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A western United States snow reanalysis dataset over the Landsat era from water years 1985 to 2021.


ABSTRACT: Water stored in mountain snowpacks (i.e., snow water equivalent, SWE) represents an important but poorly characterized component of the terrestrial water cycle. The Western United States snow reanalysis (WUS-SR) dataset is novel in its combination of spatial resolution (~500 m), spatial extent (31°-49° N; 102°-125° W), and temporal continuity (daily over 1985-2021). WUS-SR is generated using a Bayesian framework with model-based snow estimates updated through the assimilation of cloud-free Landsat fractional snow-covered area observations. Over the WUS, the peak SWE verification with independent in situ measurements show correlation coefficient, mean difference (MD), and root mean squared difference (RMSD) of 0.77, -0.15 m, and 0.28 m, respectively. The effects of forest cover and Landsat image availability on peak SWE are assessed. WUS-SR peak SWE is well correlated (ranging from 0.75 to 0.91) against independent lidar-derived SWE taken near April 1st, with MD <0.15 m and RMSD <0.38 m. The dataset is useful for characterizing WUS mountain snow storage, and ultimately for improving snow-derived water resources management.

SUBMITTER: Fang Y 

PROVIDER: S-EPMC9640559 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature

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A western United States snow reanalysis dataset over the Landsat era from water years 1985 to 2021.

Fang Yiwen Y   Liu Yufei Y   Margulis Steven A SA  

Scientific data 20221107 1


Water stored in mountain snowpacks (i.e., snow water equivalent, SWE) represents an important but poorly characterized component of the terrestrial water cycle. The Western United States snow reanalysis (WUS-SR) dataset is novel in its combination of spatial resolution (~500 m), spatial extent (31°-49° N; 102°-125° W), and temporal continuity (daily over 1985-2021). WUS-SR is generated using a Bayesian framework with model-based snow estimates updated through the assimilation of cloud-free Lands  ...[more]

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