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Using meteorological station observations, ERA5-L and reanalysis data, and Landsat remote sensing imagery from 2010 to 2023, we analysed the spatiotemporal characteristics of dust storms in the Ebinur Lake Basin of Xinjiang Uygur Autonomeus Region, northwest China. The generalized grey correlation model was applied to quantitatively assess the influence of surface wind speed, soil moisture, and vegetation coverage on the frequency of dust storm occurrences. The results showed an overall upward trend in dust storm days during 2010~2023 (+0.08d/a). In particular, there was a significant increase from 2010 to 2014 (+0.60d/a), followed by a short decline from 2014 to 2017 (-0.70d/a), and a rise after 2018(+0.31d/a). Spring was identified as the peak season for dust storm occurrences, with a lower frequency observed in summer and autumn, and no recorded events in winter. Spatially, the Jinghe meteorological station emerged as the high-frequency centre over the past 14 years. Compared with the late 20th century, the standard deviation of annual dust storm days across the five meteorological stations decreased by 88.42%, indicating a substantial reduction in regional disparities. It revealed that surface wind speed was the most critical driver of dust storms. Soil moisture was the second most influential factor, showing a distinct seasonal lag effect, while vegetation coverage exerted a comparatively minor influence on dust storm occurrence.

, authors=Chen-wei WANG^{1, 2, 3}, Xiao-xiao ZHANG^{1, *}, Yi-bo XUE^{1, 2}, Jie ZHOU¹, Jia-qiang LEI¹, Sheng-yu LI¹, authorsList=Chen-wei WANG, Xiao-xiao ZHANG, Yi-bo XUE, Jie ZHOU, Jia-qiang LEI, Sheng-yu LI, authorCompany=null, correspAuthors=Xiao-xiao ZHANG, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1314918256473891634, articleId=1314918255618253616, tenantId=1146029695717560320, journalId=1234093305789726721, language=CN, title=艾比湖流域2010~2023年沙尘暴时空变化及驱动因素研究, columnId=1234106388364981004, journalTitle=中国环境科学, columnName=大气污染与控制, runingTitle=null, highlight=null, articleAbstract=

以新疆艾比湖流域为研究区，基于气象站点观测数据、ERA5-Land再分析数据及Landsat遥感影像等多源数据，探究流域内沙尘暴的时空变化特征，并通过广义灰色关联度分析模型定量评估地表风速、土壤湿度和植被覆盖对流域内沙尘暴发生日数的影响．结果显示：2010~2023年间艾比湖流域沙尘暴日数呈现波动上升趋势（+0.08d/a），其中2010~2014年增速显著（+0.60d/a），2014~2017年短暂下降（-0.70d/a），2018年后恢复增长态势（+0.31d/a）；春季为沙尘暴高发季节，夏秋季次之，冬季无沙尘暴天气记录；空间分布上，精河站为近14a沙尘暴高频中心；相较20世纪末，各气象站点年均沙尘暴日数标准差下降88.42%，表明区域差异性显著降低．地表风速是艾比湖流域沙尘暴的首要驱动因素；土壤湿度的影响次之，并呈现季节性时滞效应；相较于地表风速和土壤湿度，植被覆盖对沙尘暴发生日数的影响相对有限．

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王陈伟（2002-），男，陕西榆林人，中国科学院大学硕士研究生，主要从事干旱区大气环境研究．wangchenwei24@mails.ucas.ac.cn.

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王陈伟（2002-），男，陕西榆林人，中国科学院大学硕士研究生，主要从事干旱区大气环境研究．wangchenwei24@mails.ucas.ac.cn.

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