mlsanityData to 14 Oct 2026

Generative data assimilation highlights fronts as key regulators of ocean energy cascade

arXiv 2608.14955 ↗First posted 15 Aug 2026physics.ao-ph cs.AIcited by 0

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Abstract (arXiv)

Mesoscale eddies are fundamental to the ocean circulation, yet the extent to which submesoscale motions, a few kilometers across, influence mesoscale eddy energetics through a kinetic energy cascade remains uncertain. High-resolution simulations predict that submesoscale fronts are key regulators of the cascade, transferring energy both downscale towards dissipation and upscale to sustain and shape the seasonality of mesoscale eddies. Testing these predictions has remained difficult because existing observations and state estimates cannot resolve submesoscale currents over sufficiently broad domains. Here we map the ocean's submesoscale energy cascade by combining multi-source satellite observations with a generative deep learning framework, reconstructing gap-free, kilometer-scale surface currents with physically plausible dynamics learned from simulations. Applying this to the eddy-rich Agulhas Current system, we find that submesoscales energize the mesoscale through an upscale energy cascade above 10 km, contributing to the seasonality of mesoscale eddies. Below 10 km, convergence at submesoscale fronts drives a downscale cascade towards dissipation. Both upscale and downscale pathways concentrate within fronts, where cross-scale transfer is up to an order of magnitude more efficient. Despite their limited extent, fronts account for a substantial fraction of the domain-integrated cascade, establishing them as key regulators of the cascade and targets for next-generation eddy parameterizations.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 9 of its 74 references that are in the map. First posted on arXiv 15 Aug 2026.

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References · 9

  1. 2020Denoising Diffusion Probabilistic Modelscited by 21,076
  2. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 9,122
  3. 2022Elucidating the Design Space of Diffusion-Based Generative Modelscited by 3,045
  4. 2022Video Diffusion Modelscited by 2,305
  5. 2023Score-based Data Assimilationcited by 96
  6. 2024Generative Data Assimilation of Sparse Weather Station Observations at Kilometer Scalescited by 27
  7. 2022Inversion of sea surface currents from satellite-derived SST-SSH synergies with 4DVarNetscited by 4
  8. 2020Filtering Internal Tides From Wide-Swath Altimeter Data Using Convolutional Neural Networkscited by 2
  9. 2024Multi-scale decomposition of sea surface height snapshots using machine learningcited by 2

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