The Influence of Internal Climate Variability on Projections of Synoptically Driven Beijing Haze

Abstract

Beijing has suffered a series of poor air quality (“haze”) episodes which have damaged human health and economic growth. Beijing's haze is generally driven by pollutant-trapping meteorological conditions, but climate model projections differ on how these conditions will evolve under forcing. Such differences are driven in part by (1) disagreements over which meteorological conditions matter most and (2) an undersampling of internal variability in projections. To resolve these differences, we show that Beijing haze is associated with anticyclonic circulation, thereby linking multiple meteorological ingredients to a single process well simulated by models. We use this to inform our assessment of future haze risks in both a multimodel ensemble and a single-model large ensemble, partitioning model uncertainty and internal variability. We estimate that forcing increases haze-favorable conditions, but internal variability significantly affects these projections, emphasizing the importance of fully sampling sources of uncertainty to ensure accurate projections of haze risks.