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    Identifying human influences on atmospheric temperature

    Santer, Benjamin D. and Painter, Jeffrey F. and Mears, Carl A. and Doutrauix, Charles and Caldwell, Peter and Arblaster, Julie M. and Cameron-Smith, Philip J. and Gillett, Nathan P. and Gleckler, Peter J. and Lanzante, John and Perlwitz, J. and Solomon, Susan and Stott, Peter A. and Taylor, Karl E. and Terray, Laurent and Thorne, Peter and Wehner, Michael F. and Wentz, Frank J. and Wigley, Tom M. and Wilcox, Laura J. and Zou, Cheng-Zhi (2013) Identifying human influences on atmospheric temperature. Proceedings of the National Academy of Sciences, 110 (1). pp. 26-33. ISSN 1091-6490

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    We perform a multimodel detection and attribution study with climate model simulation output and satellite-based measurements of tropospheric and stratospheric temperature change. We use simulation output from 20 climate models participating in phase 5 of the Coupled Model Intercomparison Project. This multimodel archive provides estimates of the signal pattern in response to combined anthropogenic and natural external forcing (the fingerprint) and the noise of internally generated variability. Using these estimates, we calculate signal-to-noise (S/N) ratios to quantify the strength of the fingerprint in the observations relative to fingerprint strength in natural climate noise. For changes in lower stratospheric temperature between 1979 and 2011, S/N ratios vary from 26 to 36, depending on the choice of observational dataset. In the lower troposphere, the fingerprint strength in observations is smaller, but S/N ratios are still significant at the 1% level or better, and range from three to eight. We find no evidence that these ratios are spuriously inflated by model variability errors. After removing all global mean signals, model fingerprints remain identifiable in 70% of the tests involving tropospheric temperature changes. Despite such agreement in the large-scale features of model and observed geographical patterns of atmospheric temperature change, most models do not replicate the size of the observed changes. On average, the models analyzed underestimate the observed cooling of the lower stratosphere and overestimate the warming of the troposphere. Although the precise causes of such differences are unclear, model biases in lower stratospheric temperature trends are likely to be reduced by more realistic treatment of stratospheric ozone depletion and volcanic aerosol forcing.

    Item Type: Article
    Keywords: climate change; detection; attribution; climate modeling; multimodel analysis;
    Academic Unit: Faculty of Social Sciences > Geography
    Faculty of Social Sciences > Research Institutes > Irish Climate Analysis and Research Units, ICARUS
    Item ID: 6487
    Identification Number:
    Depositing User: Peter Thorne
    Date Deposited: 20 Oct 2015 15:32
    Journal or Publication Title: Proceedings of the National Academy of Sciences
    Publisher: National Academy of Sciences
    Refereed: Yes
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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