On the Use of Large Ensembles for Studying Climate and Air Quality

Episodes of poor air quality can be extremely detrimental to human health and economic growth. These episodes occur when the emission of pollutants combines with stagnant meteorology to allow the accumulation of those pollutants in the near-surface atmosphere. A wide array of research over the past two decades has found that these meteorological conditions may become more frequent or intense as a result of anthropogenic climate change. However, despite both its human costs and potential changes under forcing, stagnant meteorology is highly sensitive to internal climate variability. Diagnosing the influence of internal variability on poor air quality in a changing climate is therefore critical to constrain forecasts of the “climate penalty” on future air quality. Here we synthesize recent research to highlight the value of initial-condition ensembles in studying the climate change-air quality connection, including “ingredients-based” studies of stagnant meteorology in such ensembles without active chemistry, as well as ensembles that actively simulate atmospheric chemistry and explicitly forecast pollutant concentrations. Together, these studies make clear that internal variability can play a significant role in influencing pollutant trajectories in the 21^st century, in some cases as much as the influence of anthropogenic climate change. Finally, we discuss promising avenues for the future use of large ensembles in air quality research, in particular the possible use of these ensembles to quantify the air quality co-benefits of climate policy.