Articles | Volume 25, issue 9
https://doi.org/10.5194/hess-25-4651-2021
https://doi.org/10.5194/hess-25-4651-2021
Research article
 | 
31 Aug 2021
Research article |  | 31 Aug 2021

Assimilation of citizen science data in snowpack modeling using a new snow data set: Community Snow Observations

Ryan L. Crumley, David F. Hill, Katreen Wikstrom Jones, Gabriel J. Wolken, Anthony A. Arendt, Christina M. Aragon, Christopher Cosgrove, and Community Snow Observations Participants

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Latest update: 13 Dec 2024
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Short summary
In this study, we use a new snow data set collected by participants in the Community Snow Observations project in coastal Alaska to improve snow depth and snow water equivalence simulations from a snow process model. We validate our simulations with multiple datasets, taking advantage of snow telemetry (SNOTEL), snow depth and snow water equivalence, and remote sensing measurements. Our results demonstrate that assimilating citizen science snow depth measurements can improve model performance.