Preprints
https://doi.org/10.5194/egusphere-2025-5872
https://doi.org/10.5194/egusphere-2025-5872
04 Feb 2026
 | 04 Feb 2026
Status: this preprint is open for discussion and under review for Geoscientific Model Development (GMD).

Dynamic drag partitioning in GEOS-Chem (v. 14.2.3) eliminatessource function and tuning, revealing equifinality of atmosphericdust observations

Boyan Liu, Hongquan Song, Adrian Chappell, and Zhuoli Zhou

Abstract. Large surface roughness elements (typically vegetation) extract momentum from near-surface winds partitioning it between the vegetation canopy and the unsheltered soil surface, altering the spatial distribution and intensity of dust emission. Data for global drag partition varying over space and time are limited and classical dust models often adopt simplified assumptions or neglect the effect of roughness entirely, relying instead on empirical dust source function to reproduce observed atmospheric dust. Such approaches ignore the three-dimensional spatiotemporal sheltering provided by vegetation and the soil roughness which limits the physical fidelity and predictive capability of dust models. Here we implement the global sheltering parameterization based on surface albedo data in the dust emission scheme of a global atmospheric chemical transport model and evaluate its impact on simulated global dust emissions. We compare simulations from this sheltering parameterization with default settings from classical dust modelling and validate our results against atmospheric dust observations following the widely accepted approach. This is the first study to evaluate the performance of the albedo-based sheltering parameterization globally. The approach eliminates the need for an empirical source function to constrain sources and avoids the need to tune dust emission models. It produces atmospheric dust loadings consistent with atmospheric dust observations despite substantially altering the frequency and spatial pattern of dust emissions. Evidently, different patterns of dust emission frequency can produce similar atmospheric dust loadings, revealing that previous studies intent on reproducing general patterns of large-scale atmospheric dust burden have overlooked the equifinality of dust emission frequency. Accurate dust emission magnitude and frequency remain hampered by entrainment threshold fixed over space, static over time with endless sediment supply, consistent with all other models.

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Boyan Liu, Hongquan Song, Adrian Chappell, and Zhuoli Zhou

Status: open (until 01 Apr 2026)

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Boyan Liu, Hongquan Song, Adrian Chappell, and Zhuoli Zhou
Boyan Liu, Hongquan Song, Adrian Chappell, and Zhuoli Zhou

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Short summary
We studied how vegetation and soil roughness shape released dust. Conceptualising light reflected from the land surface to represent wind sheltering, we improved a global dust model. This approach removes the need for guesswork about where dust comes from and still matches observed dust in the atmosphere. It also shows that different paths can lead to similar dust levels, which encourages better ways to track how often dust is lifted. This helps guide efforts to predict dust and its impacts.
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