Compound Extreme Events Associated With Extreme Dust Events in the Gobi Desert Shift From Extreme Dust‐Extreme Cold Events to Extreme Hot‐Extreme Dust Events

Abstract Compound extreme weather events are frequent and exhibit new features in the context of global change. This study unravels the characteristics, variations, and driving factors of compound extreme temperature‐extreme dust events in the Gobi Desert (GD) during the springs of 2000–2023. The temperature in the GD is high before extreme dust events (EDEs), while that is low during EDEs. Correspondingly, extreme hot events (EHEs) occur prior to EDEs and extreme cold events (ECEs) occur during EDEs. The frequency of EHEs associated with EDEs in 2012–2023 is 100% higher than that in 2000–2011, while the frequency of ECEs associated with EDEs in 2012–2023 is 75% lower than that in 2000–2011. Accordingly, compound extreme events associated with EDEs shift from EDE‐ECEs to EHE‐EDEs. By strengthening East Asian anomalous high pressure, enhanced Arctic Oscillation during the pre‐EDE periods and weakened Eurasian teleconnection during EDEs increases EHEs and decreases ECEs, respectively, and combined drive the shift in the compound extreme events. This study reveals a new feature of compound extreme weather events in the context of climate change, which manifests as the shift from EDE‐ECEs to EHE‐EDEs in the GD. The occurrence of more EHE‐EDEs will put already fragile ecosystems of the GD at even greater risk. Therefore, the containment of global warming, especially in arid and semiarid regions, is necessary and urgent.

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Publication Details

Journal
Journal of Geophysical Research Atmospheres
Published
2025-05-06
DOI
https://doi.org/10.1029/2025jd043325
Citations
1
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
1.11

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article

Compound Extreme Events Associated With Extreme Dust Events in the Gobi Desert Shift From Extreme Dust‐Extreme Cold Events to Extreme Hot‐Extreme Dust Events

Qingzhe Zhu, Yuzhi Liu, Rui Jia, Na Xiao
1 citations
Journal of Geophysical Research Atmospheres
Climate variability and models
1.11
article

Compound Extreme Events Associated With Extreme Dust Events in the Gobi Desert Shift From Extreme Dust‐Extreme Cold Events to Extreme Hot‐Extreme Dust Events

Qingzhe Zhu, Yuzhi Liu, Rui Jia, Na Xiao
article en
1 citations

Abstract

Abstract Compound extreme weather events are frequent and exhibit new features in the context of global change. This study unravels the characteristics, variations, and driving factors of compound extreme temperature‐extreme dust events in the Gobi Desert (GD) during the springs of 2000–2023. The temperature in the GD is high before extreme dust events (EDEs), while that is low during EDEs. Correspondingly, extreme hot events (EHEs) occur prior to EDEs and extreme cold events (ECEs) occur during EDEs. The frequency of EHEs associated with EDEs in 2012–2023 is 100% higher than that in 2000–2011, while the frequency of ECEs associated with EDEs in 2012–2023 is 75% lower than that in 2000–2011. Accordingly, compound extreme events associated with EDEs shift from EDE‐ECEs to EHE‐EDEs. By strengthening East Asian anomalous high pressure, enhanced Arctic Oscillation during the pre‐EDE periods and weakened Eurasian teleconnection during EDEs increases EHEs and decreases ECEs, respectively, and combined drive the shift in the compound extreme events. This study reveals a new feature of compound extreme weather events in the context of climate change, which manifests as the shift from EDE‐ECEs to EHE‐EDEs in the GD. The occurrence of more EHE‐EDEs will put already fragile ecosystems of the GD at even greater risk. Therefore, the containment of global warming, especially in arid and semiarid regions, is necessary and urgent.

Journal of Geophysical Research AtmospheresVol. 130(9)
Jilin Weather Modification Office (CN), Ocean University of China (CN), Lanzhou University (CN)
Ocean University of China, Natural Science Foundation of Shandong Province, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 24%
Climate variability and models
1.11
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