Synthetic aperture radar (SAR) plays an important role in measuring directional ocean wave spectra with continuous and global coverage. In this article, satellite SAR images were used to estimate the wave parameters in the East China Sea. The Max-Planck Institut (MPI) method was applied to retrieve directional wave spectra from the SAR imagers with the Simulating WAves Nearshore (SWAN) model data as the first guess wave spectra. In order to validate the SAR retrieved wave spectra, a set of buoy measurements during the SAR imaging times was collected and used. The SAR retrieved significant wave heights (SWHs) were analyzed against the buoy measurements to assess the wave retrieval of this study. The root-mean-square error between the SAR SWHs and the buoy measurements is 0.25 m, which corresponds to a relative error of 12%. The case study here shows that the SWAN model data is a potential first guess wave spectra source to the MPI method to retrieve ocean wave spectra from SAR imagery.
The Geostationary Ocean Color Imager (GOCI) is the first geostationary ocean color satellite sensor launched in June
2010 on board the South Korean Communication, Ocean and Meteorological Satellite (COMS). The GOCI has a local
coverage area of the western Pacific Ocean including Bohai, Yellow Sea and East Sea of China. Jiaozhou Bay is a semienclosed
basin in the western part of the Yellow Sea, which is an important representative of gulf ecosystem in the North
Temperate Zone. The GOCI data can provide useful information with an-hour temporal and 500-m spatial resolutions for
monitoring oceanic and atmospheric process in Jiaozhou Bay. The performance of the atmospheric and optical
algorithms of GOCI was evaluated by comparing with the simultaneous data from MODIS/Aqua. The match-up products
include remote sensing reflectance (Rrs) and chlorophyll-a concentration ([chl-a]) and they were derived by GDPS
software for GOCI data and SeaDAS software for MODIS and GOCI data, respectively, using default atmospheric
correction and bio-optical algorithms. Our analyses show that GOCI products (i.e., Rrs(490), Rrs(555) and [chl-a]) are
compared well with MODIS products. GOCI shows a potential capability of oceanography investigations in Jiaozhou
Bay and Qingdao coastal area. The consistency of Rrs between GOCI and MODIS is relatively good but significant
difference was observed in [chl-a] especially in Jiaozhou Bay. Moreover, it is suggested to improve GOCI standard
atmospheric correction algorithm for high turbid water and cloud detection to increase data utilization.
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