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The IPCC's scientific assessment of the timing of net-zero emissions and 2030 emission reduction targets consistent with limiting warming to 1.5°C or 2°C rests on large scenario databases. Updates to this assessment, such as between the IPCC's Special Report on Global Warming of 1.5°C (SR1.5) of warming and the Sixth Assessment Report (AR6), are the result of intertwined, sometimes opaque, factors. Here we isolate one factor: the Earth System Model emulators used to estimate the global warming implications of scenarios. We show that warming projections using AR6-calibrated emulators are consistent, to within around 0.1°C, with projections made by the emulators used in SR1.5. The consistency is due to two almost compensating changes: the increase in assessed historical warming between SR1.5 (based on AR5) and AR6, and a reduction in projected warming due to improved agreement between the emulators' response to emissions and the assessment to which it is calibrated.

Accepted manuscript version. VoR with minor editorial changes available at https://doi.org/10.1029/2022GL098808. Climate model emulators are widely used to generate temperature projections for climate scenarios, including in the recent Intergovernmental Panel on Climate Change Sixth Assessment Report. Here we evaluate the performance of a two-layer energy balance model in emulating historical and future temperature projections from Coupled Model Intercomparison Project Phase 6 models. We find that emulation errors can be large (>0.5°C for SSP2-4.5) and differ markedly between climate models, forcing scenarios and time periods. Errors arise in emulating the near-surface temperature response to both greenhouse gas and aerosol forcing; in some periods the errors due to these forcings oppose one another, giving the spurious impression of better emulator performance. Climate feedbacks are assumed constant in the emulator, introducing time-varying or state dependent feedbacks may reduce prediction errors. Close emulations can be produced for a given period but, crucially, this does not guarantee reliable emulations of other scenarios and periods. Therefore, rigorous out-of-sample evaluation is necessary to characterize emulator performance.