Evaluating the utility of Sentinel-1 in a Data Assimilation System for estimating snow depth in a mountainous basin

Mirza, Bareera N.; Small, Eric E.; Raleigh, Mark S.

doi:10.5194/tc-19-6691-2025

Articles | Volume 19, issue 12

https://doi.org/10.5194/tc-19-6691-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/tc-19-6691-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 19, issue 12

Research article

|

09 Dec 2025

Research article |

| 09 Dec 2025

Evaluating the utility of Sentinel-1 in a Data Assimilation System for estimating snow depth in a mountainous basin

Bareera N. Mirza, Eric E. Small, and Mark S. Raleigh

Supplement

https://doi.org/10.5194/tc-19-6691-2025-supplement

Data sets

A meteorology and snow dataset from adjacent forested and meadow sites at Crested Butte H. M. Bonner et al. https://doi.org/10.5281/zenodo.6618553

Short summary

This study tests snow depth retrieved from Sentinel-1 radar and its use in a data assimilation (DA) model for the East River Basin, Colorado (2017–2021). Results show large and uneven errors, with temporal root mean square error (RMSE) around 0.4 m and spatial RMSE over 0.7 m. Combining Sentinel-1 with Moderate Resolution Imaging Spectroradiometer (MODIS) Snow Disappearance Date data did not improve results, indicating limited value for mountain snow mapping.