Search for: All records

Abstract. Desert dust is an important atmospheric aerosol that affects the Earth's climate, biogeochemistry, and air quality. However, current Earth system models (ESMs) struggle to accurately capture the impact of dust on the Earth's climate and ecosystems, in part because these models lack several essential aeolian processes that couple dust with climate and land surface processes. In this study, we address this issue by implementing several new parameterizations of aeolian processes detailed in our companion paper in the Community Earth System Model version 2 (CESM2). These processes include (1) incorporating a simplified soil particle size representation to calculate the dust emission threshold friction velocity, (2) accounting for the drag partition effect of rocks and vegetation in reducing wind stress on erodible soils, (3) accounting for the intermittency of dust emissions due to unresolved turbulent wind fluctuations, and (4) correcting the spatial variability of simulated dust emissions from native to higher spatial resolutions on spatiotemporal dust variability. Our results show that the modified dust emission scheme significantly reduces the model bias against observations compared with the default scheme and improves the correlation against observations of multiple key dust variables such as dust aerosol optical depth (DAOD), surface particulate matter (PM) concentration, and deposition flux. Our scheme's dust also correlates strongly with various meteorological and land surface variables, implying higher sensitivity of dust to future climate change than other schemes' dust. These findings highlight the importance of including additional aeolian processes for improving the performance of ESM aerosol simulations and potentially enhancing model assessments of how dust impacts climate and ecosystem changes. 

Abstract. Desert dust accounts for most of the atmosphere's aerosol burden by mass andproduces numerous important impacts on the Earth system. However, currentglobal climate models (GCMs) and land-surface models (LSMs) struggle toaccurately represent key dust emission processes, in part because ofinadequate representations of soil particle sizes that affect the dustemission threshold, surface roughness elements that absorb wind momentum,and boundary-layer characteristics that control wind fluctuations.Furthermore, because dust emission is driven by small-scale (∼ 1 km or smaller) processes, simulating the global cycle of desert dust inGCMs with coarse horizontal resolutions (∼ 100 km) presents afundamental challenge. This representation problem is exacerbated by dustemission fluxes scaling nonlinearly with wind speed above a threshold windspeed that is sensitive to land-surface characteristics. Here, we addressthese fundamental problems underlying the simulation of dust emissions inGCMs and LSMs by developing improved descriptions of (1) the effect of soiltexture on the dust emission threshold, (2) the effects of nonerodibleroughness elements (both rocks and green vegetation) on the surface windstress, and (3) the effects of boundary-layer turbulence on drivingintermittent dust emissions. We then use the resulting revised dust emissionparameterization to simulate global dust emissions in a standalone modelforced by reanalysis meteorology and land-surface fields. We further propose(4) a simple methodology to rescale lower-resolution dust emissionsimulations to match the spatial variability of higher-resolution emissionsimulations in GCMs. The resulting dust emission simulation showssubstantially improved agreement against regional dust emissionsobservationally constrained by inverse modeling. We thus find that ourrevised dust emission parameterization can substantially improve dustemission simulations in GCMs and LSMs. 

Abstract. We present the dust module in the Multiscale Online Non-hydrostatic AtmospheRe CHemistry model (MONARCH) version 2.0, a chemical weather prediction system that can be used for regional and global modeling at a range of resolutions. The representations of dust processes in MONARCH were upgraded with a focus on dust emission (emission parameterizations, entrainment thresholds, considerations of soil moisture and surface cover), lower boundary conditions (roughness, potential dust sources), and dust–radiation interactions. MONARCH now allows modeling of global and regional mineral dust cycles using fundamentally different paradigms, ranging from strongly simplified to physics-based parameterizations. We present a detailed description of these updates along with four global benchmark simulations, which use conceptually different dust emission parameterizations, and we evaluate the simulations against observations of dust optical depth. We determine key dust parameters, such as global annual emission/deposition flux, dust loading, dust optical depth, mass-extinction efficiency, single-scattering albedo, and direct radiative effects. For dust-particle diameters up to 20 µm, the total annual dust emission and deposition fluxes obtained with our four experiments range between about 3500 and 6000 Tg, which largely depend upon differences in the emitted size distribution. Considering ellipsoidal particle shapes and dust refractive indices that account for size-resolved mineralogy, we estimate the global total (longwave and shortwave) dust direct radiative effect (DRE) at the surface to range between about −0.90 and −0.63 W m−2 and at the top of the atmosphere between −0.20 and −0.28 W m−2. Our evaluation demonstrates that MONARCH is able to reproduce key features of the spatiotemporal variability of the global dust cycle with important and insightful differences between the different configurations. 

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.