Overview of Aerosols in the E3SM Version 3: New Model Features and Their Impacts
Hailong Wang, Mingxuan Wu, Ziming Ke, Yan Feng, Manish Shrivastava, Qi Tang, Hui Wan, Xiaohong Liu, Richard C. Easter, Wuyin Lin, Balwinder Singh, Christopher R. Terai, Susannah M. Burrows, Jiwen Fan, Po‐Lun Ma, Naser Mahfouz, Johannes Mülmenstädt, Yun Qian, Yunpeng Shan, Kai Zhang, Yuying Zhang, L. Ruby Leung, Philip J. Rasch, Shaocheng XieAbstract
Accurate and comprehensive representation of aerosols in Earth system models (ESMs) is critical for modeling radiative forcing and seasonal‐to‐decadal variability. With increasing computing power, detailed physical and chemical processes representing aerosols and their interactions with other components of the Earth system can be treated more explicitly and accurately in ESMs. Like many other ESMs, the U.S. DOE Energy Exascale Earth System Model (E3SM) versions 1 and 2 have a state‐of‐the‐art treatment of major aerosol species but crudely treat or even neglect some aerosol components that become increasingly important in the future with decreasing sulfur emissions. Several science‐driven model developments of new aerosol features, including an explicit treatment of nitrate and ammonium aerosol species using MOSAIC coupled with the chemUCI gas chemistry scheme, explicit secondary organic aerosol (SOA) formation and loss, prognostic stratospheric sulfate (using chemical, microphysical and optical treatments instead of prescribing optical properties for volcanic aerosol), improved convective wet removal, improved numerical coupling of aerosol processes (i.e., emission, dry deposition, and turbulent mixing), and a new dust particle emission scheme, have been included in E3SM version 3 (E3SMv3) to better capture their roles in the Earth system. These new aerosol developments also require coupling with relatively comprehensive atmospheric chemistry to represent the reactions involving precursor gases and oxidants. Besides the new modeling capabilities, the aerosol improvements (e.g., SOA and dust lifetime and spatial distribution) contribute to E3SMv3's better performance in reproducing the historical temperature trends and enable the model to better project near‐future Earth system changes.