The Cryosphere
The Cryosphere
TC
Articles | Volume 20, issue 6
Articles | Volume 20, issue 6
https://doi.org/10.5194/tc-20-3345-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-20-3345-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 20, issue 6
Research article
 | 
10 Jun 2026
Research article |  | 10 Jun 2026

Assessing the impact of meteorological forcing and its uncertainty on snow modeling and reanalysis

Haorui Sun and Steven A. Margulis

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Short summary
Estimating Snow Water Equivalent (SWE) has large uncertainties from meteorological data, with no single dataset being universally superior. Our multi-forcing approach, which combines datasets, yields more accurate SWE estimates than single-forcing methods by mitigating bias. Even after data assimilation corrects for prior errors, the multi-forcing ensemble improves accuracy and uncertainty characterization, offering a more robust and reliable strategy for water resource management.
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