Probabilistic reanalysis of storm surge extremes in Europe
Probabilistic reanalysis of storm surge extremes in Europe
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DOI：
10.1073/pnas.1913049117
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发表时间：
2020-01-28
影响因子：
11.1
通讯作者：
Marcos, Marta
中科院分区：
文献类型：
--
作者：
Calafat, Francisco M.;Marcos, Marta
极端海平面对生命、财产和环境构成重大威胁。沿海规划者通过实施风险缓解策略来管理这些威胁。这种策略的核心是对极端事件概率的了解。通常，这些概率是通过将合适的分布拟合到观察到的极端数据来估计的。然而，由于潮汐测量记录中的极端事件数量很少，并且只能在测量地点获得，因此估计值通常是不确定的。这限制了我们实施具有成本效益的缓解措施的能力。关于海平面极端值的一个值得注意的事实是存在空间依赖性，但迄今为止绝大多数研究都是逐个地点地分析极端值。在这里，我们证明可以利用空间依赖性来解决观测记录的时空稀疏性所带来的限制。我们通过贝叶斯分层模型将所有验潮仪数据汇集在一起来实现这一目标，该模型描述了潮汐极值的分布如何随时间和空间变化。我们的方法有两个非常理想的优点：1）它可以跨数据站点共享信息，从而大大减少估计的不确定性； 2) 它允许在任意未测量位置对极值和极值分布参数进行插值。使用我们的模型，我们对 1960 年至 2013 年期间覆盖整个大西洋和欧洲北海沿岸的海浪极端事件进行了基于观测的概率再分析。
Extreme sea levels are a significant threat to life, property, and the environment. These threats are managed by coastal planers through the implementation of risk mitigation strategies. Central to such strategies is knowledge of extreme event probabilities. Typically, these probabilities are estimated by fitting a suitable distribution to the observed extreme data. Estimates, however, are often uncertain due to the small number of extreme events in the tide gauge record and are only available at gauged locations. This restricts our ability to implement cost-effective mitigation. A remarkable fact about sea-level extremes is the existence of spatial dependences, yet the vast majority of studies to date have analyzed extremes on a site-by-site basis. Here we demonstrate that spatial dependences can be exploited to address the limitations posed by the spatiotemporal sparseness of the observational record. We achieve this by pooling all of the tide gauge data together through a Bayesian hierarchical model that describes how the distribution of surge extremes varies in time and space. Our approach has two highly desirable advantages: 1) it enables sharing of information across data sites, with a consequent drastic reduction in estimation uncertainty; 2) it permits interpolation of both the extreme values and the extreme distribution parameters at any arbitrary ungauged location. Using our model, we produce an observation-based probabilistic reanalysis of surge extremes covering the entire Atlantic and North Sea coasts of Europe for the period 1960-2013.