Letter | Published:

Evidence for climate change in the satellite cloud record

Nature volume 536, pages 7275 (04 August 2016) | Download Citation

Abstract

Clouds substantially affect Earth’s energy budget by reflecting solar radiation back to space and by restricting emission of thermal radiation to space1. They are perhaps the largest uncertainty in our understanding of climate change, owing to disagreement among climate models and observational datasets over what cloud changes have occurred during recent decades and will occur in response to global warming2,3. This is because observational systems originally designed for monitoring weather have lacked sufficient stability to detect cloud changes reliably over decades unless they have been corrected to remove artefacts4,5. Here we show that several independent, empirically corrected satellite records exhibit large-scale patterns of cloud change between the 1980s and the 2000s that are similar to those produced by model simulations of climate with recent historical external radiative forcing. Observed and simulated cloud change patterns are consistent with poleward retreat of mid-latitude storm tracks, expansion of subtropical dry zones, and increasing height of the highest cloud tops at all latitudes. The primary drivers of these cloud changes appear to be increasing greenhouse gas concentrations and a recovery from volcanic radiative cooling. These results indicate that the cloud changes most consistently predicted by global climate models are currently occurring in nature.

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Acknowledgements

National Oceanic and Atmospheric Administration (NOAA) awards NA10OAR4310140 and NA10OAR4310141 supported work by J.R.N. and A.T.E. The efforts of M.D.Z. and S.A.K. were supported by the US Department of Energy (DOE), Office of Science, Office of Biological and Environmental Research through its Regional and Global Climate Modeling Program and were performed under the auspices of the DOE by Lawrence Livermore National Laboratory under contract DE-AC52-07NA27344. Part of the work by M.D.Z. was supported by the National Aeronautics and Space Administration (NASA) New Investigator Program (NNH14AX83I). The MAC-LWP climatology is supported by the NASA MEaSUREs Program (NNH12ZDA001N). We acknowledge the World Climate Research Programme’s (WCRP’s) Working Group on Coupled Modelling, which is responsible for the Coupled Model Intercomparison Project (CMIP), and we thank the climate modelling groups for producing and making available their model output. For CMIP the US DOE’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.

Author information

Affiliations

  1. Scripps Institution of Oceanography, University of California at San Diego, La Jolla, California, USA

    • Joel R. Norris
    •  & Amato T. Evan
  2. Department of Earth Sciences, University of California at Riverside, Riverside, California, USA

    • Robert J. Allen
  3. Program for Climate Model Diagnosis and Intercomparison, Lawrence Livermore National Laboratory, Livermore, California, USA

    • Mark D. Zelinka
    •  & Stephen A. Klein
  4. Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, Colorado, USA

    • Christopher W. O’Dell

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Contributions

J.R.N. designed the study, provided ERBS, CERES, and ISCCP data, did the main analysis, and wrote the paper; R.J.A. provided standard model cloud output for CMIP5 simulations and analysed CMIP5 meteorological output; A.T.E. provided corrected PATMOS-x data; M.D.Z. provided CMIP5 COSP cloud output; C.W.O. provided MAC-LWP liquid water path data; and S.A.K. provided background information and ideas. All authors discussed the results and commented on the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Joel R. Norris.

Corrected ISCCP and PATMOS-x cloud amount data are available from the Research Data Archive at NCAR at http://dx.doi.org/10.5065/D62J68XR.

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https://doi.org/10.1038/nature18273

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