A dataset of storm surge reconstructions in the Western North Pacific using CNN

Abstract

The relatively short duration of available tide gauge records poses challenges for conducting comprehensive statistical analyses of storm surges in the Western North Pacific. To address this issue, we employ a convolutional neural network model to reconstruct the maximum daily storm surge at 160 tide gauges from 1900 to 2010 in the Western North Pacific. The reconstructed dataset serves multiple purposes. Firstly, it facilitates the identification of regions where notable changes in the storm surges have occurred in the past. Additionally, the dataset enables long-term analyses of the storm surge climate, offering insights into historical patterns and variations. Furthermore, it provides a solid foundation for conducting robust extreme value analyses. To ensure accessibility, the data are publicly available through a repository, allowing for easy access and utilization by the broader scientific community and the general public. Overall, our research contributes to the field of oceanography by providing a dataset that aids in understanding the historical storm surge dynamics in the Western North Pacific region.