Drivers of recent decline in dust activity over East Asia

It is essential to understand the factors driving the recent decline of dust activity in East Asia for future dust projections. Using a physically-based dust emission model, here we show that the weakening of surface wind and the increasing of vegetation cover and soil moisture have all contributed to the decline in dust activity during 2001 to 2017. The relative contributions of these three factors to the dust emission reduction during 2010-2017 relative to 2001 are 46%, 30%, and 24%, respectively. Much (78%) of the dust emission reduction is from barren lands, and a small fraction (4.6%) of the reduction is attributed to grassland vegetation increase that is partly ascribed to the ecological restoration. This suggests that the ecological restoration plays a minor role in the decline of dust activity. Rather, the decline is mainly driven by climatic factors, with the weakening of surface wind playing the dominant role.

Comparison of Scanning LiDAR with Other Remote Sensing Measurements and Transport Model Predictions for a Saharan Dust Case

The evolution and the properties of a Saharan dust plume were studied near the city of Karlsruhe in southwest Germany (8.4298°E, 49.0953°N) from 7 to 9 April 2018, combining a scanning LiDAR (90°, 30°), a vertically pointing LiDAR (90°), a sun photometer, and the transport model ICON-ART. Based on this Saharan dust case, we discuss the advantages of a scanning aerosol LiDAR and validate a method to determine LiDAR ratios independently. The LiDAR measurements at 355 nm showed that the dust particles had backscatter coefficients of 0.86 ± 0.14 Mm−1 sr−1, extinction coefficients of 40 ± 0.8 Mm−1, a LiDAR ratio of 46 ± 5 sr, and a linear particle depolarisation ratio of 0.27 ± 0.023. These values are in good agreement with those obtained in previous studies of Saharan dust plumes in Western Europe. Compared to the remote sensing measurements, the transport model predicted the plume arrival time, its layer height, and its structure quite well. The comparison of dust plume backscatter values from the ICON-ART model and observations for two days showed a correlation with a slope of 0.9 ± 0.1 at 355 nm. This work will be useful for future studies to characterise aerosol particles employing scanning LiDARs.

Simulation of a Severe Sand and Dust Storm Event in March 2021 in Northern China: Dust Emission Schemes Comparison and the Role of Gusty Wind

Northern China experienced a severe sand and dust storm (SDS) on 14/15 March 2021. It was difficult to simulate this severe SDS event accurately. This study compared the performances of three dust-emission schemes on simulating PM10 concentration during this SDS event by implementing three vertical dust flux parameterizations in the Comprehensive Air-Quality Model with Extensions (CAMx) model. Additionally, a statistical gusty-wind model was implemented in the dust-emission scheme, and it was used to quantify the gusty-wind contribution to dust emissions and peak PM10 concentration. As a result, the LS scheme (Lu and Shao 1999) produced the minimum errors for peak PM10 concentrations, the MB scheme (Marticorena and Bergametti 1995) underestimated the PM10 concentrations by 70–90%, and the KOK scheme (Kok et al. 2014) overestimated PM10 concentrations by 10–50% in most areas. The gusty-wind model could reasonably reproduce the probability density function of 2-min wind speeds. There were 5–40% more dust-emission flux and 5–40% more peak PM10 concentrations generated by the gusty wind than the hourly wind in the dust-source regions. The increase of peak PM10 concentration caused by gusty wind in the non-dust-source regions was higher than in the dust-source regions, with 10–50%. Implementing the gusty-wind model could help improve the LS scheme’s performance in simulating PM10 concentrations of this severe SDS event. More work is still needed to investigate the reliability of the gusty-wind model and LS scheme on various SDS events.

Characteristics of solar radiation at Xiaotang, in the northern marginal zone of the Taklimakan Desert

The characteristics of solar radiation and the influence of sand and dust on solar radiation in the northern margin of Taklimakan Desert were analyzed using radiation observation data from 2018. The results showed that the annual total radiation, direct radiation, and scattered radiation at Xiaotang were 5,781.8, 2,337.9, and 3,323.8 MJ m⁻², respectively. The maximum monthly total radiation, direct radiation, and scattered radiation were observed in July (679.8 MJ m⁻²), August (317.3 MJ m⁻²), and May (455.7 MJ m⁻²), respectively. The aerosol optical depth corresponded well with the scattered radiation, and the maximum value was in May. Further analysis showed a significant correlation between the total radiation and solar height angle under different weather conditions. Under the same solar height angle, total radiation was higher during clear days but lower on sandstorm days. Calculation of atmospheric transmittance showed that the average atmospheric transmittance on a clear day was 0.67; on sand-and-dust days, it was 0.46. When the atmospheric transmittance was 0.5, the increase in scattering radiation by aerosol in the air began to decrease. Probability analysis of radiation indicated the following probabilities of total radiation <500 W m⁻² occurring on clear, floating-dust, blowing-sand, and sandstorm days: 67.1%, 76.3%, 76.1%, and 91.8%, respectively. Dust had the greatest influence on direct radiation; the probabilities of direct radiation <200 W m⁻²occurring on clear, floating-dust, blowing-sand, and sandstorm days were 44.5%, 93.5%, 91.3%, and 100%, respectively, whereas those of scattered radiation <600 W m⁻²were 100%, 99.1%, 98.1%, and 100%, respectively. Therefore, the presence of dust in the air will reduce scattered radiation.

