Dust storms are rare but are a significant natural source of global aerosol budget. They are difficult to predict, and whilst they inundate local regions with human health and infrastructure risks, the Earth system is highly sensitive to their global influence via myriad processes (cloud nucleation, phytoplankton nutrient limitation, etc.). The weather during a dust storm is the dominant control on its severity and duration, yet an understanding of the physical processes is lacking.

At White Sands, New Mexico, we conducted concurrent in situ and satellite observations of dust storms in the 2018 windy season. Using a sand saltation sensor, doppler lidar, meteorological tower, cup anemometer array and machine learning on GOES satellite data, we captured system dynamics from the grain scale to the synoptic scale. This allowed us to view dust storm weather at an unprecedented scale. 

Our results show the evolution of atmospheric conditions that lead to a dust storm, where the diurnal stability and humidity cycles play a central role. Firstly, humidity and temperature conditions during the night prior mustn’t form dew on the sand. Second, surface heating produces strong convection in the boundary layer (BL) in the early afternoon. Third, synoptic momentum forcing the BL must be sufficiently large. These conditions kick-start afternoon activity; together, BL buoyancy and shear forces mix the synoptic-scale momentum downward to the dry grains, emitting a regional dust plume. Events end in the evening as developing stability blocks synoptic momentum. Remarkably, all dust storms observed adhere to this evolution.

We see that dust storms are made in regions of high sediment availability sensitive to non-equilibrium dynamics of stability in the local BL, but also to non-local sources of humidity and momentum. These may offer forecasters and longer timescale predictors avenues through which to scrutinize their models, and insurers further risk indicators