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Temporal and Spatial Dynamics of Dust Storms in Uzbekistan from Meteorological Station Records (2010–2023)

Natella RakhmatovaHydrometeorological Research Institute, Agency of Hydrometeorological Service of the Republic of Uzbekistan, Tashkent 100052, UzbekistanBakhriddin NishonovFaculty of Hydrometeorology, National University of Uzbekistan, Tashkent 100174, UzbekistanLyudmila ShardakovaHydrometeorological Research Institute, Agency of Hydrometeorological Service of the Republic of Uzbekistan, Tashkent 100052, UzbekistanAlbina AkhmedovaAlisher KhudoyberdievHydrometeorological Research Institute, Agency of Hydrometeorological Service of the Republic of Uzbekistan, Tashkent 100052, UzbekistanValeriya RakhmatovaGraduate School of Engineering, Kyoto University, Gokasho, Uji 611-0011, JapanDmitry BelikovCenter for Environmental Remote Sensing, Chiba University, Chiba 263-8522, Japan
Atmospherejournal2025en
ABI

Аннотация

This study provides a comprehensive spatiotemporal analysis of sand and dust storms (SDSs) in Uzbekistan using ground-based meteorological data from 2010 to 2023. The results reveal significant spatial heterogeneity in the SDS activity, with the highest frequency of SDS days observed in the southern and western regions, including Surkhandarya, Kashkadarya, Bukhara, Khorezm, and Republic of Karakalpakstan. In the most vulnerable areas, such as Karakalpakstan, Surkhandarya, and Kashkadarya, the annual number of SDS days can exceed 80 in certain years, reflecting a high recurrence of extreme dust events in certain climatic zones. About 53% of the SDS events were regional, affecting several stations, while 47% were localized, indicating a combination of large-scale dust transport and localized emissions. Seasonal patterns showed a peak SDS activity between March and August, coinciding with the dry season characterized by elevated temperatures, reduced soil moisture, and intense agricultural activity, all of which contribute to the surface exposure and increased vulnerability. This study found a significant variation in the event duration across regions, with Karakalpakstan and Surkhandarya experiencing the highest proportion of prolonged events due to its orography and persistent southerly wind patterns. Using ERA5 data and a decision tree regressor, the analysis identified the wind direction and mean wind speed as the most influential meteorological factors, followed by the maximum wind speed and soil temperature, with other variables such as solar radiation and soil moisture playing moderate roles. This study highlights the importance of regional wind patterns and geomorphology in SDS formation, with prevailing wind directions from the northwest, west, and south. The integration of the ERA5 reanalysis and machine learning techniques offers significant potential for improving SDS monitoring and studies.

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