Progress developing the PRIME framework and using it in FASTMIP.

Regionalized climate risk assessments are crucial for understanding impacts on ecosystems and society, and to allow planning for climate change. While existing Earth System Models (ESMs) provide a framework for such assessments, they often lack the critical processes simulated by dedicated Impact Models. However, Impact Models are often driven by output data from ESMs, which may need bias-correcting, and therefore, there is a significant time lag in the modelling chain. Furthermore, reliance on existing ESM data for Impact Models limits our analysis to the handful of scenarios (i.e. SSPs) and models that ran them (an “ensemble of opportunity” bias), while there is a need for multiple model simulations to try to capture uncertainty in future climate.

Over the last few years, we have developed the PRIME framework for producing scenarios of regional impacts for user-prescribed future emissions scenarios. PRIME combines global mean temperature and CO2 concentrations from the emissions driven FaIR simple climate model, as used in the IPCC Sixth Assessment Report, with patterns of climate change from CMIP6 (Coupled Model Intercomparison Project Phase 6) Earth System models to drive the JULES land surface model. This modelling framework projects regional changes to the land surface and carbon cycle. We will describe PRIME for the benefit of a new audience and demonstrate how this powerful and flexible approach answers questions on regional impacts using a range of scenarios. We will also talk about the FASTMIP modelling activity led by ETH Zurich with strong contributions of the UK metoffice and PNNL, which aims to provide a coordinated experiment of regional emulators for a wide range of scenarios. We will discuss how these systems tend to be flexible and fast to run and therefore represent a wealth of future development opportunities. In particular we will focus on how PRIME and similar frameworks will enable rapid probabilistic assessment of novel scenarios emissions scenarios that have not yet been run in ESMs thereby providing a useful insight and the capability to quantify societally-relevant climate impacts.