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A minimal model for estimating climate sensitivity

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  • Loehle, Craig

Abstract

Climate sensitivity summarizes the net effect of a change in forcing on Earth's surface temperature. Estimates based on energy balance calculations give generally lower values for sensitivity (<2°C per doubling of forcing) than those based on general circulation models, but utilize uncertain historical data and make various assumptions about forcings. A minimal model was used that has the fewest possible assumptions and the least data uncertainty. Using only the historical surface temperature record, the periodic temperature oscillations often associated with the Pacific Decadal Oscillation and Atlantic Multidecadal Oscillation were estimated and subtracted from the surface temperature data, leaving a linear warming trend identified as an anthropogenic signal. This estimated rate of warming was related to the fraction of a log CO2 doubling from 1959 to 2013 to give an estimated transient sensitivity of 1.093°C (0.96–1.23°C 95% confidence limits) and equilibrium climate sensitivity of 1.99°C (1.75–2.23°C). It is argued that higher estimates derived from climate models are incorrect because they disagree with empirical estimates.

Suggested Citation

  • Loehle, Craig, 2014. "A minimal model for estimating climate sensitivity," Ecological Modelling, Elsevier, vol. 276(C), pages 80-84.
    • Handle: RePEc:eee:ecomod:v:276:y:2014:i:c:p:80-84
    DOI: 10.1016/j.ecolmodel.2014.01.006
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    1. John C. Fyfe & Nathan P. Gillett & Francis W. Zwiers, 2013. "Overestimated global warming over the past 20 years," Nature Climate Change, Nature, vol. 3(9), pages 767-769, September.
    2. Magne Aldrin & Marit Holden & Peter Guttorp & Ragnhild Bieltvedt Skeie & Gunnar Myhre & Terje Koren Berntsen, 2012. "Bayesian estimation of climate sensitivity based on a simple climate model fitted to observations of hemispheric temperatures and global ocean heat content," Environmetrics, John Wiley & Sons, Ltd., vol. 23(3), pages 253-271, May.
    3. J. Annan & J. Hargreaves, 2011. "On the generation and interpretation of probabilistic estimates of climate sensitivity," Climatic Change, Springer, vol. 104(3), pages 423-436, February.
    4. Nicola Scafetta, 2013. "Solar and Planetary Oscillation Control on Climate Change: Hind-Cast, Forecast and a Comparison with the Cmip5 Gcms," Energy & Environment, , vol. 24(3-4), pages 455-496, June.
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    Cited by:

    1. Patrick J. Michaels, 2014. "The Systemic Failure of General Circulation Climate Models: A Tribute to S. Fred Singer," Energy & Environment, , vol. 25(6-7), pages 1153-1161, August.
    2. Ronan Connolly & Michael Connolly & Robert M. Carter & Willie Soon, 2020. "How Much Human-Caused Global Warming Should We Expect with Business-As-Usual (BAU) Climate Policies? A Semi-Empirical Assessment," Energies, MDPI, vol. 13(6), pages 1-51, March.
    3. Cawley, Gavin C. & Cowtan, Kevin & Way, Robert G. & Jacobs, Peter & Jokimäki, Ari, 2015. "On a minimal model for estimating climate sensitivity," Ecological Modelling, Elsevier, vol. 297(C), pages 20-25.

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    Keywords

    Greenhouse effect; Forcing; CO2; Climate change;
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