Modeling polarized solar spectra reflected by particulate snow, melt-form snow, and melt-freeze snow crust for CLARREO inter-calibration applications

Solar radiation interacting with a snow surface is polarized by ice crystals, melt-form snow, or melt-freeze snow crusts. This can be a source of measurement errors in satellite data if a non-polarimetric radiometric sensor is sensitive to the polarization of light. To obtain highly accurate spectral solar radiation data from the Earth-atmosphere system for the space-borne inter-calibration studies as proposed in NASA's Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission and the CLARREO Pathfinder (CPF) mission, the spectral polarization state of the reflected solar light at the top of atmosphere (TOA) must be known with sufficient accuracy. The degree of polarization (DOP) and the angle of polarization of the light at the TOA as functions of incident and viewing geometry and scene type construct the Polarization Distribution Models (PDMs) for correction of polarization-induced error of satellite data. In this work, algorithms for modeling the spectral polarization state of reflected sunlight from various types of snow including particulate snow, melt-form snow, and melt-freeze snow crusts are developed. A particulate snow surface model based on a mixture of spherical and hexagonal-column particle shapes is used. A rough-surface facet model is introduced to approximate the melt-form snow and melt-freeze snow crusts. The model results are compared with satellite data from the PARASOL and ground measurements conducted in Hokkaido, Japan, and northwest Greenland ice sheet to estimate the area fraction of particulate snow, melt-form snow, and melt-freeze snow crusts. The comparisons demonstrate that the model can provide a reliable approach for making the spectral PDMs for wavelengths between 320 and 2300 nm for satellite inter-calibration applications as proposed in the CLARREO and the CLARREO CPF missions for all kinds of snow surfaces.