Monte Carlo Photon Modeling to Explore the Dependence of Snow Bidirectional Reflectance on Grain Shape and Size

Abstract:

The spectral albedo of a snow-covered surface is sensitive to effective snow grain size. Snow metamorphism, then, affects the strength of surface albedo feedback and changes the radiative energy budget of the planet. The Near-Infrared Emitting Reflectance Dome (NERD) is an instrument in development designed to measure snow effective radius from in situ bidirectional reflectance factors (BRFs) by illuminating a surface with nadir positioned light emitting diodes centered around 1.30 and 1.55 microns. Better understanding the dependences of BRFs on snow grain shape and size is imperative to constraining measurements taken by the NERD. Here, we use the Monte Carlo method for photon transport to explore BRFs of snow surfaces of different shapes and sizes. In addition to assuming spherical grains and using Mie theory, we incorporate into the model the scattering phase functions and other single scattering properties of the following nine aspherical grain shapes: hexagonal columns, plates, hollow columns, droxtals, hollow bullet rosettes, solid bullet rosettes, 8-element column aggregates, 5-element plate aggregates, and 10-element plate aggregates. We present the simulated BRFs of homogeneous snow surfaces for these ten shape habits and show their spectral variability for a wide range of effective radii. Initial findings using Mie theory indicate that surfaces of spherical particles exhibit rather Lambertian reflectance for the two incident wavelengths used in the NERD and show a monotonically decreasing trend in black-sky albedo with increasing effective radius. These results are consistent with previous studies and also demonstrate good agreement with models using the two-stream approximation.