Dust emission response to precipitation and temperature anomalies under different climatic conditions

The dust-drought nexus has received more attention in recent years, particularly in light of global warming. This study aims to better understand the interacting role of temperature and precipitation climatology on global dust emission. Simulated global arid regions' dust emissions from 11 CMIP6 Earth System Models (ESMs) (65 years from 1950 to 2014) and MERRA2 reanalysis (41 years from 1980 to 2020) are analyzed. We calculate dust emission sensitivity to precipitation and temperature using multiple linear regression with near-surface (10 m) wind speed, precipitation, and 2 m air temperature as predictors. The results show that simulated dust emission from most models is significantly correlated with precipitation and temperature over large arid dust source regions. All ESMs show both positive and negative dust emission sensitivity to precipitation (β_P) and temperature (β_T). The climatological mean state affects the strength of the relationships. The precipitation sensitivity is larger over the cold regions while the temperature sensitivity is larger in wet regions. The precipitation sensitivity symmetrically increases with latitude due to the variability of temperature with latitude. Future changes to mean temperature and precipitation have competing effects on dust emission and are likely to alter the hemispheric balance of atmospheric dust.

Evaluation of Nine Operational Models in Forecasting Different Types of Synoptic Dust Events in the Middle East

This study investigates four types of synoptic dust events in the Middle East region, including cyclonic, pre-frontal, post-frontal and Shamal dust storms. For each of these types, three intense and pervasive dust events are analyzed from a synoptic meteorological and numerical simulation perspective. The performance of 9 operational dust models in forecasting these dust events in the Middle East is qualitatively and quantitatively evaluated against Terra-MODIS observations and AERONET measurements during the dust events. The comparison of model AOD outputs with Terra-MODIS retrievals reveals that despite the significant discrepancies, all models have a relatively acceptable performance in forecasting the AOD patterns in the Middle East. The models enable to represent the high AODs along the dust plumes, although they underestimate them, especially for cyclonic dust storms. In general, the outputs of the NASA-GEOS and DREAM8-MACC models present greater similarity with the satellite and AERONET observations in most of the cases, also exhibiting the highest correlation coefficient, although it is difficult to introduce a single model as the best for all cases. Model AOD predictions over the AERONET stations showed that DREAM8-MACC exhibited the highest R2 of 0.78, followed by NASA_GEOS model (R2 = 0.74), which both initially use MODIS data assimilation. Although the outputs of all models correspond to valid time more than 24 h after the initial time, the effect of data assimilation on increasing the accuracy is important. The different dust emission schemes, soil and vegetation mapping, initial and boundary meteorological conditions and spatial resolution between the models, are the main factors influencing the differences in forecasting the dust AODs in the Middle East.

Improved representation of the global dust cycle using observational constraints on dust properties and abundance

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.

GISS-E2.1: Configurations and Climatology

This paper describes the GISS-E2.1 contribution to the Coupled Model Intercomparison Project, Phase 6 (CMIP6). This model version differs from the predecessor model (GISS-E2) chiefly due to parameterization improvements to the atmospheric and ocean model components, while keeping atmospheric resolution the same. Model skill when compared to modern era climatologies is significantly higher than in previous versions. Additionally, updates in forcings have a material impact on the results. In particular, there have been specific improvements in representations of modes of variability (such as the Madden-Julian Oscillation and other modes in the Pacific) and significant improvements in the simulation of the climate of the Southern Oceans, including sea ice. The effective climate sensitivity to 2 × CO2 is slightly higher than previously at 2.7-3.1°C (depending on version) and is a result of lower CO2 radiative forcing and stronger positive feedbacks.

Can MERRA-2 Reanalysis Data Reproduce the Three-Dimensional Evolution Characteristics of a Typical Dust Process in East Asia? A Case Study of the Dust Event in May 2017

This study used the MERRA-2 reanalysis dataset and ground-based and satellite observational data to comprehensively analyze a typical dust storm event in east Asia on 2–7 May 2017 which engulfed most of China as well as ocean and Japan, and explore the accuracy and comprehensiveness of the MERRA-2 dataset in the analysis of dust processes. The results of comparison show that the description of the spatiotemporal distribution and evolution of the dust aerosols in the dust event using the MERRA-2 data is consistent with the data of AERONET, National Urban Air Quality Real-time Publishing Platform and Hamawari-8. Gobi Deserts was the most influential source area of this dust event with the highest emissions reaching 1.9 × 106 μg/m3. The vertical motion of the atmosphere can lift dust from the source area above 500 hPa. There were low-pressure troughs at 500 and 850 hPa and the winds behind and in front of the trough led to the high-altitude, long-distance transport of dust. Dust gradually affected the northwest China, north China, northeast China, and even the ocean and Japan on 2–7 May. This study demonstrates that although there is some uncertainty about the source of dust emission in the MERRA-2 model, the data accurately simulated the evolution of the dust event and analyze it comprehensively, while the accuracy of simulating the long-term evolution of dust requires further evaluation.

