Quantifying stochastic uncertainty in detection time of human-caused climate signals

Santer, Benjamin D., Fyfe, John C., Solomon, Susan, Painter, Jeffrey F., Bonfils, Céline, Pallotta, Giuliana and Zelinka, Mark D. (2019) Quantifying stochastic uncertainty in detection time of human-caused climate signals. Proceedings of the National Academy of Sciences of the United States of America, 116 (40). pp. 19821-19827. ISSN 0027-8424

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Abstract

Large initial condition ensembles of a climate model simulation provide many different realizations of internal variability noise superimposed on an externally forced signal. They have been used to estimate signal emergence time at individual grid points, but are rarely employed to identify global fingerprints of human influence. Here we analyze 50- and 40-member ensembles performed with 2 climate models; each was run with combined human and natural forcings. We apply a pattern-based method to determine signal detection time td in individual ensemble members. Distributions of td are characterized by the median td{m} and range td{r}, computed for tropospheric and stratospheric temperatures over 1979 to 2018. Lower stratospheric cooling—primarily caused by ozone depletion—yields td{m} values between 1994 and 1996, depending on model ensemble, domain (global or hemispheric), and type of noise data. For greenhouse-gas–driven tropospheric warming, larger noise and slower recovery from the 1991 Pinatubo eruption lead to later signal detection (between 1997 and 2003). The stochastic uncertainty td{r} is greater for tropospheric warming (8 to 15 y) than for stratospheric cooling (1 to 3 y). In the ensemble generated by a high climate sensitivity model with low anthropogenic aerosol forcing, simulated tropospheric warming is larger than observed; detection times for tropospheric warming signals in satellite data are within td{r} ranges in 60% of all cases. The corresponding number is 88% for the second ensemble, which was produced by a model with even higher climate sensitivity but with large aerosol-induced cooling. Whether the latter result is physically plausible will require concerted efforts to reduce significant uncertainties in aerosol forcing.

Item Type:	Article
Additional Information:	Publisher Copyright: © 2019 National Academy of Sciences. All rights reserved.
Uncontrolled Keywords:	climate change,detection and attribution,large ensembles,general ,/dk/atira/pure/subjectarea/asjc/1000
Faculty \ School:	Faculty of Science > School of Environmental Sciences
Related URLs:	http://www.scopus.com/inward/record.url?...
Depositing User:	LivePure Connector
Date Deposited:	18 Mar 2026 12:30
Last Modified:	18 Mar 2026 12:30
URI:	https://ueaeprints.uea.ac.uk/id/eprint/102402
DOI:	10.1073/pnas.1904586116

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