Assessment of satellite ocean color products of MERIS,MODIS and SeaWiFS along the East China Coast (in the Yellow Sea and East China Sea) |
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| Institution: | 1. School of Ocean Sciences, China University of Geosciences, Beijing 100083, China;2. Key Laboratory of Marine Hydrocarbon Resources and Environmental Geology, Qingdao Institute of Marine Geology, Qingdao 266071, China;3. Shaanxi Agricultural Remote Sensing Information Center, Xian 71000, China;4. First Institute of Oceanography, State Oceanic Administration, Qingdao 266071, China;5. National Satellite Ocean Application Service, Beijing 100081, China |
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| Abstract: | The validation of satellite ocean-color products is an important task of ocean-color missions. The uncertainties of these products are poorly quantified in the Yellow Sea (YS) and East China Sea (ECS), which are well known for their optical complexity and turbidity in terms of both oceanic and atmospheric optical properties. The objective of this paper is to evaluate the primary ocean-color products from three major ocean-color satellites, namely the Moderate Resolution Imaging Spectroradiometer (MODIS), Medium Resolution Imaging Spectrometer (MERIS), and Sea-viewing Wide Field-of-view Sensor (SeaWiFS). Through match-up analysis with in situ data, it is found that satellite retrievals of the spectral remote sensing reflectance Rrs(λ) at the blue-green and green bands from MERIS, MODIS and SeaWiFS have the lowest uncertainties with a median of the absolute percentage of difference (APDm) of 15–27% and root-mean-square-error (RMS) of 0.0021–0.0039 sr?1, whereas the Rrs(λ) uncertainty at 412 nm is the highest (APDm 47–62%, RMS 0.0027–0.0041 sr?1). The uncertainties of the aerosol optical thickness (AOT) τa, diffuse attenuation coefficient for downward irradiance at 490 nm Kd(490), concentrations of suspended particulate sediment concentration (SPM) and Chlorophyll a (Chl-a) were also quantified. It is demonstrated that with appropriate in-water algorithms specifically developed for turbid waters rather than the standard ones adopted in the operational satellite data processing chain, the uncertainties of satellite-derived properties of Kd(490), SPM, and Chl-a may decrease significantly to the level of 20–30%, which is true for the majority of the study area. This validation activity advocates for (1) the improvement of the atmosphere correction algorithms with the regional aerosol optical model, (2) switching to regional in-water algorithms over turbid coastal waters, and (3) continuous support of the dedicated in situ data collection effort for the validation task. |
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| Keywords: | Oceanography Comparison Retrieval Algorithm Satellite Accuracy Optical |
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