Vol. 128, No. 2 * Pages 143–286 * April - June 2024

This study concerns the interpolation of daily and hourly precipitation data in regions where small but intense thunderstorms, such as supercells, have occurred, and which, due to their size, often evade conventional meteorological stations. Consequently, relying solely on these measurements for interpolation can introduce errors and yield incomplete representations. To mitigate these issues, this research incorporates radar background information. The study selects days marked by significant precipitation during summer season and employs the Meteorological Interpolation based on Surface Homogenized Data (MISH) method for interpolation, both with and without radar-derived background data. Furthermore, our research also investigates the adaptability of the MISH method in handling radar anomalies, which encompass errors, missing data, and spurious measurements resulting from unintended radar reflections. Additionally, it examines whether the precipitation measured by radar can be used for climatic purposes on its own (without traditional measurements). Statistical techniques are employed to assess the improvement in interpolation quality with the inclusion of radar data and to quantify the relationship between interpolations with and without supplementary radar information. The study underscores the critical role of combining measurement data and radar products in the interpolation framework. This approach has implications for societal and agricultural sectors and offers potential benefits for hazard forecasting accuracy.