title: Ocean color products from the Korean Geostationary Ocean Color Imager (GOCI).
abstract: The first geostationary ocean color satellite sensor, Geostationary Ocean Color Imager (GOCI), which is onboard South Korean Communication, Ocean, and Meteorological Satellite (COMS), was successfully launched in June of 2010. GOCI has a local area coverage of the western Pacific region centered at around 36°N and 130°E and covers ~2500 × 2500 km(2). GOCI has eight spectral bands from 412 to 865 nm with an hourly measurement during daytime from 9:00 to 16:00 local time, i.e., eight images per day. In a collaboration between NOAA Center for Satellite Applications and Research (STAR) and Korea Institute of Ocean Science and Technology (KIOST), we have been working on deriving and improving GOCI ocean color products, e.g., normalized water-leaving radiance spectra (nLw(λ)), chlorophyll-a concentration, diffuse attenuation coefficient at the wavelength of 490 nm (Kd(490)), etc. The GOCI-covered ocean region includes one of the world's most turbid and optically complex waters. To improve the GOCI-derived nLw(λ) spectra, a new atmospheric correction algorithm was developed and implemented in the GOCI ocean color data processing. The new algorithm was developed specifically for GOCI-like ocean color data processing for this highly turbid western Pacific region. In this paper, we show GOCI ocean color results from our collaboration effort. From in situ validation analyses, ocean color products derived from the new GOCI ocean color data processing have been significantly improved. Generally, the new GOCI ocean color products have a comparable data quality as those from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the satellite Aqua. We show that GOCI-derived ocean color data can provide an effective tool to monitor ocean phenomenon in the region such as tide-induced re-suspension of sediments, diurnal variation of ocean optical and biogeochemical properties, and horizontal advection of river discharge. In particular, we show some examples of ocean diurnal variations in the region, which can be provided effectively from satellite geostationary measurements.
authors.affiliation: NOAA National Environmental Satellite, Data, and Information Service, Center for Satellite Applications and Research, E/RA3, 5830 University Research Ct., College Park, Maryland 20740, USA. Menghua.Wang@noaa.gov
authors.forename: Menghua
authors.initials: M
authors.lastname: Wang
authors.forename: Jae-Hyun
authors.initials: JH
authors.lastname: Ahn
authors.forename: Lide
authors.initials: L
authors.lastname: Jiang
authors.forename: Wei
authors.initials: W
authors.lastname: Shi
authors.forename: SeungHyun
authors.initials: S
authors.lastname: Son
authors.forename: Young-Je
authors.initials: YJ
authors.lastname: Park
authors.forename: Joo-Hyung
authors.initials: JH
authors.lastname: Ryu
mesh_terms: D000465:Algorithms; D003124:Colorimetry / Q000379:methods*; D004784:Environmental Monitoring / Q000379:methods*; D009792:Oceans and Seas; D018531:Spacecraft; D013057:Spectrum Analysis / Q000379:methods*; D014867:Water / Q000032:analysis* / Q000737:chemistry*
chemical_list: D014867:Water