TY - CONF T1 - Surface shear velocity estimates in a sparsely vegetated rangeland landscape T2 - AGU 2023 Fall Meeting: Wide. Open. Science. Y1 - 2023 A1 - Zhang, P. A1 - Edwards, B.L. A1 - Webb, N.P. A1 - Ziegler, N.P. A1 - Van Zee, J.W. A1 - Wheeler, B. A1 - Okin, G.S. A1 - Gillies, J. KW - landscape KW - rangeland KW - sparsely KW - surface shear KW - vegetated KW - velocity estimates AB -

Accurate estimates of shear velocity at the soil surface are critical to understanding aeolian processes in vegetated landscapes—where momentum from the wind is partitioned among plants, other roughness elements, and erodible sediments. Shear velocities estimated from wind speed profiles extending above the canopy are not ideal for characterizing conditions at the sediment bed because they include the influence of vegetation on the wind field. Sonic anemometers have been used to estimate shear velocity on largely unvegetated, homogenous surfaces or for eddy covariance applications above the canopy. Shear velocity estimates from sonic anemometers, however, are susceptible to errors from instrument tilt, slope, and complex terrain or roughness. Raw u, v, and w wind vectors are typically reoriented to wind streamlines using one of three methods, double rotation, triple rotation, or planar fit, each of which has limitations depending on meteorological conditions and site complexity. Another recent approach uses invariants of the Reynolds stress tensor to estimate shear velocity without the need for tilt corrections. Here, we evaluate shear velocity estimates from the four methods for sonic anemometers deployed adjacent to a honey mesquite (Prosopis glandulosa Torr.) shrub from October 2022 to July 2023 and compare with estimates from collocated Irwin sensors deployed flush with the soil surface. Shear velocities estimated using the Reynolds stress tensor method were in general slightly larger over the study period (~6–7%) and exhibited the most variability among methods, but results confirm the suitability of the method for aeolian studies in sparsely vegetated landscapes. Shear velocity also varied significantly with wind direction and position relative to the shrub. We map shear velocity estimates from anemometers and Irwin sensors by wind speed and direction. Results suggest including the lateral influence of vegetation could improve drag partition estimates.

JF - AGU 2023 Fall Meeting: Wide. Open. Science. CY - San Francisco, California ER - TY - JOUR T1 - Plant phenology drives seasonal changes in shear stress partitioning in a semi-arid rangeland JF - Agricultural and Forest Meteorology Y1 - 2023 A1 - Ziegler, N.P. A1 - Webb, N.P. A1 - Gillies, J.A. A1 - Edwards, B.L. A1 - Nikolich, G. A1 - Van Zee, J.W. A1 - Cooper, B.F. A1 - Browning, D.M. A1 - Courtright, E.M. A1 - LeGrand, S.L. KW - aerodynamic roughness KW - Drag partition KW - Shear stress ratio KW - Surface shear velocity AB -

Accurate representation of surface roughness in predictive models of aeolian sediment transport and dust emission is required for model accuracy and for models to inform wind erosion management. While past wind tunnel and field studies have examined roughness effects on drag partitioning, the spatial and temporal variability of surface shear velocity and the shear stress ratio remain poorly described. Here, we use a four-month dataset of total shear velocity (u*) and soil surface shear velocity (us*) measurements to examine the spatiotemporal variability of the shear stress ratio (R) before, during, and after vegetation green-up at a honey mesquite (Prosopis glandulosa Torr.) shrub-invaded grassland in the Chihuahuan Desert, New Mexico, USA. Results show that vegetation green-up, the emergence of leaves, led to increased drag and surface aerodynamic sheltering and a reduction in us* and R magnitude and variability. We found that us* decreased from 20% to 5% of u* as the vegetation form drag and its sheltering effect increased. Similarly, the spatiotemporal variability of R was found to be linked directly to plant phenological phases. We conclude that drag partition schemes should incorporate seasonal vegetation change, via dynamic drag coefficients and/or R, to accurately predict the timing and magnitude of seasonal aeolian sediment fluxes. The drag partition response to mesquite phenological phases also provided insight to potential mesquite herbicide treatment effects which, if successful, could increase wind erosivity and the onsite and downwind impacts of wind erosion unless protection by herbaceous plants is maintained.

VL - 330 ER - TY - JOUR T1 - Scale invariance of albedo‐based wind friction velocity JF - Journal of Geophysical Research: Atmospheres Y1 - 2020 A1 - Ziegler, N.P. A1 - Webb, N.P. A1 - Chappell, A. A1 - LeGrand, S.L. KW - aeolian KW - aerodynamic roughness KW - Albedo KW - dust KW - friction velocity KW - satellite remote sensing AB -

Obtaining reliable estimates of aerodynamic roughness is necessary to interpret and accurately predict aeolian sediment transport dynamics. However, inherent uncertainties in field measurements and models of surface aerodynamic properties continue to undermine aeolian research, monitoring, and dust modeling. A new relation between aerodynamic shelter and land surface shadow has been established at the wind tunnel scale, enabling the potential for estimates of wind erosion and dust emission to be obtained across scales from albedo data. Here, we compare estimates of wind friction velocity (u*) derived from traditional methods (wind speed profiles) with those derived from the albedo model at two separate scales using bare soil patch (via net radiometers) and landscape (via Moderate Resolution Imaging Spectroradiometer [MODIS] 500 m) data sets. Results show that profile‐derived estimates of u* are highly variable in anisotropic surface roughness due to changes in wind direction and fetch. Wind speed profiles poorly estimate soil surface (bed) wind friction velocities necessary for aeolian sediment transport research and modeling. Albedo‐based estimates of u* at both scales have small variability because the estimate is integrated over a defined, fixed area and resolves the partition of wind momentum between roughness elements and the soil surface. We demonstrate that the wind tunnel‐based calibration of albedo for predicting wind friction velocities at the soil surface (us*) is applicable across scales. The albedo‐based approach enables consistent and reliable drag partition correction across scales for model and field estimates of us* necessary for wind erosion and dust emission modeling.

VL - 125 ER -