{
  "abstract": "High-resolution precipitation information is essential for hydrometeorological applications such as extreme weather monitoring, flood forecasting, and disaster risk management. Despite substantial advances in satellite, radar, and gauge observations, producing kilometre-resolution sub-daily precipitation analyses over continental domains remains challenging due to heterogeneous data availability, scale mismatches, and computational constraints. This study presents the design and trial implementation of BRAIN (blended rainfall), a continental-scale, kilometre-resolution hourly precipitation analysis for Australia. In this initial implementation, BRAIN integrates three key data sources from the Australian Bureau of Meteorology: geostationary satellite rainfall estimates (2 km, 10 min) from Himawari, radar rainfall estimates (1 km, 5 min) from the national radar network, and rainfall observations from sub-daily rain gauges. The trialled system incorporates quality control, spatiotemporal aggregation, bias correction, and a simplified statistical interpolation configuration designed to balance analysis performance and computational scalability at the continental scale. Source contributions are weighted according to their spatial and temporal error characteristics, allowing each data type to influence the analysis where it is most informative. The initial implementation produces hourly rainfall fields at 2 km resolution across the Australian continent. Evaluation over the 2022–2023 trial period indicates that the blended analysis improves overall upon satellite-only, radar-only, and satellite–gauge products. Comparisons with gauge-based interpolation and the current daily operational product further illustrate the spatial characteristics of the blended analysis, including finer-scale rainfall structures and intensity variations that are not represented by these products. These results demonstrate the feasibility of the proposed design for continental-scale, high-resolution multi-source precipitation analysis in the Australian context, with potential applications to long-term historical reconstruction and near-real-time rainfall analysis. The flexible and scalable system design also allows future upgrades, including finer spatial and temporal resolutions and the incorporation of additional data sources. Beyond Australia, this study provides a practical reference for developing large-scale multi-source precipitation analyses at kilometre and hourly resolutions.",
  "abstract_shown": true,
  "affiliations": [
    "The University of Melbourne (Melbourne, Australia)",
    "Hohai University (Nanjing, China)",
    "Bureau of Meteorology (Melbourne, Australia)"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 8,
  "authors": [
    {
      "name": "Yuhang Zhang",
      "orcid": "0000-0001-6996-0008"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Quan J. Wang",
      "orcid": "0000-0002-8787-2738"
    },
    {
      "affs": [
        2
      ],
      "name": "Andrew J. Frost"
    },
    {
      "name": "Jayaram Pudashine",
      "orcid": "0000-0003-3851-6849"
    },
    {
      "name": "Blair Trewin"
    },
    {
      "name": "Carlos Velasco-Forero",
      "orcid": "0000-0003-2352-1223"
    },
    {
      "name": "Chun-Hsu Su"
    },
    {
      "name": "Vincent Villani"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/ae2ppy8pha0jw.bib",
  "cited_by": 0,
  "doi": "10.5194/hess-30-6701-2026",
  "fulltext_url": null,
  "id": "ae2ppy8pha0jw",
  "issns": [
    "1607-7938"
  ],
  "landing_url": "https://doi.org/10.5194/hess-30-6701-2026",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "feed-journal",
      "earth/hydrology-soils"
    ]
  ],
  "openalex": null,
  "pdf_url": null,
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-30",
  "publisher": "Copernicus GmbH",
  "ris": "https://research.draconitic.com/paper/ae2ppy8pha0jw.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T18:20:22Z",
      "native_id": "10.5194/hess-30-6701-2026",
      "source": "feed-copernicus",
      "url": "https://doi.org/10.5194/hess-30-6701-2026"
    },
    {
      "first_seen": "2026-10-31T00:21:11Z",
      "native_id": "10.5194/hess-30-6701-2026",
      "source": "crossref",
      "url": "https://hess.copernicus.org/articles/30/6701/2026/"
    }
  ],
  "subjects": [
    {
      "field": "earth",
      "origin": "feed-journal:earth/hydrology-soils",
      "subfield": "hydrology-soils"
    }
  ],
  "title": "Design and trial implementation of a continental-scale, kilometre-resolution hourly precipitation analysis for Australia using satellite, radar and gauges",
  "title_text": "Design and trial implementation of a continental-scale, kilometre-resolution hourly precipitation analysis for Australia using satellite, radar and gauges",
  "type": "peer-reviewed",
  "updated_at": "2026-11-01T00:21:09Z",
  "url": "https://research.draconitic.com/paper/ae2ppy8pha0jw",
  "venue": "Hydrology and Earth System Sciences",
  "versions": [
    {
      "doi": "10.5194/egusphere-2026-666",
      "pid": null,
      "relation": "preprint",
      "title": null,
      "venue": null
    }
  ]
}