CR 16:61-78 (2000)  -  doi:10.3354/cr016061

A protocol to articulate and quantify uncertainties in climate change detection and attribution

James S. Risbey1,*, Milind Kandlikar1, David J. Karoly2

1Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
2CRC for Southern Hemisphere Meteorology, Monash University, Clayton 3168, Australia

ABSTRACT: This work develops and describes a formal probabilistic protocol via which the process of identifying lines of evidence for climate change, assessing likely causes for changes in the evidence, and combining the lines of evidence to make overall attributions of cause to greenhouse gases can be made. This open and detailed model of the detection and attribution process is designed to identify issues at stake in detection and attribution, and to facilitate scrutiny and understanding on this contentious issue in broader communities. The protocol provides a convenient means to make each of the judgements in this issue explicit. These judgements are characterized via expert elicitation techniques in both quantitative and qualitative form. The protocol focuses on detecting climate change and attributing causes to the enhanced greenhouse effect rather than on more general anthropogenic change, because the former is more consequential. Major uncertainties identified in the protocol relate to characterization of natural variability for each line of evidence, non-greenhouse forcings, and the climate response to forcing. The relative roles of uncertainty in climate sensitivity and climate forcings are still unclear in making determinations of attribution. Measures of attribution need to account for both the amount of signal explained by a postulated cause as well as its associated probability. When combining lines of evidence to form overall measures of attribution, the level of dependence assumed among lines of evidence is critical. Finally, the protocol highlights the need to reevaluate standards of evidence for attributing greenhouse climate change.

KEY WORDS: Detection · Attribution · Climate change · Expert judgement

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