Implementing a Physically-Based Hyperspectral Snow Albedo Scheme in Regional and Global Climate Models for Improved Ice Sheet Mass Balance Estimates

Abstract:

Surface albedo plays an important role in the mass balance of ice sheets, particularly over the Greenland ice sheet, where shortwave radiation dominates the surface energy balance. Here we incorporate the Snow, Ice, Atmosphere Radiative Transfer Model (SNICAR) into the Modèle Atmosphérique Régionale regional climate model (MAR RCM) and NASA Goddard Institute for Space Studies (NASA GISS) ModelE general circulation model (GISS-E GCM). We dynamically link model-simulated snow density, temperature, temperature gradient, and liquid water content integrated over a fixed depth with SNICAR-simulated snow optical grain size evolution and compute a hyperspectral albedo over the 300-5000 micrometer wavelength range at a spectral resolution of 10 micrometers. The calculated albedo in turn improves the model-simulated surface mass and energy balance. Additionally, we take into account the impact of atmospheric deposition of dust and black carbon within the GISS-E GCM. The albedo scheme is a substantial improvement over previous schemes as a result of its physically-based approach and high spectral resolution. We validate the albedo scheme coupled with climate model simulations against satellite and in-situ measurements over the period 2001-2020. We also perform a sensitivity analysis to investigate the dominant processes driving changes in surface albedo and surface mass balance over the Greenland Ice Sheet.