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Beam attenuation, scattering and backscattering of marine particles in relation to particle size distribution and composition in H udson B ay ( C anada)
Author(s) -
Xi Hongyan,
Larouche Pierre,
Michel Christine,
Tang Shilin
Publication year - 2015
Publication title -
journal of geophysical research: oceans
Language(s) - English
Resource type - Journals
eISSN - 2169-9291
pISSN - 2169-9275
DOI - 10.1002/2014jc010668
Subject(s) - particulates , attenuation , chlorophyll a , composition (language) , particle (ecology) , scattering , biogeochemical cycle , range (aeronautics) , mineralogy , chemistry , environmental chemistry , analytical chemistry (journal) , materials science , oceanography , geology , optics , physics , composite material , linguistics , philosophy , biochemistry , organic chemistry
This study investigated the relationships between the concentration of biogeochemical parameters and particulate beam attenuation ( c p ), scattering ( b p ), and backscattering ( b bp ) in Hudson Bay. Results showed that most of the variability resulted from the presence of a deep chlorophyll maximum. c p , b p , and b bp were all adequate proxies to estimate total suspended matter (TSM) but were mostly sensitive to particulate inorganic matter (PIM) in the surface layer, and particulate organic matter (POM) at the chlorophyll maximum depth. The backscattering ratiob ∼ b pvaried in the range of 0.005–0.05 and was inversely related to the POM : TSM ratio. According to the Twardowski et al. (2001) model, the PSD slope ξ well representedb ∼ b pand bulk refractive indexn ¯ pin relation to particulate composition. For inorganic particulate dominated waters, bothb ∼ b pandn ¯ phad a larger range and a higher mean value than at organic particulate dominated waters. This knowledge on the optical properties related to the PSD and particulate composition provides valuable information for further investigation and broadens our understanding of ocean optics in high latitude waters leading to potential improvements of regional scale remote sensing algorithms.