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; Zelinka, Mark D.

doi:10.1073/pnas.1904586116

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

Journal Article · 16 September 2019 · Proceedings of the National Academy of Sciences of the United States of America

DOI: https://doi.org/10.1073/pnas.1904586116 · OSTI ID:1562311

^[1]; Fyfe, John C. ^[2];

^[3];

^[1]; Bonfils, Céline ^[1];

^[1];

^[1]

Program for Climate Model Diagnosis and Intercomparison, Lawrence Livermore National Laboratory, Livermore, CA 94550,
Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada, Victoria, BC V8W 2Y2, Canada,
Earth, Atmospheric, and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139

Significance Climate observations comprise one sequence of natural internal variability and the response to external forcings. Large initial condition ensembles (LEs) performed with a single climate model provide many different sequences of internal variability and forced response. LEs allow analysts to quantify random uncertainty in the time required to detect forced “fingerprint” patterns. For tropospheric temperature, the consistency between fingerprint detection times in satellite data and in 2 different LEs depends primarily on the size of the simulated warming in response to greenhouse gas increases and the simulated cooling caused by anthropogenic aerosols. Consistency is closest for a model with high sensitivity and large aerosol-driven cooling. Assessing whether this result is physically reasonable will require reducing currently large aerosol forcing uncertainties.

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Research Organization:: Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)

Sponsoring Organization:: USDOE; USDOE National Nuclear Security Administration (NNSA)

Grant/Contract Number:: AC52-07NA27344

OSTI ID:: 1562311

Report Number(s):: LLNL-JRNL--770081

Journal Information:: Proceedings of the National Academy of Sciences of the United States of America, Journal Name: Proceedings of the National Academy of Sciences of the United States of America Journal Issue: 40 Vol. 116; ISSN 0027-8424

Publisher:: Proceedings of the National Academy of SciencesCopyright Statement

Country of Publication:: United States

Language:: English

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

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