{
  "abstract": "Ocean wave forecasting is essential for maritime safety, offshore operations, and coastal resilience, yet remains challenging due to systematic biases in physics-based models. Physical models, while widely used, rely on approximations and parameterizations that limit their accuracy under complex ocean-atmosphere conditions. To enhance ocean wave forecasting, we propose BridgeCast, within a physics-AI hybrid framework for bias correction. BridgeCast is a probabilistic model based on conditional flow matching (CFM) that learns to transform physical model forecasts into reanalysis-like fields. It treats physical forecasts as corrupted observations and employs a continuous-time generative process to bridge their distribution toward that of reanalysis data. BridgeCast is parameterized by a Transformer-based architecture that enables spatiotemporal modeling, incorporation of exogenous atmospheric variables, and flexible inference via both ordinary and stochastic differential equation formulations. Extensive experiments on real-world datasets demonstrate that BridgeCast consistently outperforms state-of-the-art baselines across regions and forecast lead times.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2610.03759",
  "author_total": 5,
  "authors": [
    {
      "name": "Siyu Gan"
    },
    {
      "name": "Dongsheng Luo"
    },
    {
      "name": "Kunxiaojia Yuan"
    },
    {
      "name": "Dongjin Song"
    },
    {
      "name": "Jingchao Ni"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/djp1jggrsfwpw.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2610.03759",
  "fulltext_url": null,
  "id": "djp1jggrsfwpw",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2610.03759",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "http://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "cs.AI"
    ],
    [
      "arxiv",
      "cs.LG"
    ],
    [
      "arxiv",
      "physics.ao-ph"
    ],
    [
      "openalex",
      "1910|Ocean Waves and Remote Sensing"
    ]
  ],
  "openalex": "W7220647875",
  "pdf_url": "https://arxiv.org/pdf/2610.03759",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-20",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/djp1jggrsfwpw.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:34:04Z",
      "native_id": "2610.03759",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2610.03759"
    }
  ],
  "subjects": [
    {
      "field": "earth",
      "origin": "arxiv:physics.ao-ph",
      "subfield": "atmospheric"
    }
  ],
  "title": "BridgeCast: Bridging Ocean Wave Forecasts to Reanalysis via Flow Matching with Exogenous Variables",
  "title_text": "BridgeCast: Bridging Ocean Wave Forecasts to Reanalysis via Flow Matching with Exogenous Variables",
  "type": "preprint",
  "updated_at": "2026-10-30T12:34:04Z",
  "url": "https://research.draconitic.com/paper/djp1jggrsfwpw",
  "venue": "arXiv",
  "versions": []
}