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 storm tide 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. 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 6-13 and Tables 1-2 in the manuscript) are located in "results_plotting_scripts.zip". Requires EnsemblePerturbation python toolbox.

本仓库包含与题为《热带气旋风暴潮与漫溢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：模型数据为针对3场美国登陆历史飓风（2017年厄玛飓风、2018年佛罗伦斯飓风及2020年劳拉飓风）开展的集合48小时预报ADCIRC模型模拟所得的最大风暴潮位，存储于以"NameYYYY_Results.tar"命名的归档文件中，归档内包含"maxele.63.nc"文件。该归档文件中还包含自动化热带气旋预报（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）。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"压缩包内。包含考虑与不考虑漫溢场景的联合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，该代码依赖EnsemblePerturbation Python工具库。用于分析并绘制KL-PC结果（对应论文中的图6至图13与表1至表2）的Python脚本存储于"results_plotting_scripts.zip"压缩包中，同样依赖EnsemblePerturbation Python工具库。