Global emissions pathways under different socioeconomic scenarios for use in CMIP6: a dataset of harmonized emissions trajectories through the end of the century

TLDR

The study presents nine future emissions scenarios for anthropogenic sources as a key deliverable of the ScenarioMIP experiment in CMIP6. The authors generate harmonized, downscaled integrated assessment model outputs for 14 species and 13 sectors, producing scenarios that span a wide range of radiative forcing to yield statistically significant regional temperature differences. The scenarios cover radiative forcing from 1.9 to 8.5 W m⁻², enabling analysis of sub‑2 °C to nearly 5 °C warming, and supply global, regional, and gridded emissions datasets for CMIP6. Abstract.

Abstract

Abstract. We present a suite of nine scenarios of future emissions trajectories of anthropogenic sources, a key deliverable of the ScenarioMIP experiment within CMIP6. Integrated assessment model results for 14 different emissions species and 13 emissions sectors are provided for each scenario with consistent transitions from the historical data used in CMIP6 to future trajectories using automated harmonization before being downscaled to provide higher emissions source spatial detail. We find that the scenarios span a wide range of end-of-century radiative forcing values, thus making this set of scenarios ideal for exploring a variety of warming pathways. The set of scenarios is bounded on the low end by a 1.9 W m−2 scenario, ideal for analyzing a world with end-of-century temperatures well below 2 ∘C, and on the high end by a 8.5 W m−2 scenario, resulting in an increase in warming of nearly 5 ∘C over pre-industrial levels. Between these two extremes, scenarios are provided such that differences between forcing outcomes provide statistically significant regional temperature outcomes to maximize their usefulness for downstream experiments within CMIP6. A wide range of scenario data products are provided for the CMIP6 scientific community including global, regional, and gridded emissions datasets.