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Characterization of Suspended Particle Size Distribution in Global Highly Turbid Waters From VIIRS Measurements
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2019
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Source: Journal of Geophysical Research: Oceans, 124, 3796–3817
[PDF-8.17 MB]
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Journal Title:Journal of Geophysical Research-Oceans
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Description:Normalized water-leaving radiance spectra nLw(λ) at the near-infrared (NIR) bands from six years of observations (2012–2017) with the Visible Infrared Imaging Radiometer Suite (VIIRS) on-board the Suomi National Polar-orbiting Partnership are used to derive both the power law slope η of the particle backscattering coefficient spectra bbp(λ) and the particle size power law slope ξ for turbid coastal and inland waters. Based on the fact that the absorption coefficient of sea water aw(λ) is generally much larger than those of the other constituents aiop(λ) at the NIR wavelengths in coastal and inland waters, a NIR-based bbp(λ) algorithm for turbid waters has been used to derive the power law slope η. A three-order polynomial function between η and ξ in Kostadinov et al. (2009, https://doi.org/10.1029/2009JC005303) is applied to calculate the particle size slope ξ. Seasonal and interannual variations of η and ξ in China's east coastal region, the Amazon River Estuary, the La Plata River Estuary, the Meghna River Estuary, and the Atchafalaya River Estuary are characterized and quantified. Except for the Amazon River Estuary, η and ξ have significant seasonal dependence in these highly turbid regions. Among the global highly turbid waters, the Meghna River Estuary shows the most significant seasonal variations in η and ξ with the largest particle size in the surface layer. The peaks of the climatology η and ξ are at ~ −1.2 and 3.2 in the Meghna River Estuary, respectively. Particle size parameters η and ξ are also shown to be related to the magnitude of nLw(λ) (or bbp(λ)) at the NIR bands with strong regional dependence. This study demonstrates that η and ξ increase from the inshore to offshore regions in these highly turbid waters, illustrating the more large particles in the inshore waters than the offshore ocean regions. In addition, wind and precipitation data in the Amazon River Estuary and Meghna River Estuary show that wind forcing is the major driver for the particle size distribution dynamics in these highly turbid water regions.
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Source:Journal of Geophysical Research: Oceans, 124, 3796–3817
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