Articles | Volume 20, issue 1
https://doi.org/10.5194/tc-20-737-2026
https://doi.org/10.5194/tc-20-737-2026
Research article
 | 
28 Jan 2026
Research article |  | 28 Jan 2026

Ensemble-based snow depth data assimilation for a multi-layer snow scheme over the European Arctic

Åsmund Bakketun, Jostein Blyverket, and Malte Müller

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Short summary
Obtaining accurate estimates of seasonal snow conditions requires a combination of observations and numerical models. We use a model accounting for the vertical structure of the snow, and a data assimilation method representing varying uncertainty of the model in time and space. Compared to existing products, neglecting these considerations, our system produced improved estimates of seasonal snow conditions. Snow mass estimates suggest a potential impact on derived hydrological applications.
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