Reducing Resolution Dependency of Dust Emission Modeling Using Albedo-Based Wind Friction

Numerical simulations of dust emission processes are essential for dust cycle modeling and dust-atmosphere interactions. Models have coarse spatial resolutions which, without tackling sub-grid scale heterogeneity, bias finely resolved dust emission. Soil surface wind friction velocity (us*) drives dust emission non-linearly with increasing model resolution, due mainly to thresholds of sediment entrainment. Albedo is area-integrated, scales linearly with resolution, is related to us* and hence represents its sub-grid scale heterogeneity. Calibrated albedo-based global dust emission estimates decreased by only 2 Tg y-1 (10.5%) upscaled from 0.5 to 111 km, largely independent of resolution. Without adjusting wind fields, this scaling uncertainty is within recent estimates of global dust emission model uncertainty (+/- 14.9 Tg y-1). This intrinsic scaling capability of the albedo-based approach offers considerable potential to reduce resolution dependency of dust cycle modeling and improve the representation of local dust emission in Earth system models and operational air quality forecasting. Global computer models for atmospheric dust were developed to understand the global dust cycle. However, these coarse resolution global dust models cannot accurately represent small-scale dust emission processes and partly cause different dust emission estimations between the models. Using our new approach based on satellite products, we show that global dust emission estimation is largely independent of model resolution. Wind friction velocity calibrated to linearly upscaled albedo was largely independent of model resolution between 0.5 and 111 km Without modifying wind fields, global dust emissions decreased by only 10.5% (within model uncertainty) from 0.5 to 111 km model resolution Sub-grid scale heterogeneity is necessary to accurately represent grain-scale sediment supply and entrainment in large scale modeling