DOI: 10.5194/tc-9-13-2015
Scopus记录号: 2-s2.0-84920733238
论文题名: Independent evaluation of the SNODAS snow depth product using regional-scale lidar-derived measurements
作者: Hedrick A ; , Marshall H ; -P ; , Winstral A ; , Elder K ; , Yueh S ; , Cline D
刊名: Cryosphere
ISSN: 19940416
出版年: 2015
卷: 9, 期: 1 起始页码: 13
结束页码: 23
语种: 英语
英文关键词: data assimilation
; data set
; lidar
; remote sensing
; snow cover
; snowpack
; United States
英文摘要: Repeated light detection and ranging (lidar) surveys are quickly becoming the de facto method for measuring spatial variability of montane snowpacks at high resolution. This study examines the potential of a 750 km2 lidar-derived data set of snow depths, collected during the 2007 northern Colorado Cold Lands Processes Experiment (CLPX-2), as a validation source for an operational hydrologic snow model. The SNOw Data Assimilation System (SNODAS) model framework, operated by the US National Weather Service, combines a physically based energy-and-mass-balance snow model with satellite, airborne and automated ground-based observations to provide daily estimates of snowpack properties at nominally 1 km resolution over the conterminous United States. Independent validation data are scarce due to the assimilating nature of SNODAS, compelling the need for an independent validation data set with substantial geographic coverage. Within 12 distinctive 500 × 500 m study areas located throughout the survey swath, ground crews performed approximately 600 manual snow depth measurements during each of the CLPX-2 lidar acquisitions. This supplied a data set for constraining the uncertainty of upscaled lidar estimates of snow depth at the 1 km SNODAS resolution, resulting in a root-mean-square difference of 13 cm. Upscaled lidar snow depths were then compared to the SNODAS estimates over the entire study area for the dates of the lidar flights. The remotely sensed snow depths provided a more spatially continuous comparison data set and agreed more closely to the model estimates than that of the in situ measurements alone. Finally, the results revealed three distinct areas where the differences between lidar observations and SNODAS estimates were most drastic, providing insight into the causal influences of natural processes on model uncertainty. © 2015 Author(s). Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/75359
Appears in Collections: 影响、适应和脆弱性 气候变化与战略
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作者单位: Boise State University, Center for Geophysical Investigation of Shallow Subsurface, Boise, ID, United States; USDA, ARS Northwest Watershed Research Center, 800 Park Blvd., Boise, ID, United States; USDA Forest Service, Rocky Mountain Research Station, Fort Collins, CO, United States; Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States; NOAA-NWS, Hydrology Laboratory, Office of Hydrologic Development, Silver Spring, MD, United States
Recommended Citation:
Hedrick A,, Marshall H,-P,et al. Independent evaluation of the SNODAS snow depth product using regional-scale lidar-derived measurements[J]. Cryosphere,2015-01-01,9(1)