2025/12/02 by J. W. Skinner, Jack William Skinner, Jörn Callies +6 · 1 voice
Earth and Planetary Sciences · Physics and Astronomy · #Atmospheric and Oceanic Physics (physics.ao-ph) #FOS: Physical sciences #Meteorological Phenomena and Simulations #Ocean Waves and Remote Sensing #Oceanographic and Atmospheric Processes #physics.ao-ph
paper · pdf · doi:10.48550/arxiv.2512.03258
openalex publication_date 2025/12/02 · arxiv published 2025/12/02 · arxiv updated 2025/12/02 · openalex created_date 2025/12/05 · openalex updated_date 2026/07/28
The Surface Water and Ocean Topography (SWOT) mission provides two-dimensional sea surface height (SSH) maps at unprecedented resolution, but its signal is a combination of balanced meso- and submesoscale turbulence, unbalanced internal waves, and small-scale noise. Interpreting the meso- and submesoscale flow features captured by SWOT requires a careful isolation of the balanced signal. We present a statistical method to do so in regions where internal-wave signals are negligible, such as western boundary current regions and the Southern Ocean. Our method assumes Gaussian statistics for both the balanced flow and the noise, which we infer by fitting parametric models to the observed SSH wavenumber spectrum. Using these inferred parameters, we perform a Bayesian inversion to reconstruct swath-aligned SSH maps that fill the nadir gap. We evaluate the method using synthetic data from a high-resolution simulation with realistic SWOT-like noise added. Comparisons with the underlying model data show that our reconstruction successfully removes small-scale noise while preserving meso- and submesoscale eddies, fronts, and filaments down to a feature scale of 10km. The comparison also demonstrates that the posterior uncertainty is a reliable estimate of the error.