Letter | Published:

Human-induced global ocean warming on multidecadal timescales

Nature Climate Change volume 2, pages 524529 (2012) | Download Citation


Large-scale increases in upper-ocean temperatures are evident in observational records1. Several studies have used well-established detection and attribution methods to demonstrate that the observed basin-scale temperature changes are consistent with model responses to anthropogenic forcing and inconsistent with model-based estimates of natural variability2,3,4,5. These studies relied on a single observational data set and employed results from only one or two models. Recent identification of systematic instrumental biases6 in expendable bathythermograph data has led to improved estimates of ocean temperature variability and trends7,8,9 and provide motivation to revisit earlier detection and attribution studies. We examine the causes of ocean warming using these improved observational estimates, together with results from a large multimodel archive of externally forced and unforced simulations. The time evolution of upper ocean temperature changes in the newer observational estimates is similar to that of the multimodel average of simulations that include the effects of volcanic eruptions. Our detection and attribution analysis systematically examines the sensitivity of results to a variety of model and data-processing choices. When global mean changes are included, we consistently obtain a positive identification (at the 1% significance level) of an anthropogenic fingerprint in observed upper-ocean temperature changes, thereby substantially strengthening existing detection and attribution evidence.

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We acknowledge the climate model development groups for providing their simulation output for analysis, PCMDI for collecting and archiving this data and the World Climate Research Programme’s Working Group on Coupled Modelling for organizing the model data analysis activity. The CMIP3 multimodel data set is supported by the Office of Science, US Department of Energy. Work at Lawrence Livermore National Laboratory (by P.J.G., P.M.C., B.D.S. and K.E.T.) was carried out under the auspices of the US Department of Energy under contract DE-AC52-07NA27344. C.M.D. was partly financially supported by a CSIRO Office of the Chief Executive Postdoctoral Fellowship, the Australian Climate Change Science Program and the Australian Academy of Science (Scientific Visit to North America Program). D.W.P. was partially funded by the US Department of Energy's International ad hoc Detection and Attribution Group (IDAG).

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  1. Program for Climate Model Diagnosis and Intercomparison, Lawrence Livermore National Laboratory, Mail Code L-103, 7000 East Avenue, Livermore, California 94550, USA

    • P. J. Gleckler
    • , B. D. Santer
    • , K. E. Taylor
    •  & P. M. Caldwell
  2. Antarctic and Climate Ecosystems Cooperative Research Centre, Hobart, Australia

    • C. M. Domingues
  3. Centre for Australian Weather and Climate Research and Wealth from Oceans Flagship, CSIRO Marine and Atmospheric Research, GPO Box 1538, Hobart, Tasmania 7001, Australia

    • C. M. Domingues
    •  & J. A. Church
  4. Climate Research Division, Scripps Institution of Oceanography, Mail Stop 0224, La Jolla 92093, USA

    • D. W. Pierce
    •  & T. P. Barnett
  5. Indian Institute of Technology, Delhi 110 016, India

    • K. M. AchutaRao
  6. National Oceanographic Data Center, National Oceanic and Atmospheric Administration, Silver Spring 20910, USA

    • T. P. Boyer
  7. Climate Research Department, Meteorological Research Institute, 1-1, Nagamine, Tsukuba, Ibaraki 305-0052, Japan

    • M. Ishii


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P.J.G., B.D.S., D.W.P., T.P.Barnett and K.E.T. designed the research. C.M.D., T.P.Boyer and M.I. contributed new analytic tools. P.J.G., B.D.S., C.M.D., J.A.C., T.P.Boyer, P.M.C. and K.M.A. analysed the data. P.J.G., B.D.S., C.M.D., J.A.C., D.W.P. and K.E.T. wrote the paper.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to P. J. Gleckler.

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