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Causes of differences in model and satellite tropospheric warming rates

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Abstract

In the early twenty-first century, satellite-derived tropospheric warming trends were generally smaller than trends estimated from a large multi-model ensemble. Because observations and coupled model simulations do not have the same phasing of natural internal variability, such decadal differences in simulated and observed warming rates invariably occur. Here we analyse global-mean tropospheric temperatures from satellites and climate model simulations to examine whether warming rate differences over the satellite era can be explained by internal climate variability alone. We find that in the last two decades of the twentieth century, differences between modelled and observed tropospheric temperature trends are broadly consistent with internal variability. Over most of the early twenty-first century, however, model tropospheric warming is substantially larger than observed; warming rate differences are generally outside the range of trends arising from internal variability. The probability that multi-decadal internal variability fully explains the asymmetry between the late twentieth and early twenty-first century results is low (between zero and about 9%). It is also unlikely that this asymmetry is due to the combined effects of internal variability and a model error in climate sensitivity. We conclude that model overestimation of tropospheric warming in the early twenty-first century is partly due to systematic deficiencies in some of the post-2000 external forcings used in the model simulations.

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Figure 1: Time series and difference series of simulated and observed tropospheric temperature.
Figure 2: Trends (left column) and trend significance (right column) for TMT difference series.
Figure 3: Asymmetries in the statistical significance of differences between modelled and observed tropospheric temperature trends.
Figure 4: Overall statistical significance of the γ1, γ2 and γ3 asymmetry statistics as a function of the analysis timescale and the satellite data used to compute the ‘MMA minus observed’ difference time series.

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Acknowledgements

We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modelling groups for producing and making available their model output. For CMIP, the US Department of Energy’s Program for Climate Model Diagnosis and Intercomparison (PCMDI) provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. We thank M. Zelinka (PCMDI) for providing CMIP5 climate sensitivity results, S. Solomon (M.I.T.) for helpful discussions, and N. Swart and V. Arora (both CCCma) for constructive comments. The views, opinions, and findings contained in this report are those of the authors and should not be construed as a position, policy, or decision of the US Government, the US Department of Energy, or the National Oceanic and Atmospheric Administration.

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Authors and Affiliations

  1. Program for Climate Model Diagnosis and Intercomparison (PCMDI), Lawrence Livermore National Laboratory, Livermore, California, 94550, USA

    Benjamin D. Santer, Giuliana Pallotta, Jeffrey F. Painter, Céline Bonfils, Ivana Cvijanovic & Stephen Po-Chedley

  2. Canadian Centre for Climate Modelling and Analysis (CCCma), Environment and Climate Change Canada, Victoria, British Columbia, V8W 2Y2, Canada

    John C. Fyfe & Gregory M. Flato

  3. National Center for Atmospheric Research, Boulder, Colorado, 80307, USA

    Gerald A. Meehl

  4. ARC Centre of Excellence for Climate System Science, University of New South Wales, New South Wales, 2052, Australia

    Matthew H. England

  5. Department of Meteorology, National Centre for Atmospheric Science, University of Reading, Reading, RG6 6BB, UK

    Ed Hawkins

  6. Department of Meteorology and Earth and Environmental Systems Institute, Pennsylvania State University, University Park, Pennsylvania, 16802, USA

    Michael E. Mann

  7. Remote Sensing Systems, Santa Rosa, California, 95401, USA

    Carl Mears & Frank J. Wentz

  8. Department of Atmospheric Sciences, University of Washington, Seattle, Washington, 98195, USA

    Qiang Fu

  9. Center for Satellite Applications and Research, NOAA/NESDIS, College Park, Maryland, 20740, USA

    Cheng-Zhi Zou

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  1. Benjamin D. Santer
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  2. John C. Fyfe
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  3. Giuliana Pallotta
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  4. Gregory M. Flato
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  5. Gerald A. Meehl
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  7. Ed Hawkins
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  8. Michael E. Mann
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  14. Stephen Po-Chedley
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  15. Qiang Fu
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Contributions

B.D.S., J.C.F., G.P., G.M.F. and E.H. designed the analysis. B.D.S. performed all statistical analyses. J.F.P. calculated synthetic satellite temperatures from model simulation output and provided assistance with processing of observed temperature data. C.M., F.J.W., S.P.-C., Q.F. and C.-Z.Z. provided satellite temperature data. I.C., C.B. and J.F.P. assisted with the processing of the CMIP5 simulations analysed here. All authors contributed to the writing and review of the manuscript.

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Correspondence to Benjamin D. Santer.

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Santer, B., Fyfe, J., Pallotta, G. et al. Causes of differences in model and satellite tropospheric warming rates. Nature Geosci 10, 478–485 (2017). https://doi.org/10.1038/ngeo2973

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