A weighting framework to improve the use of emissions scenario ensembles of opportunity

Abstract Integrated assessment models produce large ensembles of socioeconomic scenarios that are used profusely in climate change research. The Intergovernmental Panel on Climate Change (IPCC), non-governmental organizations or national climate committees often rely on ensemble statistics to identify mitigation strategies and set climate targets. A limitation of such evidence is the opportunistic nature of scenario ensembles: they are an unstructured, serendipitous collection of evidence. Drawing on concepts from physical climate science and ensemble analysis, we present an approach for the flexible, multidimensional weighting of emission scenario data that accounts for relevance, quality and diversity. Our illustrative application to the latest IPCC scenario database demonstrates a reduction in dominance of highly represented models and studies, and sees net-zero emission milestones differ to those originally reported. Our framework formalizes decisions otherwise made in an ad hoc manner, providing a tool contributing to the broader challenge of assessing ensembles of opportunity.