Using albedo to reform wind erosion modelling, mapping and monitoring

Wind erosion and dust emission models are used to assess the impacts of dust on radiative forcing in the atmosphere, cloud formation, nutrient fertilisation and human health. The models are underpinned by a two-dimensional geometric property (lateral cover; L) used to characterise the three-dimensional aerodynamic roughness (sheltered area or wakes) of the Earth's surface and calibrate the momentum it extracts from the wind. We reveal a fundamental weakness in L and demonstrate that values are an order of magnitude too small and significant aerodynamic interactions between roughness elements and their sheltered areas have been omitted, particularly under sparse surface roughness. We describe a solution which develops published work to establish a relation between sheltered area and the proportion of shadow over a given area; the inverse of direct beam directional hemispherical reflectance (black sky albedo; BSA). We show direct relations between shadow and wind tunnel measurements and thereby provide direct calibrations of key aerodynamic properties. Estimation of the aerodynamic parameters from albedo enables wind erosion assessments over areas, across platforms from the field to airborne and readily available satellite data. Our new approach demonstrated redundancy in existing wind erosion models and thereby reduced model complexity and improved fidelity. We found that the use of albedo enabled an adequate description of aerodynamic sheltering to characterise fluid dynamics and predict sediment transport without the use of a drag partition scheme (Rt) or threshold friction velocity (u∗t). We applied the calibrations to produce global maps of aerodynamic properties which showed very similar spatial patterns to each other and confirmed the redundancy in the traditional parameters of wind erosion modelling. We evaluated temporal patterns of predicted horizontal mass flux at locations across Australia which revealed variation between land cover types that would not be detected using traditional models. Our new approach provided new opportunities to investigate the dynamics of wind erosion in space and time and elucidate aeolian processes across scales.