X-band radar for high-resolution flood risk assessment in Honolulu

A Strategic X-Band Weather Radar for High-Resolution Flood Risk Assessment and Early Warning

Deploy a state-of-the-art X-band weather radar over the densely populated Honolulu metropolitan area, in collaboration with the NWS Weather Forecast Office in Honolulu and the University of Hawaiʻi at Mānoa (UHM), to provide accurate, real-time precipitation measurement at scales relevant to flood inundation assessment and early warning.

Flood risk in urban and coastal regions such as Honolulu is increasingly driven by short-duration, high-intensity rainfall events. These events generate highly localized runoff responses that cannot be adequately captured using coarse-resolution precipitation data. High-resolution precipitation mapping is essential for accurately representing storm structures, rainfall intensities, and spatial gradients that directly influence flood magnitude, timing, and extent. Without this level of detail, flood inundation models are subject to substantial uncertainties, limiting their effectiveness in supporting emergency management, infrastructure operations, and public safety. X-band radar technology offers a promising solution to these limitations by providing precipitation observations at spatial and temporal resolutions that align with the requirements of urban hydrologic and hydraulic modeling.

The existing WSR-88D regional weather radar network, with coverage extending from neighboring islands, provides valuable large-scale precipitation monitoring for Oʻahu. However, its spatial and temporal resolution limits its ability to adequately capture localized, short-duration, high-intensity rainfall events that drive flash flooding in urban watersheds. The proposed UHM–NWS X-band radar will fill this critical gap.

Key capabilities of the proposed radar include rapid scanning strategies, high sensitivity to precipitation microphysics, and improved detection of localized convective cells in complex urban environments. The system will be particularly well suited for monitoring heavy rainfall, storm evolution, and precipitation variability at neighborhood scales. These capabilities will support a range of flood-related applications, including real-time rainfall estimation, short-term precipitation nowcasting, and post-event analysis for hydrologic and hydraulic model validation and improvement.