Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2019WR025350 |
Characterizing Biases in Mountain Snow Accumulation From Global Data Sets | |
Wrzesien, Melissa L.1; Pavelsky, Tamlin M.1; Durand, Michael T.2,3; Dozier, Jeff4; Lundquist, Jessica D.5 | |
2019-11-27 | |
发表期刊 | WATER RESOURCES RESEARCH
![]() |
ISSN | 0043-1397 |
EISSN | 1944-7973 |
出版年 | 2019 |
文章类型 | Article;Early Access |
语种 | 英语 |
国家 | USA |
英文摘要 | Mountain snow has a fundamental role in regional water budgets through its seasonal accumulation, storage, and melt. However, characterizing snow accumulation over large regions remains difficult because of limited observational networks and the inability of available satellite instruments to remotely sense snow depth or water equivalent in mountains. Models offer some ability to estimate snow water storage (SWS) on mountain range to continental scales. Here we compare four commonly used global data sets to understand whether there is a consensus regarding mountain SWS estimates among them. The data sets-European Centre for Medium-Range Weather Forecasts Reanalysis-Interim, Global Land Data Assimilation System, Modern-Era Retrospective Analysis for Research and Applications version 2, and Variable Infiltration Capacity-agree to within +/- 36% of the four-data set average for total global SWS. When mountain areas are extracted using a new seasonal mountain snow classification data set, the four data products have more agreement, where all are within +/- 21% of the seasonal SWS for mountain regions. However, when compared to high-resolution (9 km) simulations of SWS from the Weather Research and Forecasting (WRF) regional model, the four global products differ from WRF-estimated North American mountain snow accumulation by 40-66%, with a negative bias up to 651 km(3), comparable to the annual streamflow of the Mississippi River. If we extend the North America SWS bias to global mountains, the global data sets may miss as much as 1,500 km(3) of SWS, equivalent to 4% of the flow in all the world's rivers. The potential difference of SWS suggests more work must be done to characterize water resources in snow-dominated regions, particularly in mountains. |
英文关键词 | snow accumulation global reanalysis regional modeling snow water equivalent |
领域 | 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000498769300001 |
WOS关键词 | LAND-SURFACE WATER ; ROCKY-MOUNTAINS ; UNITED-STATES ; EQUIVALENT ; CLIMATE ; COVER ; MODEL ; PRECIPITATION ; ASSIMILATION ; IMPACTS |
WOS类目 | Environmental Sciences ; Limnology ; Water Resources |
WOS研究方向 | Environmental Sciences & Ecology ; Marine & Freshwater Biology ; Water Resources |
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/223934 |
专题 | 资源环境科学 |
作者单位 | 1.Univ N Carolina, Dept Geol Sci, Chapel Hill, NC 27515 USA; 2.Ohio State Univ, Sch Earth Sci, Columbus, OH 43210 USA; 3.Ohio State Univ, Byrd Polar & Climate Res Ctr, Columbus, OH 43210 USA; 4.Univ Calif Santa Barbara, Bren Sch Environm Sci & Management, Santa Barbara, CA 93106 USA; 5.Univ Washington, Civil & Environm Engn, Seattle, WA 98195 USA |
推荐引用方式 GB/T 7714 | Wrzesien, Melissa L.,Pavelsky, Tamlin M.,Durand, Michael T.,et al. Characterizing Biases in Mountain Snow Accumulation From Global Data Sets[J]. WATER RESOURCES RESEARCH,2019. |
APA | Wrzesien, Melissa L.,Pavelsky, Tamlin M.,Durand, Michael T.,Dozier, Jeff,&Lundquist, Jessica D..(2019).Characterizing Biases in Mountain Snow Accumulation From Global Data Sets.WATER RESOURCES RESEARCH. |
MLA | Wrzesien, Melissa L.,et al."Characterizing Biases in Mountain Snow Accumulation From Global Data Sets".WATER RESOURCES RESEARCH (2019). |
条目包含的文件 | 条目无相关文件。 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论