Use of critical snow water content to retrieve vertical variation of snow properties from visible and near-infrared channels of the GCOM-C1/SGLI sensor

The Global Change Observation Mission-Climate/Second-generation Global Imager (GCOM-C1/SGLI) is scheduled to be launched in 2014. The SGLI instrument has two major new features: 250 m spatial resolution and polarization/multidirectional observation capabilities. The 250 m resolution provides enhanced observation capability over snow/ice/mountain areas which are sensitive to climate change. The multidirectional observations with polarization channels have the potential to do accurate snow/atmosphere retrievals, which will help to improve climate prediction models. We have developed new algorithms for retrievals of snow/atmosphere parameters, including aerosol optical depth, mass concentration of snow impurity, and snow grain size by using visible and near-infrared channels. Our previous algorithms were based on a one-layer homogeneous snow model, which is unrealistic because snow has significant vertical variation. The radiance measured in the visible and the near-infrared channels originates from different snow vertical depths, and longer wavelengths carry information about a shallower layer of the snow. Hence it will be possible to obtain information about the vertical distribution of the snow grain size, since SGLI has four near-infrared channels at 868, 1020, 1640 and 2210 nm. In order to obtain information about the vertical variation of the snow grain size, we examined the effect of snow vertical information on the SGLI channels by using a multi-layered radiative transfer model for the coupled atmospheric-snow system. This radiative transfer model simulates the measured spectral radiant quantities. We will explore the potential for retrieving information about the vertical variation of snow parameters from the radiance measurements provided by the SGLI sensor, by using the critical snow water content rather than the penetration depth used previously.