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Deriving Snow Depth From ICESat-2 Lidar Multiple Scattering Measurements
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| Zeitschriftentitel: | Frontiers in Remote Sensing |
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| Personen und Körperschaften: | , , , , , , , , , , , , , , , , , , , , |
| In: | Frontiers in Remote Sensing, 3, 2022 |
| Format: | E-Article |
| Sprache: | Unbestimmt |
| veröffentlicht: |
Frontiers Media SA
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| Schlagwörter: |
| author_facet |
Hu, Yongxiang Lu, Xiaomei Zeng, Xubin Stamnes, Snorre A Neuman, Thomas A. Kurtz, Nathan T. Zhai, Pengwang Gao, Meng Sun, Wenbo Xu, Kuanman Liu, Zhaoyan Omar, Ali H. Baize, Rosemary R. Rogers, Laura J. Mitchell, Brandon O. Stamnes, Knut Huang, Yuping Chen, Nan Weimer, Carl Lee, Jennifer Fair, Zachary Hu, Yongxiang Lu, Xiaomei Zeng, Xubin Stamnes, Snorre A Neuman, Thomas A. Kurtz, Nathan T. Zhai, Pengwang Gao, Meng Sun, Wenbo Xu, Kuanman Liu, Zhaoyan Omar, Ali H. Baize, Rosemary R. Rogers, Laura J. Mitchell, Brandon O. Stamnes, Knut Huang, Yuping Chen, Nan Weimer, Carl Lee, Jennifer Fair, Zachary |
|---|---|
| author |
Hu, Yongxiang Lu, Xiaomei Zeng, Xubin Stamnes, Snorre A Neuman, Thomas A. Kurtz, Nathan T. Zhai, Pengwang Gao, Meng Sun, Wenbo Xu, Kuanman Liu, Zhaoyan Omar, Ali H. Baize, Rosemary R. Rogers, Laura J. Mitchell, Brandon O. Stamnes, Knut Huang, Yuping Chen, Nan Weimer, Carl Lee, Jennifer Fair, Zachary |
| spellingShingle |
Hu, Yongxiang Lu, Xiaomei Zeng, Xubin Stamnes, Snorre A Neuman, Thomas A. Kurtz, Nathan T. Zhai, Pengwang Gao, Meng Sun, Wenbo Xu, Kuanman Liu, Zhaoyan Omar, Ali H. Baize, Rosemary R. Rogers, Laura J. Mitchell, Brandon O. Stamnes, Knut Huang, Yuping Chen, Nan Weimer, Carl Lee, Jennifer Fair, Zachary Frontiers in Remote Sensing Deriving Snow Depth From ICESat-2 Lidar Multiple Scattering Measurements General Medicine |
| author_sort |
hu, yongxiang |
| spelling |
Hu, Yongxiang Lu, Xiaomei Zeng, Xubin Stamnes, Snorre A Neuman, Thomas A. Kurtz, Nathan T. Zhai, Pengwang Gao, Meng Sun, Wenbo Xu, Kuanman Liu, Zhaoyan Omar, Ali H. Baize, Rosemary R. Rogers, Laura J. Mitchell, Brandon O. Stamnes, Knut Huang, Yuping Chen, Nan Weimer, Carl Lee, Jennifer Fair, Zachary 2673-6187 Frontiers Media SA General Medicine http://dx.doi.org/10.3389/frsen.2022.855159 <jats:p>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.</jats:p> Deriving Snow Depth From ICESat-2 Lidar Multiple Scattering Measurements Frontiers in Remote Sensing |
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| title |
Deriving Snow Depth From ICESat-2 Lidar Multiple Scattering Measurements |
| title_unstemmed |
Deriving Snow Depth From ICESat-2 Lidar Multiple Scattering Measurements |
| title_full |
Deriving Snow Depth From ICESat-2 Lidar Multiple Scattering Measurements |
| title_fullStr |
Deriving Snow Depth From ICESat-2 Lidar Multiple Scattering Measurements |
| title_full_unstemmed |
Deriving Snow Depth From ICESat-2 Lidar Multiple Scattering Measurements |
| title_short |
Deriving Snow Depth From ICESat-2 Lidar Multiple Scattering Measurements |
| title_sort |
deriving snow depth from icesat-2 lidar multiple scattering measurements |
