Increased Importance of Earth System Model Emulators in the IPCCs Sixth Assessment Report Working Group 1
Abstract
Earth system emulators, also called reduced complexity climate models, are used more extensively in the Working Group 1 (WG1) contribution to the IPCCs Sixth Assessment Report (AR6) than in previous report cycles. This is in spite of the increasing sophistication of full-complexity Earth System Models. While Earth System models remain the best tools for the detailed representation of atmospheric, oceanic and biogeochemical processes, simple models are proving increasingly useful in climate science. Emulators can be calibrated to reproduce large-scale behaviours of CMIP6 models and assessed ranges of various climate system characteristics (like ECS, TCR, TCRE, airborne fraction of CO2 or future warming under certain scenarios). These calibrated emulators can then also be constrained to observable quantities like the historical surface temperature and ocean heat uptake. Ensembles can then be run probabilistically to obtain best estimates and likely ranges of warming under various emissions scenarios that are consistent with observations. Emulators are used in AR6 WG1 to provide CO2-equivalent metrics, determine future expected warming from SSP emissions scenarios, generate radiative forcing time series, estimate committed warming, derive sea-level rise projections, and attribute present-day and future warming to numerous anthropogenic and natural forcing components, to name a few examples. For AR6 WG1 an extensive calibration and validation exercise with four emulators (MAGICC7.5.1, FaIR1.6.2, OSCAR3.1.1 and CICERO-SCM) was performed with the aim of simultaneously achieving multiple assessed constraints. The calibrated emulators are then passed on to IPCC Working Group 3 to assess the emission pathways derived from integrated assessment models, work that would be computationally infeasible in Earth System models. This link ensures that these cross-Working Group aspects of the IPCCs Sixth Assessment Report are more integrated and self-consistent than ever before.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2021
- Bibcode:
- 2021AGUFMGC15C0704S