Efficient Probabilistic Prediction and Uncertainty Quantification of Tropical Cyclone-driven Storm Tides and Inundation: Model Data and Analysis Code

This repository contains model data and analysis codes related to the manuscript entitled "Efficient Probabilistic Prediction and Uncertainty Quantification of Tropical Cyclone-driven Storm Tides and Inundation", as follows: Model data are maximum water surface elevations of ensemble 48-hr forecast ADCIRC model simulations for three historical US landfalling hurricanes: 2017 Irma, 2018 Florence, and 2020 Laura. These are located in the "NameYYYY_Results.tar" archive files as "maxele.63.nc" files. Also included in the tar files are the hurricane forecast track files in Automated Tropical Cyclone Forecasting (ATCF) system format (*.22) and the error variable parameters (*.json) for each forecast. Model data of best-track runs for the 2017 Irma, 2018 Florence, and 2020 Laura hurricanes, and astronomical tide-only runs for the corresponding time periods are located in the "NameYYYY_besttrack+tides.tar" archive files. Both the maximum water surface elevations "maxele.63.nc" and the time series of water surface elevations "fort.63.nc" are included. ADCIRC input mesh (*.14) and mesh property files (*.13) are included in "ADCIRC_mesh_files.zip". Joint Karhunen-Loeve Polynomial Chaos (KL-PC) analysis python scripts with and without considering inundation are located in "klpc_analysis_scripts.zip". Requires EnsemblePerturbation python toolbox. Python scripts for analyzing and plotting the KL-PC results (Figures 6-14 and Table 1 in the manuscript) are located in "results_plotting_scripts.zip". Requires EnsemblePerturbation python toolbox.

本代码仓库包含与题为《热带气旋风暴潮与淹没的高效概率预测及不确定性量化》的学术论文相关的模型数据与分析代码，具体如下：针对3场美国登陆历史飓风（2017年艾玛飓风、2018年佛罗伦斯飓风与2020年劳拉飓风）的集合预报48小时ADCIRC模型模拟最大水面高程数据，存储于以"NameYYYY_Results.tar"命名的归档文件中，对应数据文件为"maxele.63.nc"；该归档文件中还包含自动热带气旋预报（Automated Tropical Cyclone Forecasting, ATCF）系统格式的飓风预报路径文件（*.22），以及每场预报的误差变量参数文件（*.json）。2017年艾玛、2018年佛罗伦斯及2020年劳拉飓风的最佳路径模拟数据，以及对应时段的纯天文潮汐模拟数据，存储于"NameYYYY_besttrack+tides.tar"归档文件中，其中包含最大水面高程文件"maxele.63.nc"与水面高程时间序列文件"fort.63.nc"。ADCIRC模型输入网格文件（*.14）与网格属性文件（*.13）包含于"ADCIRC_mesh_files.zip"压缩包中。包含考虑与未考虑淹没情景的联合Karhunen-Loeve多项式混沌（Joint Karhunen-Loeve Polynomial Chaos, KL-PC）分析Python脚本，存储于"klpc_analysis_scripts.zip"压缩包中，该脚本依赖EnsemblePerturbation Python工具箱。用于分析与绘制KL-PC分析结果（对应论文中图6-14与表1）的Python脚本存储于"results_plotting_scripts.zip"压缩包中，同样依赖EnsemblePerturbation Python工具箱。