TY - JOUR
T1 - Deriving Snow Depth From ICESat-2 Lidar Multiple Scattering Measurements
AU - Hu, Yongxiang
AU - Lu, Xiaomei
AU - Zeng, Xubin
AU - Stamnes, Snorre A.
AU - Neuman, Thomas A.
AU - Kurtz, Nathan T.
AU - Zhai, Pengwang
AU - Gao, Meng
AU - Sun, Wenbo
AU - Xu, Kuanman
AU - Liu, Zhaoyan
AU - Omar, Ali H.
AU - Baize, Rosemary R.
AU - Rogers, Laura J.
AU - Mitchell, Brandon O.
AU - Stamnes, Knut
AU - Huang, Yuping
AU - Chen, Nan
AU - Weimer, Carl
AU - Lee, Jennifer
AU - Fair, Zachary
N1 - Publisher Copyright:
Copyright © 2022 Hu, Lu, Zeng, Stamnes, Neuman, Kurtz, Zhai, Gao, Sun, Xu, Liu, Omar, Baize, Rogers, Mitchell, Stamnes, Huang, Chen, Weimer, Lee and Fair.
PY - 2022
Y1 - 2022
N2 - Snow is a crucial element in the Earth’s system, but snow depth and mass are very challenging to be measured globally. Here, we provide the theoretical foundation for deriving snow depth directly from space-borne lidar (ICESat-2) snow multiple scattering measurements for the first time. First, based on the Monte Carlo lidar radiative transfer simulations of ICESat-2 measurements of 532-nm laser light propagation in snow, we find that the lidar backscattering path length follows Gamma distribution. Next, we derive three simple analytical equations to compute snow depth from the average, second-, and third-order moments of the distribution. As a preliminary application, these relations are then used to retrieve snow depth over the Antarctic ice sheet and the Arctic sea ice using the ICESat-2 lidar multiple scattering measurements. The robustness of this snow depth technique is demonstrated by the agreement of snow depth computed from the three derived relations using both modeled data and ICESat-2 observations.
AB - Snow is a crucial element in the Earth’s system, but snow depth and mass are very challenging to be measured globally. Here, we provide the theoretical foundation for deriving snow depth directly from space-borne lidar (ICESat-2) snow multiple scattering measurements for the first time. First, based on the Monte Carlo lidar radiative transfer simulations of ICESat-2 measurements of 532-nm laser light propagation in snow, we find that the lidar backscattering path length follows Gamma distribution. Next, we derive three simple analytical equations to compute snow depth from the average, second-, and third-order moments of the distribution. As a preliminary application, these relations are then used to retrieve snow depth over the Antarctic ice sheet and the Arctic sea ice using the ICESat-2 lidar multiple scattering measurements. The robustness of this snow depth technique is demonstrated by the agreement of snow depth computed from the three derived relations using both modeled data and ICESat-2 observations.
KW - average path length
KW - ICESat-2
KW - lidar
KW - multiple scattering
KW - path length distribution
KW - snow depth
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U2 - 10.3389/frsen.2022.855159
DO - 10.3389/frsen.2022.855159
M3 - Article
AN - SCOPUS:85145773798
VL - 3
JO - Frontiers in Remote Sensing
JF - Frontiers in Remote Sensing
M1 - 855159
ER -