Exploration of a geometric approach for estimating snow surface roughness
Date
2015
Authors
Kamin, David Jeffrey, author
Fassnacht, Steven R., advisor
Stednick, John D., committee member
Bauerle, William, committee member
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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.
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Subject
aerodynamic roughness length
anemometric
geometric
snow