ABSTRACT: Drought is currently one of the most severe natural disasters affecting the world. Therefore, characterizing the temporal and spatial characteristics of droughts is critical to managing drought disasters and coping with global climate change. In this study, we apply the ensemble empirical mode decomposition (EEMD), empirical orthogonal function (EOF) decomposition, and the drought event division method of run theory to analyze the temporal and spatial characteristics of meteorological droughts across the globe from 1901 to 2020 using the self-calibrated Palmer drought severity index (scPDSI). We found that the world was gradually becoming wetter from 1901 to 2020, but the severity and duration of severe and extreme drought events also increased. In contrast to the PDSI, which showed no obvious short-period changes, the annual drought severity (ADS) had short cycle changes of 8 and 17 yr. Based on the EOF decomposition results of drought characteristics, dry and wet trends of local PDSI are inconsistent with increasing or decreasing trends of severe and extreme drought events. This research on the temporal and spatial decomposition of severe and extreme drought events provides a new perspective on drought research and analysis, which is critical for the further characterization of drought and the prevention and management of drought disasters.

中文翻译：

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1901 年至 2020 年年度干旱严重程度、持续时间和频率的时空变化

摘要：干旱是目前影响世界的最严重的自然灾害之一。因此，表征干旱的时空特征对于管理干旱灾害和应对全球气候变化至关重要。在这项研究中，我们应用集合经验模态分解（EEMD）、经验正交函数（EOF）分解和运行理论的干旱事件划分方法来分析 1901-2020 年全球气象干旱的时空特征，使用自校准帕尔默干旱严重程度指数（scPDSI）。我们发现，从 1901 年到 2020 年，世界逐渐变得更加湿润，但严重和极端干旱事件的严重程度和持续时间也在增加。与没有明显短期变化的 PDSI 相比，年干旱严重程度（ADS）有8年和17年的短周期变化。根据干旱特征的EOF分解结果，局部PDSI的干湿趋势与严重和极端干旱事件的增加或减少趋势不一致。这项对严重和极端干旱事件时空分解的研究为干旱研究和分析提供了新的视角，这对于进一步表征干旱和干旱灾害的预防和管理至关重要。