DOI: 10.5061/dryad.g4f4qrfvb
title: Data for: Saturation of ocean surface wave slopes observed during hurricanes

description: Observational wave data and modeled wind data to accompany the article J.
 Davis et al. (2023) "Saturation of ocean surface wave slopes observed
 during hurricanes" in Geophysical Research Letters. The observations
 include targeted aerial deployments into Hurricane Ian (2022) and
 opportunistic measurements from the free-drifting Sofar Ocean Spotter
 global network in Hurricane Fiona (2022). Surface wind speeds are modeled
 using the U.S. Naval Research Laboratory’s Coupled Ocean-Atmosphere
 Mesoscale Prediction System for Tropical Cyclones (COAMPS-TC). The
 datasets are table-like and include the following: 1) hourly records of
 surface wave statistics in the form of scalar energy spectra, directional
 moments, derived products (including mean square slope), and modeled wind
 speeds; 2) data to reproduce the binned mean square slopes and model wind
 speeds presented in the article; 3) data to reproduce the mean energy
 density versus wind speed plot; and 4) data to reproduce the mean energy
 density versus wave age plot.
description: This dataset contains wave measurements collected by
 free-drifting Spotter buoys (Sofar Ocean) which use GPS-derived motions to
 report hourly records of surface wave statistics in the form of scalar
 energy spectra and directional moments. The observational data are
 combined with modeled surface wind speeds from the U.S. Naval Research
 Laboratory’s Coupled Ocean-Atmosphere Mesoscale Prediction System for
 Tropical Cyclones (COAMPS-TC) which are interpolated onto the Spotter wave
 observations in time and space.
description: The datasets are stored as text-based JSON and CSV files which
 can be read without the use of special software. The JSON files are
 created using the Python Pandas package `DataFrame.to_json` method with
 orient='records'. Example code is provided in MATLAB and
 Python.
description: # Data to accompany the article "Saturation of ocean surface wave
 slopes observed during hurricanes" --- Contains wave observations by
 free-drifting Spotter buoys from targeted aerial deployments into
 Hurricane Ian (2022) and opportunistic measurements from the free-drifting
 Sofar Ocean Spotter global network in Hurricane Fiona (2022). The
 observations are co-located with modeled surface wind speeds from the U.S.
 Naval Research Laboratorys Coupled Ocean-Atmosphere Mesoscale Prediction
 System for Tropical Cyclones (COAMPS-TC). The data are used in the article
 to show the saturation of mean square slope at extreme wind speeds and the
 coincident transition from an equilibrium-dominated spectral tail to a
 saturation-dominated tail. This archive contains two main, table-like
 datasets of wind-wave data (from Ian and Fiona) and three derived datasets
 necessary to reproduce the results and figures in the article. ##
 Description of the data and file structure The dataset is organized into
 five files: * `ian_spotter_coamps_data.json` - the main dataset from
 Hurricane Ian (2022) containing hourly records of surface wave statistics
 in the form of scalar energy spectra, directional moments, and derived
 products (including mean square slope) with co-located modeled surface
 wind speeds from COAMPS-TC. The data can be sorted by Spotter id (using
 the `spotter_id` variable) to observe individual drift tracks as a
 function of time, or can be taken in aggregate to study bulk trends as a
 function of wind speed, etc. (as is done in the article with mean square
 slope versus wind speed). * `fiona_spotter_coamps_data.json` - same as
 above, but for Hurricane Fiona (2022). * `binned_mss_data.csv` - data to
 reproduce the binned mean square slopes and model wind speeds presented in
 the article. * `wave_spectra_binned_by_wind_speed_data.json` - mean energy
 density data, binned by wind speed, to reproduce the mean energy density
 versus wind speed plot in the article. This data is derived from
 `ian_spotter_coamps_data.json` and `fiona_spotter_coamps_data.json` by
 binning and averaging the `energy_density` in 10 m/s bins using
 `COAMPS_10m_wind_speed`. * `wave_spectra_binned_by_wave_age_data.json` -
 mean energy density data, binned by mean period wave age, to reproduce the
 mean energy density versus wave age plot in the article. This data is
 derived from `ian_spotter_coamps_data.json` and
 `fiona_spotter_coamps_data.json` by binning and averaging the
 `energy_density` using `mean_wave_age`. Variable descriptions are provided
 in `dataset_description.pdf`. ## Sharing/Access information Data was
 derived from the following sources: * Spotter buoys are a product of Sofar
 Ocean (San Francisco, CA). Data are accessible at
 . * COAMPS-TC is developed and
 operated by the U.S. Naval Research Laboratory, Monterey Marine
 Meteorology Division. More information can be found at
 . This is the only
 publicly accessible location of this dataset. ## Code/Software The
 datasets are stored as text-based JSON and CSV files which can be read
 without the use of special software. The JSON files are created using the
 Python Pandas package `DataFrame.to_json` method with
 `orient='records'`. Example usage in Python and MATLAB are
 provided in `example.py` and `example.m`.