Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 29, issue 23
Articles | Volume 29, issue 23
https://doi.org/10.5194/hess-29-6935-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-29-6935-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 29, issue 23
Research article
 | 
02 Dec 2025
Research article |  | 02 Dec 2025

High-resolution snow water equivalent estimation: a data-driven method for localized downscaling of climate data

Fatemeh Zakeri, Gregoire Mariethoz, and Manuela Girotto

Viewed

Total article views: 1,247 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
924 289 34 1,247 79 41 62
  • HTML: 924
  • PDF: 289
  • XML: 34
  • Total: 1,247
  • Supplement: 79
  • BibTeX: 41
  • EndNote: 62
Views and downloads (calculated since 14 Aug 2024)
Cumulative views and downloads (calculated since 14 Aug 2024)

Viewed (geographical distribution)

Total article views: 1,247 (including HTML, PDF, and XML) Thereof 1,235 with geography defined and 12 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 03 Dec 2025
Download
Short summary
Our study presents a method to estimate high-resolution snow water equivalent (HR-SWE) using low-resolution climate data (LR-CD). By using a data-driven approach, we analyze historical weather patterns from LR-CD to generate HR-SWE maps. Machine learning and statistical relationships between LR-CD and HR-SWE enable estimation for dates without HR-SWE data. This method enhances water resource management and climate impact assessments, especially in data-scarce regions.
Read more
Share