Numerical simulation of the influence of wind speed and vegetation on dust weather in Inner Mongolia， China

doi:10.7522/j.issn.1000-694X.2023.00050

Journal of Desert Research ›› 2023, Vol. 43 ›› Issue (6): 29-39.DOI: 10.7522/j.issn.1000-694X.2023.00050

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Numerical simulation of the influence of wind speed and vegetation on dust weather in Inner Mongolia， China

Zhulei Dong¹(), Xuegong Jiang²(), Nana Yi³, Zhili Xu³, Yuehe Hang², Shuiyan Yu³

^1.Inner Mongolia Climate Center，Hohhot 010000，China
^2.Inner Mongolia Meteorological Observatory，Hohhot 010000，China
^3.Inner Mongolia Weather Modification Center，Hohhot 010000，China

Received:2023-02-02 Revised:2023-04-19 Online:2023-11-20 Published:2023-11-30
Contact: Xuegong Jiang

Abstract

Abstract:

The quantitative effects of vegetation coverage and wind speed on the initiation， transport and sand size distribution of a dust process was studied by WRF-Chem in Inner Mongolia. At the same time， based on the dust data of 119 national stations in Inner Mongolia during 1991-2020 and the global atmospheric reanalysis data of China， the temporal changes and spatial distribution of total dust weather frequency， wind speed and vegetation coverage were counted. It is found that the frequency of total dust weather had decreased， the vegetation coverage had increased， and the zonal （radial） wind had significantly decreased in the areas with high dust rates of Inner Mongolia during 1991-2020. The effect of increasing vegetation cover on dust weather was significantly stronger than that of wind speed： the 5% increase in vegetation cover was comparable to the 30% decrease in wind speed that reduces sand emission. Both vegetation and wind speed have a stronger effect on the reduction of small particle size dust in the dust source. Therefore， desertification control projects such as afforestation should first be carried out in semi-desertification areas with fine particles， and on the basis of protecting native vegetation and rational use of water resources， the final vegetation coverage of afforestation can be increased by 10%-15%.

Key words: dust frequency, wind speed, vegetation coverage, WRF-Chem mode, dust concentration, particle size

CLC Number:

P427.2

Zhulei Dong, Xuegong Jiang, Nana Yi, Zhili Xu, Yuehe Hang, Shuiyan Yu. Numerical simulation of the influence of wind speed and vegetation on dust weather in Inner Mongolia， China[J]. Journal of Desert Research, 2023, 43(6): 29-39.

Figures/Tables 13

Fig.1 The spatial distribution of 118 national observation stations in Inner Mongolia

Fig.2 The spatial distribution of the average frequency of dust weather in Inner Mongolia from 1991 to 2020

Fig.3 The time changes of frequency of sand lifting， dust floating， sandstorms and total dust weather in Inner Mongolia from 1991 to 2020， and the dotted line represents the trend of total dust weather frequency

Fig.4 Spatial distribution of zonal （A） and meridional （C） average wind speed at 10 m height and zonal （B） and meridional （D） climatic variability in spring in Inner Mongolia and surrounding areas from 1991 to 2020. The dotted area passed the 90% reliability test

Fig.5 Spatial distribution of average vegetation coverage （unit： %） in year （A） and spring （C） and climatic variability （unit： %·a-1） in year （B） and spring （D） in Inner Mongolia and surrounding areas from 1991 to 2020. The dotted area passed the 90% reliability test

Fig.6 The sea level pressure field （unit： hPa） and wind field （unit： m·s-1） at the initial moment of the model. The black rectangular box area represents the windy area which was modified in sensitivity experiments， and the blue recta-ngular box area represents the vegetation cover was modified by the simulation experiment

Table 1 Subgroup of sensitivity experiments

植被覆盖率敏感性试验分组	植被覆盖率变化方案	风速敏感性试验分组	风速变化方案
casev1	+5%	casew1	-20%
casev2	+10%	casew2	-30%
casev3	+15%	casew3	-40%
casev4	+20%	casew4	-50%

Fig.7 The spatial distribution of actual sand emission （A） and sand emission （unit： μg·m-2） simulated by casev1 （B）， casev2 （C）， casev3 （D）， casev4 （E）， casew1 （F）， casew2 （G）， casew3 （H）， casew4 （I） at 04:00 on May 15， 2019. The black rectangular box area is sand source， and the black dots indicate the southern site of Mongolia （43.12°N，109.21°E） and Erenhot （43.39°N，112.00°E）

Fig.8 The actual sand emission of southern Mongolia （A） and Erenhot （C）， and the simulated sand emission of southern Mongolia （B） and Erenhot （D）

Table 2 Total sand emission and the reduction of total sand emission by vegetation and wind in southern Mongolia and Erenhot in different sensitivity experiments

分组	蒙古国南部		二连浩特（第一次）		二连浩特（第二次）
分组	总起沙量/（μg·m^-2）	削减率%	总起沙量/（μg·m^-2）	削减率/%	总起沙量/（μg·m^-2）	削减率/%
实际	6 673.8	—	11 145.0	—	722.3	—
casev1	2 362.8	64.6	2 634.8	76.4	63.4	91.2
casev2	365.5	94.5	444.0	96.0	0.0	100.0
casev3	13.9	99.8	38.6	99.7	0.0	100.0
casev4	0.0	100.0	0.0	100	0.0	100.0
casew1	2 918.7	56.3	4 419.1	60.3	417.9	42.1
casew2	2 013.6	69.8	2 938.5	73.6	270.8	62.5
casew3	1 199.2	82.0	1 869.8	83.2	199.1	72.4
casew4	884.5	86.7	1 502.7	86.5	170.5	76.4

Fig.9 The spatial distribution of actual critical friction velocity （A） and critical friction velocity simulated by casev1 （B）， casev2 （C）， casev3 （D）， casev4 （E）， casew1 （F）， casew2 （G）， casew3 （H）， casew4 （I） at 04:00 on May 15. The black grid area indicates sand emission flux is 50-3 000 μg·m-2. The blue box area indicates the sand source of the process

Fig.10 The actual contribution rate （A） of different particle sizes to the sand emission in Erenhot and contribution rates simulated by casev1 （B）， casev2 （C）， casev3 （D）， casew1 （E）， casew2 （F）， casew3 （G）， casew4 （H）

Fig.11 The actual contribution rate of different sizes particle to the surface sand concentration （A） in Baicheng Station in downstream of the sand source， the concentration of different sizes particle in different vegetation coverage （B） and wind speed （D） sensitivity tests， the concentrations reduction rate of vegetation coverage （C） and wind speed （E） to different sizes particle， and fitting of surface sand concentrations in different vegetation coverage （F） and wind speed （G） sensitivity experiments

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Numerical simulation of the influence of wind speed and vegetation on dust weather in Inner Mongolia， China

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