Application of a parameterization based on satellite-retrieved sheltering for dust event simulation with WRF-Chem v4.1

Authors: LEGRAND, SANDRA - Environmental Laboratory, Us Army Engineer Research And Development Center, Waterways Experiment St; LETCHER, THEODORE - Environmental Laboratory, Us Army Engineer Research And Development Center, Waterways Experiment St; OKIN, GREGORY - University Of California (UCLA); WEBB, NICHOLAS - New Mexico State University; GALLAGHER, ALEX - Environmental Laboratory, Us Army Engineer Research And Development Center, Waterways Experiment St; DHITAL, SAROJ - New Mexico State University; HODGDON, TAYLOR - Environmental Laboratory, Us Army Engineer Research And Development Center, Waterways Experiment St; ZIEGLER, NANCY - Environmental Laboratory, Us Army Engineer Research And Development Center, Waterways Experiment St; MICHAELS, MICHELLE - Environmental Laboratory, Us Army Engineer Research And Development Center, Waterways Experiment St; CHAPPELL, ADRIAN - Cardiff University

Submitted to: Geoscientific Model Development
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/6/2023
Publication Date: 2/9/2023
Citation: LeGrand, S.L., Letcher, T.W., Okin, G.S., Webb, N.P., Gallagher, A.R., Dhital, S., Hodgdon, T.S., Ziegler, N.P., Michaels, M.L., Chappell, A. 2023. Application of a parameterization based on satellite-retrieved sheltering for dust event simulation with WRF-Chem v4.1. Geoscientific Model Development. 16(3):1009–1038. https://doi.org/10.5194/gmd-16-1009-2023.
DOI: https://doi.org/10.5194/gmd-16-1009-2023

Interpretive Summary: Roughness features (e.g., rocks, vegetation, furrows, etc.) that reduce wind speeds at the soil surface can considerably affect wind erosion. Current models often rely on vegetation attributes from land-use datasets or remotely-sensed greenness indicators to represent vegetation effects on wind erosion. However, these overly simplistic approaches do not represesnt the three-dimensional nature or changes across space and through time of roughness elements. They also ignore the effects of non-vegetation roughness features and photosynthetically-inactive (i.e., brown) vegetation common in drylands. Here, we explore the use of a surfce albedo-based approach to represent roughness effects in a dust transport modeling application of the Air Force Weather Agency (AFWA) dust model in the Weather Research and Forecasting model with Chemistry (WRF-Chem). Our analysis focused on a convective dust event case study from 3-4 July 2014 for the southwest United States desert region. 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 albedo-based approach to model markedly improved the amount 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 reduced from 17,151 µg m-3 to 8,539 µg m-3), bringing the simulated results into alignment with the observed PM10 measurements. We show that similar model improvements can be achieved by replacing the wind friction speed parameter in the original dust model with globally-scaled surface wind speeds, suggesting that a well-tuned constant could be used as a substitute for the albedo-based product for event-based simulations where surface roughness is not expected to change and for landscapes where roughness is constant over years to months. Overall, our results demonstrate how dust 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.

Technical Abstract: Roughness features (e.g., rocks, vegetation, furrows, etc.) 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 represesnt 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 southwest 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 reduced from 17,151 µg m-3 to 8,539 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 where surface roughness is not expected to change and for landscapes where 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.