Influences of soil moisture and vegetation cover on dust emission using satellite observations

Abstract

This study presents an observational analysis of dust emission co-factors to high winds using remote sensing data across the North Africa and Western Asia dust belt. Co-factors are parameterized in climate and weather models. Observational evidence of their role and functional dependencies advance our capability to model and predict the important role of dust in radiative processes, far-field ecological nutrient transfers, and human health impacts. We use multiple years of high-temporal resolution (hourly) dust plume data, which enables analyses of emission sources, and plume extents. It also allows us to co-locate environmental factors such as wind speed, soil moisture, and vegetation and synchronize them with the time and location of major dust emission events. We focus on the combined effect of these factors in determining the frequency and intensity of dust storms, as well as identifying wind speed thresholds for dust emission at source areas. Key findings reveal wind speed thresholds twice as high as those reported in previous studies. We focus on two case studies to demonstrate the prominence of the co-factors. The case study of the Syrian Desert during the summer of 2022 illustrates the impact of dry soil, strong winds, and declining vegetation cover on the formation of severe dust storms. Additionally, the case study of the Bodélé Depression demonstrates the influence of reduced wind speed on emission frequency. The findings offer insights into how environmental conditions influence dust emission dynamics, establishing the basis for the development of more accurate dust emission models.