The Cryosphere
The Cryosphere
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Articles | Volume 17, issue 12
Articles | Volume 17, issue 12
https://doi.org/10.5194/tc-17-5175-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-17-5175-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 17, issue 12
Research article
 | 
07 Dec 2023
Research article |  | 07 Dec 2023

Spatiotemporal snow water storage uncertainty in the midlatitude American Cordillera

Yiwen Fang, Yufei Liu, Dongyue Li, Haorui Sun, and Steven A. Margulis

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Cited articles

Bair, E. H., Dozier, J., Rittger, K., Stillinger, T., Kleiber, W., and Davis, R. E.: How do tradeoffs in satellite spatial and temporal resolution impact snow water equivalent reconstruction?, The Cryosphere, 17, 2629–2643, https://doi.org/10.5194/tc-17-2629-2023, 2023. 
Beaudoing, H. and Rodell, M.: NASA/GSFC/HSL (2020), GLDAS Noah Land Surface Model L4 3 hourly 0.25 × 0.25 degree V2.1, Greenbelt, Maryland, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/E7TYRXPJKWOQ, 2020a. 
Beaudoing, H. and Rodell, M.: NASA/GSFC/HSL (2020), GLDAS Noah Land Surface Model L4 3 hourly 1.0 × 1.0 degree V2.1, Greenbelt, Maryland, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/IIG8FHR17DA9, 2020b. 
Beaudoing, H. and Rodell, M.: NASA/GSFC/HSL (2020), GLDAS VIC Land Surface Model L4 3 hourly 1.0 × 1.0 degree V2.1, Greenbelt, Maryland, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/ZOG6BCSE26HV, 2020c. 
Broxton, P., Zeng, X., and Dawson, N.: Daily 4 km Gridded SWE and Snow Depth from Assimilated In-Situ and Modeled Data over the Conterminous US, Version 1, Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], https://doi.org/10.5067/0GGPB220EX6A, 2019. 
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Short summary
Using newly developed snow reanalysis datasets as references, snow water storage is at high uncertainty among commonly used global products in the Andes and low-resolution products in the western United States, where snow is the key element of water resources. In addition to precipitation, elevation differences and model mechanism variances drive snow uncertainty. This work provides insights for research applying these products and generating future products in areas with limited in situ data.
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