Within chemical transport models or earth system models, we typically make grossly simplifying assumptions about the diversity in aerosol composition. This introduces considerable structural uncertainty in our predictions of aerosol climate impacts, which has been challenging to quantify. This presentation will show how targeted particle-resolved simulations can be used to quantify structural uncertainty in more approximate aerosol models.
The particle-resolved approach resolves the aerosol using individual computational particles that evolve in size and composition during their simulated lifetime in the atmosphere.
I will illustrate to what extent simplifying the diversity of aerosol composition introduces errors in our estimates of cloud condensation nuclei concentration and aerosol optical properties. I’ll conclude the presentation by demonstrating how machine learning can leverage particle-resolved simulation data to efficiently bridge to the global scale.
Nicole Riemer is a Professor at the Department of Atmospheric Sciences and an Affiliate of the Department of Civil and Environmental Engineering at the University of Illinois at Urbana-Champaign. She received her doctorate in Meteorology from the University of Karlsruhe, Germany. Her research focus is the development of computer simulations that describe how aerosol particles are created, transported, and transformed in the atmosphere. Her group uses these simulations, together with observational and satellite data, to understand how aerosol particles impact human health, weather, and climate. She has received the NSF CAREER award, the AGU Ascent award, and is an editor for Aerosol Science & Technology and Journal of Geophysical Research.