Uncertainty As Knowledge: Harnessing Ambiguity and Uncertainty into Policy Constraints

Abstract:

There are numerous sources of uncertainty that impact policy decisions relating to climate change: There is scientific uncertainty, as for example encapsulated in estimates of climate sensitivity. There is policy uncertainty, which arises when mitigation efforts are erratic or are reversed (as recently happened in Australia). There is also technological uncertainty which affects the mitigation pathway. How can policy decisions be informed in light of these multiple sources of uncertainty? We propose an “ordinal” approach that relies on comparisons such as “greater than” or “lesser than” (known as ordinal), which can help sidestep disagreement about specific parameter estimates (e.g., climate sensitivity). To illustrate, recent analyses (Lewandowsky et al., 2014, Climatic Change) have shown that the magnitude of uncertainty about future temperature increases is directly linked with the magnitude of future risk: the greater the uncertainty, the greater the risk of mitigation failure (defined as exceeding a carbon budget for a predetermined threshold). Here we extend this approach to other sources of uncertainty, with a particular focus on “ambiguity” or “second-order” uncertainty, which arises when there is dissent among experts.