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

Minseok Kim; Jhoon Kim; Hyunkwang Lim; Seoyoung Lee; Yeseul Cho; P. W. Chan

doi:10.1063/5.0183243

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

Minseok Kim, Jhoon Kim, Hyunkwang Lim, Seoyoung Lee, Yeseul Cho, P. W. Chan

Department of Atmospheric Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

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.

Original language	English
Title of host publication	AIP Conference Proceedings
Editors	Alkiviadis F. Bais, Peter Pilewskie, Manfred Wendisch
Publisher	American Institute of Physics Inc.
Edition	1
ISBN (Electronic)	9780735447790
DOIs	https://doi.org/10.1063/5.0183243
Publication status	Published - 2024 Jan 18
Event	International Radiation Symposium 2022 on Radiation Processes in the Atmosphere and Ocean, IRS 2022 - Thessaloniki, Greece Duration: 2022 Jul 4 → 2022 Jul 8

Publication series

Name	AIP Conference Proceedings
Number	1
Volume	2988
ISSN (Print)	0094-243X
ISSN (Electronic)	1551-7616

Conference

Conference	International Radiation Symposium 2022 on Radiation Processes in the Atmosphere and Ocean, IRS 2022
Country/Territory	Greece
City	Thessaloniki
Period	22/7/4 → 22/7/8

Bibliographical note

Publisher Copyright:
© 2024 Author(s).

All Science Journal Classification (ASJC) codes

General Physics and Astronomy

Access to Document

10.1063/5.0183243

Cite this

Kim, M., Kim, J., Lim, H., Lee, S., Cho, Y., & Chan, P. W. (2024). Implementation of the Yonsei Aerosol retrieval algorithm in the GK-2A/AMI and FY-4A/AGRI remote-sensing systems. In A. F. Bais, P. Pilewskie, & M. Wendisch (Eds.), AIP Conference Proceedings (1 ed.). Article 050002 (AIP Conference Proceedings; Vol. 2988, No. 1). American Institute of Physics Inc.. https://doi.org/10.1063/5.0183243

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

abstract = "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.",

author = "Minseok Kim and Jhoon Kim and Hyunkwang Lim and Seoyoung Lee and Yeseul Cho and Chan, {P. W.}",

note = "Publisher Copyright: {\textcopyright} 2024 Author(s).; International Radiation Symposium 2022 on Radiation Processes in the Atmosphere and Ocean, IRS 2022 ; Conference date: 04-07-2022 Through 08-07-2022",

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doi = "10.1063/5.0183243",

language = "English",

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Kim, M, Kim, J, Lim, H, Lee, S, Cho, Y & Chan, PW 2024, Implementation of the Yonsei Aerosol retrieval algorithm in the GK-2A/AMI and FY-4A/AGRI remote-sensing systems. in AF Bais, P Pilewskie & M Wendisch (eds), AIP Conference Proceedings. 1 edn, 050002, AIP Conference Proceedings, no. 1, vol. 2988, American Institute of Physics Inc., International Radiation Symposium 2022 on Radiation Processes in the Atmosphere and Ocean, IRS 2022, Thessaloniki, Greece, 22/7/4. https://doi.org/10.1063/5.0183243

Implementation of the Yonsei Aerosol retrieval algorithm in the GK-2A/AMI and FY-4A/AGRI remote-sensing systems. / Kim, Minseok; Kim, Jhoon; Lim, Hyunkwang et al.
AIP Conference Proceedings. ed. / Alkiviadis F. Bais; Peter Pilewskie; Manfred Wendisch. 1. ed. American Institute of Physics Inc., 2024. 050002 (AIP Conference Proceedings; Vol. 2988, No. 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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T1 - Implementation of the Yonsei Aerosol retrieval algorithm in the GK-2A/AMI and FY-4A/AGRI remote-sensing systems

AU - Kim, Minseok

AU - Kim, Jhoon

AU - Lim, Hyunkwang

AU - Lee, Seoyoung

AU - Cho, Yeseul

AU - Chan, P. W.

PY - 2024/1/18

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N2 - 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.

AB - 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.

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BT - AIP Conference Proceedings

A2 - Bais, Alkiviadis F.

A2 - Pilewskie, Peter

A2 - Wendisch, Manfred

PB - American Institute of Physics Inc.

T2 - International Radiation Symposium 2022 on Radiation Processes in the Atmosphere and Ocean, IRS 2022

Y2 - 4 July 2022 through 8 July 2022

ER -

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

Abstract

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