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Statistical properties of fresh snow roughness
Author(s) -
Manes C.,
Guala M.,
Löwe H.,
Bartlett S.,
Egli L.,
Lehning M.
Publication year - 2008
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/2007wr006689
Subject(s) - snow , scaling , surface finish , surface roughness , scale (ratio) , length scale , roughness length , meteorology , environmental science , materials science , optics , statistical physics , mathematics , geometry , physics , mechanics , wind speed , quantum mechanics , wind profile power law , composite material
We present results from a series of experiments in which fresh snow roughness was measured by means of digital photography and analyzed using the random field approach. The aim of the paper is to investigate the scaling properties of fresh‐snow‐covered surfaces and to capture key roughness length scales which can characterize the surface geometry and the size of the snow crystals. Results from our experiments show the following: (1) fresh snow roughness exhibits two distinguished scaling regimes, one at scales comparable with the crystals size and another one at larger scales; (2) we confirm that the large scales are built up during snowfall and their scaling behavior is consistent with that of Ballistic Deposition (BD) processes; and (3) we suggest that the crossover length scale separating the two scaling regimes effectively defines a representative length scale of the aggregated snow crystals on the surface. The definition of this length scale is independent of the difficulties associated with measuring snow grain sizes by means of standard microscopic analysis of disaggregated crystals. Furthermore it can be obtained from a low‐cost and quick experimental procedure. Results from this study provide a plausible justification for the wide scatter of aerodynamic roughness length values encountered in the literature for fresh snow. Moreover, they provide insight on the key roughness length scales which should be used for the modeling of this parameter.