Journal Article
Geoscientific Model Development, vol. 12, iss. 4, pp. 1477-1489, 2019
Authors
Robert Link, Abigail Snyder, Cary Lynch, Corinne Hartin, Ben Kravitz, Ben Bond-Lamberty
Abstract
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 the Earth
system model (ESM) temperature output, based on the construction of a deterministic
model for the mean response to global temperature. The residuals between the
mean response and the ESM output 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 applications that require them. 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 be useful in the study of climate variability
and its contribution to uncertainties in the interactions between human and
Earth systems.
