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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.

This MATLAB scripts is used to plot Fig. 4 of Huang et al. (2020), in review. This scripts first uses Monte-Carlo methodto sample a large number (10^8) of volume-equivalent dust particles from the globally-averaged shape distributions of AR and HWR (compiled in Supplementary Tables S2 and S3 of Huang et al., 2020). Second, for each of these generated particles, we used Eqs. (5) - (7) and Eq. (4), respectively, to obtain its the gravitational settling speed and that of its volume-equivalent spherical dust. Finally, for each dust particle, we calculated the reduction in terminal velocity and the enhancement of lifetime due to dust asphericity. Contact Yue Huang (hyue4@ucla.edu) if you are interested in our research!