Data for: Saturation of ocean surface wave slopes observed during hurricanes

Observational wave data and modeled wind data to accompany the article \"Saturation of ocean surface wave slopes observed during hurricanes,\" which is currently in revision for publication in Geophysical Research Letters (a preprint is attached as a supplement). 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 versu..., 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., 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., # 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 fi...本数据集配套于目前处于出版修订阶段的论文《飓风期间观测到的海洋表面波斜率饱和现象》，该论文已提交至《地球物理研究快报（Geophysical Research Letters）》，其预印本作为补充附件提供。观测数据包含针对2022年飓风伊恩（Hurricane Ian）的定向空中浮标布设观测，以及2022年飓风菲奥娜（Hurricane Fiona）期间来自自由漂流的Sofar Ocean Spotter全球观测网络的机会性观测数据。表面风速采用美国海军研究实验室（U.S. Naval Research Laboratory）的热带气旋耦合海洋大气中尺度预报系统（Coupled Ocean-Atmosphere Mesoscale Prediction System for Tropical Cyclones，缩写COAMPS-TC）进行模拟。本数据集以表格形式组织，包含以下内容：1) 以标量能谱、方向矩、衍生参数（含均方斜率）以及模拟风速形式记录的每小时表面波统计数据；2) 用于复现论文中呈现的分箱均方斜率与模拟风速的数据集；3) 用于复现平均能量密度随……（原文此处截断）的数据集。 本数据集包含由Sofar Ocean Spotter浮标采集的波浪观测数据，该浮标通过GPS衍生运动数据以每小时为间隔，上报标量能谱与方向矩形式的表面波统计信息。观测数据与美国海军研究实验室COAMPS-TC模拟的表面风速数据进行时空配准插值。 本数据集以文本格式的JSON与CSV文件存储，无需专用软件即可读取。其中JSON文件通过Python Pandas库的`DataFrame.to_json`方法生成，参数设置为`orient='records'`。同时提供MATLAB与Python示例代码。# 配套论文《飓风期间观测到的海洋表面波斜率饱和现象》 --- 本数据集包含来自2022年飓风伊恩的定向空中浮标布设波浪观测数据，以及2022年飓风菲奥娜期间来自Sofar Ocean Spotter全球自由漂流观测网络的机会性观测数据。观测数据与美国海军研究实验室COAMPS-TC模拟的表面风速数据进行时空匹配。本数据集用于支撑论文中关于极端风速下均方斜率饱和现象，以及从平衡主导的谱尾向饱和主导谱尾的同步转变的研究结论。本归档包含两组主要的风浪表格数据集（分别来自飓风伊恩与菲奥娜），以及三组用于复现论文结果与图表的衍生数据集。 ## 数据与文件结构说明 本数据集按……进行组织（原文此处截断）。