- 1International Institute for Applied Systems Analysis (IIASA), Energy, Climate, and Environment, Laxenburg, Austria
- 2Joint Global Change Research Institute, Pacific Northwest National Laboratory, College Park, MD, USA
- 3Centre for Environmental Policy, Imperial College London, London, United Kingdom
- 4Climate Resource, Melbourne, Australia
We present a harmonized dataset of globally comprehensive up-to-date emissions trajectories and their emulated climate outcomes, developed to support the ScenarioMIP experiment within CMIP7. Drawing from a set of around 90 candidate scenarios, a small subset of 7 marker scenarios is selected to span a wide range of emissions and climate outcomes to be simulated by earth system models (ESMs) in the AR7 Fast-Track.
These scenarios are calculated using seven Integrated Assessment Models (AIM, COFFEE, GCAM, IMAGE, MESSAGE-GLOBIOM-GAINS, REMIND-MAgPIE, and WITCH) and are based on newly updated socioeconomic pathways (SSPs).
In CMIP6, ESM projections have mainly been driven by changes in atmospheric concentrations. CMIP7 prioritises emissions-driven climate projections, meaning the harmonization and spatial distribution of emissions are of increased importance.
For CMIP7, we combine multiple strands of previous work into one workflow that includes: (1) compiling a common historical emissions dataset, for each IAM region, and all climatically relevant emissions species, (2) harmonizing sectoral emissions pathways to 2023 emissions, (3) generating harmonized gridded emissions data, (4) running updated simple climate models to emulate the range of possible climate outcomes of the emissions pathways.
In this presentation, we present: the workflow, the new CMIP7 scenario set, and how it compares to the CMIP6 scenarios.
The data presented are meant support earth system modelling and impact assessment across the CMIP7 Assessment Fast-Track and beyond, including model intercomparison projects such as ISIMIP, AerChemMIP, and CDRMIP, and in doing so, support upcoming IPCC assessments.
References
- Van Vuuren, D., O’Neill, B., Tebaldi, C., Chini, L., Friedlingstein, P., Hasegawa, T., Riahi, K., Sanderson, B., Govindasamy, B., Bauer, N., Eyring, V., Fall, C., Frieler, K., Gidden, M., Gohar, L., Jones, A., King, A., Knutti, R., Kriegler, E., Lawrence, P., Lennard, C., Lowe, J., Mathison, C., Mehmood, S., Prado, L., Zhang, Q., Rose, S., Ruane, A., Schleussner, C.-F., Seferian, R., Sillmann, J., Smith, C., Sörensson, A., Panickal, S., Tachiiri, K., Vaughan, N., Vishwanathan, S., Yokohata, T., Ziehn, T., 2025. The Scenario Model Intercomparison Project for CMIP7 (ScenarioMIP-CMIP7). EGUsphere 1–38. https://doi.org/10.5194/egusphere-2024-3765
How to cite: Kikstra, J., Högner, A., Zecchetto, M., Ahsan, H., Gidden, M., Riahi, K., Smith, C., Smith, S., and Nicholls, Z.: CMIP7-ScenarioMIP emissions set and probabilistic climate outcomes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14856, https://doi.org/10.5194/egusphere-egu26-14856, 2026.