GOCI Yonsei Aerosol Retrieval (YAER) algorithm and validation during the DRAGON-NE Asia 2012 campaign

Myungje Choi, Jhoon Kim, Jaehwa Lee, Mijin Kim, Young Je Park, Ukkyo Jeong, Woogyung Kim, Hyunkee Hong, Brent Holben, Thomas F. Eck, Chul H. Song, Jae Hyun Lim, Chang Keun Song

Research output: Contribution to journalArticle

19 Citations (Scopus)

Abstract

The Geostationary Ocean Color Imager (GOCI) onboard the Communication, Ocean, and Meteorological Satellite (COMS) is the first multi-channel ocean color imager in geostationary orbit. Hourly GOCI top-of-atmosphere radiance has been available for the retrieval of aerosol optical properties over East Asia since March 2011. This study presents improvements made to the GOCI Yonsei Aerosol Retrieval (YAER) algorithm together with validation results during the Distributed Regional Aerosol Gridded Observation Networks - Northeast Asia 2012 campaign (DRAGONNE Asia 2012 campaign). The evaluation during the spring season over East Asia is important because of high aerosol concentrations and diverse types of Asian dust and haze. Optical properties of aerosol are retrieved from the GOCI YAER algorithm including aerosol optical depth (AOD) at 550 nm, fine-mode fraction (FMF) at 550 nm, single-scattering albedo (SSA) at 440 nm, Ångström exponent (AE) between 440 and 860 nm, and aerosol type. The aerosol models are created based on a global analysis of the Aerosol Robotic Networks (AERONET) inversion data, and covers a broad range of size distribution and absorptivity, including nonspherical dust properties. The Cox-Munk ocean bidirectional reflectance distribution function (BRDF) model is used over ocean, and an improved minimum reflectance technique is used over land. Because turbid water is persistent over the Yellow Sea, the land algorithm is used for such cases. The aerosol products are evaluated against AERONET observations and MODIS Collection 6 aerosol products retrieved from Dark Target (DT) and Deep Blue (DB) algorithms during the DRAGON-NE Asia 2012 campaign conducted from March to May 2012. Comparison of AOD from GOCI and AERONET resulted in a Pearson correlation coefficient of 0.881 and a linear regression equation with GOCI AOD = 1.083 × AERONET AOD-0.042. The correlation between GOCI and MODIS AODs is higher over ocean than land. GOCI AOD shows better agreement with MODIS DB than MODIS DT. The other GOCI YAER products (AE, FMF, and SSA) show lower correlation with AERONET than AOD, but still show some skills for qualitative use.

Original languageEnglish
Pages (from-to)1377-1398
Number of pages22
JournalAtmospheric Measurement Techniques
Volume9
Issue number3
DOIs
Publication statusPublished - 2016 Apr 1

Fingerprint

aerosol
optical depth
MODIS
GOCI
Asia
ocean
optical property
albedo
scattering
dust
data inversion
top of atmosphere
bidirectional reflectance
spring (season)
ocean color
haze
radiance
reflectance
AERONET
communication

All Science Journal Classification (ASJC) codes

  • Atmospheric Science

Cite this

Choi, Myungje ; Kim, Jhoon ; Lee, Jaehwa ; Kim, Mijin ; Park, Young Je ; Jeong, Ukkyo ; Kim, Woogyung ; Hong, Hyunkee ; Holben, Brent ; Eck, Thomas F. ; Song, Chul H. ; Lim, Jae Hyun ; Song, Chang Keun. / GOCI Yonsei Aerosol Retrieval (YAER) algorithm and validation during the DRAGON-NE Asia 2012 campaign. In: Atmospheric Measurement Techniques. 2016 ; Vol. 9, No. 3. pp. 1377-1398.
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author = "Myungje Choi and Jhoon Kim and Jaehwa Lee and Mijin Kim and Park, {Young Je} and Ukkyo Jeong and Woogyung Kim and Hyunkee Hong and Brent Holben and Eck, {Thomas F.} and Song, {Chul H.} and Lim, {Jae Hyun} and Song, {Chang Keun}",
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Choi, M, Kim, J, Lee, J, Kim, M, Park, YJ, Jeong, U, Kim, W, Hong, H, Holben, B, Eck, TF, Song, CH, Lim, JH & Song, CK 2016, 'GOCI Yonsei Aerosol Retrieval (YAER) algorithm and validation during the DRAGON-NE Asia 2012 campaign', Atmospheric Measurement Techniques, vol. 9, no. 3, pp. 1377-1398. https://doi.org/10.5194/amt-9-1377-2016

GOCI Yonsei Aerosol Retrieval (YAER) algorithm and validation during the DRAGON-NE Asia 2012 campaign. / Choi, Myungje; Kim, Jhoon; Lee, Jaehwa; Kim, Mijin; Park, Young Je; Jeong, Ukkyo; Kim, Woogyung; Hong, Hyunkee; Holben, Brent; Eck, Thomas F.; Song, Chul H.; Lim, Jae Hyun; Song, Chang Keun.

In: Atmospheric Measurement Techniques, Vol. 9, No. 3, 01.04.2016, p. 1377-1398.

Research output: Contribution to journalArticle

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AU - Kim, Jhoon

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AU - Kim, Mijin

AU - Park, Young Je

AU - Jeong, Ukkyo

AU - Kim, Woogyung

AU - Hong, Hyunkee

AU - Holben, Brent

AU - Eck, Thomas F.

AU - Song, Chul H.

AU - Lim, Jae Hyun

AU - Song, Chang Keun

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N2 - The Geostationary Ocean Color Imager (GOCI) onboard the Communication, Ocean, and Meteorological Satellite (COMS) is the first multi-channel ocean color imager in geostationary orbit. Hourly GOCI top-of-atmosphere radiance has been available for the retrieval of aerosol optical properties over East Asia since March 2011. This study presents improvements made to the GOCI Yonsei Aerosol Retrieval (YAER) algorithm together with validation results during the Distributed Regional Aerosol Gridded Observation Networks - Northeast Asia 2012 campaign (DRAGONNE Asia 2012 campaign). The evaluation during the spring season over East Asia is important because of high aerosol concentrations and diverse types of Asian dust and haze. Optical properties of aerosol are retrieved from the GOCI YAER algorithm including aerosol optical depth (AOD) at 550 nm, fine-mode fraction (FMF) at 550 nm, single-scattering albedo (SSA) at 440 nm, Ångström exponent (AE) between 440 and 860 nm, and aerosol type. The aerosol models are created based on a global analysis of the Aerosol Robotic Networks (AERONET) inversion data, and covers a broad range of size distribution and absorptivity, including nonspherical dust properties. The Cox-Munk ocean bidirectional reflectance distribution function (BRDF) model is used over ocean, and an improved minimum reflectance technique is used over land. Because turbid water is persistent over the Yellow Sea, the land algorithm is used for such cases. The aerosol products are evaluated against AERONET observations and MODIS Collection 6 aerosol products retrieved from Dark Target (DT) and Deep Blue (DB) algorithms during the DRAGON-NE Asia 2012 campaign conducted from March to May 2012. Comparison of AOD from GOCI and AERONET resulted in a Pearson correlation coefficient of 0.881 and a linear regression equation with GOCI AOD = 1.083 × AERONET AOD-0.042. The correlation between GOCI and MODIS AODs is higher over ocean than land. GOCI AOD shows better agreement with MODIS DB than MODIS DT. The other GOCI YAER products (AE, FMF, and SSA) show lower correlation with AERONET than AOD, but still show some skills for qualitative use.

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