Abstract

Computer simulators often contain options to include extensions, leading to different versions of a particular simulator with slightly different input spaces. We develop hierarchical emulation, a method for emulating such simulators and for learning about the differences between versions of a simulator. In an example using data from an ocean carbon cycle model, hierarchical emulators outperformed standard emulators both in their predictive accuracy and their coherence with the emulation model. The hierarchical emulator performed particularly well when a comparatively small amount of training data came from the extended simulator. This benefit of hierarchical emulation is advantageous when the extended simulator is costly to run compared to the simpler version.

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