气候变化领域集成服务门户(CCPortal): Theoretical analysis of errors when estimating snow distribution through point measurements

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DOI	10.5194/tc-9-1249-2015
	Theoretical analysis of errors when estimating snow distribution through point measurements
	Trujillo E.; Lehning M.
发表日期	2015
ISSN	19940416
卷号	9 期号:3
英文摘要	In recent years, marked improvements in our knowledge of the statistical properties of the spatial distribution of snow properties have been achieved thanks to improvements in measuring technologies (e.g., LIDAR, terrestrial laser scanning (TLS), and ground-penetrating radar (GPR)). Despite this, objective and quantitative frameworks for the evaluation of errors in snow measurements have been lacking. Here, we present a theoretical framework for quantitative evaluations of the uncertainty in average snow depth derived from point measurements over a profile section or an area. The error is defined as the expected value of the squared difference between the real mean of the profile/field and the sample mean from a limited number of measurements. The model is tested for one- and two-dimensional survey designs that range from a single measurement to an increasing number of regularly spaced measurements. Using high-resolution (∼ 1 m) LIDAR snow depths at two locations in Colorado, we show that the sample errors follow the theoretical behavior. Furthermore, we show how the determination of the spatial location of the measurements can be reduced to an optimization problem for the case of the predefined number of measurements, or to the designation of an acceptable uncertainty level to determine the total number of regularly spaced measurements required to achieve such an error. On this basis, a series of figures are presented as an aid for snow survey design under the conditions described, and under the assumption of prior knowledge of the spatial covariance/correlation properties. With this methodology, better objective survey designs can be accomplished that are tailored to the specific applications for which the measurements are going to be used. The theoretical framework can be extended to other spatially distributed snow variables (e.g., SWE - snow water equivalent) whose statistical properties are comparable to those of snow depth. © Author(s) 2015.
学科领域	conceptual framework; depth determination; error analysis; ground penetrating radar; lidar; optimization; snow cover; spatial distribution; survey design; theoretical study; Colorado; United States
语种	英语
scopus关键词	conceptual framework; depth determination; error analysis; ground penetrating radar; lidar; optimization; snow cover; spatial distribution; survey design; theoretical study; Colorado; United States
来源期刊	Cryosphere
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/119882
作者单位	School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland; WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland
推荐引用方式 GB/T 7714	Trujillo E.,Lehning M.. Theoretical analysis of errors when estimating snow distribution through point measurements[J],2015,9(3).
APA	Trujillo E.,&Lehning M..(2015).Theoretical analysis of errors when estimating snow distribution through point measurements.Cryosphere,9(3).
MLA	Trujillo E.,et al."Theoretical analysis of errors when estimating snow distribution through point measurements".Cryosphere 9.3(2015).