysical Union. Received 12 Feb 2014. Accepted 26 Apr 2014. Accepted article online 4 May 2014. Published online 20 May 2014. We are thankful to Jay Mace, Eric J. Fetzer, and William G. Read for helpful discussions of data quality. Discussions with Kevin Bowman, Duane Waliser, and Michael Gunson are appreciated. This paper is greatly improved owing to the detailed comments and constructive suggestions by Mark Zelinka and two other reviewers. We acknowledge the World Climate Research Programme's Working Group on Coupled Modelling, which is responsible for CMIP. We thank the climate modeling groups listed in Table 1 for producing and making available their model output. The U.S. Department of Energy (DOE) 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 A-Train satellite data are available at NASA Distributed Active Archive Centers (DAAC). H.S., J.H.J., C.Z., and J.T.S. acknowledge funding support from NASA NEWS, COUND, and AST programs and Aura MLS and CloudSat projects. J.D.N. was supported by NOAA NA11OAR4310099 and NSF AGS-1102838. Y.L.Y. was supported by UHOUST.130027 subcontract from the University of Houston. This work was performed at Jet Propulsion Laboratory, California Institute of Technology, under contract with NASA.

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August 22, 2023
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