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Abstract Desert dust accounts for a large fraction of shortwave radiation absorbed by aerosols, which adds to the climate warming produced by greenhouse gases. However, it remains uncertain exactly how much shortwave radiation dust absorbs. Here, we leverage in-situ measurements of dust single-scattering albedo to constrain absorption at mid-visible wavelength by North African dust, which accounts for approximately half of the global dust. We find that climate and chemical transport models overestimate North African dust absorption aerosol optical depth (AAOD) by up to a factor of two. This occurs primarily because models overestimate the dust imaginary refractive index, the effect of which is partially masked by an underestimation of large dust particles. Similar factors might contribute to an overestimation of AAOD retrieved by the Aerosol Robotic Network, which is commonly used to evaluate climate and chemical transport models. The overestimation of dust absorption by models could lead to substantial biases in simulated dust impacts on the Earth system, including warm biases in dust radiative effects. 

Abstract. Mineral dust aerosols cool and warm the atmosphere byscattering and absorbing solar (shortwave: SW) and thermal (longwave: LW)radiation. However, significant uncertainties remain in dust radiativeeffects, largely due to differences in the dust size distribution andspectral optical properties simulated in Earth system models. Dust modelstypically underestimate the coarse dust load (more than 2.5 µm indiameter) and assume a spherical shape, which leads to an overestimate ofthe fine dust load (less than 2.5 µm) after the dust emissions in themodels are scaled to match observed dust aerosol optical depth at 550 nm(DAOD550). Here, we improve the simulated dust properties with data setsthat leverage measurements of size-resolved dust concentration, asphericityfactor, and refractive index in a coupled global chemical transport modelwith a radiative transfer module. After the adjustment of size-resolved dustconcentration and spectral optical properties, the global and annual averageof DAOD550 from the simulation increases from 0.023 to 0.029 and fallswithin the range of a semi-observationally based estimate (0.030 ± 0.005). The reduction of fine dust load after the adjustment leads to areduction of the SW cooling at the top of the atmosphere (TOA). To improveagreement against a semi-observationally based estimate of the radiativeeffect efficiency at TOA, we find that a less absorptive SW dust refractiveindex is required for coarser aspherical dust. Thus, only a minor differenceis estimated for the net global dust radiative effect at TOA (−0.08 vs.−0.00 W m−2 on a global scale). Conversely, our sensitivitysimulations reveal that the surface warming is substantially enhanced nearthe strong dust source regions (less cooling to −0.23 from −0.60 W m−2 on a global scale). Thus, less atmospheric radiativeheating is estimated near the major source regions (less heating to 0.15from 0.59 W m−2 on a global scale), because of enhanced LWwarming at the surface by the synergy of coarser size and aspherical shape. 

Coarse mineral dust (diameter, ≥5 μm) is an important component of the Earth system that affects clouds, ocean ecosystems, and climate. Despite their significance, climate models consistently underestimate the amount of coarse dust in the atmosphere when compared to measurements. Here, we estimate the global load of coarse dust using a framework that leverages dozens of measurements of atmospheric dust size distributions. We find that the atmosphere contains 17 Tg of coarse dust, which is four times more than current climate models simulate. Our findings indicate that models deposit coarse dust out of the atmosphere too quickly. Accounting for this missing coarse dust adds a warming effect of 0.15 W·m −2 and increases the likelihood that dust net warms the climate system. We conclude that to properly represent the impact of dust on the Earth system, climate models must include an accurate treatment of coarse dust in the atmosphere. 

