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Forcing, feedback and internal variability in global temperature trends

Author

Listed:
  • Jochem Marotzke

    (Max Planck Institute for Meteorology, Bundesstrasse 53, 20146 Hamburg, Germany)

  • Piers M. Forster

    (School of Earth and Environment, University of Leeds, Leeds LS2 9JT, UK)

Abstract

Most present-generation climate models simulate an increase in global-mean surface temperature (GMST) since 1998, whereas observations suggest a warming hiatus. It is unclear to what extent this mismatch is caused by incorrect model forcing, by incorrect model response to forcing or by random factors. Here we analyse simulations and observations of GMST from 1900 to 2012, and show that the distribution of simulated 15-year trends shows no systematic bias against the observations. Using a multiple regression approach that is physically motivated by surface energy balance, we isolate the impact of radiative forcing, climate feedback and ocean heat uptake on GMST—with the regression residual interpreted as internal variability—and assess all possible 15- and 62-year trends. The differences between simulated and observed trends are dominated by random internal variability over the shorter timescale and by variations in the radiative forcings used to drive models over the longer timescale. For either trend length, spread in simulated climate feedback leaves no traceable imprint on GMST trends or, consequently, on the difference between simulations and observations. The claim that climate models systematically overestimate the response to radiative forcing from increasing greenhouse gas concentrations therefore seems to be unfounded.

Suggested Citation

  • Jochem Marotzke & Piers M. Forster, 2015. "Forcing, feedback and internal variability in global temperature trends," Nature, Nature, vol. 517(7536), pages 565-570, January.
    • Handle: RePEc:nat:nature:v:517:y:2015:i:7536:d:10.1038_nature14117
    DOI: 10.1038/nature14117
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    Cited by:

    1. Philippe Goulet Coulombe & Maximilian Göbel, 2021. "On Spurious Causality, CO 2 , and Global Temperature," Econometrics, MDPI, vol. 9(3), pages 1-18, September.
    2. Bjørn H. Samset & Jan S. Fuglestvedt & Marianne T. Lund, 2022. "Reply to: Uncertainty in near-term temperature evolution must not obscure assessments of climate mitigation benefits," Nature Communications, Nature, vol. 13(1), pages 1-3, December.
    3. Kočí, Jan & Kočí, Václav & Maděra, Jiří & Černý, Robert, 2019. "Effect of applied weather data sets in simulation of building energy demands: Comparison of design years with recent weather data," Renewable and Sustainable Energy Reviews, Elsevier, vol. 100(C), pages 22-32.
    4. Louis-Gaëtan Giraudet & Céline Guivarch, 2016. "Global warming as an asymmetric public bad," Working Papers 2016.26, FAERE - French Association of Environmental and Resource Economists.
    5. Qionghuan Liu & Xiuhong Wang & Yili Zhang & Huamin Zhang & Lanhui Li, 2019. "Vegetation Degradation and Its Driving Factors in the Farming–Pastoral Ecotone over the Countries along Belt and Road Initiative," Sustainability, MDPI, vol. 11(6), pages 1-16, March.
    6. Philippe Goulet Coulombe & Maximilian Gobel, 2021. "On Spurious Causality, CO2, and Global Temperature," Papers 2103.10605, arXiv.org.

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