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The application of diffusion theory and Monte Carlo lidar radiative transfer simulations presented in Part I of this series of study suggests that snow depth can be derived from the first-, second- and third-order moments of the lidar backscattering pathlength distribution. These methods are now applied to the satellite ICESat-2 lidar measurements over the Arctic sea ice and land surfaces of Northern Hemisphere. Over the Arctic sea ice, the ICESat-2 retrieved snow depths agree well with co-located IceBridge snow radar measured values with a root-mean-square (RMS) difference of 7.8 cm or 29.2% of the mean snow depth. The terrestrial snow depths derived from ICESat-2 show drastic spatial variation of the snowpack along ICESat-2 ground tracks over the Northern Hemisphere, which are consistent with the University of Arizona (UA) and Canadian Meteorological Centre (CMC) gridded daily snow products. The RMS difference in snow depths between ICESat-2 and UA gridded daily snow products is 14 c ....

Languedoc Roussillon , United States , Hunan Province , Monte Carlo , Boulder Colo , Le Gac , Yuekui Yang , Dems Treichler , Icesat Abshire , Icebridge Arctic , Canadian Meteorological Centre Daily Snow Depth Version , Ice Data Center Distributed Active Archive , Ice Data Center , California Department Of Water Resources Snow Telemetry , Ocean Subsurface Optical Properties , National Snow , Variability American Geophysical Union , National Weather Service Cooperative Observer , University Of Arizona , Canadian Meteorological Centre , Advanced Microwave Scanning Radiometer , Advanced Topographic Laser Altimeter System , Cloud Aerosol Lidar , Orthogonal Polarization , California Department , Water Resources Snow Telemetry ,