Deriving gridded hourly rainfall on Oʻahu by combining gauge and radar rainfall

Abstract

High temporal and spatial resolution precipitation datasets are essential for hydrological and flood modeling to assist water resources management and emergency responses, particularly for small watersheds such as those in Hawaiʻi, USA. Unfortunately, fine temporal (sub-daily) and spatial (< 1-km) resolution of rainfall datasets are not always readily available for applications. Radar provides indirect measurements of rain rate over a large spatial extent with a reasonable temporal resolution, while rain gauges provide “ground truth”. There are potential advantages to combining the two, which have not been fully exlored in tropical islands. In this study, we applied kriging with external drift (KED) to integrate hourly gauge and radar rainfall into a 250 m by 250 m gridded dataset for the tropical island of Oʻahu. The results were validated with leave-one-out cross validation for 18 severe storm events, including five different storm types (e.g., tropical cyclone, cold front, upper-level trough, Kona low, and a mix of upper-level trough and Kona low) and different rainfall structures (e.g., stratiform and convective). KED merged rainfall estimates outperformed both the radar only and gauge only datasets by: (1) reducing the error from radar rainfall; and (2) improving the underestimation issues from gauge rainfall, particularly during convective rainfall. We confirmed the KED method can be used to merge radar with gauge data to generate reliable rainfall estimates, particularly for storm events, on mountainous tropical islands. In addition, KED rainfall estimates were consistently more accurate in depicting spatial distribution and maximum rainfall value within various storm types and rainfall structures.