A New Inversion Model to Estimate Bulk Refractive Index of Particles in Coastal Oceanic Waters: Implications for Remote Sensing

An inversion model is developed to estimate bulk refractive index (
${\etab _{\mbi{bp}}}$
relative to water) for understanding the particle assemblages and dynamics in coastal oceanic waters. The model is based on an inversion of Mie theory combined with parameterizations such as the backscattering ratio, hyperbolic slope of the particle size distribution, and bulk density (relative to water). With the advent of high-frequency in-situ spectral attenuation and fluorescence-turbidity sensors, these parameters can be easily measured and used in the new model to estimate the
${\etab _{\mbi{bp}}}$
values. To test the robustness of this model, the
${\etab_{\mbi{bp}}}$
values estimated from the new model are verified with the Mie input refractive index values (relative to water) and those produced by an existing model. The new model is also applied to spatial, temporal, and vertical in-situ profile data measured from turbid coastal waters off Point Calimere and clear waters off Chennai, southeast part of India. The
${\etab_{\mbi{bp}}}$
values estimated by the present model are generally agreeable with the previously reported
${\etab _{\mbi{bp}}}$
values (1.02–1.28) for these waters. By contrast, the existing model tends to provide relatively high
${\etab _{\mbi{bp}}}$
values (1.10) for clear waters and low
${\etab _{\mbi{bp}}}$
values (1.215) for relatively clear and sediment-laden waters. Application of these models to time-series in-situ data from moderately turbid and highly turbid waters reveals that the vertical distribution patterns of
${\etab _{\mbi{bp}}}$
from the new model correspond better with turbidity patterns (with an increasing
${\etab _{\mbi{bp}}}$
trend in sediment-laden bottom waters) that display large variations depending on the tidal cycles of the day. However, the existing model produces a very narrow range of
${\etab _{\mbi{bp}}}$
values displaying nearly homogenous patterns regardless of the turbidity variation along the depth. The new model enables more reliable estimates of
${\etab _{\mbi{bp}}}$
for living cells (1.02–1.07 because of higher water content) in clear waters, detrital particles (1.07–1.15) and minerals/mineral-detrital particles (>1.15 because of lower water content). These results suggest that the new model will have important implications for studies of the particle assemblages in coastal oceanic waters, with the feasibility of remote estimation of
${\etab_{\mbi{bp}}}$
with the proof-of-concept approaches which will inspire further research into the nature of particles in the ocean and their variability on regional and global scales.