Abstract. Roughness features (e.g., rocks, vegetation, furrows) that shelter or attenuate wind flow over the soil surface can considerably affect the magnitude and spatial distribution of sediment transport in active aeolian environments. Existing dust and sediment transport models often rely on vegetation attributes derived from static land use datasets or remotely sensed greenness indicators to incorporate sheltering effects on simulated particle mobilization. However, these overly simplistic approaches do not represent the three-dimensional nature or spatiotemporal changes of roughness element sheltering. They also ignore the sheltering contribution of non-vegetation roughness features and photosynthetically inactive (i.e., brown) vegetation common to dryland environments. Here, we explore the use of a novel albedo-based sheltering parameterization in a dust transport modeling application of the Weather Research and Forecasting model with Chemistry (WRF-Chem). The albedo method estimates sheltering effects on surface wind friction speeds and dust entrainment from the shadows cast by subgrid-scale roughness elements. For this study, we applied the albedo-derived drag partition to the Air Force Weather Agency (AFWA) dust emission module and conducted a sensitivity study on simulated PM10 concentrations using the Georgia Institute of Technology–Goddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) model as implemented in WRF-Chem v4.1. Our analysis focused on a convective dust event case study from 3–4 July 2014 for the southwestern United States desert region discussed by other published works. Previous studies have found that WRF-Chem simulations grossly overestimated the dust transport associated with this event. Our results show that removing the default erodibility map and adding the drag parameterization to the AFWA dust module markedly improved the overall magnitude and spatial pattern of simulated dust conditions for this event. Simulated PM10 values near the leading edge of the storm substantially decreased in magnitude (e.g., maximum PM10 values were reduced from 17 151 to 8539 µg m−3), bringing the simulated results into alignment with the observed PM10 measurements. Furthermore, the addition of the drag partition restricted the erroneous widespread dust emission of the original model configuration. We also show that similar model improvements can be achieved by replacing the wind friction speed parameter in the original dust emission module with globally scaled surface wind speeds, suggesting that a well-tuned constant could be used as a substitute for the albedo-based product for short-duration simulations in which surface roughness is not expected to change and for landscapes wherein roughness is constant over years to months. Though this alternative scaling method requires less processing, knowing how to best tune the model winds a priori could be a considerable challenge. Overall, our results demonstrate how dust transport simulation and forecasting with the AFWA dust module can be improved in vegetated drylands by calculating the dust emission flux with surface wind friction speed from a drag partition treatment.

Employing numerical prediction models can be a powerful tool for forecasting air quality and visibility hazards related to dust events. However, these numerical models are sensitive to surface conditions. Roughness features (e.g., rocks, vegetation, furrows, etc.) that shelter or attenuate wind flow over the soil surface affect the magnitude and spatial distribution of dust emission. To aide in simulating the emission phase of dust transport, we used a previously published albedo-based drag partition parameterization to better represent the component of wind friction speed affecting the immediate soil sur-face. This report serves as a guide for integrating this parameterization into the Weather Research and Forecasting with Chemistry (WRF-Chem) model. We include the procedure for preprocessing the required input data, as well as the code modifications for the Air Force Weather Agency (AFWA) dust emission module. In addition, we provide an example demonstration of output data from a simulation of a dust event that occurred in the Southwestern United States, which incorporates use of the drag partition.

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