To assess the performance of the improved Dynamical-Statistical-Analog Ensemble Forecast model for Landfalling Typhoon Precipitation (DSAEF_LTP model) during the impact of Super Typhoon Doksuri (2305) on the Fujian region, the forecast typhoon precipitation by the DSAEF_LTP model is evaluated by using conventional and spatial verification methods. The results are compared with the ECMWF (European Centre for Medium-Range Weather Forecasts) numerical prediction products (hereafter referred to as ECMWF) and the revised precipitation products of Fujian Meteorological Service based on OTS (optimal threat score) (hereafter referred to as FZECMOS). The main findings are summarized as follows. (1) The DSAEF_LTP model forecast of intense precipitation distribution in the coastal areas of Fujian and the intense precipitation center in the northeastern part of Fujian closely align with actual observations. The TS values of the DSAEF_LTP model show significant improvement compared to ECMWF and FZECMOS at the precipitation equal to or greater than 100/250 mm. However, the DSAEF_LTP model has shortcomings such as a significantly smaller forecast area for very heavy rainstorm. (2) At the precipitation equal to or greater than 100/250 mm, the spatial verification results of MODE (Method for Object-based Diagnostic Evaluation) reveal that the DSAEF_LTP model outperforms ECMWF and FZECMOS in overall similarity, particularly in forecasting intense precipitation in isolated small areas. (3) As the magnitude of precipitation increases, the overlap area between the DSAEF_LTP model forecast products and the observations also increases, indicating the model’s effectiveness in forecasting extreme precipitation. (4) The DSAEF_LTP model demonstrates its ability to flexibly adjust and screen historically similar TCs (tropical cyclones) according to the latest observations and forecast of tracks, allowing for the reasonable retention of similar TCs and their associated precipitation distributions, which enhances the effect of ensemble forecast.