Combining emulators and demographics: Building a flexible toolkit for lifetime exposure assessments

Across the globe, today’s young generations will be more frequently exposed to climate extremes over their lifetime than earlier generations. Previous work has established this finding by combining simulations of historical and projected trends in climate extremes together with data on past and future demographic changes (Thiery et al. 2021, Grant et al. 2025). However, it has so far focused on a limited set of climate extreme indicators, using climate (impact) simulations from ISIMIP2 and demographics datasets that are now outdated, and did not fully assess uncertainty across the climate impact modelling chain. 

 

We now build on this existing lifetime exposure framework and combine it with a chain of emulators constituted of a Simple Climate Model (SCM) and the Rapid Impact Model Emulator Extended (RIME-X, Schwind et al., submitted). RIME-X can translate the GMT distributions generated by an SCM for a given emission scenario into spatially explicit distributions of climate or climate impact indicators. It has already been used to produce projections for 40+ indicators derived from ISIMIP3 and other climate model simulations, and this list can be extended to further indicators whose evolution predominantly depends on the level of global warming and for which historical and future simulations are available.   

 

We also update the lifetime exposure framework to consider more recent demographic data, and package it into a GitHub repository called dem4cli (short for ‘demographics for climate’) that will be made publicly available. We use spatially explicit population reconstructions and projections from the COMPASS project, and national-level life expectancy and cohort size estimates and projections from UNWPP2024.  

 

This work delivers more robust calculations of lifetime exposure to changes in extremes or climate impacts, by leveraging the ability of the SCM-RIME-X emulator chain to represent both their forced response to emissions as well as the combined uncertainty arising from the GMT response to emissions, the local climate response to global warming, and interannual variability, in combination with updated demographic data. This new framework is designed to generate such policy-relevant information in a more flexible and systematic manner, as it can in theory be applied to any available emission or GMT trajectories, and extended to a broad range of climate hazards.

Thiery, W. et al. Intergenerational inequities in exposure to climate extremes. Science 374, 158–160 (2021) 

Grant, L., Vanderkelen, I., Gudmundsson, L. et al. Global emergence of unprecedented lifetime exposure to climate extremes. Nature 641, 374–379 (2025) 

Schwind et al. RIME-X v1.0: Combining Simple Climate Models, Earth System Models, and Climate Impact Models into a Unified Statistical Emulator for Regional Climate Indicators. Geoscientific Model Development (submitted)