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Exploration of a geometric approach for estimating snow surface roughness

Abstract

dc:description.abstract

The roughness of a surface that influences atmospheric turbulence is estimated as the aerodynamic roughness length (Z0), and is used to understand the flow of air, temperature, and moisture over a surface. Z0 is a critical variable for estimating latent and sensible fluxes at the surface, but most land surface models treat Z0 simply as a function of land cover and do not address the variability of this value, such as due to changing snow surfaces. This is due in large part to the difficulty and cost of obtaining reliable estimates of Z0 under field conditions. This work addresses the need for versatile methods to evaluate snow surface roughness on a plot-scale. This study used anemometric data from a meteorological tower near Fort Collins, Colorado over two winters (2013-2014). Thorough screening yielded 153 wind-speed profiles which were used to calculate the aerodynamic roughness length at different times and under different snow conditions. The anemometric Z0 values observed in this study with changing surface conditions ranged by 2.5 orders of magnitude from 0.2 to 52 x 10-3m. Concurrently, a terrestrial laser scanner was used periodically to measure surface geometry and generate point clouds across the study site. Point clouds were processed and interpolated onto a regular grid for estimation of Z0 based on the geometry and distribution of surface roughness elements. Two different geometric evaluations, the Lettau and Counihan methods, were used for the estimation of Z0. The estimates based on surface geometry were evaluated and compared to anemometric Z0 values calculated from field observations of wind turbulence across the surface of the study site. The Lettau method Z0 values compared well to the measured anemometric results, with low but acceptable Nash-Sutcliffe Efficiency Coefficient (NSE) of 0.14 and a strong coefficient of determination (R2 = 0.90). While the NSE was small, the Lettau Z0¬ values could easily be scaled to the anemometric Z0. The Counihan method yielded less accurate results compared to the anemometric data, with a NSE of -1.1. The data also showed a strong correlation between Z0 and changing snow cover. The coefficient of determination between Z0 and snow-covered area for both the anemometric and Lettau methods was greater than 0.7, indicating that both methods responded well to changing surface conditions.

Degree

thesis:*
Name thesis:degree_name
Master of Science (M.S.)
Level thesis:degree_level
Masters
Discipline thesis:degree_discipline
Ecosystem Science and Sustainability
Grantor dc:publisher
Colorado State University. Libraries
Year dc:date.issued
2015

Author and committee

dc:creator, dc:contributor.*
Authors dc:creator
  • Kamin, David Jeffrey, author
  • Fassnacht, Steven R., advisor
  • Stednick, John D., committee member
  • Bauerle, William, committee member

Subjects

dc:subject × 4

Rights

dc:rights
Statement dc:rights
  • Copyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
Language dc:language.iso
eng, English

Identifiers

dc:identifier.*
OAI identifier oai:identifier
oai:mountainscholar.org:10217/170391

Chain of custody

source
Harvested from
Colorado State University
Base URL
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Last updated
2026-07-27
Source record
OAI-PMH GetRecord
citation

Kamin, David Jeffrey, author; Fassnacht, Steven R., advisor; Stednick, John D., committee member; Bauerle, William, committee member. Exploration of a geometric approach for estimating snow surface roughness. Masters thesis, Colorado State University. Libraries, 2015. http://hdl.handle.net/10217/170391