Computationally Efficient Emulators for Earth System Models

Abstract. Earth System Models (ESMs) are the gold standard for producing future projections of climate change, but running them is difficult and costly, and thus researchers are generally limited to a small selection of scenarios. This paper presents a technique for detailed emulation of Earth System Model (ESM) temperature output, based on constructing a deterministic model for the mean response to global temperature. The residuals between the mean response and the observed temperature fields are used to construct variability fields that are added to the mean response to produce the final product. The method produces grid-level output with spatially and temporally coherent variability. Output fields include random components, so the system may be run as many times as necessary to produce large ensembles of fields for uncertainty studies and similar uses. We describe the method, show example outputs, and present statistical verification that it reproduces the ESM properties it is intended to capture. This method, available as an open-source R package, should have utility in the study of climate uncertainty and variability, extreme events, and climate change mitigation.