{
  "abstract": "High-resolution oceanographic fields are critical for resolving mesoscale and sub-mesoscale coastal dynamics, yet their generation remains constrained by both computational cost and observational sparsity. We present OcDiffSR, a conditional denoising diffusion probabilistic model (DDPM) for oceanographic super-resolution that reconstructs high-resolution sea-surface fields from coarse-resolution reanalysis inputs. The model is trained on ten years (2011-2020) of paired low-resolution (GLORYS12V1, 1/12) and high-resolution (Mediterranean Sea Physics Reanalysis, Med MFC, 1/24) data, and evaluated on an independent test year (2009) over the Adriatic Sea. OcDiffSR employs a conditional U-Net augmented with multi-scale low-resolution encoders, cross-attention bottleneck layers, and sinusoidal seasonal embeddings via Feature-wise Linear Modulation (FiLM), enabling joint super-resolution of sea-surface temperature (SST), salinity (SSS), and horizontal velocity components with visually coherent circulation patterns. Benchmarked against bilinear interpolation and the state-of-the-art residual diffusion model CorrDiff, OcDiffSR achieves substantially lower reconstruction errors for scalar fields (RMSESST=0.477 C, RMSESSS=0.346 psu), near-unity Pearson correlation (PCC >= 0.999), and high structural similarity (SSIM >= 0.964). For dynamical vector fields, OcDiffSR outperforms both baselines in absolute error and spatial coherence, though moderate correlation (PCC = 0.64) reflects the intrinsic stochasticity of oceanic velocity fields. Daily and monthly evaluations confirm temporal robustness across all seasons. These results establish OcDiffSR as a reliable framework for high-fidelity oceanographic downscaling and reanalysis enhancement, producing fields that are visually consistent with known ocean dynamics.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2609.22574",
  "author_total": 6,
  "authors": [
    {
      "name": "Rajat Srivastava"
    },
    {
      "name": "Muhammad Sarmad"
    },
    {
      "name": "Emanuele Mele"
    },
    {
      "name": "Massimo Cafaro"
    },
    {
      "name": "Marco Pulimeno"
    },
    {
      "name": "Italo Epicoco"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/fcj0mx8b8mea0.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2609.22574",
  "fulltext_url": null,
  "id": "fcj0mx8b8mea0",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2609.22574",
  "language": null,
  "licence": "CC-BY-SA-4.0",
  "licence_label": "CC BY-SA 4.0",
  "licence_source": "article",
  "licence_url": "http://creativecommons.org/licenses/by-sa/4.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "physics.ao-ph"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://arxiv.org/pdf/2609.22574",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-18",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/fcj0mx8b8mea0.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:23:19Z",
      "native_id": "2609.22574",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2609.22574"
    }
  ],
  "subjects": [
    {
      "field": "earth",
      "origin": "arxiv:physics.ao-ph",
      "subfield": "atmospheric"
    }
  ],
  "title": "Diffusion-Based Super-Resolution of Adriatic Sea Oceanographic Fields",
  "title_text": "Diffusion-Based Super-Resolution of Adriatic Sea Oceanographic Fields",
  "type": "preprint",
  "updated_at": "2026-10-30T12:23:19Z",
  "url": "https://research.draconitic.com/paper/fcj0mx8b8mea0",
  "venue": "arXiv",
  "versions": []
}