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

Zakeri, Fatemeh; Mariethoz, Gregoire; Girotto, Manuela

doi:10.5194/hess-29-6935-2025

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

Supplement

https://doi.org/10.5194/hess-29-6935-2025-supplement

Model code and software

fatemehzakeri/SWE-Downscaling-High-Resolution-Snow-Water-Equivalent-Mapping: k-NN SWE Downscaling (Version V1) Fatemeh Zakeri https://doi.org/10.5281/zenodo.17108974

Video supplement

High-Resolution SWE Estimation for Colorado: Analysis Using 'cnrm-esm2-1' Model at 9 km Resolution F. Zakeri et al. https://doi.org/10.5446/68237

High-Resolution SWE Estimation for California: Using 'ec-earth3-veg' Estimator at 100 km Resolution F. Zakeri et al. https://doi.org/10.5446/68236

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.