Enhancing snow albedo modeling in Community Land Model (CLM/CTSM)

Snow albedo plays a critical role in accurate modeling of seasonal snow evolution due to a strong positive albedo feedback. In this study, we update the snow albedo and radiative transfer scheme (SNICAR) in the widely-used Community Land Model (CLM/CTSM) by adding several new features and enhancements. Specifically, we implement new ice and aerosol optical properties for aerosol-snow-radiation interaction, new downward solar spectra, a more accurate snowpack radiative transfer solver, new parameterizations accounting for non-spherical snow grains and dust/soot-snow internal mixing, and a new hyperspectral (480 bands versus default 5 bands) snow radiative transfer modeling capability. We conduct model sensitivity simulations to quantify the impact of each of the aforementioned new features on global snow albedo and seasonal snowpack evolution. We also systematically evaluate model simulations against observations and reanalysis of global snow albedo, snow water equivalent, snow depth, and snow cover. Our analyses will further focus on seasonal variations of these impacts.