Abstract: To meet the urgent demands for disaster weather forecasting, early warning operations, and refined professional meteorological services in the Yangtze River Basin, a 1-km resolution hourly rapid cycling assimilation and forecast system, referred to as the IHR-RUC (Institute of Heavy Rain-Rapid Update Cycle) system, was developed based on the CMA-MESO (China Meteorological Administration MESO scale weather forecast system) version 6.0 model. The system implements assimilation applications for eight types of observations. Using operational trial results from the summer of 2025 (June to August), this study evaluates its assimilation diagnostics, verifies surface variable forecasts and multi-lead-time precipitation forecasts, and compares forecast performance with the CMS-MESO 3-km model. The results are as follows. (1) For warm starts, the assimilation background field comes from the 1-h forecast of the previous cycle, which reduces the background root-mean-square error (RMSE) by 25%~35% compared to cold starts. (2) The IHR-RUC effectively assimilates diverse observations and captures convection, but it tends to overextend heavy precipitation areas and underestimate peak intensity. The GNSS (Global Navigation Satellite System) water vapor assimilation can mitigate these biases. (3) Forecast verification indicates that IHR-RUC generally outperforms the CMA-MESO 3 km in surface variables, notably the 10-m wind speed. (4) For 3-hourly heavy precipitation forecasts (>20 mm) at multi-lead-time (3-12 h) by IHR-RUC, the precipitation intensity bias peaks at 3-6 h, while precipitation frequency is best predicted at 9-12 h. In short-term forecasts (12-36 h), IHR-RUC overpredicts the 24-h precipitation but attains higher TS than CMA-MESO 3 km. These results can provide references for model improvement and operational applications at different forecast lead times.