Implementation of the Yonsei Aerosol retrieval algorithm in the GK-2A/AMI and FY-4A/AGRI remote-sensing systems

The Yonsei AErosol Retrieval Algorithm (YAER) has been developed and improved for application with geostationary satellite-based imagers such as the Geostationary Ocean Color Imager (GOCI) and Advanced Himawari Imager (AHI). In this study its application was extended to the Advanced Meteorological I...

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Bibliographic Details
Main Authors: Kim, Minseok, Kim, Jhoon, Lim, Hyunkwang, Lee, Seoyoung, Cho, Yeseul, Chan, P. W.
Format: Conference Proceeding
Language:English
Subjects:
Aerosol Robotic Network
Aerosols
Algorithms
Channels
Cirrus clouds
Ocean color
Optical thickness
Pixels
Remote sensing
Retrieval
Short wave radiation
Synchronous satellites
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Summary:The Yonsei AErosol Retrieval Algorithm (YAER) has been developed and improved for application with geostationary satellite-based imagers such as the Geostationary Ocean Color Imager (GOCI) and Advanced Himawari Imager (AHI). In this study its application was extended to the Advanced Meteorological Imager (AMI) and Advanced Geostationary Radiation Imager (AGRI). With the 12 AMI and 11 AGRI infrared channels, the observed data from both sensors can mask bright pixels with considerable accuracy. Detection of cirrus cloud pixels is more accurate with the AMI and AGRI than with other imagers (e.g., GOCI, AHI), as the former have a 1.3 μm shortwave infrared channel. Despite there being two visible channels in AGRI and three in AMI, retrieved aerosol optical depth products are qualitatively consistent with Aerosol Robotic Network (AERONET) data. Retrieval of aerosol properties with the AMI and AGRI YAER algorithm will enhance the aerosol monitoring capability of GOCI and AHI systems, both spatially and temporally.
ISSN:0094-243X
1551-7616
DOI:10.1063/5.0183243