Diagnosis of severe dust weather process based on multi-source observational data

doi:10.7522/j.issn.1000-694X.2024.00075

Journal of Desert Research ›› 2024, Vol. 44 ›› Issue (6): 195-206.DOI: 10.7522/j.issn.1000-694X.2024.00075

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Diagnosis of severe dust weather process based on multi-source observational data

Yue Wang¹(), Nana Yi²(), Xuegong Jiang³, Guicai Ning¹, Lian Su¹, Haiyun Xia¹()

^1.School of Atmospheric Physics，Nanjing University of Information Science Technology，Nanjing 210044，China
^2.Inner Mongolia Weather Modification Center，Hohhot 010000，China
^3.Inner Mongolia Meteorological Observatory，Hohhot 010000，China

Received:2024-04-26 Revised:2024-08-28 Online:2024-11-20 Published:2024-12-06
Contact: Nana Yi,Haiyun Xia

Abstract

Abstract:

Study utilized multi-source data including vertical observations from lidar， conventional atmospheric pollution， meteorological observations， satellite observations， and reanalysis data， combined with backward trajectory simulations and weather diagnostic analyses to investigate the structural characteristics and evolution mechanisms of a severe dust event occurring in northern China from March 21st to 23rd， 2023. The results indicate that under the influence of Mongolian cyclones， the event spread from northwest to southeast， passing through Bayannur City， Hohhot City， and Zhangjiakou City before reaching Beijing. During this period， the peak PM₁₀ concentration in Beijing reached 1 667 μg?m^-3， significantly lower than the peak concentration in its upstream neighbor， Zhangjiakou City （9 993 μg?m^-3）. The reasons for this can be attributed to the significant attenuation of dust concentration after passing through Zhangjiakou due to the obstruction of the Yan Mountains. Furthermore， backward trajectory results indicate that some dust particles were transported northeastward after leaving Zhangjiakou， influenced by the southwest airflow ahead of the cyclone's front. The vertical structure of the dust event shows that dust transport heights over Beijing can reach 6 000 m. The vertical movement of the troposphere is a sandwich-like structure， characterized by subsidence from near the surface to 920 hPa， ascent from 920 hPa to 700 hPa， and subsidence again from 650 hPa to 450 hPa. This sandwich-like structure is not conducive to dust settling in Beijing area， which is the key reasons for the low dust concentration in Beijing. The temporal evolution of the dust event indicates a rapid increase followed by a slow decrease in the backscattering coefficient derived from Beijing lidar data， while the PM_2.5/PM₁₀ ratio decreased from 0.73 to 0.18.

Key words: dust trajectory, vertical distribution, Beijing City, meteorological factors, lidar

CLC Number:

P457

Yue Wang, Nana Yi, Xuegong Jiang, Guicai Ning, Lian Su, Haiyun Xia. Diagnosis of severe dust weather process based on multi-source observational data[J]. Journal of Desert Research, 2024, 44(6): 195-206.

Figures/Tables 11

Table 1 Key parameters of the CDWL

参数	值
波长	1.5 μm
脉冲能量	150 μJ
望远镜口径	70 mm
脉冲重复频率	10 kHz
时间分辨率	1 s
空间分辨率	30 m
最大探测距离	15 km
方位角	0°~360°
俯仰角	0°~90°

Fig.1 500 hPa temperature （shading； units： ℃；A，C，E，G）， 500 hPa geopotential height （contours； units： gpm；A，C，E，G）， sea level pressure （contours；B，D，F，H）， 10 m gust wind plume （B，D，F，H；unit：m·s-1） at 08:00 BJT on 21（A，B）， 01:00 BJT on 22（C，D）， 06:00 BJT on 22 （E，F） and 17:00 BJT on 22（G，H）， March 2023

Fig.2 Spatial distribution of the typical dust storm occurred for multi-source datasets （DAOD/AOD， DCMD） at （A， D） 14:30 BJT on 21 March，（B， E） 06:30 BJT and （C， F） 17:30 BJT on 22， March 2023

Fig.3 Spatial distribution of the typical dust storm occurred for PM10 concentration at （A） 15:00 BJT on 21 March，（B） 06:00 BJT and （C） 18:00 BJT on 22， March 2023

Fig.4 Hourly variation characteristics of PM10 concentration during sand and dust pollution weather events in cities along the route of dust pollution weather event from 12:00 BJT 21 to 00:00 BJT 23， March 2023 （Missing values at 02:00 and 05:00 on March 22）

Fig.5 The type of aerosol observed by CALIPSO satellite at 04:32 BJT on 22， March 2023 （Satellite trajectory： grey shading）

Fig.6 Time series of particle concentration， proportion and gaseous pollutant concentration in Beijing City before and after the impact of dust （Missing values at 02:00 and 05:00 on March 22）

Fig.7 Vertical profiles of vertical velocity （A）， backscattering coefficient （B） by lidar before and after the impact of dust

Fig.8 （A） The Skew T-lnP diagram of Beijing Sounding Station at 08:00 BJT on 22， March 2023，（B） Time series of wind speed， wind direction， temperature， relative humidity， ground pressure in Beijing City from 00:00 BJT 21 to 00:00 BJT 23， March 2023，（C） The temporal changes of PM10 and wind field （u，v） during sand and dust pollution weather events in cities along the route of dust pollution weather event from 12:00 BJT 21 to 00:00 BJT 23， March 2023 （Missing PM10 values at 02:00 and 05:00 on March 22）

Fig.9 Backward trajectory during dust pollution weather events. （A， C） spatial distribution of MERRA-2 Dust Mixing Ratio；（B， D） spatial distribution of ground PM10 concentration along the route of dust pollution weather event， respectively. The dashed line is the 500 m air mass path， the dashed line is the 2 000 m air mass path， and the dash dot line is the 4 000 m air mass path

Fig.10 The temporal changes of PM10 and wind field （v， w×（-50）） during sand and dust pollution weather events in cities along the route of dust pollution weather event from 12:00 BJT 21 to 00:00 BJT 23， March 2023 （Missing PM10 values at 02:00 and 05:00 on March 22）

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Diagnosis of severe dust weather process based on multi-source observational data

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