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Article

Improved Algorithms for Remote Sensing-Based Aerosol Retrieval during Extreme Biomass Burning Events

1
School of Applied Information Technology, The Kyoto College of Graduate Studies for Informatics, Sakyo, Kyoto 606-8225, Japan
2
Faculty of Science and Technology, Kindai University, Higashi-Osaka 577-8502, Japan
3
Faculty of Applied Sociology, Kindai University, Higashi-Osaka 577-8502, Japan
*
Author to whom correspondence should be addressed.
Academic Editor: Ying Tsai
Atmosphere 2021, 12(3), 403; https://doi.org/10.3390/atmos12030403
Received: 20 February 2021 / Revised: 16 March 2021 / Accepted: 16 March 2021 / Published: 20 March 2021
(This article belongs to the Special Issue Aerosol Pollution in Asia)
This study proposed an aerosol characterization process using satellites for severe biomass burning events. In general, these severely hazy cases are labeled as “undecided” or “hazy.” Because atmospheric aerosols are significantly affected by factors such as air quality, global climate change, local environmental risk, and human and biological health, efficient and accurate algorithms for aerosol retrieval are required for global satellite data processing. Our previous classification of aerosol types was based primarily on near-ultraviolet (UV) data, which facilitated subsequent aerosol retrieval. In this study, algorithms for aerosol classification were expanded to events with serious biomass burning aerosols (SBBAs). Once a biomass burning event is identified, the appropriate radiation simulation method can be applied to characterize the SBBAs. The second-generation global imager (SGLI) on board the Japanese mission JAXA/Global Change Observation Mission-Climate contains 19 channels, including red (674 nm) and near-infrared (869 nm) polarization channels with a high resolution of 1 km. Using the large-scale wildfires in Kalimantan, Indonesia in 2019 as an example, the complementarity between the polarization information and the nonpolarized radiance measurements from the SGLI was demonstrated to be effective in radiation simulations for biomass burning aerosol retrieval. The retrieved results were verified using NASA/AERONET ground-based measurements, and then compared against JAXA/SGLI/L2-version-1 products, and JMA/Himawari-8/AHI observations. View Full-Text
Keywords: GCOM-C/SGLI; satellite; severe biomass burning aerosols; radiative transfer GCOM-C/SGLI; satellite; severe biomass burning aerosols; radiative transfer
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MDPI and ACS Style

Mukai, S.; Sano, I.; Nakata, M. Improved Algorithms for Remote Sensing-Based Aerosol Retrieval during Extreme Biomass Burning Events. Atmosphere 2021, 12, 403. https://doi.org/10.3390/atmos12030403

AMA Style

Mukai S, Sano I, Nakata M. Improved Algorithms for Remote Sensing-Based Aerosol Retrieval during Extreme Biomass Burning Events. Atmosphere. 2021; 12(3):403. https://doi.org/10.3390/atmos12030403

Chicago/Turabian Style

Mukai, Sonoyo, Itaru Sano, and Makiko Nakata. 2021. "Improved Algorithms for Remote Sensing-Based Aerosol Retrieval during Extreme Biomass Burning Events" Atmosphere 12, no. 3: 403. https://doi.org/10.3390/atmos12030403

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