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Extreme Storm Surge estimation and projection through the Metastatistical Extreme Value Distribution
Natural Hazards and Earth System Sciences ( IF 4.2 ) Pub Date : 2021-08-18 , DOI: 10.5194/nhess-2021-236
Maria Francesca Caruso , Marco Marani

Abstract. Accurate estimates of the probability of extreme sea levels are pivotal for assessing risk and the design of coastal defense structures. This probability is typically estimated by modelling observed sea-level records using one of a few statistical approaches. In this study we comparatively apply the Generalized Extreme Value (GEV) distribution, based on Block Maxima (BM) and Peak-Over-Threshold (POT) formulations, and the recently Metastatistical Extreme Value Distribution (MEVD) to four long time series of sea-level observations distributed along European coastlines. A cross-validation approach, dividing available data in separate calibration and test sub-samples, is used to compare their performances in high-quantile estimation. To address the limitations posed by the length of the observational time series, we quantify the estimation uncertainty associated with different calibration sample sizes, from 5 to 30 years. Focusing on events with a high return period, we find that the GEV-based approaches and MEVD perform similarly when considering short samples (5 years), while the MEVD estimates outperform the traditional methods when longer calibration sample sizes (10-30 years) are considered. We then investigate the influence of sea-level rise through 2100 on storm surges frequencies. The projections indicate an increase in the height of storm surges for a fixed return period that are spatially heterogeneous across the coastal locations explored.

中文翻译:

通过 Metastatistical 极值分布估计和预测极端风暴潮

摘要。准确估计极端海平面的概率对于评估风险和海岸防御结构的设计至关重要。这种概率通常是通过使用几种统计方法之一对观察到的海平面记录进行建模来估计的。在这项研究中,我们比较应用广义极值 (GEV) 分布,基于块最大值 (BM) 和峰值超过阈值 (POT) 公式,以及最近的元统计极值分布 (MEVD) 到四个长时间序列的海沿欧洲海岸线分布的水平观测。交叉验证方法将可用数据划分为单独的校准和测试子样本,用于比较它们在高分位数估计中的性能。为了解决观测时间序列长度带来的限制,我们量化了与不同校准样本量相关的估计不确定性,从 5 年到 30 年不等。关注具有高回报期的事件,我们发现基于 GEV 的方法和 MEVD 在考虑短样本(5 年)时表现相似,而当较长的校准样本量(10-30 年)为时,MEVD 估计优于传统方法考虑。然后,我们调查了 2100 年海平面上升对风暴潮频率的影响。预测表明,在所探索的沿海地区空间异质性的固定重现期内,风暴潮的高度会增加。我们发现基于 GEV 的方法和 MEVD 在考虑短样本(5 年)时表现相似,而当考虑更长的校准样本量(10-30 年)时,MEVD 估计优于传统方法。然后,我们调查了 2100 年海平面上升对风暴潮频率的影响。预测表明,在所探索的沿海地区空间异质性的固定重现期内,风暴潮的高度会增加。我们发现基于 GEV 的方法和 MEVD 在考虑短样本(5 年)时表现相似,而当考虑更长的校准样本量(10-30 年)时,MEVD 估计优于传统方法。然后,我们调查了 2100 年海平面上升对风暴潮频率的影响。预测表明,在所探索的沿海地区空间异质性的固定重现期内,风暴潮的高度会增加。
更新日期:2021-08-19
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