To expand our understanding of dust sources, emission, transport, and variability across multiple time scales
Dust emission depends upon both the strength of the surface wind and the condition of the land surface, which are controlled by processes that extend over multiple time scales. On the short-term, dust emission increases non-linearly like the third power of the wind velocity above a threshold, so that intense gusts make a disproportionately large contribution to the aerosol mass. Meteorological phenomena associated with dust mobilization include large-scale monsoon-type flows, synoptic-scale systems such as anticyclones, cyclones and their cold fronts, gust fronts generated by outflow from moist convective storms, and intense dry convection in the daytime planetary boundary layer. Seasonal dust variations follow seasonal changes in the circulation and the vegetation. Interannual and decadal variations are controlled by changes in relevant climate parameters like the surface wind, the magnitude and distribution of precipitation, and modifications to vegetation cover resulting from both changes in climate and land use. Reducing current uncertainties in dust forecasts and projections requires an improved better understanding of these processes along with their proper representation in models.
Within this strategic goal, the plan is to focus on three areas of research.
The identification of dust sources is one of the crucial aspects for representing dust mobilization in models. Satellite retrievals combined with vegetation, land-use, soil and surface datasets, and other observations will be used to derived high-resolution dust source inventories to accurately represent present-day dust sources in models at high-resolution.
Dust models show moderately good behaviour when dust outbreaks are caused by synoptic-scale systems. However, the representation of haboobs (i.e. immense walls of blowing sand and dust produced by strong mesoscale downdrafts), as well as the simulation of wind gusts associated to topographic effects and dry convective eddies, is a challenge for dust prediction on weather timescales but also for climate modelling applications.
While models have improved the representation of the present-day cycle and its seasonality, they are typically unable to reproduce observed interannual and decadal dust trends. Understanding and quantifying the interannual and decadal changes in dust sources is not only important for better understanding of 20th-century climate change, but also a requirement to eventually develop long-range dust prediction and dust projection capabilities while improving climate projections.