Liu Siqiu, Zhang Yongwen
Data Science Research Center, Faculty of Science, Kunming University of Science and Technology, Kunming, 650500, China.
Sci Rep. 2025 Jul 2;15(1):22943. doi: 10.1038/s41598-025-06644-z.
Understanding the spatiotemporal interplay between the duration of extreme precipitation events and wet-day frequency (i.e., the relative number of days that exceed a minimal daily precipitation threshold) is critical for predicting hydrological risks in a changing climate. Here, we analyze ERA5 reanalysis and employ percentile thresholds to define extreme precipitation events in daily scale, investigating global patterns of the duration of extreme precipitation events across areas classified by wet-day frequency. Our analysis reveals that increased wet-day frequencies are generally associated with a steeper decay of duration distribution and lower mean durations, except in areas with a frequency exceeding 0.8, where the mean duration slightly increases. This overall negative correlation mainly stems from limitations in atmospheric moisture availability, while the anomalous increase in high wet-day frequency areas is attributed to their concentration in low-latitude regions, where extreme precipitation events have longer durations. Further analysis reveals a distinct latitudinal dichotomy under this phenomenon: mid-latitude regions (30°-60°) show a strong linear negative correlation (r = - 0.77), governed by synoptic-scale dynamics and wind-modulated precipitation systems. In contrast, low-latitude regions (0°-30°) demonstrate a nonlinear (initially increasing then decreasing) relationship with a significant correlation (r = 0.63) between these durations and amplified annual precipitation cycles, typically linked to seasonal rainfall clustering mechanisms. Threshold sensitivity tests confirm the robustness of these results, except in low latitudes and at the 99th percentile threshold, due to limited data sample. The MSWEP and PERSIANN datasets are also tested with similar results found. These finding can enhance prediction accuracy for extreme precipitation events and inform regional flood risk management.
了解极端降水事件的持续时间与湿日频率（即超过每日最小降水阈值的相对天数）之间的时空相互作用，对于预测气候变化中的水文风险至关重要。在此，我们分析了ERA5再分析资料，并采用百分位阈值来定义日尺度上的极端降水事件，研究了按湿日频率分类的各区域极端降水事件持续时间的全球模式。我们的分析表明，除了频率超过0.8的区域，湿日频率增加通常与持续时间分布的更陡峭衰减和更低的平均持续时间相关，在频率超过0.8的区域，平均持续时间略有增加。这种总体负相关主要源于大气水分供应的限制，而高湿日频率区域的异常增加归因于它们集中在低纬度地区，在这些地区极端降水事件持续时间更长。进一步分析揭示了这种现象下明显的纬度二分法：中纬度地区（30°-60°）呈现出强烈的线性负相关（r = -0.77），受天气尺度动力学和风调制降水系统控制。相比之下，低纬度地区（0°-30°）呈现出非线性（先增加后减少）关系，这些持续时间与放大的年降水周期之间存在显著相关性（r = 0.63），通常与季节性降雨聚集机制有关。阈值敏感性测试证实了这些结果的稳健性，但在低纬度地区和第99百分位阈值处除外，因为数据样本有限。对MSWEP和PERSIANN数据集也进行了测试，发现了类似的结果。这些发现可以提高极端降水事件的预测准确性，并为区域洪水风险管理提供信息。
