Observed and CMIP6-model-simulated organic aerosol response to drought in the contiguous United States during summertime

Abstract

Abstract. Drought events have been linked with the enhancements of organic aerosols (OAs), but the mechanisms have not been comprehensively understood. This study investigates the relationships between the monthly standardized precipitation–evapotranspiration index (SPEI) and surface OA in the contiguous United States (CONUS) during the summertime from 1998 to 2018. OA under severe drought conditions shows a significant increase in mass concentrations across most of the CONUS relative to non-drought periods, with the Pacific Northwest (PNW) and Southeast United States (SEUS) experiencing the highest average enhancement of 1.79 µg m−3 (112 %) and 0.92 µg m−3 (33 %), respectively. In the SEUS, a linear regression approach between OA and sulfate was used to estimate the epoxydiol-derived secondary organic aerosol (IEPOX SOA), which is the primary driver of the OA enhancements under droughts due to the simultaneous increase in emissions of biogenic volatile organic compounds (VOCs; such as isoprene and monoterpene) and sulfate. The rise in sulfate is mainly caused by the reduced wet deposition because of the up to 62 % lower precipitation amount. In the PNW, OA enhancements are closely linked to intensified wildfire emissions, which raise OA mass concentrations to be 4–8 times higher relative to non-fire conditions. All 10 Earth system models participating in the sixth phase of the Coupled Model Intercomparison Project (CMIP6) can capture the slopes between SPEI and OA in the PNW, with CESM2-WACCM and GFDL-ESM4 performing the best and worst in predicting the OA enhancement under severe droughts. However, all models significantly underestimate the OA increase in the SEUS, with Nor-ESM2-LM and MIRCO6 showing relatively better performance. This study reveals the key drivers of the elevated OA levels under droughts in the CONUS and underscores the deficiencies of current climate models in their predictive capacity for assessing the impact of future droughts on air quality.