The new emulator demonstrates a method to assess climate impacts by preserving natural variability in temperatures from models, suggesting greater efficiency in simulations.
Extreme events – which often include contributions from both anthropogenic forcing and internal (natural) climate variability – are expected to be responsible for a significant portion of fatalities and economic damages caused by climate change. Large ensembles of Earth System Model (ESM) simulations have been used to quantify the influence of natural variability in climate change impact projections. However, such ensembles have high computational costs. Future climate scenarios can be simulated at much lower cost using statistical climate emulators that mimic the output of more complex ESMs. Most climate emulators do not include internal variability, which can limit their utility for climate impacts assessment. We present a new method for emulating spatially resolved natural temperature variability using Vector Auto-Regression models and empirical orthogonal function analysis of temperature data from an existing ESM large ensemble. The emulator preserves statistical, spatial, and temporal characteristics of temperature variability in ESMs.
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Saenger et al. (2025) studied this question.
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