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Published October 21, 2022 | Version v2

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

  • 1. Argonne National Laboratory
  • 2. NOAA Office of Coast Survey
  • 3. Sandia National Laboratories

Description

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:

  1. 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. 
  2. ADCIRC input mesh (*.14) and mesh property files (*.13) are included in "ADCIRC_mesh_files.zip".
  3. 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. 
  4. 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. 

Files

ADCIRC_mesh_files.zip

Files (21.1 GB)

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Additional details

Related works

Is cited by
Preprint: 10.31223/X5VW6D (DOI)