Journal metrics

Journal metrics

  • IF value: 4.256 IF 4.256
  • IF 5-year value: 4.819 IF 5-year 4.819
  • CiteScore value: 4.10 CiteScore 4.10
  • SNIP value: 1.412 SNIP 1.412
  • SJR value: 2.023 SJR 2.023
  • IPP value: 3.97 IPP 3.97
  • h5-index value: 58 h5-index 58
  • Scimago H index value: 99 Scimago H index 99
Volume 22, issue 5 | Copyright
Hydrol. Earth Syst. Sci., 22, 2655-2668, 2018
https://doi.org/10.5194/hess-22-2655-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 04 May 2018

Research article | 04 May 2018

Obtaining sub-daily new snow density from automated measurements in high mountain regions

Kay Helfricht1, Lea Hartl1, Roland Koch2, Christoph Marty3, and Marc Olefs2 Kay Helfricht et al.
  • 1IGF – Institute for Interdisciplinary Mountain Research, Austrian Academy of Sciences, Innsbruck, 6020, Austria
  • 2ZAMG – Zentralanstalt für Meteorologie und Geodynamik, Climate research department, 1190 Vienna, Austria
  • 3WSL Institute for Snow and Avalanche Research SLF, 7260 Davos, Switzerland

Abstract. 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 68kgm−3, with a standard deviation of 9kgm−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.

Download & links
Publications Copernicus
Download
Short summary
We calculated hourly new snow densities from automated measurements. This time interval reduces the influence of settling of the freshly deposited snow. We found an average new snow density of 68 kg m−3. The observed variability could not be described using different parameterizations, but a relationship to temperature is partly visible at hourly intervals. Wind speed is a crucial parameter for the inter-station variability. Our findings are relevant for snow models working on hourly timescales.
We calculated hourly new snow densities from automated measurements. This time interval reduces...
Citation
Share