MAGARA: a Multi-Angle Geostationary Aerosol Retrieval Algorithm

Abstract

Abstract. For over 40 years, the Geostationary Operational Environmental Satellite (GOES) system has provided frequent snapshots of the Western Hemisphere. The advanced baseline imagers (ABIs) on the GOES-16, GOES-17, and GOES-18 platforms are the first GOES-series imagers that meet the precision requirements for high-quality, aerosol-related research. We present MAGARA, a Multi-Angle Geostationary Aerosol Retrieval Algorithm, that leverages multi-angle ABI imagery to exploit the differences in autocorrelation timescales between surface reflectance, aerosol type, and aerosol loading. MAGARA retrieves pixel-level (up to 1 km) aerosol loading and fine-mode fraction at up to the cadence of the measurements (10 min), fine- and coarse-mode aerosol particle properties at a daily cadence, and surface properties by combining the multi-angle radiances with robust surface characterization inherent to temporally tiled algorithms. We present three case studies, and because GOES-17 was not making observations for one case, we present this as a unique demonstration of the multi-angle algorithm using only a single ABI sensor. We also compare MAGARA retrievals of fine-mode (FM) aerosol optical depth (AOD), coarse-mode (CM) AOD, and single-scattering albedo (SSA) statistically, with coincident AErosol RObotic NETwork (AERONET) spectral deconvolution algorithm (SDA) and inversion retrievals for the same period, and against bias-corrected NOAA GOES-16 and GOES-17 retrieved 550 nm AOD. For MAGARA vs. coincident AERONET over-land 500 nm fine-mode fraction and AOD>0.3, MAE=0.031, RMSE=0.100, and r=0.902, indicating good sensitivity to fine-mode fraction over land, especially for smoky regions. For bias-corrected MAGARA vs. coincident AERONET spectral single-scattering albedo with MAGARA AOD>0.5 (n=116), MAE=0.010, RMSE=0.015, and the correlation is 0.87. MAGARA performs best in regions where surface reflectance varies over long timescales with minimal clouds. This represents a large portion of the western half of the United States, much of north-central Africa and the Middle East, some of central Asia, and much of Australia. For these regions, aerosol type and aerosol loading on timescales as short as 10 min could allow for novel research into aerosol–cloud interactions, improvements to air-quality modeling and forecasting, and tighter constraints on direct aerosol radiative forcing.