International audienceThis study explores a situation of staged accession to a global climate policy regime from the current situation of regionally fragmented and moderate climate action. The analysis is based on scenarios in which a front runner coalition - the EU or the EU and China - embarks on immediate ambitious climate action while the rest of the world makes a transition to a global climate regime between 2030 and 2050. We assume that the ensuing regime involves strong mitigation efforts but does not require late joiners to compensate for their initially higher emissions. Thus, climate targets are relaxed, and although staged accession can achieve significant reductions of global warming, the resulting climate outcome is unlikely to be consistent with the goal of limiting global warming to 2 degrees. The addition of China to the front runner coalition can reduce pre-2050 excess emissions by 20-30%, increasing the likelihood of staying below 2 degrees. Not accounting for potential co-benefits, the cost of front runner action is found to be lower for the EU than for China. Regions that delay their accession to the climate regime face a trade-off between reduced short term costs and higher transitional requirements due to larger carbon lock-ins and more rapidly increasing carbon prices during the accession period

he Paris Agreement sets the framework for international climate action. Within that context, countries are aiming to hold warming well below 2 °C and pursue limiting it to 1.5 °C. How such global temperature outcomes can be achieved has been explored widely in the scientific literature [1][2][3][4] and assessed by the IPCC, for example, in its Fifth Assessment Report (AR5; ref. 5 ) and its Special Report on Global Warming of 1.5 °C (SR1.5; ref. 6 ). Studies explore aspects of the timing and costs of emissions reductions and the contribution of different sectors 3,7,8 . However, there has been critique that, with the exception of a few notable studies [9][10][11][12] , the scenarios in the literature first exceed the prescribed temperature limits in the hope of recovering from this overshoot later through net-negative emissions [13][14][15][16] . Some pioneering studies [10][11][12] have explored implications of limiting overshoot through, for example, zero emissions goals, or have looked into the role of bioenergy with carbon capture and storage (BECCS) in reaching different temperature targets 9 . All these studies have relied on one or two models and/or a limited set of temperature targets.We bring together nine international modelling teams and conduct a comprehensive modelling intercomparison project (MIP) on this topic. Specifically, we explore mitigation pathways for reaching different temperature change targets with limited overshoot. We do this by adopting the scenario design from ref. 11 and contrast scenarios with a fixed remaining carbon budget until the time when net-zero CO 2 emissions (net-zero budget scenarios) are reached with scenarios that use an end-of-century budget design. The latter carbon budget for the full century permits the budget to be temporarily overspent, as long as net-negative CO 2 emissions (NNCE)

International audienceIntegrated assessments of how climate policy interacts with energy-economy systems can be performed by a variety of models with different functional structures. In order to provide insights into why results differ between models, this article proposes a diagnostic scheme that can be applied to a wide range of models. Diagnostics can uncover patterns of model behavior and indicate how results differ between model types. Such insights are informative since model behavior can have a significant impact on projections of climate change mitigation costs and other policy-relevant information. The authors propose diagnostic indicators to characterize model responses to carbon price signals and test these in a diagnostic study of 11 global models. Indicators describe the magnitude of emission abatement and the associated costs relative to a harmonized baseline, the relative changes in carbon intensity and energy intensity, and the extent of transformation in the energy system. This study shows a correlation among indicators suggesting that models can be classified into groups based on common patterns of behavior in response to carbon pricing. Such a classification can help to explain variations among policy-relevant model results

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