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DOI | 10.1029/2018JD030140 |
Regional Snow Parameters Estimation for Large-Domain Hydrological Applications in the Western United States | |
Sun, Ning1; Yan, Hongxiang1; Wigmosta, Mark S.1,2; Leung, L. Ruby3; Skaggs, Richard1; Hou, Zhangshuan1 | |
2019-05-27 | |
发表期刊 | JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES |
ISSN | 2169-897X |
EISSN | 2169-8996 |
出版年 | 2019 |
卷号 | 124期号:10页码:5296-5313 |
文章类型 | Article |
语种 | 英语 |
国家 | USA |
英文摘要 | In snow-dominated regions, a key source of uncertainty in hydrologic prediction and forecasting is the magnitude and distribution of snow water equivalent (SWE). With ensemble simulations, this work demonstrates 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 parametersthree 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 suggest 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 (T-s) shows marked spatial variation correlated with relative humidity; the T-s values increase from 0.2 degrees C in the higher-humidity Pacific Northwest to 4.0 degrees C in the colder, lower-humidity Rocky Mountains. Plain Language Summary About 50% of the total runoff in the western United States originates as snowmelt, where snow modeling is a key source of uncertainty in hydrologic prediction for water management. However, appropriate regional parameterization of snow processes is not well addressed in current large-domain hydrologic modeling that generally focus on matching simulations to observed streamflows. In this context, this work develops regionally coherent snow parameters, for a relatively simple mass and energy-balance snow model, for eight ecological regions covering the mountain ranges of the western United States. The snow parameters proven to be critical for simulating snow processes consist of three snow albedo parameters and one snow temperature threshold for rain/snow partitioning. Results demonstrate that regional snow parameters can largely capture the snow regime at the daily time scale across the western United States represented by 246 Snow Telemetry stations characterized by diverse hydroclimatic conditions. While the three albedo parameters show limited spatial variability across all regions, the snow temperature threshold shows marked spatial variation negatively correlated with relative humidity. In sum, the regional snow parameters are expected to reduce uncertainties in regional to continental snow and hydrologic modeling. |
英文关键词 | snow model skill precipitation partitioning regional snow parameters DHSVM hydrological application western United States |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000471237200010 |
WOS关键词 | RAIN-ON-SNOW ; SENSITIVITY-ANALYSIS ; PROBABILITY SCORE ; SURFACE-ENERGY ; MODEL ; PRECIPITATION ; CLIMATE ; PREDICTION ; TEMPERATURE ; COVER |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/183343 |
专题 | 气候变化 |
作者单位 | 1.Pacific Northwest Natl Lab, Energy & Environm Directorate, Richland, WA 99352 USA; 2.Univ Washington, Dept Civil & Environm Engn, Seattle, WA 98195 USA; 3.Pacific Northwest Natl Lab, Earth & Biol Sci Directorate, Richland, WA 99352 USA |
推荐引用方式 GB/T 7714 | Sun, Ning,Yan, Hongxiang,Wigmosta, Mark S.,et al. Regional Snow Parameters Estimation for Large-Domain Hydrological Applications in the Western United States[J]. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,2019,124(10):5296-5313. |
APA | Sun, Ning,Yan, Hongxiang,Wigmosta, Mark S.,Leung, L. Ruby,Skaggs, Richard,&Hou, Zhangshuan.(2019).Regional Snow Parameters Estimation for Large-Domain Hydrological Applications in the Western United States.JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,124(10),5296-5313. |
MLA | Sun, Ning,et al."Regional Snow Parameters Estimation for Large-Domain Hydrological Applications in the Western United States".JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES 124.10(2019):5296-5313. |
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