Abstract:

For over 40 years, the Geostationary Operational Environmental Satellite (GOES) system has provided frequent snapshots of the Western Hemisphere, with its data used for a variety of tasks ranging from weather forecasting to wildfire detection. Located on the GOES-16, GOES-17, and GOES-18 platforms, the Advanced Baseline Imager (ABI) is the first GOES-series imager that meets the precision requirements (e.g., ≥ 10 bits per datum) for high-quality, aerosol-related research. Here, we present a pixel-level (up to 1 km) Multi-Angle Geostationary Aerosol Retrieval Algorithm (MAGARA) that leverages the ABI instruments on the GOES-16 and GOES-17 platforms, as well as the differences in autocorrelation time-scales between surface reflectance, aerosol type, and aerosol loading. MAGARA retrieves pixel-level aerosol loading and fine-mode fraction at up to the cadence of the measurements (10 minutes), fine-and-coarse mode aerosol particle properties at a daily cadence, and surface properties under a framework that combines the unique information content in multi-angle radiances (e.g., sensitivity to aerosol type from multiple scattering-angle observations) with the robust surface characterization inherent to temporally tiled algorithms such as the MAIAC method.