Articles | Volume 8, issue 2
https://doi.org/10.5194/tc-8-521-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/tc-8-521-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
27 Mar 2014
Research article |
| 27 Mar 2014
Modeling bulk density and snow water equivalent using daily snow depth observations
J. L. McCreight
Aerospace Engineering Sciences, Campus Box 399, University of Colorado, Boulder, CO 80309, USA
E. E. Small
Department of Geology, Campus Box 399, University of Colorado, Boulder, CO 80309, USA
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Colin R. Meyer and Ian J. Hewitt
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Emmy E. Stigter, Niko Wanders, Tuomo M. Saloranta, Joseph M. Shea, Marc F. P. Bierkens, and Walter W. Immerzeel
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Xicai Pan, Daqing Yang, Yanping Li, Alan Barr, Warren Helgason, Masaki Hayashi, Philip Marsh, John Pomeroy, and Richard J. Janowicz
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Francesco Avanzi, Hiroyuki Hirashima, Satoru Yamaguchi, Takafumi Katsushima, and Carlo De Michele
The Cryosphere, 10, 2013–2026, https://doi.org/10.5194/tc-10-2013-2016, https://doi.org/10.5194/tc-10-2013-2016, 2016
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Thomas Skaugen and Ingunn H. Weltzien
The Cryosphere, 10, 1947–1963, https://doi.org/10.5194/tc-10-1947-2016, https://doi.org/10.5194/tc-10-1947-2016, 2016
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In hydrological models it is important to properly simulate the spatial distribution of snow water equivalent (SWE) for the timing of spring melt floods and the accounting of energy fluxes. This paper describes a method for the spatial distribution of SWE which is parameterised from observed spatial variability of precipitation and has hence no calibration parameters. Results show improved simulation of SWE and the evolution of snow-free areas when compared with the standard method.
Florian Hanzer, Kay Helfricht, Thomas Marke, and Ulrich Strasser
The Cryosphere, 10, 1859–1881, https://doi.org/10.5194/tc-10-1859-2016, https://doi.org/10.5194/tc-10-1859-2016, 2016
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The hydroclimatological model AMUNDSEN is set up to simulate snow and ice accumulation, ablation, and runoff for a study region in the Ötztal Alps (Austria) in the period 1997–2013. A new validation concept is introduced and demonstrated by evaluating the model performance using several independent data sets, e.g. snow depth measurements, satellite-derived snow maps, lidar data, glacier mass balances, and runoff measurements.
Sarah S. Thompson, Bernd Kulessa, Richard L. H. Essery, and Martin P. Lüthi
The Cryosphere, 10, 433–444, https://doi.org/10.5194/tc-10-433-2016, https://doi.org/10.5194/tc-10-433-2016, 2016
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We show that strong electrical self-potential fields are generated in melting in in situ snowpacks at Rhone Glacier and Jungfraujoch Glacier, Switzerland. We conclude that the electrical self-potential method is a promising snow and firn hydrology sensor, owing to its suitability for sensing lateral and vertical liquid water flows directly and minimally invasively, complementing established observational programs and monitoring autonomously at a low cost.
Z. Zheng, P. B. Kirchner, and R. C. Bales
The Cryosphere, 10, 257–269, https://doi.org/10.5194/tc-10-257-2016, https://doi.org/10.5194/tc-10-257-2016, 2016
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By analyzing high-resolution lidar products and using statistical methods, we quantified the snow depth dependency on elevation, slope and aspect of the terrain and also the surrounding vegetation in four catchment size sites in the southern Sierra Nevada during snow peak season. The relative importance of topographic and vegetation attributes varies with elevation and canopy, but all these attributes were found significant in affecting snow distribution in mountain basins.
L. Scaff, D. Yang, Y. Li, and E. Mekis
The Cryosphere, 9, 2417–2428, https://doi.org/10.5194/tc-9-2417-2015, https://doi.org/10.5194/tc-9-2417-2015, 2015
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The bias corrections show significant errors in the gauge precipitation measurements over the northern regions. Monthly precipitation is closely correlated between the stations across the Alaska--Yukon border, particularly for the warm months. Double mass curves indicate changes in the cumulative precipitation due to bias corrections over the study period. Overall the bias corrections lead to a smaller and inverted precipitation gradient across the border, especially for snowfall.
R. Chen, J. Liu, E. Kang, Y. Yang, C. Han, Z. Liu, Y. Song, W. Qing, and P. Zhu
The Cryosphere, 9, 1995–2008, https://doi.org/10.5194/tc-9-1995-2015, https://doi.org/10.5194/tc-9-1995-2015, 2015
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The catch ratio of Chinese standard precipitation gauge vs. wind speed relationship for different precipitation types was well quantified by cubic polynomials and exponential functions using 5-year field data in the high-mountain environment of the Tibetan Plateau. The daily precipitation measured by shielded gauges increases linearly with that of unshielded gauges. The pit gauge catches the most local precipitation in rainy season and could be used as a reference in most regions of China.
A. Hedrick, H.-P. Marshall, A. Winstral, K. Elder, S. Yueh, and D. Cline
The Cryosphere, 9, 13–23, https://doi.org/10.5194/tc-9-13-2015, https://doi.org/10.5194/tc-9-13-2015, 2015
J. Revuelto, J. I. López-Moreno, C. Azorin-Molina, and S. M. Vicente-Serrano
The Cryosphere, 8, 1989–2006, https://doi.org/10.5194/tc-8-1989-2014, https://doi.org/10.5194/tc-8-1989-2014, 2014
E. Kantzas, S. Quegan, M. Lomas, and E. Zakharova
The Cryosphere, 8, 487–502, https://doi.org/10.5194/tc-8-487-2014, https://doi.org/10.5194/tc-8-487-2014, 2014
S. Jörg-Hess, F. Fundel, T. Jonas, and M. Zappa
The Cryosphere, 8, 471–485, https://doi.org/10.5194/tc-8-471-2014, https://doi.org/10.5194/tc-8-471-2014, 2014
G. A. Sexstone and S. R. Fassnacht
The Cryosphere, 8, 329–344, https://doi.org/10.5194/tc-8-329-2014, https://doi.org/10.5194/tc-8-329-2014, 2014
R. Mott, L. Egli, T. Grünewald, N. Dawes, C. Manes, M. Bavay, and M. Lehning
The Cryosphere, 5, 1083–1098, https://doi.org/10.5194/tc-5-1083-2011, https://doi.org/10.5194/tc-5-1083-2011, 2011
R. Mott, M. Schirmer, M. Bavay, T. Grünewald, and M. Lehning
The Cryosphere, 4, 545–559, https://doi.org/10.5194/tc-4-545-2010, https://doi.org/10.5194/tc-4-545-2010, 2010
S. H. Mernild, I. M. Howat, Y. Ahn, G. E. Liston, K. Steffen, B. H. Jakobsen, B. Hasholt, B. Fog, and D. van As
The Cryosphere, 4, 453–465, https://doi.org/10.5194/tc-4-453-2010, https://doi.org/10.5194/tc-4-453-2010, 2010
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