STITCHES: creating new scenarios of climate model output by stitching together pieces of existing simulations

Abstract

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.

Uncertainty constraints on economic impact assessments of climate change simulated by an impact emulator

“…Note that the original simulation (Takakura et al 2019) did not fully incorporate, for example, catastrophic impacts, feedback effects, and nuanced socioeconomic assumptions in the scenarios whereas some autonomic adaptations were modelled in the framework. Although the original impact simulation took into account impacts of climate extremes in the original ESMs' simulations, but uncertainties of climate extremes (Quilcaille et al 2022, Tebaldi et al 2022 were not sufficiently considered. Therefore, even if the emulator can reproduce the original economic simulation results, it does not necessarily mean the emulated economic impact is accurate.…”

A perspective on the next generation of Earth system model scenarios: towards representative emission pathways (REPs)

“…A Beusch et al, 2020;Beusch et al, 2022b;Tebaldi et al, 2022) can provide for very promising applications to explore a range of different futures in rapid fashion. However, such approaches, often based on the idea of pattern scaling of global-mean temperature, can only be used for emulation of ESM outputs, and without adequate ESM training pathways will not be able to capture key features of peak-and-decline or stabilisation pathways.…”

Rapidly evolving aerosol emissions are a dangerous omission from near-term climate risk assessments

“…Here, the required functionality is an ability to represent diverse, yet realistic, evolutions of emissions of scattering and absorbing aerosols in different regions, beyond the combinations existing in widely studied pathways such as the main SSP realizations, in combination with a prescribed level of GHG-induced warming. The emulator should be able to rapidly produce a statistical sample of regional weather conditions, taking into account both local and remote effects of the resulting combined GHG and aerosol forcing [102][103][104]. The output of such emulators could be valuable in, for example, improving aerosol-specific statistical downscaling methodologies that account for the time-varying and pattern-dependent effects of aerosols and a range of other impact applications.…”