Source code and data for

Villas Bôas, A. B., Marechal, G., and Bohé. Observing Interactions Between Waves, Winds, and Currents from SWOT. Geophysical Research Letters, Accepted.

Abstract

The Surface Water and Ocean Topography (SWOT) satellite mission enables, for the first time, two-dimensional (2D) mapping of significant wave height ($H_s$) at kilometer-scale resolution. Using data from SWOT’s Ka-band Radar Interferometer (KaRIn), this study investigates interactions between surface waves, winds, and currents across diverse dynamic regimes, including western boundary currents, mesoscale turbulence, tropical cyclones, and wave group modulation. SWOT reveals unprecedented 2D spatial gradients in $H_s$, capturing fine-scale variability previously identified only in numerical models. These observations highlight the critical role of currents in shaping the wave field and show strong agreement with theoretical predictions. SWOT’s high-resolution wave data represent a transformative advance in understanding $H_s$ gradients, paving the way for refining operational models and addressing challenges in characterizing the influence of sea state gradients on coupled air-sea processes.

Authors

• Bia Villas Boas [email protected]
• Gwendal Marechal
• Alejandro Bohé

Data

All processed data and model output used in this manuscript are available in the data directory in this repository.

Funding

This project was funded by NASA through the SWOT program (award 80NSSC24K1640), the Ocean Vector Winds Science Team (80NSSC23K0979), and the Earth System Explorer program (award 80GSFC24CA067) supporting development of the ODYSEA Concept Study Report. Additional support was obtained from the ONR MURI program (grant N00014-24-1-2554).

How to use this repository

All figures in the manuscript can be reproduced using the Python scripts from this repository and the data. To do so, follow these steps

1. Make a local copy of this repository by either cloning or downloading it.

Your directory tree should look like this:

swot_wave_current/
├── data/
├── figures/
├── notebooks/
├── src/
└── pixi.toml

2. If you would like to reproduce the figures from the manuscript using this repository, we recommend that you install Pixi. You can then run:

$ pixi shell

from the project root. This will build the dependencies and activate the Python environment for this project. You can then launch Jupyter Lab as you would normally:

$ jupyter lab

If you follow the steps above, you should be able to reproduce all figures by running the notebooks from the notebooks directory without having to adjust any paths.

How to cite this code

DOI coming soon.