Regional fresh snowfall microbiology and chemistry are driven by geography in storm-tracked events, Colorado, USA

Snowfall is a global phenomenon highly integrated with hydrology and ecology. Forays into studying bioaerosols and their dependence on aeolian movement are largely constrained to either precipitation-independent analyses or in silico models. Though snowpack and glacial microbiological studies have been conducted, little is known about the biological component of meteoric snow. Through culture-independent phylogenetic and geochemical analyses, we show that the geographical location at which snow precipitates determines snowfall’s geochemical and microbiological composition. Storm-tracking, furthermore, can be used as a valuable environmental indicator to trace down what factors are influencing bioaerosols. We estimate annual aeolian snowfall deposits of up to ∼10 kg of bacterial/archaeal biomass per hectare along our study area of the eastern Front Range in Colorado. The dominant kinds of microbiota captured in an analysis of seven snow events at two different locations, one urban, one rural, across the winter of 2016/2017 included phyla Proteobacteria, Bacteroidetes, Firmicutes, and Acidobacteria, though a multitude of different kinds of organisms were found in both. Taxonomically, Bacteroidetes were more abundant in Golden (urban plain) snow while Proteobacteria were more common in Sunshine (rural mountain) samples. Chemically, Golden snowfall was positively correlated with some metals and anions. The work also hints at better informing the “everything is everywhere” hypotheses of the microbial world and that atmospheric transport of microbiota is not only common, but is capable of disseminating vast amounts of microbiota of different physiologies and genetics that then affect ecosystems globally. Snowfall, we conclude, is a significant repository of microbiological material with strong implications for both ecosystem genetic flux and general bio-aerosol theory.

Global and regional importance of the direct dust-climate feedback

Feedbacks between the global dust cycle and the climate system might have amplified past climate changes. Yet, it remains unclear what role the dust-climate feedback will play in future anthropogenic climate change. Here, we estimate the direct dust-climate feedback, arising from changes in the dust direct radiative effect (DRE), using a simple theoretical framework that combines constraints on the dust DRE with a series of climate model results. We find that the direct dust-climate feedback is likely in the range of -0.04 to +0.02 Wm -2 K-1, such that it could account for a substantial fraction of the total aerosol feedbacks in the climate system. On a regional scale, the direct dust-climate feedback is enhanced by approximately an order of magnitude close to major source regions. This suggests that it could play an important role in shaping the future climates of Northern Africa, the Sahel, the Mediterranean region, the Middle East, and Central Asia.

Integrative analysis of desert dust size and abundance suggests less dust climate cooling

Desert dust aerosols affect Earth's global energy balance through interactions with radiation^1,2, clouds^3,4, and ecosystems⁵. But the magnitudes of these effects are so uncertain that it remains unclear whether atmospheric dust has a net warming or cooling effect on global climate^1,4,6. Consequently, it is still uncertain whether large changes in atmospheric dust loading over the past century have slowed or accelerated anthropogenic climate change^4,7-9, and the climate impact of possible future alterations in dust loading is similarly disputed^9,10. Here we use an integrative analysis of dust aerosol sizes and abundance to constrain the climatic impact of dust through direct interactions with radiation. Using a combination of observational, experimental, and model data, we find that atmospheric dust is substantially coarser than represented in current climate models. Since coarse dust warms global climate, the dust direct radiative effect (DRE) is likely less cooling than the ~0.4 W/m² estimated by models in a current ensemble^2,11-13. We constrain the dust DRE to - 0.20 (-0.48 to +0.20) W/m², which suggests that the dust DRE produces only about half the cooling that current models estimate, and raises the possibility that dust DRE is actually net warming the planet.

Seasonal dynamics of threshold friction velocity and dust emission in Central Asia