Abstract. Mineral dust is the most abundant aerosol species by massin the atmosphere, and it impacts global climate, biogeochemistry, and humanhealth. Understanding these varied impacts on the Earth system requiresaccurate knowledge of dust abundance, size, and optical properties, and howthey vary in space and time. However, current global models show substantialbiases against measurements of these dust properties. For instance, recentstudies suggest that atmospheric dust is substantially coarser and moreaspherical than accounted for in models, leading to persistent biases inmodelled impacts of dust on the Earth system. Here, we facilitate moreaccurate constraints on dust impacts by developing a new dataset: DustConstraints from joint Observational-Modelling-experiMental analysis(DustCOMM). This dataset combines an ensemble of global model simulationswith observational and experimental constraints on dust size distributionand shape to obtain more accurate constraints on three-dimensional (3-D)atmospheric dust properties than is possible from global model simulationsalone. Specifically, we present annual and seasonal climatologies of the 3-Ddust size distribution, 3-D dust mass extinction efficiency at 550 nm, andtwo-dimensional (2-D) atmospheric dust loading. Comparisons with independentmeasurements taken over several locations, heights, and seasons show thatDustCOMM estimates consistently outperform conventional global modelsimulations. In particular, DustCOMM achieves a substantial reduction in thebias relative to measured dust size distributions in the 0.5–20 µmdiameter range. Furthermore, DustCOMM reproduces measurements of dust massextinction efficiency to almost within the experimental uncertainties,whereas global models generally overestimate the mass extinction efficiency.DustCOMM thus provides more accurate constraints on 3-D dust properties, andas such can be used to improve global models or serve as an alternative toglobal model simulations in constraining dust impacts on the Earth system. 

Abstract. Even though desert dust is the most abundant aerosol bymass in Earth's atmosphere, the relative contributions of the world's majorsource regions to the global dust cycle remain poorly constrained. Thisproblem hinders accounting for the potentially large impact of regionaldifferences in dust properties on clouds, the Earth's energy balance, andterrestrial and marine biogeochemical cycles. Here, we constrain thecontribution of each of the world's main dust source regions to the globaldust cycle. We use an analytical framework that integrates an ensemble ofglobal aerosol model simulations with observationally informed constraintson the dust size distribution, extinction efficiency, and regional dustaerosol optical depth (DAOD). We obtain a dataset that constrains therelative contribution of nine major source regions to size-resolveddust emission, atmospheric loading, DAOD, concentration, and depositionflux. We find that the 22–29 Tg (1 standard error range) global loading ofdust with a geometric diameter up to 20 µm is partitioned as follows:North African source regions contribute ∼ 50 % (11–15 Tg),Asian source regions contribute ∼ 40 % (8–13 Tg), and NorthAmerican and Southern Hemisphere regions contribute ∼ 10 %(1.8–3.2 Tg). These results suggest that current models on averageoverestimate the contribution of North African sources to atmospheric dustloading at ∼ 65 %, while underestimating the contribution ofAsian dust at ∼ 30 %. Our results further show that eachsource region's dust loading peaks in local spring and summer, which ispartially driven by increased dust lifetime in those seasons. We alsoquantify the dust deposition flux to the Amazon rainforest to be∼ 10 Tg yr−1, which is a factor of 2–3 less than inferred fromsatellite data by previous work that likely overestimated dust deposition byunderestimating the dust mass extinction efficiency. The data obtained inthis paper can be used to obtain improved constraints on dust impacts onclouds, climate, biogeochemical cycles, and other parts of the Earth system. 

Abstract. Even though desert dust is the most abundant aerosol bymass in Earth's atmosphere, atmospheric models struggle to accuratelyrepresent its spatial and temporal distribution. These model errors arepartially caused by fundamental difficulties in simulating dust emission incoarse-resolution models and in accurately representing dust microphysicalproperties. Here we mitigate these problems by developing a new methodologythat yields an improved representation of the global dust cycle. We presentan analytical framework that uses inverse modeling to integrate an ensembleof global model simulations with observational constraints on the dust sizedistribution, extinction efficiency, and regional dust aerosol opticaldepth. We then compare the inverse model results against independentmeasurements of dust surface concentration and deposition flux and find thaterrors are reduced by approximately a factor of 2 relative to currentmodel simulations of the Northern Hemisphere dust cycle. The inverse modelresults show smaller improvements in the less dusty Southern Hemisphere,most likely because both the model simulations and the observationalconstraints used in the inverse model are less accurate. On a global basis,we find that the emission flux of dust with a geometric diameter up to 20 µm (PM20) is approximately 5000 Tg yr−1, which is greater than mostmodels account for. This larger PM20 dust flux is needed to matchobservational constraints showing a large atmospheric loading of coarsedust. We obtain gridded datasets of dust emission, vertically integratedloading, dust aerosol optical depth, (surface) concentration, and wet anddry deposition fluxes that are resolved by season and particle size. As ourresults indicate that this dataset is more accurate than current modelsimulations and the MERRA-2 dust reanalysis product, it can be used toimprove quantifications of dust impacts on the Earth system.