论文标题
极端沿海海平面频率增加的证据
Evidence for increasing frequency of extreme coastal sea levels
论文作者
论文摘要
极端海平面（ESL）的预测对于管理沿海风险至关重要，但由于深刻的不确定性而变得复杂。一个关键的不确定性是用于估计沿海危害的模型结构的选择。模型结构选择的差异导致估计的沿海危害的不确定性，因此表征模型结构选择如何影响ESL的估计值很重要。在这里，我们从美国东部和墨西哥湾沿岸的潮汐量规站介绍了36个ESL数据集。使用年度块最大值和阈值峰值的方法来对数据进行处理，以对极端的分布进行建模。我们使用这些数据集通过将ESL统计数据与多个气候变量相互变化，以适应一套潜在的非组织极值模型。我们演示了该数据集如何使沿海危害的深度不确定性进行查询。对于此处考虑的所有模型和站点，我们发现沿海极端海平面的频率变化比使用固定的极值模型可以更好地拟合。
Projections of extreme sea levels (ESLs) are critical for managing coastal risks, but are made complicated by deep uncertainties. One key uncertainty is the choice of model structure used to estimate coastal hazards. Differences in model structural choices contribute to uncertainty in estimated coastal hazard, so it is important to characterize how model structural choice affects estimates of ESL. Here, we present a collection of 36 ESL data sets, from tide gauge stations along the United States East and Gulf Coasts. The data are processed using both annual block maxima and peaks-over-thresholds approaches for modeling distributions of extremes. We use these data sets to fit a suite of potentially nonstationary extreme value models by covarying the ESL statistics with multiple climate variables. We demonstrate how this data set enables inquiry into deep uncertainty surrounding coastal hazards. For all of the models and sites considered here, we find that accounting for changes in the frequency of coastal extreme sea levels provides a better fit than using a stationary extreme value model.