An improved model representation of mineral dust cycle is critical to reducing the uncertainty of dust-induced environmental and climatic impact. Here we present a mesoscale model study of the seasonal dust activity in the semiarid drylands of Central Asia, focusing on the effects of wind speed, soil moisture, surface roughness heterogeneity, and vegetation phenology on the threshold friction velocity (u_*t ) and dust emission during the dust season of 1 March to 31 October 2001. The dust model WRF-Chem-DuMo allows us to examine the uncertainties in seasonal dust emissions due to the selection of dust emission scheme and soil grain size distribution data. To account for the vegetation effects on the u_*t , we use the Moderate Resolution Imaging Spectroradiometer monthly normalized difference vegetation index to derive the dynamic surface roughness parameters required by the physically based dust schemes of Marticorena and Bergametti (1995, hereinafter MB) and Shao et al. (1996, hereinafter Shao). We find the springtime u_*t is strongly enhanced by the roughness effects of temperate steppe and desert ephemeral plants and, to less extent, the binding effects of increased soil moisture. The u_*t decreases as the aboveground biomass dies back and soil moisture depletes during summer. The u_*t dynamics determines the dust seasonality by causing more summer dust emission, despite a higher frequency of strong winds during spring. Due to the presence of more erodible materials in the saltation diameter range of 60-200 µm, the dry-sieved soil size distribution data lead to eight times more season-total dust emission than the soil texture data, but with minor differences in the temporal distribution. On the other hand, the Shao scheme produces almost the same amount of season-total dust emission as the MB scheme, but with a strong shift toward summer due to the strong sensitivity of the u_*t to vegetation. By simply averaging the MB and Shao model experiments, we obtain a mean estimate (Exp_mean) of season-total dust emission of 255.6 Mt (megaton), of which 26.8%, 50.4%, and 22.8% are produced in spring (March-April-May), summer (June-July-August), and autumn (September-October), respectively. The Exp_mean estimate identifies the Ustyurt Plateau, dried seabed of Aral Sea (called Aralkum), Caspian Sea coast, and loess deserts as the strongest dust source areas in Central Asia. The spatial distribution and seasonality of the Exp_mean estimate are in general agreement with ground station dusty weather observations and satellite aerosol optical depth and absorbing aerosol index products. Compared to Cakmur et al. (2006), the Exp_mean estimate suggests Central Asia contributes 10-17% to the global dust emission in 2001.

KEY POINTS

The WRF-Chem-DuMo model is used to study dust seasonality in Central Asia An accurate representation of u_*t is critical for dust seasonality Multiexperiment mean dust emission estimate agrees with observations.

Atmospheric transport and deposition of mineral dust to the ocean: implications for research needs

This paper reviews our knowledge of the measurement and modeling of mineral dust emissions to the atmosphere, its transport and deposition to the ocean, the release of iron from the dust into seawater, and the possible impact of that nutrient on marine biogeochemistry and climate. Of particular concern is our poor understanding of the mechanisms and quantities of dust deposition as well as the extent of iron solubilization from the dust once it enters the ocean. Model estimates of dust deposition in remote oceanic regions vary by more than a factor of 10. The fraction of the iron in dust that is available for use by marine phytoplankton is still highly uncertain. There is an urgent need for a long-term marine atmospheric surface measurement network, spread across all oceans. Because the southern ocean is characterized by large areas with high nitrate but low chlorophyll surface concentrations, that region is particularly sensitive to the input of dust and iron. Data from this region would be valuable, particularly at sites downwind from known dust source areas in South America, Australia, and South Africa. Coordinated field experiments involving both atmospheric and marine measurements are recommended to address the complex and interlinked processes and role of dust/Fe fertilization on marine biogeochemistry and climate.

The physics of wind-blown sand and dust

The transport of sand and dust by wind is a potent erosional force, creates sand dunes and ripples, and loads the atmosphere with suspended dust aerosols. This paper presents an extensive review of the physics of wind-blown sand and dust on Earth and Mars. Specifically, we review the physics of aeolian saltation, the formation and development of sand dunes and ripples, the physics of dust aerosol emission, the weather phenomena that trigger dust storms, and the lifting of dust by dust devils and other small-scale vortices. We also discuss the physics of wind-blown sand and dune formation on Venus and Titan.

A scaling theory for the size distribution of emitted dust aerosols suggests climate models underestimate the size of the global dust cycle

Mineral dust aerosols impact Earth's radiation budget through interactions with clouds, ecosystems, and radiation, which constitutes a substantial uncertainty in understanding past and predicting future climate changes. One of the causes of this large uncertainty is that the size distribution of emitted dust aerosols is poorly understood. The present study shows that regional and global circulation models (GCMs) overestimate the emitted fraction of clay aerosols (< 2 μm diameter) by a factor of ∼2-8 relative to measurements. This discrepancy is resolved by deriving a simple theoretical expression of the emitted dust size distribution that is in excellent agreement with measurements. This expression is based on the physics of the scale-invariant fragmentation of brittle materials, which is shown to be applicable to dust emission. Because clay aerosols produce a strong radiative cooling, the overestimation of the clay fraction causes GCMs to also overestimate the radiative cooling of a given quantity of emitted dust. On local and regional scales, this affects the magnitude and possibly the sign of the dust radiative forcing, with implications for numerical weather forecasting and regional climate predictions in dusty regions. On a global scale, the dust cycle in most GCMs is tuned to match radiative measurements, such that the overestimation of the radiative cooling of a given quantity of emitted dust has likely caused GCMs to underestimate the global dust emission rate. This implies that the deposition flux of dust and its fertilizing effects on ecosystems may be substantially larger than thought.

Dust storms: recent developments

Dust storms have a number of impacts upon the environment including radiative forcing, and biogeochemical cycling. They transport material over many thousands of kilometres. They also have a range of impacts on humans, not least on human health. In recent years the identification of source areas for dust storms has been an important area or research, with the Sahara (especially Bodélé) and western China being recognised as the strongest sources globally. Another major development has been the recognition of the degree to which dust storm activity has varied at a range of time scales, millennial, century, decadal, annual and seasonal.