Improved retrievals of fresh and aged smoke properties from GOES

Observations from geostationary satellites offer unprecedented opportunity to track and better understand smoke plumes in the atmosphere. Smoke plumes evolve physically and chemically as they are transported downwind, manifested as changes in their optical properties. If such changes can be properly characterized from spaceborne observations, this information would provide powerful constraints for regional and global models that represent biomass burning emissions and their chemical and physical changes during atmospheric transport, necessary information for evaluation of their impacts on climate and on human and environmental health. This project aims to improve aerosol retrievals from geostationary satellite observations, with six specific objectives: (1) Build and test a comprehensive suite of smoke-specific aerosol models constrained by dual-view Geostationary Operational Environmental Satellite (GOES) -16 and -17 observations, AErosol RObotic NETwork (AERONET), and lab and field campaign measurements, for biomass burning emissions near source and transported; (2) Develop a new, machine learning based aerosol retrieval method for GOES observations; (3) Characterize short-term temporal variability in near-field emissions, using new GOES retrievals; (4) Implement advanced methods for tracking smoke plume height, motion, and dispersion; (5) Examine the impacts of transport and aging on smoke properties; and (6) Assess the feasibility of transitioning advancements to operational GOES Advanced Baseline Imager (ABI) retrievals of smoke aerosols.