Comparison of aerodynamically and model-derived roughness lengths (zo) over diverse surfaces, central Mojave Desert, California, USA

The vulnerability of dryland surfaces to wind erosion depends importantly on the absence or the presence and character of surface roughness elements, such as plants, clasts, and topographic irregularities that diminish wind speed near the surface. A model for the friction velocity ratio has been developed to account for wind sheltering by many different types of co-existing roughness elements. Such conditions typify a monitored area in the central Mojave Desert, California, that experiences frequent sand movement and dust emission. Two additional models are used to convert the friction velocity ratio to the surface roughness length (zo) for momentum. To calculate roughness lengths from these models, measurements were made at 11 sites within the monitored area to characterize the surface roughness element. Measurements included (1) the number of roughness species (e.g., plants, small-scale topography, clasts), and their associated heights and widths, (2) spacing among species, and (3) vegetation porosity (a measurement of the spatial distribution of woody elements of a plant). Documented or estimated values of drag coefficients for different species were included in the modeling. At these sites, wind-speed profiles were measured during periods of neutral atmospheric stability using three 9-m towers with three or four calibrated anemometers on each. Modeled roughness lengths show a close correspondence (correlation coefficient, 0.84–0.86) to the aerodynamically determined values at the field sites. ometric properties of the roughness elements in the model are amenable to measurement at much higher temporal and spatial resolutions using remote-sensing techniques than can be accomplished through laborious ground-based methods. A remote-sensing approach to acquire values of the modeled roughness length is particularly important for the development of linked surface/atmosphere wind-erosion models sensitive to climate variability and land-use changes in areas such as the southwestern United States, where surface roughness has large spatial and temporal variations.