scenario was rejected in favor of a robust decision making process designed to incorporate multiple and at times conflicting sources of climate information. The analysis of the Great Lakes Basin plan comprised three phases.

59. **First, stakeholders defined performance benchmarks and identified vulnerabilities that would lead to unacceptable performance.** To prioritize concerns for the regulation of Lake Superior, stakeholder experts were convened from state, provincial, federal, and local government agencies, as well as special interest groups (boating, hydroelectricity, navigation), and environmental groups (e.g. The Nature Conservancy). The experts were tasked with identifying the metrics by which they would like the candidate regulation plans to be evaluated. Based on these goals, the stakeholder groups then defined what combination of lake level and duration led to acceptable outcomes, and what levels led to impacts that were either less favorable or unacceptable. In this way, thresholds designating of acceptable performance for candidate regulations plans were established. This allowed the evaluation of regulation plans using a common numeraire for each of the different interests, namely, the occurrence of unacceptable lake levels as defined by each interest.

60. **Second, stakeholders quantified the climate sensitivity for each proposed plan.** Analysts created a climate response function, which estimated the consequences (lake levels and associated performance metrics) of a given decision (regulation plan) for a set of mean climate conditions that were varied to evaluate a broadly defined plausible range of climate change. The function thus related climate effects to the performance metrics influencing the decision in a way that was independent of any assumptions about the relative likelihood of future climate conditions. Using a parametrically varied set of stochastic time series (each representing a given mean climate), analysts identified those climate conditions that presented risks (unacceptable lake levels) to each regulation plan. Note that climate model projections had not been used in the analysis to this point, yet the vulnerability of proposed plans to potential climate futures was revealed.

61. **Third, the plausibility (relative probability) of those conditions was estimated through tailored climate information.** Given the uncertainty associated with the probability estimates even after maximizing credibility, the term ‘‘plausibility’’ is used in place of probability. The decision maker, in this case the Study Board, was presented with the risk of each candidate regulation plan, where risk was defined as the plausibility of problematic climate conditions (the climate changes that would cause unacceptable performance). The plausibility estimates were represented as imprecise probabilities, where a range of probabilities was shown for each climate state based on the difference sources of climate information (e.g., climate projections, stochastic analysis, paleo-climate data, and expert opinion). Thus, plans could be evaluated in terms of the range of climate change over which they maintained acceptable lake levels, i.e., their robustness to climate change. The result was a climate-informed robustness index for each candidate plan. The plausibility estimates could be adjusted based on different comfort levels of the Board members with different sources of climate information. For example, some preferred considering only the probabilities generated from climate model projections, while others preferred only probabilities from historical observations.

62. **In sum, recommendation for a final regulation plan focused on two plans that performed best over a very wide range of future climates.** The analysis also revealed that even these “best” plans were not robust to climate changes that were quite plausible, leading the Study Board to also recommend that the regulation plan be coupled with an adaptive management program to address future uncertainty. The Board expressed satisfaction in the use of climate information to make this decision.

24