A Bidirectional Subsurface Remote Sensing Reflectance Model Explicitly Accounting for Particle Backscattering Shapes

The subsurface remote sensing reflectance (rrs, sr−1), particularly its bidirectional reflectance distribution function (BRDF), depends fundamentally on the angular shape of the volume scattering functions (VSFs, m−1 sr−1). Recent technological advancement has greatly expanded the collection, and the knowledge of natural variability, of the VSFs of oceanic particles. This allows us to test the Zaneveld\u27s theoretical rrs model that explicitly accounts for particle VSF shapes. We parameterized the rrs model based on HydroLight simulations using 114 VSFs measured in three coastal waters around the United States and in oceanic waters of North Atlantic Ocean. With the absorption coefficient (a), backscattering coefficient (bb), and VSF shape as inputs, the parameterized model is able to predict rrs with a root mean square relative error of ∼4% for solar zenith angles from 0 to 75°, viewing zenith angles from 0 to 60°, and viewing azimuth angles from 0 to 180°. A test with the field data indicates the performance of our model, when using only a and bb as inputs and selecting the VSF shape using bb, is comparable to or slightly better than the currently used models by Morel et al. and Lee et al. Explicitly expressing VSF shapes in rrs modeling has great potential to further constrain the uncertainty in the ocean color studies as our knowledge on the VSFs of natural particles continues to improve. Our study represents a first effort in this direction