The Cryosphere
The Cryosphere
TC
Articles | Volume 17, issue 2
Articles | Volume 17, issue 2
https://doi.org/10.5194/tc-17-977-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-17-977-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 17, issue 2
Research article
 | 
01 Mar 2023
Research article |  | 01 Mar 2023

Spatio-temporal reconstruction of winter glacier mass balance in the Alps, Scandinavia, Central Asia and western Canada (1981–2019) using climate reanalyses and machine learning

Matteo Guidicelli, Matthias Huss, Marco Gabella, and Nadine Salzmann

Viewed

Total article views: 3,979 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
2,687 1,205 87 3,979 271 108 144
  • HTML: 2,687
  • PDF: 1,205
  • XML: 87
  • Total: 3,979
  • Supplement: 271
  • BibTeX: 108
  • EndNote: 144
Views and downloads (calculated since 27 Apr 2022)
Cumulative views and downloads (calculated since 27 Apr 2022)

Viewed (geographical distribution)

Total article views: 3,979 (including HTML, PDF, and XML) Thereof 3,888 with geography defined and 91 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 05 Dec 2025
Download
Short summary
Spatio-temporal reconstruction of winter glacier mass balance is important for assessing long-term impacts of climate change. However, high-altitude regions significantly lack reliable observations, which is limiting the calibration of glaciological and hydrological models. We aim at improving knowledge on the spatio-temporal variations in winter glacier mass balance by exploring the combination of data from reanalyses and direct snow accumulation observations on glaciers with machine learning.
Read more
Share