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Empirical ocean color algorithm for estimating particulate organic carbon in the South China Sea

  • Physics
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Abstract

We examined regional empirical equations for estimating the surface concentration of particulate organic carbon (POC) in the South China Sea. These algorithms are based on the direct relationships between POC and the blue-to-green band ratios of spectral remotely sensed reflectance, R rs (λ B)/R rs(555). The best error statistics among the considered formulas were produced using the power function POC (mg/m3)=262.173 [R rs(443)/R rs(555)]−0.940. This formula resulted in a small mean bias of approximately −2.52%, a normalized root mean square error of 31.1%, and a determination coefficient of 0.91. This regional empirical equation is different to the results of similar studies in other oceanic regions. Our validation results suggest that our regional empirical formula performs better than the global algorithm, in the South China Sea. The feasibility of this band ratio algorithm is primarily due to the relationship between POC and the green-toblue ratio of the particle absorption coefficient. Colored dissolved organic matter can be an important source of noise in the band ratio formula. Finally, we applied the empirical algorithm to investigate POC changes in the southwest of Luzon Strait.

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Correspondence to Wenxi Cao  (曹文熙).

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Supported by the National Natural Science Foundation of China (Nos. 41376042, 41176035), the Natural Science for Youth Foundation (No. 41206029), the Youth Foundation by South China Sea Institute of Oceanology, Chinese Academy of Sciences (No. SQ201102), the Open Research Fund of State Key Laboratory of Estuarine and Coastal Research (No. SKLEC-KF201302), and the Open Project Program of State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences (No. LTOZZ1201)

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Hu, S., Cao, W., Wang, G. et al. Empirical ocean color algorithm for estimating particulate organic carbon in the South China Sea. Chin. J. Ocean. Limnol. 33, 764–778 (2015). https://doi.org/10.1007/s00343-015-4203-x

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  • DOI: https://doi.org/10.1007/s00343-015-4203-x

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