Satellite-based radiative forcing by light-absorbing particles in snow across the Northern Hemisphere

Snow is the most reflective natural surface on Earth and consequently plays an important role in Earth's climate. Light-absorbing particles (LAPs) deposited on the snow surface can effectively decrease snow albedo, resulting in positive radiative forcing. In this study, we used remote-sensing data from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) and the Snow, Ice, and Aerosol Radiative (SNICAR) model to quantify the reduction in snow albedo due to LAPs before validating and correcting the data against in situ observations. We then incorporated these corrected albedo-reduction data in the Santa Barbara DISORT (Discrete Ordinate Radiative Transfer) Atmospheric Radiative Transfer (SBDART) model to estimate Northern Hemisphere radiative forcing except for midlatitude mountains in December-May for the period 2003-2018. Our analysis reveals an average corrected reduction in snow albedo (Delta(LAPs)(alpha MODIS,corrected)) of similar to 0.021 under all-sky conditions, with daily radiative forcing (RFMODIS,dailyLAPs) values of similar to 2.9 W m(-2), over land areas with complete or near-complete snow cover and with little or no vegetation above the snow in the Northern Hemisphere. We also observed significant spatial variations in Delta(LAPs)(alpha MODIS,corrected) and RFMODIS,dailyLAPs, with the lowest respective values (similar to 0.016 and similar to 2.6 W m(-2)) occurring in the Arctic and the highest (similar to 0.11 and similar to 12 W m(-2)) in northeastern China. From MODIS retrievals, we determined that the LAP content of snow accounts for 84 % and 70 % of the spatial variability in albedo reduction and radiative forcing, respectively. We also compared retrieved radiative forcing values with those of earlier studies, including local-scale observations, remote- sensing retrievals, and model-based estimates. Ultimately, estimates of radiative forcing based on satellite-retrieved data are shown to represent true conditions on both regional and global scales.