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DOI10.5194/hess-22-2655-2018
Obtaining sub-daily new snow density from automated measurements in high mountain regions
Helfricht K.; Hartl L.; Koch R.; Marty C.; Olefs M.
发表日期2018
ISSN1027-5606
起始页码2655
结束页码2668
卷号22期号:5
英文摘要The density of new snow is operationally monitored by meteorological or hydrological services at daily time intervals, or occasionally measured in local field studies. However, meteorological conditions and thus settling of the freshly deposited snow rapidly alter the new snow density until measurement. Physically based snow models and nowcasting applications make use of hourly weather data to determine the water equivalent of the snowfall and snow depth. In previous studies, a number of empirical parameterizations were developed to approximate the new snow density by meteorological parameters. These parameterizations are largely based on new snow measurements derived from local in situ measurements. In this study a data set of automated snow measurements at four stations located in the European Alps is analysed for several winter seasons. Hourly new snow densities are calculated from the height of new snow and the water equivalent of snowfall. Considering the settling of the new snow and the old snowpack, the average hourly new snow density is 68 kg mg-3, with a standard deviation of 9 kg mg-3. Seven existing parameterizations for estimating new snow densities were tested against these data, and most calculations overestimate the hourly automated measurements. Two of the tested parameterizations were capable of simulating low new snow densities observed at sheltered inner-alpine stations. The observed variability in new snow density from the automated measurements could not be described with satisfactory statistical significance by any of the investigated parameterizations. Applying simple linear regressions between new snow density and wet bulb temperature based on the measurements' data resulted in significant relationships (r2 > 0.5 and p ≤ 0.05) for single periods at individual stations only. Higher new snow density was calculated for the highest elevated and most wind-exposed station location. Whereas snow measurements using ultrasonic devices and snow pillows are appropriate for calculating station mean new snow densities, we recommend instruments with higher accuracy e.g. optical devices for more reliable investigations of the variability of new snow densities at sub-daily intervals. © 2018 Author(s).
语种英语
scopus关键词Automation; Parameter estimation; Parameterization; Snowfall measurement; Automated measurement; Hydrological services; In-situ measurement; Meteorological condition; Meteorological parameters; Simple linear regression; Statistical significance; Wet bulb temperature; Snow; automation; data set; density; in situ measurement; model; mountain region; nowcasting; parameterization; snow; snow water equivalent; temperature; Alps
来源期刊Hydrology and Earth System Sciences
文献类型期刊论文
条目标识符http://gcip.llas.ac.cn/handle/2XKMVOVA/160037
作者单位Helfricht, K., IGF - Institute for Interdisciplinary Mountain Research, Austrian Academy of Sciences, Innsbruck, 6020, Austria; Hartl, L., IGF - Institute for Interdisciplinary Mountain Research, Austrian Academy of Sciences, Innsbruck, 6020, Austria; Koch, R., ZAMG - Zentralanstalt für Meteorologie und Geodynamik, Climate Research Department, Vienna, 1190, Austria; Marty, C., WSL Institute for Snow and Avalanche Research SLF, Davos, 7260, Switzerland; Olefs, M., ZAMG - Zentralanstalt für Meteorologie und Geodynamik, Climate Research Department, Vienna, 1190, Austria
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Helfricht K.,Hartl L.,Koch R.,et al. Obtaining sub-daily new snow density from automated measurements in high mountain regions[J],2018,22(5).
APA Helfricht K.,Hartl L.,Koch R.,Marty C.,&Olefs M..(2018).Obtaining sub-daily new snow density from automated measurements in high mountain regions.Hydrology and Earth System Sciences,22(5).
MLA Helfricht K.,et al."Obtaining sub-daily new snow density from automated measurements in high mountain regions".Hydrology and Earth System Sciences 22.5(2018).
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