

Jamet, C; Loisel, H; Kuchinke, CP; Ruddick, K; Zibordi, G; Feng, H (2011). Comparison of three SeaWiFS atmospheric correction algorithms for turbid waters using AERONETOC measurements. REMOTE SENSING OF ENVIRONMENT, 115(8), 19551965. Abstract The use of satellites to monitor the color of the ocean requires effective removal of the atmospheric signal. This can be performed by extrapolating the aerosol optical properties in the visible from the nearinfrared (NIR) spectral region assuming that the seawater is totally absorbant in this latter part of the spectrum. However, the nonnegligible waterleaving radiance in the NIR which is characteristic of turbid waters may lead to an overestimate of the atmospheric radiance in the whole visible spectrum with increasing severity at shorter wavelengths. This may result in significant errors, if not complete failure, of various algorithms for the retrieval of chlorophylla concentration, inherent optical properties and biogeochemical parameters of surface waters. This paper presents results of an intercomparison study of three methods that compensate for NIR waterleaving radiances and that are based on very different hypothesis: 1) the standard Sea WiFS algorithm (Stumpfet al., 2003; Bailey et al., 2010) based on a biooptical model and an iterative process; 2) the algorithm developed by Ruddick et al. (2000) based on the spatial homogeneity of the NIR ratios of the aerosol and waterleaving radiances; and 3) the algorithm of Kuchinke et al. (2009) based on a fully coupled atmosphereocean spectral optimization inversion. They are compared using normalized waterleaving radiance nL(w) in the visible. The reference source for comparison is groundbased measurements from three AERONETOcean Color sites, one in the Adriatic Sea and two in the East Coast of USA. Based on the matchup exercise, the best overall estimates of the nL(w) are obtained with the latest SeaWiFS standard algorithm version with relative error varying from 14.97% to 35.27% for lambda = 490 nm and lambda = 670 nm respectively. The least accurate estimates are given by the algorithm of Ruddick, the relative errors being between 16.36% and 42.92% for lambda = 490 nm and lambda = 412 nm, respectively. The algorithm of Kuchinke appears to be the most accurate algorithm at 412 nm (30.02%), 510 (15.54%) and 670 nm (32.32%) using its default optimization and biooptical model coefficient settings. Similar conclusions are obtained for the aerosol optical properties (aerosol optical thickness tau(865) and the Angstrom exponent, alpha(510, 865)). Those parameters are retrieved more accurately with the SeaWiFS standard algorithm (relative error of 33% and 54.15% for tau(865) and alpha(510, 865)). A detailed analysis of the hypotheses of the methods is given for explaining the differences between the algorithms. The determination of the aerosol parameters is critical for the algorithm of Ruddick et al. (2000) while the biooptical model is critical for the algorithm of Stumpf et al. (2003) utilized in the standard SeaWiFS atmospheric correction and both aerosol and biooptical model for the coupled atmosphericocean algorithm of Kuchinke. The Kuchinke algorithm presents model aerosolsize distributions that differ from real aerosolsize distribution pertaining to the measurements. In conclusion, the results show that for the given atmospheric and oceanic conditions of this study, the SeaWiFS atmospheric correction algorithm is most appropriate for estimating the marine and aerosol parameters in the given turbid waters regions. (C) 2011 Elsevier Inc. All rights reserved. DOI: 00344257 ISSN: 10.1016/j.rse.2011.03.018 