Vegetation is a major control on dust emission because it extracts momentum from the wind and shelters the soil surface, protecting dry and loose material from erosion by winds. Many traditional dust emission models (TEMs) assume that the Earth’s land surface is devoid of vegetation, adjust dust emission using a vegetation cover complement, and calibrate the magnitude of modelled emissions to atmospheric dust. We compare this approach with a novel albedo-based dust emission model (AEM) which calibrates Earth’s land surface normalised shadow (1-albedo) to shelter depending on wind speed, to represent aerodynamic roughness spatio-temporal variation. Existing datasets of satellite observed dust emission from point sources (DPS) and dust optical depth (DOD) show little spatial relation and DOD frequency exceeds DPS frequency by up to two orders of magnitude. Relative to DPS frequency, both dust emission models showed strong relations, but over-estimate dust emission frequency, suitable for calibration to observed dust emission. Our results show that TEMs over-estimate large dust emission over vast vegetated areas and produce considerable false change in dust emission, relative to the AEM. It is difficult to avoid the conclusion, raised by other literature, that calibrating dust cycle models to atmospheric dust has hidden for more than two decades, these TEM modelling weaknesses and its poor performance. The AEM overcomes these weaknesses and improves performance without masks or vegetation cover. Considerable potential exists for Earth System Models driven by prognostic albedo, to reveal new insights of aerosol effects on, and responses to, contemporary and environmental change projections.
