RETENCJAPL Sp. Z o.o., Marynarki Polskiej 163, 80-868, Gdańsk, Poland.
Faculty of Natural Sciences, University of Silesia in Katowice, Będzińska 60, 41-200, Sosnowiec, Poland.
Ambio. 2025 Jan;54(1):86-104. doi: 10.1007/s13280-024-02069-6. Epub 2024 Sep 16.
In the light of observed variability in precipitation patterns, there is a growing need for comprehensive data mining of regularly updated rainfall recording databases. Therefore, an analysis of heavy rainfall and hyetographs was conducted using a 30-year high-resolution dataset from 100 rain gauges across Poland, covering 31 646 rainfall events. Distributions of rainfall depths, durations, and intensities were explored, and maxima were compared to global records. Spatial analysis revealed significant variations in the frequency, depths, and durations of extreme rainfall across different regions. Cluster analysis determined model hyetographs for each station. The likelihood of regions belonging to clusters with three to five model hyetographs was assessed using Indicator Kriging. Findings underscore the importance of using local, characteristics rainfalls in hydrodynamic modelling of drainage systems and future rainfall scenarios. These results provide a foundational step towards understanding and monitoring the impacts of climate change on rainfall characteristics, especially extremes, in future decades.
鉴于降水模式的可变性，人们越来越需要对定期更新的降雨记录数据库进行全面的数据挖掘。因此，使用波兰 100 个雨量计的 30 年高分辨率数据集，对大雨和降雨强度图进行了分析，涵盖了 31646 次降雨事件。探讨了降雨深度、持续时间和强度的分布，并将最大值与全球记录进行了比较。空间分析显示，不同地区极端降雨的频率、深度和持续时间存在显著差异。聚类分析确定了每个站点的模型降雨强度图。使用指示克里金法评估了区域属于具有三到五个模型降雨强度图的聚类的可能性。研究结果强调了在排水系统的水动力模型中使用当地特征降雨和未来降雨情景的重要性。这些结果为了解和监测未来几十年气候变化对降雨特征（尤其是极端情况）的影响提供了一个基础步骤。
