Stratospheric ozone and associated climate impacts in the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) simulations are evaluated in the recent past (1980–2000), and examined in the long-term (1850–2100) using the Representative Concentration Pathways (RCPs) low- and high-emission scenarios (RCP2.6 and RCP8.5, respectively) for the period 2000–2100. ACCMIP multi-model mean total column ozone (TCO) trends compare favourably, within uncertainty estimates, against observations. Particularly good agreement is seen in the Antarctic austral spring (−11.9 % dec−1 compared to observed ∼ −13.9 ± 10.4 % dec−1), although larger deviations are found in the Arctic's boreal spring (−2.1 % dec−1 compared to observed ∼ −5.3 ± 3.3 % dec−1). The simulated ozone hole has cooled the lower stratosphere during austral spring in the last few decades (−2.2 K dec−1). This cooling results in Southern Hemisphere summertime tropospheric circulation changes captured by an increase in the Southern Annular Mode (SAM) index (1.3 hPa dec−1). In the future, the interplay between the ozone hole recovery and greenhouse gases (GHGs) concentrations may result in the SAM index returning to pre-ozone hole levels or even with a more positive phase from around the second half of the century (−0.4 and 0.3 hPa dec−1 for the RCP2.6 and RCP8.5, respectively). By 2100, stratospheric ozone sensitivity to GHG concentrations is greatest in the Arctic and Northern Hemisphere midlatitudes (37.7 and 16.1 DU difference between the RCP2.6 and RCP8.5, respectively), and smallest over the tropics and Antarctica continent (2.5 and 8.1 DU respectively). Future TCO changes in the tropics are mainly determined by the upper stratospheric ozone sensitivity to GHG concentrations, due to a large compensation between tropospheric and lower stratospheric column ozone changes in the two RCP scenarios. These results demonstrate how changes in stratospheric ozone are tightly linked to climate and show the benefit of including the processes interactively in climate models.