Next Article in Journal
Modeling Dry-Snow Densification without Abrupt Transition
Next Article in Special Issue
Generating Observation-Based Snow Depletion Curves for Use in Snow Cover Data Assimilation
Previous Article in Journal
Comment on “Non-Mineralized Fossil Wood” by George E. Mustoe (Geosciences, 2018)
Previous Article in Special Issue
Analysis of QualitySpec Trek Reflectance from Vertical Profiles of Taiga Snowpack
Open AccessArticle

Geometric Versus Anemometric Surface Roughness for a Shallow Accumulating Snowpack

1
Geosciences, Colorado State University, Fort Collins, CO 80523-1482, USA
2
Natural Resources Ecology Laboratory, Colorado State University, Fort Collins, CO 80523-1499, USA
3
ESS-Watershed Science, Colorado State University, Fort Collins, CO 80523-1476, USA
4
Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO 80523-1375, USA
5
Now with Xcel Energy, 1800 Larimer St, Denver, CO 80202, USA
6
Colorado Water Science Center, U.S. Geological Survey, Lakewood, CO 80225, USA
7
Horticulture and Landscape Architecture, Colorado State University, Fort Collins, CO 80523, USA
8
Mathematics, Colorado State University, Fort Collins, CO 80523, USA
*
Author to whom correspondence should be addressed.
Geosciences 2018, 8(12), 463; https://doi.org/10.3390/geosciences8120463
Received: 2 November 2018 / Revised: 28 November 2018 / Accepted: 1 December 2018 / Published: 6 December 2018
(This article belongs to the Special Issue Remote Sensing of Snow and Its Applications)
When applied to a snow-covered surface, aerodynamic roughness length, z0, is typically considered as a static parameter within energy balance equations. However, field observations show that z0 changes spatially and temporally, and thus z0 incorporated as a dynamic parameter may greatly improve models. To evaluate methods for characterizing snow surface roughness, we compared concurrent estimates of z0 based on (1) terrestrial light detection and ranging derived surface geometry of the snowpack surface (geometric, z0G) and (2) vertical wind profile measurements (anemometric, z0A). The value of z0G was computed from Lettau’s equation and underestimated z0A but compared well when scaled by a factor of 2.34. The Counihan method for computing z0G was found to be unsuitable for estimating z0 on a snow surface. During snowpack accumulation in early winter, z0 varied as a function of the snow-covered area (SCA). Our results show that as the SCA increases, z0 decreases, indicating there is a topographic influence on this relation. View Full-Text
Keywords: aerodynamic roughness length; terrestrial lidar; snow surface topography; wind profile; snow energy balance; snow accumulation aerodynamic roughness length; terrestrial lidar; snow surface topography; wind profile; snow energy balance; snow accumulation
Show Figures

Figure 1

MDPI and ACS Style

Sanow, J.E.; Fassnacht, S.R.; Kamin, D.J.; Sexstone, G.A.; Bauerle, W.L.; Oprea, I. Geometric Versus Anemometric Surface Roughness for a Shallow Accumulating Snowpack. Geosciences 2018, 8, 463.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop