RIME-X: Emulating regional climate impact distributions using simple climate models and impact models

Simple climate models (SCMs) are widely used to simulate global mean temperature (GMT) trajectories across a wide range of emission scenarios by combining simplified representations of the carbon cycle and other Earth system processes. These simulations depend on uncertain Earth system parameters, and ensembles of SCM simulations are created by exploring plausible parameter sets, resulting in scenario-specific distributions of GMT for all considered years.

In this work, we introduce RIME-X (Rapid Impact Model Emulator Extended), a novel emulator approach that extends SCM outputs by translating GMT distributions into distributions of regionally aggregated climate or climate impact indicators. RIME-X uses historical and scenario simulations from climate and impact modeling intercomparison projects, such as CMIP and ISIMIP, to record relationships between global warming levels and indicators. By extracting distributions of indicators at specific global warming levels from those records and combining them with the GMT distributions from SCM ensembles, RIME-X produces scenario-dependent distributions of these indicators over time.

This framework integrates multiple sources of uncertainty along the modeling chain, including model uncertainty (from diverse climate or impact model records), Earth system parameter uncertainty (from SCM ensembles), and internal variability, depending on the indicator’s temporal resolution.

RIME-X is broadly applicable to any indicator whose distribution is predominantly influenced by the global warming level, offering a versatile and efficient tool for assessing climate impacts across a variety of scenarios. We demonstrate the capabilities of RIME-X by emulating a diverse set of regionally aggregated climate and climate impact variables available from ISIMIP3 and beyond for the NGFS (Network for Greening the Financial System) climate scenarios.