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

Abstract

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.

Modelling the 2021 East Asia super dust storm using FLEXPART and FLEXDUST and its comparison with reanalyses and observations

“…In particular, the KOK14 scheme simulates more (less) emission over Taklimakan desert (northeastern China) than the MB95 scheme (Figure 12D; Supplementary Figure S8), which is more consistent with MERRA-2 and CAMS-F. The better performance of the KOK14 scheme has been demonstrated in Kok et al (2014) and has been shown in previous studies that the KOK14 scheme tends to predict more dust emission than the MB95 scheme during the Asian dust storm event (Wu et al, 2019;Zeng et al, 2020;Wang et al, 2022) and thus shows better agreement with observation. This can be linked to the high sensitivity of dust flux in the KOK14 scheme to the soil's threshold friction velocity, as it accounts for soil's increased ability to produce dust under continuous saltation bombardment, taking also into account an increased scaling of the vertical dust flux with wind speed (Kok et al, 2014).…”

“…FLEXPART using the output of FLEXDUST-update yields comparable results to MERRA-2 and CAMS-F, and similar to the two dataset, it still underestimates the observed peak of surface PM 10 (by an order of magnitude at some sites) during the dust storm event (Figure 5). It is also noticed that studies using the meso-scale model WRF-CHEM and an offline chemical transport model CAMx also exhibit a similar magnitude of underestimation of surface PM 10 during Frontiers in Environmental Science frontiersin.org the East Asian dust storm events using their default settings (Song et al, 2019;Wang et al, 2022). The underestimation of the observed surface PM 10 peak during the dust storm event can be largely ascribed to the underestimation of the dust emission in the models.…”

“…ERA5 indeed exhibits small biases in the mean wind speed in TA (+.3 m/s), GB (−.2 m/s) and NC (+.1 m/s). On the other hand, Wang et al (2022) has shown that the use of gusty wind to capture short-term variation in wind speed can increase dust emission and concentration by more than 50% for the 2021 dust storm. Using gusty wind instead of hourly-average wind speed in FLEXDUST may help reducing the underestimation of dust emission.…”

“…It has been found that the barer, drier and more loosened soil due to the anomalous early snow melting and a lack of precipitation in spring over the dust source region, together with the exceptionally strong Mongolian cyclone developed over the source region (i.e., central and eastern Mongolia), had triggered the emission and transport of enormous amounts of dust to East Asia during this event (Gui et al, 2022;Yin et al, 2022). The 2021 East Asia sandstorm has provided a unique testbed for dust modelling, particularly in regard to dust emission schemes which has the largest uncertainties (Jin et al, 2022;Wang et al, 2022). The ability of dust models in reproducing such extreme dust events will be critical for understanding the causes and projecting the occurrences of such extreme events in the future.…”

Important role of turbulent wind gust and its coherent structure in the rapid removal of urban air pollution

“…Cheng et al (2012) explained the mechanism of soil erosion and sand entrainment by the coherent structure of wind gusts by means of Lattice Boltzmann Method. The implementation of the gust-wind model could help improve the simulation performance in the concentration of PM 10 during severe sand and dust storms (Wang et al 2022). Models for dust storm forecasting could be improved by utilizing atmospheric humidity and wind speed as the main drivers for dust generation and transport (Csavina et al 2014).…”