maladaptation, where the intervention subsequently leads to responses that increase vulnerability to climate threats. For instance, building dikes may encourage settlement and investment in the protected area, potentially exposing people to high flood risk if sea level rise is higher than expected and increases in the dike height are not or cannot be undertaken.

5. **Failure to manage deep uncertainties and competing beliefs can also hinder much-needed mitigation efforts** . Deep uncertainties exist about how much we should mitigate CO2 emissions and at what cost, the effectiveness of different policies, and the availability of future technologies. Indeed, many who are reluctant to address climate change have cited uncertainty as a reason to postpone action. There is an urgent need for methods to manage deep uncertainty and reach sound adaptation and mitigation decisions.

6. **In this paper, we seek to help decision makers better manage uncertainty and disagreement, particularly around climate change, by guiding them to the right decision making processes** . Traditional decision processes ask us to first reduce uncertainty by agreeing on assumptions about current and future conditions, and _then_ analyze our decision options. When faced with disagreement and uncertainty, these traditional “Agree-on-Assumptions” processes lack transparency, are vulnerable to bias and gridlock, and lead us to brittle decisions – those that perform poorly when the future diverges from our projections. We can instead invert these steps, deferring on agreement until we have analyzed the options under many different assumptions. This inverted “Agree-on-Decisions” process promotes consensus around robust decisions and can help manage uncertainty and disagreement around climate change and other conditions. While some decision-making methodologies assume that the analysts or experts will provide the “best” solution to the decisionmaker, agree-on-decisions methodologies usually build on participatory processes and close interactions between experts and decision-makers. As such, they aim to “ _assist the decision maker to evaluate options, to develop strategies, and to evoke and evolve preferences in light of the analysis of uncertainties_ ” (Ben-Haim 2006). Such an approach is deemed more appropriate in the presence of deep uncertainty, and ensure that decisions are legitimate (Renn 2008; World Bank 2013).

7. **By making decisions with “inverted” processes that analyze options first and seek agreement second, we can**

- Generate buy-in by including diverse beliefs and making analyses more transparent;

- Identify strategies that are robust, performing well no matter what the future brings;

- Focus decision makers’ attention on the tradeoffs between decision options;

- Seek agreement where it matters most: on actions, rather than on assumptions;

- Inform the decision while making sure that decision-makers – not experts and analysts – make the decision.

8. **The rest of this paper is divided into four sections, B through E.** In Section B, we briefly distinguish between decision metrics and decision processes, and we posit that they should be considered separately given that any decision process can be used with any decision metric. Section C then focuses “Agree-on-Assumptions” processes while Section D presents “Agree-on-Decisions” processes. In the latter, we review features of robust decisions around which decision makers can reach consensus and offer three real-world applications. We conclude in Section E. The paper also offers an introduction to climate uncertainty in Appendix 1.

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