Articles | Volume 17, issue 2
https://doi.org/10.5194/amt-17-471-2024
https://doi.org/10.5194/amt-17-471-2024
Research article
 | 
24 Jan 2024
Research article |  | 24 Jan 2024

MAGARA: a Multi-Angle Geostationary Aerosol Retrieval Algorithm

James A. Limbacher, Ralph A. Kahn, Mariel D. Friberg, Jaehwa Lee, Tyler Summers, and Hai Zhang

Viewed

Total article views: 2,595 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,793 706 96 2,595 237 100 120
  • HTML: 1,793
  • PDF: 706
  • XML: 96
  • Total: 2,595
  • Supplement: 237
  • BibTeX: 100
  • EndNote: 120
Views and downloads (calculated since 24 Jul 2023)
Cumulative views and downloads (calculated since 24 Jul 2023)

Viewed (geographical distribution)

Total article views: 2,595 (including HTML, PDF, and XML) Thereof 2,574 with geography defined and 21 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 07 Jan 2026
Download
Short summary
We present the new Multi-Angle Geostationary Aerosol Retrieval Algorithm (MAGARA) that fuses observations from GOES-16 and GOES-17 to retrieve information about aerosol loading (at 10–15 min cadence) and aerosol particle properties (daily), all at pixel-level resolution. We present MAGARA results for three case studies: the 2018 California Camp Fire, the 2019 Williams Flats Fire, and the 2019 Kincade Fire. We also compare MAGARA aerosol loading and particle properties with AERONET.
Share