A proof-of-concept method is developed to estimate bulk refractive index (ηbp) of particles for deriving information on their composition and optical properties of natural waters using satellite ocean color data. It estimates ηbp as a function of the backscattering ratio (Bp), hyperbolic slope of the particle size distribution (ξ derived from the beam attenuation slope β), and apparent density of particles (ρa) as described in our previous inversion model. For deriving these parameters from remote-sensing data, large in situ measurement data of the remote-sensing reflectance (Rrs), particulate scattering (bp), backscattering (bbp) beam attenuation (cp), and seawater constituents' concentrations are used to establish the required relationships and derive the model parameters (i.e., ηbp ← Bp, ξ, ρa; Bp ← Rrs; ξ ← β ← cp ← Turbidity; Turbidity - Rrs; and ρa ← cp). When validated with those derived from in situ data spanning the large dynamic range in water optical properties and relevant water constituents impacting the remote-sensing signal, the derived model parameters and bulk refractive index had errors of a few percent which falls well within the benchmark for a validated uncertainty of ±35% endorsed for the remote-sensing retrieval of chlorophyll-a in oceanic waters. The model was applied to regional and global images of satellite ocean color observations provided by the MODIS-Aqua sensor. Global images of seasonal climatology over a decade of MODIS-Aqua ocean color observations provided interesting insights into the seasonal variability of ηbp in coastal and open ocean waters. To further investigate the bulk particulate assemblages in some regional waters, several MODIS-Aqua imageries from different regional waters dominated by sediment-laden river plumes and phytoplankton blooms were analyzed. Satellite retrievals of the ηbp varied from 1.035 to 1.05 for clear oceanic waters, 1.045- 1.07 for phytoplankton-dominated waters (higher water content), 1.05-1.15 for f...