Imaging thermocline microstructure in 2D with swaths traced by wave-pumped χpods: dataset and code

<p><a href="https://doi.org/10.1029/2024JC022134">Associated paper</a> published in <em>J. Geophys. Res. Oceans</em></p> <h2>Dataset summary</h2> <p>Location: 0&deg;N, 140&deg;W<br>Depth: 120 m<br>Period: 16-Sep-2014 to 19-Oct-2015</p> <p>This data archive contains two types of data files:<br>data_yymmdd.mat<br>grid_yymmdd.mat<br>Each file contains 24 hours of data. There are 394 of each type.</p> <p>Arrays in data_yymmdd.mat are single precision (except the 'time' array) to keep file sizes small.</p> <h2>Contents of the data files</h2> <p>Each Matlab file contains a single struct. These structs include readmes, which are reproduced in the full PDF readme (chipod_swaths_readme.pdf).</p> <p>Files are grouped into months and zipped (yymm.zip) to ease downloading.</p> <h2>Reading the data file with Python</h2> <p>Example code to read the files into Python as dictionaries is given in the full PDF readme (chipod_swaths_readme.pdf).</p> <h2>Matlab code to produce the processed data</h2> <p>The code to read in raw chipod data and process them is primarily contained in the file 'swaths_paper_data_preparation.m'. This file calls three other files ('raw_load_chipod.m', 'deglitch.m', and 'bin.m'). All of these files are provided for completeness, but we are only archiving the processed outputs (not the raw voltage signals). Please email if more information is needed.</p> <h2>Matlab code for the convolutional neural network</h2> <p>See 'chipod_swaths_convolutional_neural_network.m'.</p>