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

Atmosphere

Makiko Nakata¹  Itaru Sano²  Sonoyo Mukai³ 

[1] Faculty of Applied Sociology, Kindai University, Higashi-Osaka 577-8502, Japan;Faculty of Science and Technology, Kindai University, Higashi-Osaka 577-8502, Japan;Kyoto College of Graduate Studies for Informatics, Sakyo, Kyoto 606-8225, Japan;

关键词: GCOM-C/SGLI;    satellite;    severe biomass burning aerosols;    radiative transfer;   

DOI  :  10.3390/atmos12030403

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown