Articles | Volume 9, issue 3
Atmos. Meas. Tech., 9, 1377–1398, 2016

Special issue: Meso-scale aerosol processes, comparison and validation studies...

Atmos. Meas. Tech., 9, 1377–1398, 2016

Research article 01 Apr 2016

Research article | 01 Apr 2016

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

Myungje Choi1, Jhoon Kim1, Jaehwa Lee2,3, Mijin Kim1, Young-Je Park4, Ukkyo Jeong1, Woogyung Kim1, Hyunkee Hong5, Brent Holben3, Thomas F. Eck3,6, Chul H. Song7, Jae-Hyun Lim8, and Chang-Keun Song8 Myungje Choi et al.
  • 1Department of Atmospheric Sciences, Yonsei University, Seoul, Republic of Korea
  • 2Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA
  • 3NASA Goddard Space Flight Center, Greenbelt, MD, USA
  • 4Korea Ocean Satellite Center, Korea Institute of Ocean Science and Technology, Ansan, Republic of Korea
  • 5Department of Spatial Information Engineering, Pukyong National University, Busan, Republic of Korea
  • 6Universities Space Research Association, Columbia, MD, USA
  • 7School of Environmental Science and Engineering, Gwangju Institute of Science and Technology (GIST), Gwangju, Republic of Korea
  • 8National Institute of Environmental Research (NIER), Incheon, Republic of Korea

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 (DRAGON-NE 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.

Short summary
The Geostationary Ocean Color Imager (GOCI) is the first ocean color sensor in geostationary orbit. It enables hourly aerosol optical properties to be observed in high spatial resolution. This study presents improvements of the GOCI Yonsei Aerosol Retrieval (YAER) algorithm and its validation results using ground-based and other satellite-based observation products during DRAGON-NE Asia 2012 Campaign. Retrieval errors are also analyzed according to various factors through the validation studies.