Design and trial implementation of a continental-scale, kilometre-resolution hourly precipitation analysis for Australia using satellite, radar and gauges

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 from Himawari (2 km, 10 min), radar rainfall estimates (1 km, 5 min), and sub-daily rain gauge observations. The trialled system incorporates quality control, spatiotemporal aggregation, bias correction, and a simplified statistical interpolation configuration designed to balance performance with scalability at 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 trial implementation produces hourly rainfall fields at 2-km resolution across the Australian continent. Evaluation for the trial period 2022–2023 indicates that the blended analysis improves upon satellite-only, radar-only, and satellite–gauge products, outperforms the gauge-based interpolation approach currently used in flood operations, and provides more spatially coherent and detailed rainfall structures than the current daily operational product. These results demonstrate the feasibility and utility of the proposed design and trial implementation in the Australian context, with potential extension to long-term historical reconstruction and near–real-time applications. The system design is flexible and scalable, enabling future upgrades such as finer spatial and temporal resolutions and the incorporation of additional data sources. Beyond the Australian context, this study provides an additional reference for large-scale multi-source precipitation analysis at kilometre and hourly resolutions.