Stepwise Assessment of Different Saltation Theories in Comparison with Field Observation Data

Wind-blown dust models use input data, including soil conditions and meteorology, to interpret the multi-step wind erosion process and predict the quantity of dust emission. Therefore, the accuracy of the wind-blown dust models is dependent on the accuracy of each input condition and the robustness of the model schemes for each elemental step of wind erosion. A thorough evaluation of a wind-blown model thus requires validation of the input conditions and the elemental model schemes. However, most model evaluations and intercomparisons have focused on the final output of the models, i.e., the vertical dust emission. Recently, a delicate set of measurement data for saltation flux and friction velocity was reported from the Japan-Australia Dust Experiment (JADE) Project, which enabled the step-by-step evaluation of wind-blown dust models up to the saltation step. When all the input parameters were provided from the observations, both the two widely used saltation schemes showed very good agreement with measurements, with the correlation coefficient and the agreement of index both being larger than 0.9, which demonstrated the strong robustness of the physical schemes for saltation. However, using the meteorology model to estimate the input conditions such as weather and soil conditions, considerably degraded the models’ performance. The critical reason for the model failure was determined to be the inaccuracy in the estimation of the threshold friction velocity (representing soil condition), followed by inaccurate estimation of surface wind speed. It was not possible to determine which of the two saltation schemes was superior, based on the present study results. Such differentiation will require further evaluation studies using more measurements of saltation flux and vertical dust emissions.

Wind speed acceleration around a single low solid roughness in atmospheric boundary layer

Air flow around vegetation is crucial for particle transport (e.g., dust grains, seeds and pollens) in atmospheric boundary layer. However, wind acceleration around vegetation is still not well understood. In this work, air flow around a single low solid roughness element (representing a dense shrub patch or clump) in atmospheric boundary layer was numerically investigated, with emphasizing wind acceleration zone located at the two lateral sides. The maximum value of dimensionless horizontal wind speed as well as its location of occurrence and the geometrical morphology and area of wind acceleration zone were systematically studied. It reveals that they could alter significantly with the change of roughness basal shape. The maximum value of dimensionless resultant horizontal speed decreases monotonously with observation height, while the area of wind acceleration zone shows a non-linear response to observation height. The dependence of the maximum speed location on observation height is generally weak, but may vary with roughness basal shape. These findings could well explain the disagreement among previous field observations. We hope that these findings could be helpful to improve our understanding of aeolian transport in sparsely vegetated land in arid and semi-arid region, and wind dispersals of seeds and pollens from shrub vegetation.

Comparisons suggest more efforts are required to parameterize wind flow around shrub vegetation elements for predicting aeolian flux

Upon interacting with the atmosphere, vegetation could alter the wind distribution and consequently the erodibility of nearby region. The parameterization of wind distribution around vegetation is crucial for the prediction of surface aeolian flux. This paper compared the performances of existing empirical distribution models in the estimation of aeolian flux for shrub vegetation, focusing on distribution pattern and vegetation porosity (main parameter of distribution function). Predicted dust fluxes directly entrained by air flow show weak sensitivity to both distribution pattern and porosity in the case of low vegetation density, which suggests some aspects in dust forecast models might be simplified. However, both distribution pattern and porosity show significant effect on sand saltation transport rate in the lee of vegetation element and, consequently, on the formation and evolution of surface aeolian landforms. The contribution of dust fluxes released in wind increase zone to the total emission by using current parameterizations increases with both the decrease of wind speed and the increase of vegetation density. Nevertheless, the parameterization of wind increase zone needs to be validated and improved by further experimental and numerical investigations.

Development and evaluation of a physics-based windblown dust emission scheme implemented in the CMAQ modeling system

A new windblown dust emission treatment was incorporated in the Community Multiscale Air Quality (CMAQ) modeling system. This new model treatment has been built upon previously developed physics-based parameterization schemes from the literature. A distinct and novel feature of this scheme, however, is the incorporation of a newly developed dynamic relation for the surface roughness length relevant to small-scale dust generation processes. Through this implementation, the effect of nonerodible elements on the local flow acceleration, drag partitioning, and surface coverage protection is modeled in a physically based and consistent manner. Careful attention is paid in integrating the new windblown dust treatment in the CMAQ model to ensure that the required input parameters are correctly configured. To test the performance of the new dust module in CMAQ, the entire year 2011 is simulated for the continental United States, with particular emphasis on the southwestern United States (SWUS) where windblown dust concentrations are relatively large. Overall, the model shows good performance with the daily mean bias of soil concentrations fluctuating in the range of ±1 μg m-3 for the entire year. Springtime soil concentrations are in quite good agreement (normalized mean bias of 8.3%) with observations, while moderate to high underestimation of soil concentration is seen in the summertime. The latter is attributed to the issue of representing the convective dust storms in summertime. Evaluations against observations for seven elevated dust events in the SWUS indicate that the new windblown dust treatment is capable of capturing spatial and temporal characteristics of dust outbreaks.

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.