@article{Beath:2026,
author = {Beath, H and Smith, C and Kikstra, JS and Dekker, M and Gidden, MJ and Rogelj, J},
journal = {Nature Climate Change},
title = {A weighting framework to improve the use of emissions scenario ensembles of opportunity},
year = {2026}
}

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TY  - JOUR
AB  - Integrated assessment models (IAMs) produce large ensembles of socioeconomic scenarios that are used profusely in climate change research. The Intergovernmental Panel on Climate Change (IPCC), non-governmental organisations 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 a novel 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 formalises decisions otherwise made in an ad hoc manner, providing a tool contributing to the broader challenge of assessing ensembles of opportunity.
AU  - Beath,H
AU  - Smith,C
AU  - Kikstra,JS
AU  - Dekker,M
AU  - Gidden,MJ
AU  - Rogelj,J
PY  - 2026///
SN  - 1758-678X
TI  - A weighting framework to improve the use of emissions scenario ensembles of opportunity
T2  - Nature Climate Change
ER  - 

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