Abstract
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.
Highlights
Aerosols have an important role in the Earth’s climate system, influencing climate directly through scattering and absorbing radiation, and indirectly by acting as cloud condensation nuclei (IPCC, 2013)
This study introduces the improvements made to the Geostationary Ocean Color Imager (GOCI) Yonsei Aerosol Retrieval (YAER) algorithm and validation results during the DRAGON-NE Asia 2012 campaign
The AOD over turbid water pixels is not retrieved in the Moderate Resolution Imaging Spectroradiometer (MODIS) Dark Target (DT) ocean algorithm, so direct comparison over turbid water is impossible (Lee et al, 2010b)
Summary
Aerosols have an important role in the Earth’s climate system, influencing climate directly through scattering and absorbing radiation, and indirectly by acting as cloud condensation nuclei (IPCC, 2013). Aerosol retrieval algorithms have been developed using meteorological imagers aboard GEO satellites, such as the Geostationary Operational Environmental Satellite (GOES), Geostationary Meteorological Satellite (GMS), and Multifunction Transport Satellite (MTSAT) (Kim et al, 2008; Knapp et al, 2002; Wang et al, 2003; Yoon et al, 2007; Urm and Sohn, 2005) These sensors provide observations at a higher temporal resolution than LEO sensors, but have fixed observation area and lower accuracy due to the wider spectral bands and fewer visible channels. The wavelength bands of the eight channels are centered at 412, 443, 490, 555, 660, 680, 745, and 865 nm, similar to other ocean color sensors such as the Coastal Zone Color Scanner (CZCS), SeaWiFS, MERIS, and MODIS, but GOCI has a high spatial resolution of 500 m × 500 m (Table 1) It observes East Asia hourly during the daytime, a total of eight times per day.
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