Identifying Human Influences on Atmospheric Temperature

TitleIdentifying Human Influences on Atmospheric Temperature
Publication TypeJournal Article
Year of Publication2013
AuthorsSanter, Benjamin D., Painter Jeffrey F., Mears Carl A., Doutriaux Charles, Cadwell Peter, Arblaster Julie M., Cameron-Smith Philip J., Gillett Nathan P., Gleckler Peter J., Lanzante John, Perlwitz Judith, Salomon Susan, Stott Peter A., Taylor Karl E., Terray Laurent, Thorne Peter W., Wehner Mike F., Wentz Frank J., Wigley Tom M. L., Wilcox Laura J., and Zou Chen-Zhi
JournalProceedings of the National Academy of Sciences
Volume110
Number1
Pages26-33
Abstract / Summary

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 finger- print) 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.

URLhttp://www.pnas.org/content/110/1/26.abstract
DOI10.1073/pnas.1210514109
Journal: Proceedings of the National Academy of Sciences
Year of Publication: 2013
Volume: 110
Number: 1
Pages: 26-33

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 finger- print) 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.

DOI: 10.1073/pnas.1210514109
Citation:
Santer, BD, JF Painter, CA Mears, C Doutriaux, P Cadwell, JM Arblaster, PJ Cameron-Smith, et al.  2013.  "Identifying Human Influences on Atmospheric Temperature."  Proceedings of the National Academy of Sciences 110(1): 26-33.  https://doi.org/10.1073/pnas.1210514109.