Articles | Volume 22, issue 5
https://doi.org/10.5194/hess-22-2655-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-22-2655-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Obtaining sub-daily new snow density from automated measurements in high mountain regions
IGF – Institute for Interdisciplinary Mountain Research, Austrian
Academy of Sciences, Innsbruck, 6020, Austria
Lea Hartl
IGF – Institute for Interdisciplinary Mountain Research, Austrian
Academy of Sciences, Innsbruck, 6020, Austria
Roland Koch
ZAMG – Zentralanstalt für Meteorologie und Geodynamik, Climate
research department, 1190 Vienna, Austria
Christoph Marty
WSL Institute for Snow and Avalanche Research SLF, 7260 Davos,
Switzerland
Marc Olefs
ZAMG – Zentralanstalt für Meteorologie und Geodynamik, Climate
research department, 1190 Vienna, Austria
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29 citations as recorded by crossref.
- Using snow depth observations to provide insight into the quality of snowpack simulations for regional-scale avalanche forecasting S. Horton & P. Haegeli 10.5194/tc-16-3393-2022
- Load-bearing tests and simulation analysis of compacted loose snow E. Xiao et al. 10.1016/j.conbuildmat.2024.135681
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- Towards large-scale daily snow density mapping with spatiotemporally aware model and multi-source data H. Wang et al. 10.5194/tc-17-33-2023
- Statistical post-processing of ensemble forecasts of the height of new snow J. Nousu et al. 10.5194/npg-26-339-2019
- Forcing and evaluating detailed snow cover models with stratigraphy observations L. Viallon-Galinier et al. 10.1016/j.coldregions.2020.103163
- Spatio-Temporal Characteristics and Differences in Snow Density between the Tibet Plateau and the Arctic W. Zhao et al. 10.3390/rs15163976
- Assessment of Snowmaking Conditions Based on Meteorological Reconstruction in the Beijing–Zhangjiakou Mountain Area of North China in 1978–2017 J. Chen et al. 10.1175/JAMC-D-20-0172.1
- An empirical model to calculate snow depth from daily snow water equivalent: SWE2HS 1.0 J. Aschauer et al. 10.5194/gmd-16-4063-2023
- Numerical Simulation and Forecasting Model of Snow Drift Hazard in Yanchong Expressway with Embankment Form Y. Chen et al. 10.1088/1742-6596/2337/1/012004
- Diverging snowfall trends across months and elevation in the northeastern Italian Alps G. Bertoldi et al. 10.1002/joc.8002
- SnowPappus v1.0, a blowing-snow model for large-scale applications of the Crocus snow scheme M. Baron et al. 10.5194/gmd-17-1297-2024
- Deposition of light-absorbing particles in glacier snow of the Sunderdhunga Valley, the southern forefront of the central Himalayas J. Svensson et al. 10.5194/acp-21-2931-2021
- Firn on ice sheets C. Amory et al. 10.1038/s43017-023-00507-9
- Multi-decadal observations in the Alps reveal less and wetter snow, with increasing variability C. Marty et al. 10.3389/feart.2023.1165861
- Exploring the use of multi-source high-resolution satellite data for snow water equivalent reconstruction over mountainous catchments V. Premier et al. 10.5194/tc-17-2387-2023
- Spatial and temporal variability in snow density across the Northern Hemisphere W. Zhao et al. 10.1016/j.catena.2023.107445
- Measurement of specific surface area of fresh solid precipitation particles in heavy snowfall regions of Japan S. Yamaguchi et al. 10.5194/tc-13-2713-2019
- Elements of future snowpack modeling – Part 2: A modular and extendable Eulerian–Lagrangian numerical scheme for coupled transport, phase changes and settling processes A. Simson et al. 10.5194/tc-15-5423-2021
- Snow water equivalents exclusively from snow depths and their temporal changes: the Δsnow model M. Winkler et al. 10.5194/hess-25-1165-2021
- (Near) Real-Time Snow Water Equivalent Observation Using GNSS Refractometry and RTKLIB L. Steiner et al. 10.3390/s22186918
- Impact of GPS Processing on the Estimation of Snow Water Equivalent Using Refracted GPS Signals L. Steiner et al. 10.1109/TGRS.2019.2934016
- Snow albedo and its sensitivity to changes in deposited light-absorbing particles estimated from ambient temperature and snow depth observations at a high-altitude site in the Himalaya J. Ström et al. 10.1525/elementa.2021.00118
- Predicting new snow density in the Italian Alps: A variability analysis based on 10 years of measurements M. Valt et al. 10.1002/hyp.13249
- Relationship between newly fallen snow density and degree of riming estimated by particles’ fall speed in Niigata Prefecture, Japan K. Takami et al. 10.3178/hrl.16.87
- The impacts of vegetation on the soil surface freezing-thawing processes at permafrost southern edge simulated by an improved process-based ecosystem model Z. Liu et al. 10.1016/j.ecolmodel.2021.109663
- Monitoring snow water equivalent using the phase of RFID signals M. Le Breton et al. 10.5194/tc-17-3137-2023
- Robust uncertainty assessment of the spatio-temporal transferability of glacier mass and energy balance models T. Zolles et al. 10.5194/tc-13-469-2019
- Assimilating snow observations to snow interception process simulations Z. Lv & J. Pomeroy 10.1002/hyp.13720
Discussed (preprint)
Latest update: 14 Dec 2024
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...