STITCHES: creating new scenarios of climate model output by stitching together pieces of existing simulations
Authors: Tebaldi Claudia , Snyder Abigail , Dorheim Kalyn 
Published: November 2022

Abstract. Climate model output emulation has long been attempted to support impact research, mainly to fill in gaps in the scenario space. Given the
computational cost of running coupled earth system models (ESMs), which are usually the domain of supercomputers and require on the order of days to weeks to complete a century-long simulation, only a handful of different scenarios are usually chosen to externally force ESM simulations. An effective
emulator, able to run on standard computers in times of the order of minutes rather than days could therefore be used to derive climate
information under scenarios that were not run by ESMs. Lately, the necessity of accounting for internal variability has also made the availability
of initial-condition ensembles, under a specific scenario, important, further increasing the computational demand. At least so far, emulators have
been limited to simplified ESM-like output, either seasonal, annual, or decadal averages of basic quantities, like temperature and precipitation,
often emulated independently of one another. With this work, we propose a more comprehensive solution to ESM output emulation. Our emulator,
STITCHES, uses existing archives of earth system models' (ESMs) scenario experiments to construct ESM-like output under new scenarios or enrich
existing initial-condition ensembles, which is what other emulators also aim to do. Importantly, however, STITCHES' output has the same
characteristics of the ESM output it sets out to emulate: multivariate, spatially resolved, and high frequency, representing both the forced
component and the internal variability around it. STITCHES extends the idea of time sampling – according to which climate outcomes are stratified by
the global warming level at which they manifest themselves, irrespective of the scenario and time at which they occur – to the construction of a
continuous history of ESM-like output over the whole 21st century, consistent with a 21st-century trajectory of global surface air temperature
(GSAT) derived from the scenario that has been chosen as the target of the emulation. STITCHES does so by first splitting the target GSAT trajectory
into decade-long windows, then matching each window in turn to a decade-long window within an existing model simulation from the available scenario
runs according to its proximity to the target in absolute size of the temperature anomaly and its rate of change. A look-up table is therefore
created of a sequence of existing experiment–time-window combinations that, when stitched together, create a GSAT trajectory “similar” to the
target. Importantly, we can then stitch together much more than GSAT from these windows, i.e., any output that the ESM has saved for these existing experiment–time-window combinations, at any frequency and spatial scale available in its archive. We show that the stitching does not introduce artifacts in
the great majority of cases (we look at temperature and precipitation at monthly frequency and on the native grid of the ESM and at an index of
ENSO activity, the Southern Oscillation Index). This is true even if the criteria for the identification of the decades to be stitched together are
chosen to work for a smoothed time series of annual GSAT, a result we expect given the larger amount of noise affecting most other variables at
finer spatial scales and higher frequencies, which therefore are more “forgiving” of the stitching. We successfully test the method's performance
over many ESMs and scenarios. Only a few exceptions surface, but these less-than-optimal outcomes are always associated with a scarcity of the
archived simulations from which we can gather the decade-long windows that form the building blocks of the emulated time series. In the great
majority of cases, STITCHES' performance is satisfactory according to metrics that reward consistency in trends, interannual and inter-ensemble
variance, and autocorrelation structure of the time series stitched together. The method therefore can be used to create ESM-like output according
to new scenarios, on the basis of a trajectory of GSAT produced according to that scenario, which could be easily obtained by a simple climate
model. It can also be used to increase the size of existing initial-condition ensembles. There are aspects of our emulator that will immediately
disqualify it for specific applications, like when climate information is needed whose characteristics result from accumulated quantities over
windows of times longer than those used as pieces by STITCHES, droughts longer than a decade for example. But for many applications, we argue that a
stitched product can satisfy the climate information needs of impact researchers. STITCHES cannot emulate ESM output from scenarios that result in
GSAT trajectories outside of the envelope available in the archive, nor can it emulate trajectories with shapes different from existing ones
(overshoots with negative derivative, for example). Therefore, the size and characteristics of the available archives of ESM output are the
principal limitations for STITCHES' deployment. Thus, we argue for the possibility of designing scenario experiments within, for example, the next
phase of the Coupled Model Intercomparison Project according to new principles, relieved of the need to produce a number of similar trajectories
that vary only in radiative forcing strength but more strategically covering the space of temperature anomalies and rates of change.