The source of dust in the global atmosphere is an important factor to better understand the role of dust aerosols in the climate system. However, it is a difficult task to attribute the airborne dust over the remote land and ocean regions to their origins since dust from various sources are mixed during long-range transport. Recently, a multi-model experiment, namely the AeroCom-III Dust Source Attribution (DUSA), has been conducted to estimate the relative contribution of dust in various locations from different sources with tagged simulations from 7 participating global models. The BASE run and a series of runs with 9 tagged regions were made to estimate the contribution of dust emitted in East- and West-Africa, Middle East, Central- and East-Asia, North America, the Southern Hemisphere, and the prominent dust hot spots of the Bodele and Taklimakan Deserts. Using the multi-model simulations, the present study has found common features among models on large scales, however models show large diversity in dust source attribution. The multi-model analysis estimates that North Africa contributes 60 % of global atmospheric dust loading, followed by Middle East and Central Asia sources (24 %). Southern hemispheric sources account for 10 % of global dust loading, however it contributes more than 70 % of dust over the Southern Hemisphere. The study provides quantitative estimates of the impact of dust emitted from different source regions on the globe and various receptor regions including remote land, ocean, and the polar regions synthesized from the 7 models.

A document by Marcelo Chamecki. Click on the document to view its contents.

Aircraft measurement campaigns have revealed that super coarse dust (diameter > 10 um) 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 measurements of super coarse dust close to dust source regions. However, the model still underestimates super coarse dust in dust outflow regions. Thus, we conclude that 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.

To correctly simulate and retrieve dust distributions and estimate dust impacts, global aerosol models and remote sensing retrieval algorithms need accurate single-scattering properties of dust aerosols. However, inconsistent and inaccurate quantifications of dust shape and shape distributions are used in models and retrieval algorithms, generating biases that propagate into the estimated dust distributions and dust impacts. To improve models and retrieval algorithms, here we for the first time account for the realistic dust shape distributions in obtaining single-scattering properties of dust aerosols. We find that approximating dust as spheres and neglecting dust asphericity, as most global aerosol models do, result in substantial underestimations in the extinction efficiency, the asymmetry factor, and the single-scattering albedo for all dust sizes in both the shortwave and longwave spectra. In addition, we find that the inaccurate quantification of dust shape in retrieval algorithms causes them to generate an incorrect magnitude and wavelength dependence of the linear depolarization ratio relative to observations. Our new ellipsoidal dust optics accounting for realistic shape distributions produce excellent agreement with the measured linear depolarization ratio. Although these new dust optics show potential to improve models and retrieval algorithms, they underestimate the magnitude of the back-scattering intensity relative to laboratory and field observations. This finding indicates that a realistic quantification of dust body shape is not sufficient and that an accurate quantification of dust surface texture is also critical to accurately reproduce dust optical properties at back-scattering angles.

A key challenge in accurate simulations of desert dust emission is the parameterization of the threshold wind speed above which dust emission occurs. However, the existing parameterizations yield a unrealistically low dust emission threshold in some climate models such as the Community Earth System Model (CESM), leading to higher simulated dust source activation frequencies than observed and requiring global tuning constants to scale down dust emissions. Here we develop a more realistic parameterization for the dust emission threshold in CESM. In particular, we account for the dissipation of surface wind momentum by surface roughness elements such as vegetation, rocks, and pebbles, which reduce the wind momentum exerted on the bare soil surface. We achieve this by implementing a dynamic wind drag partition model by considering the roughness of the time-varying vegetation as quantified by the leaf area index (LAI), as well as the time-invariant rocks and pebbles using satellite-derived aeolian roughness length. Furthermore, we account for the effect of soil size on dust emission threshold by replacing the currently used globally constant soil median diameter with a spatially varying soil texture map. Results show that with the new parameterization dust emissions decrease by 20–80% over source regions such as Africa, Middle East, and Asia, thereby reducing the need for the global tuning constant. Simulated dust emissions match better in both spatiotemporal variability and emission frequency when compared against satellite observed dust activation frequency data. Our results suggest that including more physical dust emission parameterizations into climate models can lessen bias and improve simulation results, possibly eliminate the use of empirical source functions, and reduce the need for tuning constants. This development could improve assessments of dust impacts on the Earth system.

Measurements of dust size usually obtain the optical or the projected area-equivalent diameters, whereas model calculations of dust impacts use the geometric and the aerodynamic diameters. As such, accurate conversions between the four types of diameters are critical. However, most current conversions assume dust is spherical, which is problematic as numerous studies show that dust is highly aspherical. Here, we obtain conversions between different diameter types that account for dust asphericity. Our conversions indicate that optical particle counters using optical diameter to determine dust size underestimate dust geometric diameter at coarse sizes. We further use the diameter conversions to obtain a consistent observational constraint of size distributions of emitted dust in terms of geometric and aerodynamic diameters. The resulting size distributions are coarser than accounted for by parameterizations used in climate models, which which underestimate the mass of emitted dust within 10≤D_geo≤20 μm by a factor of ~2 and do not account for dust emission with D_geo≥20 μm. This finding suggests that current models substantially underestimate coarse dust emission.