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Most of the integrated assessment modelling (IAM) literature focuses on cost-effective pathways towards given temperature goals. Conversely, using seven diverse IAMs we project global energy CO 2 emissions trajectories based on near-term mitigation efforts, and two assumptions on how these efforts continue post-2030. Despite finding a wide range of emissions by 2050, nearly all the scenarios have median warming of less than 3°C in 2100. However, the most optimistic scenario is still insufficient to limit global warming to 2°C. We furthermore highlight key modelling choices inherent to projecting where emissions are headed. First, emissions are more sensitive to the choice of IAM than to the assumed mitigation effort, highlighting the importance of heterogenous model intercomparisons. Differences across models reflect diversity in baseline assumptions and impacts of near-term mitigation efforts. Second, common practice of using economy-wide carbon prices to represent policy exaggerates carbon capture and storage (CCS) use compared to explicitly modelling policies. Ed Summ 2Mitigation pathways tend to focus on an end temperature target and calculate how to keep within these bounds. This work uses seven integrated assessment models to consider current mitigation efforts, and project likely temperature trajectories.

Abstract:In pursuit of the drastic transformations necessary for effectively responding to climate change, the Paris Agreement stresses the need to design and implement sustainable, robust, and socially acceptable policy pathways in a globally coordinated and cooperative manner. For decades, the scientific community has been carrying out quantitative modelling exercises in support of climate policy design, primarily by means of energy systems and integrated assessment modelling frameworks. Here, we describe in detail the context of a hitherto ineffective scientific contribution to policymaking, highlight the available means to formulate a new paradigm that overcomes existing and emerging challenges, and ultimately call for change. In particular, we argue that individual modelling exercises alone widen the gap between formal representation and real-life context in which decisions are taken, and investigate major criticisms to which formalised modelling frameworks are subject. We essentially highlight the importance of employing diverse modelling ensembles, placing the human factor at the core of all modelling processes, and enhancing the robustness of model-driven policy prescriptions through decision support systems. These altogether compose a truly integrative approach to supporting the design of effective climate policy and sustainable transitions and, therefore, strengthen the modelling-policymaking interface.

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