The Cryosphere
The Cryosphere
TC
Articles | Volume 15, issue 12
Articles | Volume 15, issue 12
https://doi.org/10.5194/tc-15-5639-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/tc-15-5639-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 15, issue 12
Research article
 | 
13 Dec 2021
Research article |  | 13 Dec 2021

Improving surface melt estimation over the Antarctic Ice Sheet using deep learning: a proof of concept over the Larsen Ice Shelf

Zhongyang Hu, Peter Kuipers Munneke, Stef Lhermitte, Maaike Izeboud, and Michiel van den Broeke

Viewed

Total article views: 3,984 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,646 1,241 97 3,984 94 147
  • HTML: 2,646
  • PDF: 1,241
  • XML: 97
  • Total: 3,984
  • BibTeX: 94
  • EndNote: 147
Views and downloads (calculated since 15 Apr 2021)
Cumulative views and downloads (calculated since 15 Apr 2021)

Viewed (geographical distribution)

Total article views: 3,984 (including HTML, PDF, and XML) Thereof 3,897 with geography defined and 87 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 25 Oct 2025
Download
Short summary
Antarctica is shrinking, and part of the mass loss is caused by higher temperatures leading to more snowmelt. We use computer models to estimate the amount of melt, but this can be inaccurate – specifically in the areas with the most melt. This is because the model cannot account for small, darker areas like rocks or darker ice. Thus, we trained a computer using artificial intelligence and satellite images that showed these darker areas. The model computed an improved estimate of melt.
Read more
Share
Special issue
Improving the contribution of the land cryosphere to sea level...