Measurements of nearshore waves through coherent arrays of free-drifting wave buoys

Surface gravity wave breaking occurs along coastlines in complex spatial and temporal patterns that significantly impact erosion, scalar transport, and flooding. Numerical models are used to predict these processes, but many models lack sufficient evaluation with observations during storm events. To fill the need for more nearshore wave measurements during extreme conditions, we deployed coherent arrays of small-scale, free-drifting wave buoys named microSWIFTs. The result is a large dataset covering a range of conditions. The microSWIFT is a small wave buoy with a GPS module, and Inertial Measurement Unit (IMU) used to directly measure the buoy's global position, horizontal velocities, rotation rates, accelerations, and heading. We use an Attitude and Heading Reference System (AHRS), 9 degrees-of-freedom Kalman filter to rotate the measured accelerations from the reference frame of the buoy to the Earth reference frame. We then use the corrected accelerations to compute the vertical ve..., This dataset was collected as a part of a larger collaborative effort called DUNEX (During Nearshore Events Experiment), funded through the US Coasal Research Project. The dataset was collected using small wave buoys named microSWIFTs developed as a part of the project. The data was collected from October 3–October 30th of, 2021, at the US Army Corps of Engineers Field Research Facility in Duck, North Carolina, USA. The microSWIFTs were deployed in large arrays ranging from 2–50 simultaneously deployed buoys. Each deployment is referred to as a \"mission,\" and all data from each buoy is stored in a netCDF file associated with each mission. The buoys are equipped with a GPS receiver and an inertial measurement unit (IMU). They measure their position, accelerations, rotation rates, and heading as they drift through the surf zone. The accelerations are despiked and corrected from the buoy reference frame to the Earth reference frame using a 9-degree-of-freedom indirect Kalman filter. The co..., All the data is saved in netCDF file formats that include all associated metadata with the files. The data can be read into any major programming language and multiple graphic user interfaces can also interface with the data. Common programming languages that can use this data are Python and MATLAB. Examples of using the data with Python can be found at https://github.com/SASlabgroup/DUNEXMainExp.Â