| topic |
General Medicine |
| url |
http://dx.doi.org/10.3389/frsen.2022.855159 |
| publishDate |
2022 |
| physical |
|
| description |
<jats:p>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.</jats:p> |
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| author | Hu, Yongxiang, Lu, Xiaomei, Zeng, Xubin, Stamnes, Snorre A, Neuman, Thomas A., Kurtz, Nathan T., Zhai, Pengwang, Gao, Meng, Sun, Wenbo, Xu, Kuanman, Liu, Zhaoyan, Omar, Ali H., Baize, Rosemary R., Rogers, Laura J., Mitchell, Brandon O., Stamnes, Knut, Huang, Yuping, Chen, Nan, Weimer, Carl, Lee, Jennifer, Fair, Zachary |
| author_facet | Hu, Yongxiang, Lu, Xiaomei, Zeng, Xubin, Stamnes, Snorre A, Neuman, Thomas A., Kurtz, Nathan T., Zhai, Pengwang, Gao, Meng, Sun, Wenbo, Xu, Kuanman, Liu, Zhaoyan, Omar, Ali H., Baize, Rosemary R., Rogers, Laura J., Mitchell, Brandon O., Stamnes, Knut, Huang, Yuping, Chen, Nan, Weimer, Carl, Lee, Jennifer, Fair, Zachary, Hu, Yongxiang, Lu, Xiaomei, Zeng, Xubin, Stamnes, Snorre A, Neuman, Thomas A., Kurtz, Nathan T., Zhai, Pengwang, Gao, Meng, Sun, Wenbo, Xu, Kuanman, Liu, Zhaoyan, Omar, Ali H., Baize, Rosemary R., Rogers, Laura J., Mitchell, Brandon O., Stamnes, Knut, Huang, Yuping, Chen, Nan, Weimer, Carl, Lee, Jennifer, Fair, Zachary |
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| description | <jats:p>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.</jats:p> |
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| spelling | Hu, Yongxiang Lu, Xiaomei Zeng, Xubin Stamnes, Snorre A Neuman, Thomas A. Kurtz, Nathan T. Zhai, Pengwang Gao, Meng Sun, Wenbo Xu, Kuanman Liu, Zhaoyan Omar, Ali H. Baize, Rosemary R. Rogers, Laura J. Mitchell, Brandon O. Stamnes, Knut Huang, Yuping Chen, Nan Weimer, Carl Lee, Jennifer Fair, Zachary 2673-6187 Frontiers Media SA General Medicine http://dx.doi.org/10.3389/frsen.2022.855159 <jats:p>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.</jats:p> Deriving Snow Depth From ICESat-2 Lidar Multiple Scattering Measurements Frontiers in Remote Sensing |
| spellingShingle | Hu, Yongxiang, Lu, Xiaomei, Zeng, Xubin, Stamnes, Snorre A, Neuman, Thomas A., Kurtz, Nathan T., Zhai, Pengwang, Gao, Meng, Sun, Wenbo, Xu, Kuanman, Liu, Zhaoyan, Omar, Ali H., Baize, Rosemary R., Rogers, Laura J., Mitchell, Brandon O., Stamnes, Knut, Huang, Yuping, Chen, Nan, Weimer, Carl, Lee, Jennifer, Fair, Zachary, Frontiers in Remote Sensing, Deriving Snow Depth From ICESat-2 Lidar Multiple Scattering Measurements, General Medicine |
| title | Deriving Snow Depth From ICESat-2 Lidar Multiple Scattering Measurements |
| title_full | Deriving Snow Depth From ICESat-2 Lidar Multiple Scattering Measurements |
| title_fullStr | Deriving Snow Depth From ICESat-2 Lidar Multiple Scattering Measurements |
| title_full_unstemmed | Deriving Snow Depth From ICESat-2 Lidar Multiple Scattering Measurements |
| title_short | Deriving Snow Depth From ICESat-2 Lidar Multiple Scattering Measurements |
| title_sort | deriving snow depth from icesat-2 lidar multiple scattering measurements |
| title_unstemmed | Deriving Snow Depth From ICESat-2 Lidar Multiple Scattering Measurements |
| topic | General Medicine |
| url | http://dx.doi.org/10.3389/frsen.2022.855159 |