Linking lidar multiple scattering profiles to snow depth and snow density: an analytical radiative transfer analysis and the implications for remote sensing of snow

Frontiers in Remote Sensing

Remote Sensing

Carl Weimer¹  Qiang Fu²  Xubin Zeng³  Yuping Huang⁴  Knut Stamnes⁴  Charles Gatebe⁵  Anum Ashraf⁶  Ali Omar⁶  Rosemary Baize⁶  Snorre Stamnes⁶  Garfield Creary⁶  Xiaomei Lu⁶  Yongxiang Hu⁶  Ping Yang⁷ 

[1] Ball Aerospace & Technologies Corp., Boulder, CO, United States;Department of Atmospheric Sciences, University of Washington, Seattle, WA, United States;Department of Hydrology and Atmospheric Sciences, The University of Arizona, Tucson, AZ, United States;Department of Physics, Stevens Institute of Technology, Hoboken, NJ, United States;NASA Ames Research Center, Moffett Field, CA, United States;Science Directorate, NASA Langley Research Center, Hampton, VA, United States;The Department of Atmospheric Sciences, Texas A&M, College Station, TX, United States;

关键词: snow depth;    snow density;    snow grain size;    lidar;    path length distribution;    multiple scattering;   

DOI  :  10.3389/frsen.2023.1202234

 received in 2023-04-07, accepted in 2023-08-04,  发布年份 2023

来源: Frontiers

【 摘 要 】

Lidar multiple scattering measurements provide the probability distribution of the distance laser light travels inside snow. Based on an analytic two-stream radiative transfer solution, the present study demonstrates why/how these lidar measurements can be used to derive snow depth and snow density. In particular, for a laser wavelength with little snow absorption, an analytical radiative transfer solution is leveraged to prove that the physical snow depth is half of the average distance photons travel inside snow and that the relationship linking lidar measurements and the extinction coefficient of the snow is valid. Theoretical formulas that link lidar measurements to the extinction coefficient and the effective grain size of snow are provided. Snow density can also be derived from the multi-wavelength lidar measurements of the snow extinction coefficient and snow effective grain size. Alternatively, lidars can provide the most direct snow density measurements and the effective discrimination between snow and trees by adding vibrational Raman scattering channels.

【 授权许可】

Unknown   
Copyright © 2023 United States Government as represented by the Administrator of the National Aeronautics and Space Administration and Xubin Zeng, Qiang Fu, Ping Yang, Carl Weimer, Knut Stamnes, and Yuping Huang. At least a portion of this work is authored by Yongxiang Hu, Xiaomei Lu, Charles Gatebe, Snorre Stamnes, Rosemary Baize, Ali Omar, Garfield Creary, and Anum Ashraf on behalf of the U.S government and, as regards Dr. Hu, Dr. Lu, Dr. Gatebe, Dr. Stamnes, Dr. Baize, Dr. Omar, Dr. Creary, and Dr. Ashraf, U.S. copyright protection does not attach to separable portions of a Work authored solely by U.S. Government employees as part of their official duties. The U.S. Government is the owner of foreign copyrights in such separable portions of the Work and is a joint owner (with any non-U.S. Government author) of U.S. and foreign copyrights that may be asserted in inseparable portions the Work. The U.S. Government retains the right to use, reproduce, distribute, create derivative works, perform, and display portions of the Work authored solely or co-authored by a U.S. Government employee. Non-U.S copyrights also apply.