Editing IPCC:AR6/SROCC/Chapter-3 (section)

===== 3.5.4.2.1 Participatory scenario analysis and planning =====

Participatory scenario analysis is a quickly evolving and widely used practice in polar regions, and has proven particularly useful for supporting climate adaptation at multiple scales when it uses a social-ecological perspective (ARR, 2016; AMAP, 2017a <sup>[[#fn:r2273|2273]]</sup> ; Crépin et al., 2017 <sup>[[#fn:r2274|2274]]</sup> ; Planque et al., 2019 <sup>[[#fn:r2275|2275]]</sup> ) ( ''medium confidence).'' While there are technical dimensions in scenario analysis and planning (e.g., the building of useful simulation models that capture and communicate nuanced social-ecological system dynamics such as long-fuse big bang processes, pathological dynamics, critical thresholds, and unforeseen processes (Crépin et al., 2017), there are also creative aspects, such as the use of art to help in the visualisation of possible future (e.g., Planque et al., 2019).

Participatory scenario analysis has been applied to various problem areas related to climate change responses in the polar regions. Applications demonstrate the utility of the practice for identifying possible local futures that consider climate change or socioeconomic pathways (e.g., in Alaska, Ernst and van Riemsdijk, 2013; and in Eurasian reindeer-herding systems, van Oort et al., 2015; Nilsson et al., 2017 <sup>[[#fn:r2276|2276]]</sup> ) and interacting drivers of change (e.g., in Antarctica; Liggett et al., 2017 <sup>[[#fn:r2277|2277]]</sup> ). Scenario analysis proved helpful for stakeholders with different expertise and perspectives to jointly develop scenarios to inform ecosystem-based management strategies and adaptation options (e.g., in the Barents region; Nilsson et al., 2017 <sup>[[#fn:r2278|2278]]</sup> ; Planque et al., 2019 <sup>[[#fn:r2279|2279]]</sup> ) and to identify research needs (e.g., in Alaska; Vargas-Moreno et al., 2016 <sup>[[#fn:r2280|2280]]</sup> ), including informing and applying climate downscaling efforts (e.g., in Alaska; Ernst and van Riemsdijk, 2013 <sup>[[#fn:r2281|2281]]</sup> ).

A review of scenario analysis in the Arctic, however, found that while the practice is widespread and many are using best practice methods, less than half scenarios programs incorporated climate projections and that those utilising a backcasting approach had higher local participation than those only using forecasting (Flynn et al., 2018 <sup>[[#fn:r2282|2282]]</sup> ). It noted that integrating different knowledge systems and attention to cultural factors influence program utility and acceptance. Planque et al. (2019) <sup>[[#fn:r2283|2283]]</sup> also found that most participating stakeholders had limited experience using scenario analysis, suggesting the importance of process methods for engaging stakeholders when exploring possible, likely, and desirable futures. The long-term utility of this practice in helping stakeholders engage with each other to envision possible futures and be forward thinking in decision making will depend on the science of climate projections, further development of decision support systems to inform decision makers, attention to cultural factors and worldview, as well as refinement of processes that facilitate participants’ dialogue ( ''medium confidence'' ).

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