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Frontiers | Deriving Snow Depth From ICESat-2 Lidar Multiple Scattering Measurements: Uncertainty Analyses

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

Multiyear ice thinner than thought as Arctic sea ice reaches winter max: Studies

Arctic sea ice extent continued its trending decline in winter 2022, while the Antarctic saw a record low summer minimum extent. Both regions also saw extraordinarily high temperatures for this time of year.

Cutting Through Ice with ICESat-2's Space Lasers

Cutting Through Ice with ICESat-2's Space Lasers
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Cutting Through Ice with ICESat-2's Space Lasers

Cutting Through Ice with ICESat-2's Space Lasers
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