Articles | Volume 11, issue 4
https://doi.org/10.5194/tc-11-1933-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/tc-11-1933-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Evaluation of snow cover and snow depth on the Qinghai–Tibetan Plateau derived from passive microwave remote sensing
Liyun Dai
Key Laboratory of Remote Sensing of Gansu Province, Heihe Remote Sensing Experimental Research Station, Cold and Arid Regions Environmental and Engineering
Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 21003, China
Key Laboratory of Remote Sensing of Gansu Province, Heihe Remote Sensing Experimental Research Station, Cold and Arid Regions Environmental and Engineering
Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China
Center for Excellence in Tibetan Plateau Earth Sciences, Chinese Academy of Sciences, Beijing 100101, China
Yongjian Ding
State Key Laboratory of Cryospheric Sciences, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China
Xiaohua Hao
Key Laboratory of Remote Sensing of Gansu Province, Heihe Remote Sensing Experimental Research Station, Cold and Arid Regions Environmental and Engineering
Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China
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- MT-InSAR Unveils Dynamic Permafrost Disturbances in Hoh Xil (Kekexili) on the Tibetan Plateau Hinterland P. Lu et al. 10.1109/TGRS.2023.3253937
- Microwave polarization characteristics of snow at 6.9 and 18.7 GHz: Estimating the water content of the snow layers C. Varotsos et al. 10.1016/j.jqsrt.2018.12.041
- AMSR2 snow depth downscaling algorithm based on a multifactor approach over the Tibetan Plateau, China Y. Wang et al. 10.1016/j.rse.2019.111268
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- Improved snow depth estimation on the Tibetan Plateau using AMSR2 and ensemble learning models Q. Gu et al. 10.1016/j.jag.2024.104102
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Latest update: 20 Nov 2024
Short summary
Snow depth over QTP plays a very important role in the climate and hydrological system, but there are uncertainties on the snow depth products derived from passive microwave remote sensing data. In this study, we evaluated the ability of passive microwave to detect snow cover and snow depth over QTP, presented the accuracy of passive microwave snow cover and snow depth products over QTP, and analyzed the possible reasons causing the uncertainties.
Snow depth over QTP plays a very important role in the climate and hydrological system, but...