Abstract
AbstractWater 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.
Funder
National Science Foundation
United States Department of Commerce | National Oceanic and Atmospheric Administration
National Aeronautics and Space Administration
Publisher
Springer Science and Business Media LLC
Subject
Library and Information Sciences,Statistics, Probability and Uncertainty,Computer Science Applications,Education,Information Systems,Statistics and Probability
Cited by
9 articles.
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