Climate change can impact air quality by altering atmospheric conditions that determine pollutant concentrations. Over large regions of the U.S., projected changes in climate are expected to favor formation of ground-level ozone and aggravate associated health effects. However, modeling studies exploring air quality-climate interactions have often overlooked the role of natural variability, a major source of uncertainty in projections. Here we use the largest ensemble simulation of climate-induced changes in air quality generated to date to assess the influence of natural variability on estimates of climate change impacts on U.S. ozone. We find that internal variability can significantly alter the robustness of projections of the future climate’s effect on ozone pollution. In this study, we find that a 15-year minimum is required to identify to identify a distinct anthropogenic-forced signal. Therefore, we suggest that studies assessing air quality impacts use multidecadal simulations or initial condition ensembles. With natural variability, impacts attributable to climate may be difficult to discern before midcentury or under stabilization scenarios.