Using regional ESM emulators to assess climate feedbacks to IAMs: The "FASTMIP" experimental protocol

Changes in regional climate extremes belong to the most impactful consequences of the human-induced climate crisis (Seneviratne et al. 2021). However, they are generally not or only partially considered in Integrated Assessment Models (IAMs) which are used to derive emissions scenarios underlying climate change projections. This has important implications for the assessment of plausible emissions pathways and associated policy decisions, in particular in the context of reports of the Intergovernmental Panel on Climate Change (IPCC). Recently, new regional Earth System Model (ESM) emulators such as the Modular Earth System Model Emulator with spatially Resolved output (MESMER; Beusch et al. 2020, 2022; Quilcaille et al. 2022) and STITCHES (Tebaldi et al. 2022), have been developed to allow the emulation of regional ESM features when driven with output from global climate emulators. The resulting emulator chains (e.g. Beusch et al. 2022) can derive plausible geographically-resolved trajectories for mean and extreme climate variables associated with given IAM emission pathways. This fast computation of regional projections could help assess and increase the realism of emissions pathways from IAMs, e.g., with respect to afforestation, the implementation of bioenergy with carbon capture and storage (BECCS), or projected changes in agriculture and population. This contribution presents a new experimental protocol (“FASTMIP”) building on global and regional ESM emulators and allowing the fast derivation of geographically-resolved climate change projections for new emissions scenarios, in coordination with other existing tools (e.g. Nicholls et al. 2020, Kikstra et al. 2022). The proposed FASTMIP experiment could help inform the choice of emission scenarios within the 7th phase of the Coupled Model Intercomparison Project (CMIP7), and provide new insights towards to the integration of climate feedbacks in IAMs. First analyses showing the potential of the FASTMIP experiment for constraining IAM projections will be presented.   References: Beusch, L., L. Gudmundsson, S.I. Seneviratne, 2020, Earth System Dynamics, 11, 139-​159 Beusch, L., Z. Nicholls, L. Gudmundsson, M. Hauser, M. Meinshausen, and S.I. Seneviratne, 2022, Geoscientific Model Development, 15 (5), 2085-2103, doi: 10.5194/gmd-15-2085-2022. Kikstra, J.S., et al., 2022, Geosci. Model Dev., 15, 9075–9109. Nicholls, Z.R.J., et al., 2020, Geosci. Model Dev., 13, 5175–5190. Quilcaille, Y., L. Gudmundsson, L. Beusch, M. Hauser, and S.I. Seneviratne, 2022, Geophysical Research Letters, 49, e2022GL099012. Seneviratne, S.I., X. Zhang, M. Adnan, W. Badi, C. Dereczynski, A. Di Luca, S. Ghosh, I. Iskandar, J. Kossin, S. Lewis, F. Otto, I. Pinto, M. Satoh, S.M. Vicente-Serrano, M. Wehner, and B. Zhou, 2021: Chapter 11: Weather and Climate Extreme Events in a Changing Climate. In: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V. et al. (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 1513–1766, doi:10.1017/9781009157896.013. (https://www.ipcc.ch/report/ar6/wg1/downloads/report/IPCC_AR6_WGI_Chapter11.pdf) Tebaldi, C., A. Snyder, and K. Dorheim, 2022, Earth System Dynamics, 13, 1557–1609.