Stratospheric impacts on dust transport and air pollution in West Africa and the Eastern Mediterranean.

Saharan dust intrusions strongly impact Atlantic and Mediterranean coastal regions. Today, most operational dust forecasts extend only 2-5 days. Here we show that on timescales of weeks to months, North African dust emission and transport are impacted by sudden stratospheric warmings (SSWs), which establish a negative North Atlantic Oscillation-like surface signal. Chemical transport models show a large-scale dipolar dust response to SSWs, with the burden in the Eastern Mediterranean enhanced up to 30% and a corresponding reduction in West Africa. Observations of inhalable particulate (PM10) concentrations and aerosol optical depth confirm this dipole. On average, a single SSW causes 680-2460 additional premature deaths in the Eastern Mediterranean and prevents 1180-2040 premature deaths in West Africa from exposure to dust-source fine particulate (PM2.5). Currently, SSWs are predictable 1-2 weeks in advance. Altogether, the stratosphere represents an important source of subseasonal predictability for air quality over West Africa and the Eastern Mediterranean.

Improved Parameterization for the Size Distribution of Emitted Dust Aerosols Reduces Model Underestimation of Super Coarse Dust.

Aircraft measurement campaigns have revealed that super coarse dust (diameter >10 µm) surprisingly accounts for approximately a quarter of aerosols by mass in the atmosphere. However, most global aerosol models either underestimate or do not include super coarse dust abundance. To address this problem, we use brittle fragmentation theory to develop a parameterization for the emitted dust size distribution that includes emission of super coarse dust. We implement this parameterization in the Community Earth System Model (CESM) and find that it brings the model in good agreement with aircraft measurements of super coarse dust close to dust source regions. However, the CESM still underestimates super coarse dust in dust outflow regions. Thus, we conclude that the model underestimation of super coarse atmospheric dust is in part due to the underestimation of super coarse dust emission and likely in part due to errors in deposition processes.

Improved representation of the global dust cycle using observational constraints on dust properties and abundance.

Even though desert dust is the most abundant aerosol by mass in Earth's atmosphere, atmospheric models struggle to accurately represent its spatial and temporal distribution. These model errors are partially caused by fundamental difficulties in simulating dust emission in coarse-resolution models and in accurately representing dust microphysical properties. Here we mitigate these problems by developing a new methodology that yields an improved representation of the global dust cycle. We present an analytical framework that uses inverse modeling to integrate an ensemble of global model simulations with observational constraints on the dust size distribution, extinction efficiency, and regional dust aerosol optical depth. We then compare the inverse model results against independent measurements of dust surface concentration and deposition flux and find that errors are reduced by approximately a factor of two relative to current model simulations of the Northern Hemisphere dust cycle. The inverse model results show smaller improvements in the less dusty Southern Hemisphere, most likely because both the model simulations and the observational constraints used in the inverse model are less accurate. On a global basis, we find that the emission flux of dust with geometric diameter up to 20 µm (PM20) is approximately 5,000 Tg/year, which is greater than most models account for. This larger PM20 dust flux is needed to match observational constraints showing a large atmospheric loading of coarse dust. We obtain gridded data sets of dust emission, vertically integrated loading, dust aerosol optical depth, (surface) concentration, and wet and dry deposition fluxes that are resolved by season and particle size. As our results indicate that this data set is more accurate than current model simulations and the MERRA-2 dust reanalysis product, it can be used to improve quantifications of dust impacts on the Earth system.