Identify Human Influences on Atmospheric Temperature: Are Results Robust to Uncertainties?

• Activity Number: 509
• Type: Invited
• Date/Time: Wednesday, August 7, 2013 : 10:30 AM to 12:20 PM
• Sponsor: ASA Advisory Committee on Climate Change Policy
• Author(s): Benjamin David Santer*+
• Companies: Lawrence Livermore National Laboratory
• Keywords: Climate modeling ; Climate change detection and attribution ; Tropospheric warming ; Stratospheric cooling ; Atmospheric dynamics ; Climate change

Abstract

We perform a multi-model detection and attribution study with climate model simulation output and satellite 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 multi-model 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 observations relative to fingerprint strength in natural climate noise. For lower stratospheric temperature changes, S/N ratios vary from 26 to 36, depending on the observational data set selected. In the troposphere, the fingerprint strength in observations is smaller, but S/N ratios are still significant at the 1% level, and range from 3 to 8. We find no evidence that these ratios are spuriously inflated by model variability errors. Even after removing all global-mean signals, model fingerprints remain identifiable in 70% of the tests involving tropospheric temperature change.