Abstract. Despite offsetting global mean surface temperature, various studies demonstrated that Stratospheric Aerosol Injection (SAI) could influence the recovery of stratospheric ozone and have important impacts on stratospheric and tropospheric circulation, thereby potentially playing an important role in modulating regional and seasonal climate variability. However, so far most of the assessments of such an approach have come from climate model simulations in which SO2 is injected only in a single location or a set of locations. Here we use CESM2-WACCM6 SAI simulations under a comprehensive set of SAI strategies achieving the same global mean surface temperature with different locations and/or timing of injections: an equatorial injection, an annual injection of equal amounts of SO2 at 15° N and 15° S, an annual injection of equal amounts of SO2 at 30° N and 30° S, and a polar strategy injecting SO2 at 60° N and 60° S only in spring in each hemisphere. We demonstrate that despite achieving the same global mean surface temperature, the different strategies result in contrastingly different magnitudes of the aerosol-induced lower stratospheric warming, stratospheric moistening, strengthening of stratospheric polar jets in both hemispheres and changes in the speed of the residual circulation. In conjunction with the differences in direct radiative impacts at the surface, these drive different impacts on the extratropical modes of variability (Northern and Southern Annular Mode), including important consequences on the northern winter surface climate, as well as on the intensity of tropical tropospheric Walker and Hadley Circulations, which drive tropical precipitation patterns. Finally, we demonstrate that the choice of injection strategy also plays a first-order role in the future evolution of stratospheric ozone under SAI throughout the globe. Overall, our results contribute to an increased understanding of the fine interplay of various radiative, dynamical and chemical processes driving the atmospheric response to SAI, as well as lay the ground for designing an optimal SAI strategy that could form a basis of future multi-model intercomparisons.;
