Articles | Volume 17, issue 2
https://doi.org/10.5194/amt-17-471-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-17-471-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
24 Jan 2024
Research article |
| 24 Jan 2024
| 24 Jan 2024
MAGARA: a Multi-Angle Geostationary Aerosol Retrieval Algorithm
James A. Limbacher
CORRESPONDING AUTHOR
I. M. Systems Group Inc., Rockville, MD 20850, USA
National Oceanic and Atmospheric Administration, College Park, MD 20740, USA
Ralph A. Kahn
Earth Science Division, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
The Laboratory for Atmospheric and Space Physics, University of Colorado Boulder, Boulder, CO 80303, USA
Mariel D. Friberg
Earth Science Division, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
University of Maryland, College Park, MD 20742, USA
Jaehwa Lee
Earth Science Division, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
University of Maryland, College Park, MD 20742, USA
Tyler Summers
Earth Science Division, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
Science Systems and Applications, Inc., Lanham, MD 20706, USA
Hai Zhang
I. M. Systems Group Inc., Rockville, MD 20850, USA
National Oceanic and Atmospheric Administration, College Park, MD 20740, USA
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Priyanka deSouza, Ralph A. Kahn, James A. Limbacher, Eloise A. Marais, Fábio Duarte, and Carlo Ratti
Atmos. Meas. Tech., 13, 5319–5334, https://doi.org/10.5194/amt-13-5319-2020, https://doi.org/10.5194/amt-13-5319-2020, 2020
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This paper presents a novel method to constrain the size distribution derived from low-cost optical particle counters (OPCs) using satellite data to develop higher-quality particulate matter (PM) estimates. Such estimates can enable cities that do not have access to expensive reference air quality monitors, especially those in the global south, to develop effective air quality management plans.
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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.
We present the new Multi-Angle Geostationary Aerosol Retrieval Algorithm (MAGARA) that fuses...
