Articles | Volume 18, issue 3
https://doi.org/10.5194/tc-18-1241-2024
https://doi.org/10.5194/tc-18-1241-2024
Research article
 | 
19 Mar 2024
Research article |  | 19 Mar 2024

Deep clustering in subglacial radar reflectance reveals subglacial lakes

Sheng Dong, Lei Fu, Xueyuan Tang, Zefeng Li, and Xiaofei Chen

Related authors

Mapping Antarctic Geothermal Heat Flow with Deep Neural Networks optimized by Particle Swarm Optimization Algorithm
Shaoxia Liu, Xueyuan Tang, Shuhu Yang, and Lijuan Wang
EGUsphere, https://doi.org/10.5194/egusphere-2025-3092,https://doi.org/10.5194/egusphere-2025-3092, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
A grid-level fixed-asset model developed for China from 1951 to 2020
Danhua Xin, James Edward Daniell, Zhenguo Zhang, Friedemann Wenzel, Shaun Shuxun Wang, and Xiaofei Chen
Nat. Hazards Earth Syst. Sci., 25, 1597–1620, https://doi.org/10.5194/nhess-25-1597-2025,https://doi.org/10.5194/nhess-25-1597-2025, 2025
Short summary
Revealing firn structure at Dome A region in East Antarctica using cultural seismic noise
Zhengyi Song, Yudi Pan, Jiangtao Li, Hongrui Peng, Yiming Wang, Yuande Yang, Kai Lu, Xueyuan Tang, and Xiaohong Zhang
EGUsphere, https://doi.org/10.5194/egusphere-2025-1274,https://doi.org/10.5194/egusphere-2025-1274, 2025
Short summary
Review Article: Antarctica’s internal architecture: Towards a radiostratigraphically-informed age–depth model of the Antarctic ice sheets
Robert G. Bingham, Julien A. Bodart, Marie G. P. Cavitte, Ailsa Chung, Rebecca J. Sanderson, Johannes C. R. Sutter, Olaf Eisen, Nanna B. Karlsson, Joseph A. MacGregor, Neil Ross, Duncan A. Young, David W. Ashmore, Andreas Born, Winnie Chu, Xiangbin Cui, Reinhard Drews, Steven Franke, Vikram Goel, John W. Goodge, A. Clara J. Henry, Antoine Hermant, Benjamin H. Hills, Nicholas Holschuh, Michelle R. Koutnik, Gwendolyn J.-M. C. Leysinger Vieli, Emma J. Mackie, Elisa Mantelli, Carlos Martín, Felix S. L. Ng, Falk M. Oraschewski, Felipe Napoleoni, Frédéric Parrenin, Sergey V. Popov, Therese Rieckh, Rebecca Schlegel, Dustin M. Schroeder, Martin J. Siegert, Xueyuan Tang, Thomas O. Teisberg, Kate Winter, Shuai Yan, Harry Davis, Christine F. Dow, Tyler J. Fudge, Tom A. Jordan, Bernd Kulessa, Kenichi Matsuoka, Clara J. Nyqvist, Maryam Rahnemoonfar, Matthew R. Siegfried, Shivangini Singh, Verjan Višnjević, Rodrigo Zamora, and Alexandra Zuhr
EGUsphere, https://doi.org/10.5194/egusphere-2024-2593,https://doi.org/10.5194/egusphere-2024-2593, 2024
Short summary
Brief communication: Identification of 140 000-year-old blue ice in the Grove Mountains, East Antarctica, by krypton-81 dating
Zhengyi Hu, Wei Jiang, Yuzhen Yan, Yan Huang, Xueyuan Tang, Lin Li, Florian Ritterbusch, Guo-Min Yang, Zheng-Tian Lu, and Guitao Shi
The Cryosphere, 18, 1647–1652, https://doi.org/10.5194/tc-18-1647-2024,https://doi.org/10.5194/tc-18-1647-2024, 2024
Short summary

Cited articles

Arnold, E., Leuschen, C., Rodriguez-Morales, F., Li, J., Paden, J., Hale, R., and Keshmiri, S.: CReSIS airborne radars and platforms for ice and snow sounding, Ann. Glaciol., 61, 58–67, 2020. a, b, c
Bailey, D.: Polar-cap absorption, Planet. Space Sci., 12, 495–541, 1964. a
Bell, R. E., Ferraccioli, F., Creyts, T. T., Braaten, D., Corr, H., Das, I., Damaske, D., Frearson, N., Jordan, T., Rose, K., Studinger, M., and Wolovick, M.: Widespread persistent thickening of the East Antarctic Ice Sheet by freezing from the base, Science, 331, 1592–1595, 2011. a, b
Bowling, J., Livingstone, S., Sole, A., and Chu, W.: Distribution and dynamics of Greenland subglacial lakes, Nat. Commun., 10, 1–11, 2019. a
Carter, S. P., Blankenship, D. D., Peters, M. E., Young, D. A., Holt, J. W., and Morse, D. L.: Radar-based subglacial lake classification in Antarctica, Geochem. Geophy. Geosy., 8, Q03016, https://doi.org/10.1029/2006GC001408, 2007. a, b
Download
Short summary
Subglacial lakes are a unique environment at the bottom of ice sheets, and they have distinct features in radar echo images that allow for visual detection. In this study, we use machine learning to analyze radar reflection waveforms and identify candidate subglacial lakes. Our approach detects more lakes than known inventories and can be used to expand the subglacial lake inventory. Additionally, this analysis may also provide insights into interpreting other subglacial conditions.
Share