Data underlying the publication: A rainfall threshold-based approach to early warnings in urban data-scarce regions: A case study of pluvial flooding in Alexandria, Egypt

This study aims to utilise a probabilistic approach to characterise and predict urban floods by assessing critical rainfall thresholds likely to cause flooding combined with ensemble precipitation forecast in Alexandria, Egypt. Rainfall thresholds were inferred by associating observed rainfall and historical flood information sourced from social media and newspapers. Floods were classified in a colour-coded hazard matrix as no flood (green), minor flood (yellow), significant flood (orange), and severe flood (red). The probability of occurrence of hazard classes was derived by incorporating ensemble rainfall into the hazard matrix to jointly evaluate likelihood and hazard severity. This dataset includes the Ensemble rainfall forecast TIGGE (THORPEX International Grand Global Ensemble) from the ECMWF which is part of the THORPEX (Observing System Research and Predictability Experiment). It also includes rainfall gauge data sourced from METeorological Aerodrome Report (METAR)

本研究旨在采用概率方法，通过结合可能引发洪涝的临界降雨阈值评估与埃及亚历山大市的集合降水预报，对城市洪涝进行特征刻画与预测。研究通过将实测降雨数据与源自社交媒体及报纸的历史洪涝信息相关联，推求临界降雨阈值。洪涝灾害等级通过颜色编码的灾害矩阵划分为四类：无洪涝（绿色）、轻度洪涝（黄色）、显著洪涝（橙色）与严重洪涝（红色）。通过将集合降雨预报纳入灾害矩阵，联合评估灾害发生可能性与严重程度，推导得到各灾害等级的发生概率。本数据集包含欧洲中期天气预报中心（ECMWF）发布的集合降雨预报产品TIGGE（THORPEX国际全球集合预报系统），该产品属于观测系统研究与可预报性试验（THORPEX）的组成部分。此外，数据集还包含源自航空例行天气报告（METAR）的雨量计观测数据。