Observations of Surface Gravity Wave Spectra from Moving Platforms

Abstract

Abstract Surface waves play an important role in the ocean–atmosphere coupled climate system by mediating the exchange of momentum, heat, and gas between the atmosphere and the ocean. Pseudo-Lagrangian autonomous platforms (e.g., Boeing Liquid Robotics Wave Gliders) have been used to investigate the underlying physical dynamics involved in these processes to better parameterize the air–sea exchange occurring at the scale of the surface waves. This requires accurate measurements of directional surface waves down to short scales [O(1) m], as these shorter waves support most of the stress between the atmosphere and the ocean. A challenge to overcome for pseudo-Lagrangian autonomous vehicles is that the platform’s velocity causes the observed frequency of the waves to be Doppler shifted. This leads to a modulation of the wave spectrum, particularly at high frequencies, that depends on the platform’s speed, the wave frequency, and the relative angle between the direction of wave and platform propagation. In this work, we propose a method to account for Doppler effects that considers the full directionality of the wave field. The method is validated using a unique dataset collected from a fleet of two Wave Gliders off the coast of Southern California in September 2019 operating on the perimeter of a tight square (500-m edge length) track over a 3-day deployment. This technique can be used to estimate wave spectra derived from other slow-moving surface vehicles such as Saildrones that use platform motion to characterize the surface wave field. MATLAB routines to implement this method are publicly available. Significance Statement The purpose of this study is to introduce a general approach that corrects observations of ocean surface waves collected on board autonomous surface vehicles (ASVs) for the effects on the wave period due to the vehicle’s forward motion. This is important because improving climate models requires accurate measurements of short-wavelength waves, which can be readily obtained from ASVs. Our method provides the tools for ASVs to better understand air–sea physics and the larger role ocean surface waves play in Earth’s climate system.