Regional Snow Parameters Estimation for Large-Domain Hydrological Applications in the Western United States

Sun, Ning; Yan, Hongxiang; Wigmosta, Mark S.; Leung, L. Ruby; Skaggs, Richard; Hou, Zhangshuan

doi:10.1029/2018JD030140

Title: Regional Snow Parameters Estimation for Large-Domain Hydrological Applications in the Western United States

Journal Article · Tue May 28 00:00:00 EDT 2019 · Journal of Geophysical Research: Atmospheres

DOI:https://doi.org/10.1029/2018JD030140· OSTI ID:1532548

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^[1]; Skaggs, Richard ^[1];

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Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Univ. of Washington, Seattle, WA (United States)

In snow-dominated regions, a critical source of uncertainty in hydrologic prediction and forecasting is the magnitude and distribution of snow water equivalent (SWE). With ensemble simulations, we demonstrate that SWE variability across the mountain ranges of the western United States (represented by 246 Snow Telemetry stations) can largely be captured at the daily time scale by a simple mass and energy-balance snow model with four physically reasonable parameters—three snow albedo parameters and one snow temperature threshold for precipitation partitioning. The model skill is lower in the maritime Pacific Northwest where SWE variability is more sensitive to errors associated with simulated energy balance (e.g., downward radiation fluxes) and the temperature-only precipitation partitioning approach. Poor model skill in high-altitude, windy locations in the Northern Rockies can be attributed to precipitation undercatch and underrepresented wind processes. For the purpose of large-domain hydrologic applications, regional snow parameters were developed for eight ecoregions characterized by a distinct hydroclimatic regime across the western United States. Results indicate that regionally coherent snow parameterizations are able to capture daily variations in SWE at most Snow Telemetry stations, suggesting that areas with a similar hydroclimate share a similar snow regime. While the three albedo parameters show limited spatial variability across all regions, the regional snow temperature threshold (Ts) shows marked spatial variation correlated with relative humidity; the Ts values increase from 0.2 °C in the higher-humidity Pacific Northwest to 4.0 °C in the colder, lower-humidity Rocky Mountains.

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Research Organization:: Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

Sponsoring Organization:: USDOE

Grant/Contract Number:: AC05-76RL01830; RC‐2546

OSTI ID:: 1532548

Report Number(s):: PNNL-SA-134653

Journal Information:: Journal of Geophysical Research: Atmospheres, Vol. 124, Issue 10; ISSN 2169-897X

Publisher:: American Geophysical UnionCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 23 works

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58 GEOSCIENCES
snow modeling skill
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SNOTEL
predictive uncertainty
parameter sensitivity and transferability

Title: Regional Snow Parameters Estimation for Large-Domain Hydrological Applications in the Western United States

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