Projecting Climate-Driven Changes in Extreme Ozone Pollution under Natural Variability and Uncertain Climate Sensitivity

Climate change is projected to adversely affect ground-level ozone over many populated regions, with potentially larger impacts at the extreme ends of the concentration distribution. Intensified extreme ozone pollution represents a risk to human health, but projecting these changes is complicated by internal variability in climate-chemistry simulations. In addition, modeling evidence suggests that the spread of future ozone concentration distributions may further increase under higher climate sensitivity. Here, we leverage a climate-chemistry modeling ensemble with multiple initial condition and climate sensitivity ensemble members to explore the connections among internal variability, climate sensitivity, and ozone extremes. The ensemble simulations project the climate penalty on ozone over the Unites States. To assess extremes, we first bias correct historical predictions based on observed ozone concentrations. We then apply this bias correction to projections of climate impacts on ozone under various greenhouse gas emissions pathways and multiple climate sensitivities at mid- and end-century. Our results show an increased risk for extreme ozone on top of the mean climate penalty under future climate change. We further show that internal variability can lead to over- or under-prediction of extremes if not accounted for, and that climate sensitivity exerts an important control on the future extreme climate penalty. To robustly project future extremes, adequately accounting for these sources of climate-related uncertainty in projections of air quality under climate change is needed.