• Energy Research

AbstractAnalysis of climate policy scenarios has become an important tool for identifying mitigation strategies, as shown in the latest Intergovernmental Panel on Climate Change Working Group III report1. The key outcomes of these scenarios differ substantially not only because of model and climate target differences but also because of different assumptions on behavioural, technological and socio-economic developments2–4. A comprehensive attribution of the spread in climate policy scenarios helps policymakers, stakeholders and scientists to cope with large uncertainties in this field. Here we attribute this spread to the underlying drivers using Sobol decomposition5, yielding the importance of each driver for scenario outcomes. As expected, the climate target explains most of the spread in greenhouse gas emissions, total and sectoral fossil fuel use, total renewable energy and total carbon capture and storage in electricity generation. Unexpectedly, model differences drive variation of most other scenario outcomes, for example, in individual renewable and carbon capture and storage technologies, and energy in demand sectors, reflecting intrinsic uncertainties about long-term developments and the range of possible mitigation strategies. Only a few scenario outcomes, such as hydrogen use, are driven by other scenario assumptions, reflecting the need for more scenario differentiation. This attribution analysis distinguishes areas of consensus as well as strong model dependency, providing a crucial step in correctly interpreting scenario results for robust decision-making.

AbstractAnalysis of climate policy scenarios has become an important tool for identifying mitigation strategies, as shown in the latest Intergovernmental Panel on Climate Change Working Group III report1. The key outcomes of these scenarios differ substantially not only because of model and climate target differences but also because of different assumptions on behavioural, technological and socio-economic developments2–4. A comprehensive attribution of the spread in climate policy scenarios helps policymakers, stakeholders and scientists to cope with large uncertainties in this field. Here we attribute this spread to the underlying drivers using Sobol decomposition5, yielding the importance of each driver for scenario outcomes. As expected, the climate target explains most of the spread in greenhouse gas emissions, total and sectoral fossil fuel use, total renewable energy and total carbon capture and storage in electricity generation. Unexpectedly, model differences drive variation of most other scenario outcomes, for example, in individual renewable and carbon capture and storage technologies, and energy in demand sectors, reflecting intrinsic uncertainties about long-term developments and the range of possible mitigation strategies. Only a few scenario outcomes, such as hydrogen use, are driven by other scenario assumptions, reflecting the need for more scenario differentiation. This attribution analysis distinguishes areas of consensus as well as strong model dependency, providing a crucial step in correctly interpreting scenario results for robust decision-making.

Mitigation pathways allowing for temperature overshoot often ignore the related climate and macroeconomic impacts. Net-zero pathways with limited overshoot could reduce low-probability high-consequence risks and economic loss. Mitigation pathways exploring end-of-century temperature targets often entail temperature overshoot. Little is known about the additional climate risks generated by overshooting temperature. Here we assessed the benefits of limiting overshoot. We computed the probabilistic impacts for different warming targets and overshoot levels on the basis of an ensemble of integrated assessment models. We explored both physical and macroeconomic impacts, including persistent and non-persistent climate impacts. We found that temperature overshooting affects the likelihood of many critical physical impacts, such as those associated with heat extremes. Limiting overshoot reduces risk in the right tail of the distribution, in particular for low-temperature targets where larger overshoots arise as a way to lower short-term mitigation costs. We also showed how, after mid-century, overshoot leads to both higher mitigation costs and economic losses from the additional impacts. The study highlights the need to include climate risk analysis in low-carbon pathways.

Mitigation pathways allowing for temperature overshoot often ignore the related climate and macroeconomic impacts. Net-zero pathways with limited overshoot could reduce low-probability high-consequence risks and economic loss. Mitigation pathways exploring end-of-century temperature targets often entail temperature overshoot. Little is known about the additional climate risks generated by overshooting temperature. Here we assessed the benefits of limiting overshoot. We computed the probabilistic impacts for different warming targets and overshoot levels on the basis of an ensemble of integrated assessment models. We explored both physical and macroeconomic impacts, including persistent and non-persistent climate impacts. We found that temperature overshooting affects the likelihood of many critical physical impacts, such as those associated with heat extremes. Limiting overshoot reduces risk in the right tail of the distribution, in particular for low-temperature targets where larger overshoots arise as a way to lower short-term mitigation costs. We also showed how, after mid-century, overshoot leads to both higher mitigation costs and economic losses from the additional impacts. The study highlights the need to include climate risk analysis in low-carbon pathways.