Climate policy decision making in contexts of deep uncertainty - from optimisation to robustness

• IAM are sensitive to model assumptions and distort decision making policy design. Largescale reliance of scenarios on CDR is problematic for a number reasons. There need get away from consolidative optimisation exploratory modelling. A shift best guess prediction explicit acceptance deep uncertainty also important. Deliberation with analysis allows more policies, values, participants transparency. Integrated assessment models often used evaluate the role different technologies in meeting global climate goals. Such have been criticised failing address uncertainties plurality values that fundamental energy transitions. One consequence overwhelmingly depend large-scale carbon dioxide removal hold warming below 2 °C. Here we propose an alternative approach using Scenario-Focused Decision Analysis (SFDA) as methods embrace under uncertainty. SFDA can accommodate range value sets perspectives, most importantly integrate value-based decision-making designing policy. We specifically consider Robust Making (RDM) exemplar developing outline iterative five-stage framework RDM long-term mitigation pathways example. The five steps comprise (i) participatory definition goals, potential options uncertainties; (ii) modelling performance portfolios across wide future scenarios; (iii) visualisation identification portfolio vulnerabilities; (iv) trade-offs; (v) development strategies. SFDA, RDM, provide untapped opportunities diverse actors explore robustness choices through “ deliberation analysis” . In relation methods, provides evaluating their safely goals societally acceptable manner.