Liu et al. (2026) Spatiotemporal patterns and driving forces of dust weather events in Central Asia from 2000 to 2020

Identification

• Journal: Journal of Arid Land
• Year: 2026
• Date: 2026-01-01
• Authors: Yuhan Liu, Zhao Yuanyuan, Gao Guanglei, Ding Guodong, Ning Li
• DOI: 10.1016/j.jaridl.2026.01.002

Research Groups

• School of Soil and Water Conservation, Beijing Forestry University, Beijing, China
• Guyuan Forestry and Grassland Development Service Center, Ningxia, China

Short Summary

This study investigated the spatiotemporal patterns and driving forces of dust weather in Central Asia from 2000 to 2020, revealing a dominant west-to-east "dust belt" distribution, an increase in weak dust events, a slight decrease in strong dust events, and the most significant influence from the combined effects of soil moisture and air temperature.

Objective

• To characterize the dynamic distribution of long time series of dust weather (weak, strong, and total) in Central Asia.
• To reveal the key environmental drivers affecting the distribution of dust weather in Central Asia.
• To elucidate the underlying mechanisms for the characteristics of dust weather in Central Asia and propose corresponding prevention and control measures.

Study Configuration

• Spatial Scale: Five Central Asian countries (Kazakhstan, Uzbekistan, Kyrgyzstan, Turkmenistan, and Tajikistan), covering a combined area of 5.67 × 10^6 km^2.
• Temporal Scale: 2000 to 2020 (21 years).

Methodology and Data

• Models used:
  • Theil-Sen trend analysis
  • Mann-Kendall trend test
  • Geodetector modeling method (factor detector and interaction detector)
  • Cluster analysis (using SPSS v.24.0 software for data discretization)
• Data sources:
  • Dust data: Daily ground-based meteorological observations from the Integrated Surface Dataset (ISD) of the National Climatic Data Center (NCDC), observed every 3 or 6 hours. Categorized into strong dust weather (sandstorms, strong sandstorms) and weak dust weather (floating dust, blowing dust).
  • Meteorological data: Annual precipitation, temperature, and average wind speed from 2000 to 2020, obtained from the meteorological dataset of the NCDC.
  • Vegetation data: Normalized Difference Vegetation Index (NDVI) from MOD13A2 product (1 km spatial resolution), processed via Google Earth Engine (GEE).
  • Soil moisture data: ERA5 (ECMWF Reanalysis v.5.0) dataset (0.25° × 0.25° resolution).
  • Land use data: European Space Agency (ESA) Climate Change Initiative (CCI) Land Cover dataset (300 m spatial resolution).

Main Results

• Dust weather in Central Asia is primarily distributed in a large "dust belt" extending from west to east from the northern Caspian lowland desert, concentrated in basins, plains, and other low-altitude areas.
• Strong dust weather mainly occurred in northern areas of the Aral Sea and the southern edge of Central Asia, with a maximum annual frequency of 21.9%.
• From 2000 to 2020, strong dust weather in Central Asia fluctuated and slightly decreased, with the highest frequency (1.1%) occurring in spring (March to June). Weak dust weather showed an overall increasing trend, peaking in summer (1.7% in August). Total dust frequency slowly increased with fluctuations, peaking in June (2.4%).
• The four main sandstorm source areas (north of the Aral Sea, Kyzylkum Desert, Karakum Desert, and Garabogazköl Bay region) experienced spot shifting and shrinking, with the northern Caspian lowland desert becoming the most important low-emission dust source.
• The combined effect of soil moisture and air temperature had the most significant influence on dust weather in Central Asia (q-value of 0.464 for total dust weather).
• For weak dust weather, the interaction between temperature and soil moisture had the largest q-value (0.440). For strong dust weather, the interaction between wind speed and temperature had the largest q-value (0.455).
• Individually, temperature and soil moisture were dominant factors, followed by land use type and NDVI. Precipitation and wind speed had smaller effects.

Contributions

• Provides a comprehensive, updated analysis of the spatiotemporal patterns and driving forces of weak, strong, and total dust weather in Central Asia over a 21-year period using the latest ground observations and advanced statistical methods (Geodetector).
• Presents a long-term dust weather dataset and a map of spatial and temporal distribution of dust source areas in Central Asia.
• Offers a theoretical basis for sand prevention and control, and provides important basic data support for climate change research, dust emission mechanisms, and driving factors in arid regions of Central Asia.

Funding

• National Natural Science Foundation of China (Project code: 42571311)

Citation

@article{Liu2026Spatiotemporal,
  author = {Liu, Yuhan and Yuanyuan, Zhao and Guanglei, Gao and Guodong, Ding and Li, Ning},
  title = {Spatiotemporal patterns and driving forces of dust weather events in Central Asia from 2000 to 2020},
  journal = {Journal of Arid Land},
  year = {2026},
  doi = {10.1016/j.jaridl.2026.01.002},
  url = {https://doi.org/10.1016/j.jaridl.2026.01.002}
}