PRIME: Probabilistic Regional Impacts from Model patterns and Emissions 

We present PRIME, a framework for analysis of scenarios of regional impacts for user-prescribed future emissions. 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 Earth System models to drive the JULES land model. This simulation system projects regional changes to the land surface and carbon cycle. We evaluate PRIME by running it with Shared Socioeconomic Pathways and illustrate its robustness by comparing these known scenarios with ESMs that have also been run for the same scenarios. PRIME correctly represents the climate response for these known scenarios, which gives us confidence that PRIME will be useful for rapidly providing probabilistic spatially resolved information for novel climate scenarios; substantially reducing the time between the scenarios being released and being used in impact assessments. Therefore PRIME fulfills an important need, providing the capability to include the most recent models, science and scenarios to run ensemble simulations on multi-centennial timescales and include analysis of many variables that are relevant and important for impact assessments.