Advancing snow data assimilation with a dynamic observation uncertainty

Dunmire, Devon; Bechtold, Michel; Boeykens, Lucas; De Lannoy, Gabriëlle J. M.

doi:10.5194/tc-20-609-2026

Articles | Volume 20, issue 1

https://doi.org/10.5194/tc-20-609-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/tc-20-609-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 20, issue 1

Research article

|

23 Jan 2026

Research article |

| 23 Jan 2026

Advancing snow data assimilation with a dynamic observation uncertainty

Devon Dunmire, Michel Bechtold, Lucas Boeykens, and Gabriëlle J. M. De Lannoy

Supplement

https://doi.org/10.5194/tc-20-609-2026-supplement

Data sets

Code and Data for ``A machine learning approach for estimating snow depth across the European Alps from Sentinel-1 imagery'' D. Dunmire https://doi.org/10.5281/zenodo.13342108

GCOS SWE data from 11 stations in Switzerland C. Marty https://doi.org/10.16904/15

Longterm hydrological observatory Alptal (central Switzerland) M Stähli https://doi.org/10.16904/envidat.380

Dataset on new snow water equivalent J. Magnusson and T. Jonas https://doi.org/10.16904/envidat.590

IMIS measuring network Intercantonal Measurement and Information System IMIS https://doi.org/10.16904/envidat.406

Model code and software

drdunmire1417/Snow\_DA\_LIS\_configfiles: LIS config files Devon Dunmire https://doi.org/10.5281/zenodo.18189931

Code and Data for ``A machine learning approach for estimating snow depth across the European Alps from Sentinel-1 imagery'' D. Dunmire https://doi.org/10.5281/zenodo.13342108

Short summary

Snow is vital for society and the climate, yet estimates of snowpack remain uncertain due to observational and modeling limitations. Data assimilation (DA) helps by integrating observations with models. Here, we integrate snow depth retrievals into a physically-based snow model across the European Alps. This work offers advancements for snow data assimilation, such as incorporating a dynamic observational uncertainty, which is essential for forecasting and water resource management.