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ARS Home » Pacific West Area » Boise, Idaho » Northwest Watershed Research Center » Research » Publications at this Location » Publication #246919

Title: Simple and Computationally Efficient Modeling of Surface Wind Speeds Over Heterogeneous Terrain

item Winstral, Adam
item Marks, Daniel
item GURNEY, ROBERT - University Of Reading

Submitted to: Trans American Geophysical Union
Publication Type: Abstract Only
Publication Acceptance Date: 10/1/2009
Publication Date: N/A
Citation: N/A

Interpretive Summary: Wind plays an important role in determining snow distribution and energy fluxes. In mountainous regions wind speeds are strongly variable. Exposed windy areas have very little snow accumulation whereas sheltered areas accumulate snow that lasts into the spring/summer months supporting vegetation demands. The disparate snow distribution strongly affects stream discharge and vegetation patterns. While the complexities of winds severely challenge numerical solutions, it is known that terrain structure and vegetation do play a substantial role in modifying wind speeds and consequent snow distribution. This work created computationally efficient methods of distributing point measures of wind and precipitation based on terrain shape and vegetation cover.

Technical Abstract: Wind speeds vary dramatically over short distances in mountain settings. Snow distribution is strongly affected by these disparate winds with drifts containing meters of snow-water-equivalence (SWE) often found adjacent to windward slopes containing minimal amounts of SWE. The heterogeneous snow distribution effects runoff, soil moisture, and vegetation patterns. Capturing these gradients in models is difficult due to the inherent complexity of wind fields and a general lack of data from high elevation, wind-exposed locations. This study was conducted in the Reynolds Mountain East research basin in southwest Idaho, USA. The basin is uniquely instrumented with a network of automated wind and snow depth sensors that capture a large range of variability. Additional manual snow surveys were conducted twice a year that captured the full gradient of snow distribution present in the basin. This unique dataset formed the foundation for establishing relationships between the variables of interest and readily available terrain and vegetation data. A significant relationship between upwind terrain structure and wind speed was established and further validated at two other sites. Snow accumulation rates were related to wind speed and terrain structure. Computationally efficient methods for distributing wind speed and snow accumulation from single point measurements were established from these findings. The algorithms were used to derive the spatial forcing fields for a distributed mass and energy balance snow model with effective results.