{
  "abstract": "Satellite precipitation products face a persistent trade-off: real-time estimates are timely but less accurate, whereas the most reliable products are often released months after observation. This delay keeps high-quality precipitation information outside the decision window for flood warning and disaster response. Here we report Huayu-Global, a cross-constellation deep-learning system that combines three geostationary sensor streams from five satellites through a common retrieval framework and generates coherent quasi-global precipitation fields every thirty minutes. Across more than a million independent station records from two periods outside the training years, Huayu-Global improves event detection and precipitation-amount estimation relative to the real-time products evaluated and reaches delayed-product-level skill in key metrics. Huayu-Global therefore turns operational geostationary observations into a timely, high-skill precipitation layer for flood forecasting, water management and disaster response. Its cross-constellation design also provides a scalable foundation for incorporating future geostationary missions into hydrological and weather-prediction systems.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2610.29213",
  "author_total": 9,
  "authors": [
    {
      "name": "Zijiang Song"
    },
    {
      "name": "Shuang Yang"
    },
    {
      "name": "Yuying Li"
    },
    {
      "name": "Zilong Zhu"
    },
    {
      "name": "Xigang Sun"
    },
    {
      "name": "Ting Liu"
    },
    {
      "name": "Wenye Xiao"
    },
    {
      "name": "Lina Yuan"
    },
    {
      "name": "Min Liu"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/aqwsgtv4jskdx.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2610.29213",
  "fulltext_url": null,
  "id": "aqwsgtv4jskdx",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2610.29213",
  "language": null,
  "licence": "LicenseRef-arXiv-nonexclusive-1.0",
  "licence_label": "arXiv licence",
  "licence_source": "article",
  "licence_url": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "cs.AI"
    ],
    [
      "arxiv",
      "physics.ao-ph"
    ],
    [
      "openalex",
      "1902|Precipitation Measurement and Analysis"
    ]
  ],
  "openalex": "W7223231435",
  "pdf_url": "https://arxiv.org/pdf/2610.29213",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-21",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/aqwsgtv4jskdx.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:34:19Z",
      "native_id": "2610.29213",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2610.29213"
    }
  ],
  "subjects": [
    {
      "field": "earth",
      "origin": "arxiv:physics.ao-ph",
      "subfield": "atmospheric"
    }
  ],
  "title": "Huayu-Global: Skillful real-time quasi-global precipitation retrieval",
  "title_text": "Huayu-Global: Skillful real-time quasi-global precipitation retrieval",
  "type": "preprint",
  "updated_at": "2026-10-30T12:34:19Z",
  "url": "https://research.draconitic.com/paper/aqwsgtv4jskdx",
  "venue": "arXiv",
  "versions": []
}