Stratospheric aerosol injection (SAI) is being discussed as a possible approach to reduce future global warming in addition to emission cuts, and various scenarios and Earth system model (ESM) experiments have been developed to explore its effectiveness and risks. However, given the complicated geopolitical, economic, and strategic considerations among countries, global cooperation in SAI deployment will be challenging. Alternatively, unilateral SAI deployment has been highlighted as an important research topic but is still less explored in scenario design and ESM studies. Inspired by the game theory model introduced by Bell and Keys (2023) and their newly developed framework of identifying geopolitically plausible SAI initiator(s), this paper builds a framework for integrating unilateral SAI scenario design, geopolitical game theory, ESM simulation, and climate analyses into one decision loop. Using the decision loop, we design and simulate a geopolitically plausible scenario of the initiation of unilateral SAI using CESM, and explore two independent plausible unilateral SAI reaction scenarios following the climate storylines under the initiator scenario. Our work demonstrates an approach to explore the complex feedback loop between unilateral SAI deployment scenarios and the simulation of the subsequent climate storylines.

Climate and Earth system models are important tools to assess the benefits and risks of stratospheric aerosol injection (SAI) relative to those associated with anthropogenic climate change. A “controller” algorithm has been used to specify injection amounts of sulfur dioxide in SAI experiments performed with the Community Earth System Model (CESM). The experiments are designed to maintain specific temperature targets, such as limiting global mean temperature to 1.5ºC above the pre-industrial level. However, the influence of natural climate variability on the injection amount has not been extensively documented. Our study reveals that more than 70% of the year-to-year variation in the total injection amount (excluding the long-term trend) in CESM SAI experiments is attributed to the El Niño-Southern Oscillation (ENSO). A simplified statistical model further suggests that the intrinsic, lagged response of the controller to the climate can increase the variance of global mean temperature in the model simulations.