Jessica D. Lundquist,Mimi Rose Abel,William Ryan Currier,Darren L. Jackson
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引用次数: 0
Abstract
Abstract Reported values of average annual peak snow water equivalent (SWE) in the mountains of the western United States differ by more than a factor of five, from not enough water to fill Lake Mead, the largest reservoir in the region, to enough water to fill Lake Mead five times. These products are not created equal. Many vastly underestimate snow water storage, and guidelines regarding which products are more accurate are crucial for using these products in any scientific analysis. Here, we review existing products and compare them to each other and to SWE derived from 26 aerial LiDAR acquisitions in Colorado, California, and Washington mountains of the western U.S. Products that match well with observations include (a) resolution of 9 km or finer, (b) reliance on observations of either fractional snow‐covered area or in situ SWE measurements, and (c) a well‐calibrated model framework that includes both quality precipitation estimates and accurate snowmelt. Many of the energy balance models reviewed had too much melt, likely from too much incoming radiation. Over all three regions, for the 14 flights that occurred close to peak SWE (March–April), the Western U.S. SWE Reanalysis (WUS‐SR) is least biased in reproducing near‐peak SWE (bias of 1.6%) and also best represented the spatial distribution of SWE (smallest mean absolute error). SNODAS and both of the University of Arizona products provide reasonable estimates (biases of 7.8%–10.2%). At the basin scale, ERA5‐Land also has small bias (−17.5%), but due to its coarser resolution, less accurate spatial representations.
期刊介绍:
Water Resources Research (WRR) is an interdisciplinary journal that focuses on hydrology and water resources. It publishes original research in the natural and social sciences of water. It emphasizes the role of water in the Earth system, including physical, chemical, biological, and ecological processes in water resources research and management, including social, policy, and public health implications. It encompasses observational, experimental, theoretical, analytical, numerical, and data-driven approaches that advance the science of water and its management. Submissions are evaluated for their novelty, accuracy, significance, and broader implications of the findings.