Civil, Environmental, and Construction Engineering & National Center for Integrated Coastal Research, University of Central Florida, Orlando, USA.
Sci Data. 2021 May 4;8(1):125. doi: 10.1038/s41597-021-00906-x.
Storm surges are among the deadliest coastal hazards and understanding how they have been affected by climate change and variability in the past is crucial to prepare for the future. However, tide gauge records are often too short to assess trends and perform robust statistical analyses. Here we use a data-driven modeling framework to simulate daily maximum surge values at 882 tide gauge locations across the globe. We use five different atmospheric reanalysis products for the storm surge reconstruction, the longest one going as far back as 1836. The data that we generate can be used, for example, for long-term trend analyses of the storm surge climate and identification of regions where changes in the intensity and/or frequency of storms surges have occurred in the past. It also provides a better basis for robust extreme value analysis, especially for tide gauges where observational records are short. The data are made available for public use through an interactive web-map as well as a public data repository.
风暴潮是最致命的沿海灾害之一，了解过去它们如何受到气候变化和变异性的影响对于为未来做好准备至关重要。然而，验潮仪记录通常太短，无法评估趋势和进行稳健的统计分析。在这里，我们使用数据驱动的建模框架来模拟全球 882 个验潮站的每日最大风暴潮值。我们使用五种不同的大气再分析产品进行风暴潮重建，最长的回溯到 1836 年。我们生成的数据可用于风暴潮气候的长期趋势分析，以及识别过去风暴潮强度和/或频率发生变化的区域。它还为稳健的极值分析提供了更好的基础，特别是对于观测记录较短的验潮站。这些数据通过交互式网络地图和公共数据存储库供公众使用。
