The development and evaluation of ensemble hindcasting and forecasting systems (EHS and EFS, respectively) for storm surges in the Río de la Plata Estuary (RdP) is presented. The models were forced by atmospheric sea level pressure and 10 m winds. The ensemble forcing for the EHS was generated by temporal‐spatial shifting of the operational global control ERA5 reanalysis provided by the European Centre of Medium‐Range Weather Forecast (ECMWF), because the ERA5 associated ensemble shows too little dispersion in this area. EFS was instead based on a lead time of 4 days and forced with the 50‐member high‐resolution ensemble prediction system of the ECMWF. EHS was evaluated over a long period (the 2000–2010 decade), whereas EFS was evaluated for the ten most extreme surges that occurred during that period: five positive (which caused coastal flooding) and five negative (which affected navigation and drinking water supply) events. Based on traditional statistics (area under the ROC curve and Brier scores), both systems were assessed from a probabilistic point of view. Results show that both EHS and EFS can incorporate more than 90% of the observations in the uncertainty range. They also showed good skill in hindcasting and forecasting surges, particularly extreme events, EHS being about 20% better than the control model and EFS up to 55% better, in agreement with state‐of‐the‐art models developed for other parts of the world. Results also showed that EFS can predict most of the surge peaks with 95% confidence, with a range of uncertainty of about ±0.90 m and ±9 hr. Therefore, results encourage the implementation of EHS and EFS as useful and robust tools for future climate studies, decision makers and the general public, to improve the quality of risk management decisions by quantifying forecast uncertainty.

中文翻译：

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普拉塔河口风暴潮合奏预报/后播系统的开发和评估

介绍了在拉普拉塔河口（RdP）的风暴潮合奏后预报和预报系统（分别为EHS和EFS）的开发和评估。这些模型是由大气海平面压力和10 m风推动的。EHS的合奏强迫是由欧洲中距离天气预报中心（ECMWF）提供的可操作的全球控制ERA5重新分析的时空移位产生的，因为与ERA5相关的合奏在该区域显示的分散太少。相反，EFS基于4天的交付周期，并由ECMWF的50名成员组成的高分辨率整体预测系统进行强制。对EHS进行了长期（2000-2010十年）评估，而对EFS评估了此期间发生的十次最极端的激增：五个正面事件（造成沿海洪灾）和五个负面事件（影响航行和饮用水供应）。基于传统统计数据（ROC曲线下的面积和Brier分数），从概率的角度评估了这两个系统。结果表明，在不确定性范围内，EHS和EFS均可纳入90％以上的观测值。他们还表现出了出色的后预报和预报浪潮技能，特别是在极端事件中，EHS比控制模型高出约20％，EFS高达55％，与针对该模型其他部分开发的最新模型相一致。世界。结果还表明，EFS可以以95％的置信度预测大多数浪涌峰值，不确定性范围大约为 基于传统统计数据（ROC曲线下的面积和Brier分数），从概率的角度评估了这两个系统。结果表明，在不确定性范围内，EHS和EFS均可纳入90％以上的观测值。他们还表现出了出色的后预报和预报浪潮技能，特别是在极端事件中，EHS比控制模型高出约20％，EFS高达55％，与针对该模型其他部分开发的最新模型相一致。世界。结果还表明，EFS可以以95％的置信度预测大多数浪涌峰值，不确定性范围大约为 基于传统统计数据（ROC曲线下的面积和Brier分数），从概率的角度评估了这两个系统。结果表明，在不确定性范围内，EHS和EFS均可纳入90％以上的观测值。他们还表现出了出色的后预报和预报浪潮技能，特别是在极端事件中，EHS比控制模型高出约20％，EFS高达55％，与针对该模型其他部分开发的最新模型相一致。世界。结果还表明，EFS可以以95％的置信度预测大多数浪涌峰值，不确定性范围大约为 他们还表现出了出色的后预报和预报浪潮技能，特别是在极端事件中，EHS比控制模型高出约20％，EFS则比控制模型高出55％，这与为该项目其他部分开发的最新模型一致世界。结果还表明，EFS可以以95％的置信度预测大多数浪涌峰值，不确定性范围大约为 他们还表现出了出色的后预报和预报浪潮技能，特别是在极端事件中，EHS比控制模型高出约20％，EFS高达55％，与针对该模型其他部分开发的最新模型相一致。世界。结果还表明，EFS可以以95％的置信度预测大多数浪涌峰值，不确定性范围大约为± 0.90 m和± 9 hr。因此，结果鼓励将EHS和EFS实施为未来气候研究，决策者和公众的有用而强大的工具，以通过量化预测不确定性来提高风险管理决策的质量。