The observationally constrained shape distributions of atmospheric dust

Global aerosol models and retrieval algorithms of remote sensing products generally approximate dust aerosols as spherical or spheroidal particles. However, measurements show that dust aerosols deviate substantially from spherical and spheroidal shapes, as ratios of dust length to width (the aspect ratio) and height to width (the height‐to‐width ratio) deviate substantially from unity. Here, we quantify dust asphericity by compiling dozens of measurements of aspect ratio and height‐to‐width ratio across the globe. We find that the dust length is on average 5 times larger than the height and that aerosol models and retrieval algorithms underestimate this asphericity by a factor of ~3 to 5. We find little difference in the average shape of North African dust and Asian dust, although North African dust becomes more aspherical during transport, whereas Asian dust might become less aspherical. We further find that both aspect ratio and height-to-width ratio show little dependence on dust particle size. These findings enable simple parameterizations of dust shape distributions that can be considered approximately representative of the global population of atmospheric dust.

We use these globally representative dust shape distributions to quantify the effects of dust asphericity on deposition and optics. We find that accounting for dust asphericity increases the gravitational settling lifetime by ~20%, which helps explain the underestimation of coarse dust transport by models. We further find that, relative to the ellipsoidal dust optics accounting for realistic dust asphericity, the spherical dust optics used in models  underestimate dust mass extinction efficiency, single-scattering albedo, and asymmetry factor for almost all dust sizes at both shortwave and longwave spectra. The ellipsoidal dust optics can reproduce the measured scattering matrix of feldspar and linear depolarization ratio substantially better than the spheroidal dust optics used in most retrieval algorithms. Thus, the globally representative dust shape distributions have a strong potential to improve global aerosol models and retrieval algorithms of remote sensing products.