The Cryosphere
The Cryosphere
TC
Articles | Volume 17, issue 3
Articles | Volume 17, issue 3
https://doi.org/10.5194/tc-17-1327-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-17-1327-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 17, issue 3
Research article
 | 
22 Mar 2023
Research article |  | 22 Mar 2023

Analysis of microseismicity in sea ice with deep learning and Bayesian inference: application to high-resolution thickness monitoring

Ludovic Moreau, Léonard Seydoux, Jérôme Weiss, and Michel Campillo

Viewed

Total article views: 2,747 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,901 757 89 2,747 115 154
  • HTML: 1,901
  • PDF: 757
  • XML: 89
  • Total: 2,747
  • BibTeX: 115
  • EndNote: 154
Views and downloads (calculated since 17 Nov 2022)
Cumulative views and downloads (calculated since 17 Nov 2022)

Viewed (geographical distribution)

Total article views: 2,747 (including HTML, PDF, and XML) Thereof 2,668 with geography defined and 79 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 24 Oct 2025
Download
Short summary
In the perspective of an upcoming seasonally ice-free Arctic, understanding the dynamics of sea ice in the changing climate is a major challenge in oceanography and climatology. It is therefore essential to monitor sea ice properties with fine temporal and spatial resolution. In this paper, we show that icequakes recorded on sea ice can be processed with artificial intelligence to produce accurate maps of sea ice thickness with high temporal and spatial resolutions.
Read more
Share