PNNL

Abstract

State of the art impact models characterizing aspects of the interaction between the human and Earth systems require decade-long time series of relatively high frequency, spatially resolved and often multiple variables representing climatic impact-drivers. Most commonly these are derived from Earth System Model (ESM) output, according to a standard, limited set of future scenarios, the latest being the SSP-RCPs run under CMIP6-ScenarioMIP [@Eyringetal2016;@ONeilletal2016]. Often, however, impact modeling seeks to explore new scenarios, and/or needs a larger set of initial condition ensemble members than are typically available to quantify the effects of ESM internal variability. In addition, the recognition that the human and Earth systems are fundamentally intertwined, and may feature potentially significant feedback loops, is making integrated, simultaneous modeling of the coupled human-Earth system increasingly necessary, if computationally challenging [@thornton2017biospheric]. For the dual needs of the creation of new scenario realizations and the simplified representation of ESM behavior in a coupled human-Earth system modeling framework, climate model output emulators can be the answer. We proposed a new, comprehensive approach to such emulation, STITCHES [@tebaldi2022stitches]. The corresponding `stitches` Python package uses existing archives of ESMs’ scenario experiments to construct new scenarios, or enrich existing initial condition ensembles. Its output has the same characteristics of the ESM output emulated: multivariate (spanning potentially all variables that the ESM has saved), spatially resolved (down to the native grid of the ESM), and as high frequency as the original output has been saved at.