A Generalized Framework for Multi-Parameter Optimization of Numerical Wind–Wave Model: Application to Typhoon Waves near Taiwan Island

Title: Data and code for: Multi-Parameter Optimization Framework for Numerical Wind–Wave Model

Description:

This dataset contains all code, configuration files, observational data, and atmospheric forcing data associated with the manuscript "Multi-Parameter Optimization Framework for Numerical Wind–Wave Model."

Contents:

1. WAVEWATCH III source code (WW3-6.07.1.zip): Complete WAVEWATCH III v6.07.1 source code from NOAA/NCEP (21.5 MB), ready for compilation and deployment under typhoon conditions.

2. WAVEWATCH III configuration files (ww3_config/): Input namelists (*.inp), bathymetry grid, and shell scripts for running WAVEWATCH III v6.07 under typhoon conditions.

3. Optimization framework code (optimization/): Python implementation of a multi-objective calibration framework, including Latin Hypercube Sampling (LHS) for parameter space exploration, an adaptive regression surrogate model for emulating WAVEWATCH III simulations, and NSGA-III (Non-dominated Sorting Genetic Algorithm III) for Pareto-optimal parameter identification.

4. Buoy observation data (data/): In-situ significant wave height observations from buoys around Taiwan Island for four typhoon events — Dujuan (2015), Soudelor (2015), Fitow (2013), and Nianyu (2016). These include both offshore and nearshore buoy records.

5. ERA5 atmospheric forcing data (ERA2013.nc, ERA2015.nc, ERA2016.nc): ERA5 reanalysis data subsets (10-m wind fields) used as atmospheric forcing for WAVEWATCH III simulations, covering Typhoon Fitow (2013), Dujuan and Soudelor (2015), and Nianyu (2016).

6. Model output samples (ww3_config/output/): Sample WAVEWATCH III simulation outputs in NetCDF format, including gridded field outputs and point outputs at buoy locations.

7. Manuscript figures (figures/): All figures presented in the manuscript.

8. Documentation (README.md): Comprehensive guides to archive structure, usage instructions, Python dependencies, and step-by-step reproduction procedures.

All materials are consolidated in a single archive (82.2 MB) with complete documentation for full reproducibility.