Identifying human influences on atmospheric temperature: Are results robust to uncertainties?
Abstract
We have performed a multi-model detection and attribution ("D&A") study with climate model simulation output and satellite-based measurements of tropospheric and stratospheric temperature change. We used simulation output from 19 climate models participating in phase 5 of the Coupled Model Intercomparison Project. This multi-model archive provides estimates of both the geographical pattern of response to combined anthropogenic and natural external forcing (the "fingerprint") and of internally generated variability. The signal-to-noise (S/N) ratios produced by our D&A method help to quantify the strength of the fingerprint in observations relative to fingerprint strength in natural climate "noise". For changes in lower stratospheric temperature over 1979 to 2011, S/N ratios varied from 21 to 29, depending on the choice of observational data set. In the troposphere, the fingerprint strength in observations is lower, but S/N ratios are still significant at the 1% level or better, and range from 3 to 6. We find no evidence that these ratios are spuriously inflated by model variability errors. Even after removing all information on global-mean temperature changes, model fingerprints remained identifiable in over 50% of all tests. Despite this agreement in the hemispheric-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 here underestimate the observed cooling of the lower stratosphere and overestimate the warming of the troposphere. While the precise causes of such differences are still unclear, we show that model biases in lower stratospheric temperature trends are likely to be reduced by more realistic treatment of stratospheric ozone depletion and volcanic aerosol forcing.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2012
- Bibcode:
- 2012AGUFMIN13D..01S
- Keywords:
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- 1616 GLOBAL CHANGE / Climate variability;
- 3337 ATMOSPHERIC PROCESSES / Global climate models;
- 1627 GLOBAL CHANGE / Coupled models of the climate system