Numerical simulation and spatiotemporal tracking of sand and dust storm events in East Asia

doi:10.1016/j.jaridl.2026.03.001

Journal of Arid Land

2026, Vol. 18

Issue (3): 353-371 DOI: 10.1016/j.jaridl.2026.03.001 CSTR: 32276.14.JAL.20250455

Research article

Numerical simulation and spatiotemporal tracking of sand and dust storm events in East Asia

HUANG Shaopu¹^,², WANG Juanle²^,³^,^*(

), WANG Lixin¹, GUO Yanhong¹

¹School of Ecology and Environment, Inner Mongolia University, Hohhot 010021, China
²State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
³College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China

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Abstract

Sand and dust storms (SDSs) are natural disasters that frequently occur during spring in arid and semi-arid areas., causing serious impacts on human health, air quality, transportation, and agricultural production. Accurately simulating the occurrence and evolution of SDSs is of great significance for identifying dust sources and formulating effective disaster prevention measures. In this study, numerical simulations were conducted to reveal the dynamic spatiotemporal evolution and transport of dust load across East Asia. Using the Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem) and European Centre for Medium-Range Weather Forecasts Reanalysis v5 (ERA5) data, the most severe SDS events in the spring of 2023 in East Asia were numerically simulated. The simulated results were compared and validated using meteorological observations and multisource remote sensing data. The results showed that the simulated dust load in the peak regions showed close agreement with ground-based observations during the events. The primary dust sources in spring 2023 were identified as the western desert of Mongolia, the Gobi Desert, and the Taklimakan Desert in Xinjiang Uygur Autonomous Region of China. Peak dust load and maximum wind speed occurred almost simultaneously, indicating that high wind speed was the primary driver of sand and dust mobilization during individual SDS events. Increased surface vegetation covers partially mitigated wind-driven dust emissions. In April, strong winds over the Gobi Desert on the Mongolian Plateau predominantly drove cross-border SDSs along northwestern and northward transport pathways. Dust originating from Mongolia exerts a substantial influence on particulate dust load in the central and eastern parts of Inner Mongolia Autonomous Region of China. In contrast, their impact on the northwestern regions of China remains relatively limited. These findings contribute to understanding the source areas of SDS events in East Asia by simulating the dynamic evolution of SDSs and elucidating the relationships between SDS events and local geographical and environmental factors.

Key words： sand and dust storm (SDS) dust load Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem) European Centre for Medium-Range Weather Forecasts Reanalysis v5 (ERA5) wind speed Taklimakan Desert Mongolian Plateau

Received: 15 October 2025 Published: 31 March 2026

Corresponding Authors: *WANG Juanle (E-mail: wangjl@igsnrr.ac.cn)

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Cite this article:

HUANG Shaopu, WANG Juanle, WANG Lixin, GUO Yanhong. Numerical simulation and spatiotemporal tracking of sand and dust storm events in East Asia. Journal of Arid Land, 2026, 18(3): 353-371.

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http://jal.xjegi.com/10.1016/j.jaridl.2026.03.001 OR http://jal.xjegi.com/Y2026/V18/I3/353

Fig. 1 Land cover types in the study area and the locations of the deserts

Table 1 Overview of the variables used for the three selected sand and dust storm (SDS) events in spring 2023

Table 2 Physical parameterization schemes used in the Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem)

Fig. 2 Comparison of simulated sand and dust storm (SDS) impact ranges (indicated by dust load) and remote sensing observations from the Himawari-8 satellite in spring 2023. (a), simulation at 12:00 (UTC) on 20 March; (b), Himawari-8 satellite observation at 12:00 on 20 March; (c), simulation at 10:00 on 10 April; (d), Himawari-8 satellite observation at 10:00 on 10 April. The red areas in the right panel indicate dust.

Fig. 3 Comparison between simulated and observed PM₁₀ concentrations at different ground-based stations between 9 and 14 April, 2023. (a), Hohhot; (b), Ordos; (c), Wuhai; (d), Baotou.

Fig. 4 Aerosol extinction coefficient profiles and satellite orbits derived from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) during the SDS events in spring 2023. (a), extinction coefficient profile at 07:23 on 20 March; (b), extinction coefficient profile at 07:38 on 16 May; (c), satellite orbit derived from CALIPSO at 07:23 on 20 March, showing as the black dotted line; (d), satellite orbit derived from CALIPSO at 07:38 on 16 May, showing as the black dotted line. AOD, aerosol optical depth.

Fig. 5 Simulated SDS events indicated by dust load from 19 to 23 March, 2023. (a), 06:00 on 19 March; (b), 18:00 on 19 March; (c), 06:00 on 20 March; (d), 18:00 on 20 March; (e), 06:00 on 21 March; (f), 18:00 on 21 March; (g), 06:00 on 22 March; (h), 18:00 on 22 March; (i), 06:00 on 23 March.

Fig. 6 Simulated SDS events indicated by dust load from 13 to 17 May, 2023. (a), 20:00 on 13 May; (b), 04:00 on 14 May; (c), 14:00 on 14 May; (d), 00:00 on 15 May; (e), 10:00 on 15 May; (f), 20:00 on 15 May; (g), 06:00 on 16 May; (h), 16:00 on 16 May; (i), 02:00 on 17 May.

Fig. 7 Comparison between wind speed and simulated PM₁₀ concentration at Bayannur Linhe (a) and Hohhot Baita (b) observation stations from 9 to 14 April, 2023

Fig. 8 Regional dust load before and after masking the Mongolian dust source regions. (a), regional dust load before masking the Mongolian dust source regions; (b), regional dust load after masking the Mongolian dust source regions.

Fig. 9 Dust loads before and after masking the Mongolian dust source regions at multiple observation sites (a-f), and the 850 hPa wind field during the start (9 April 2023; g) and end (15 April 2023; h) times of the SDS events. The x-axis in panels (a)-(f) represents the timing of the SDS events, spanning the period from 9 to 15 April, 2023. ERA5, European Centre for Medium-Range Weather Forecasts Reanalysis v5.

Fig. 10 Distribution of primary dust sources for the SDS events in March and May 2023 and wind speed observation stations

Fig. 11 Wind speed difference (wind speed in May minus wind speed in March) at five observation stations. The y-axis represents the difference in wind speed between the locations on 18-19 March and 14-15 May.

Fig. 12 Spatial distribution of near-surface wind speed and wind direction from 9 to 15 April, 2023 based on ERA5 data


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