This study assesses the performance of spectral nudging methodology in dynamical regional climate downscaling for summer climate over East Asia. The regional climate model NCAR-MM5v3 was used to dynamically downscale the 2.5-degree NCEP/NCAR reanalysis (NNRP) data onto 50-km regional grids. The main focus is the model's simulation of precipitation. The NCEP/CPC precipitation analysis data were used as the verification. Boreal summers (June, July, and August) in 1991, 1998, and 2003 and heavy floods that occurred in Eastern China were selected for the study. Compared to the control runs (CTLs) without spectral nudging (SN), experiments with SNs greatly reduced systematic errors in upper-level large-scale circulations and were in better agreement with the NNRP. At the same time, SNs outperformed CTLs in simulating model variables near the surface. In comparison with observational precipitation data, spectral nudging also improved the model's simulation of precipitation in spatial and temporal distributions. SN-simulated precipitation field patterns, including the spatial distribution of monthly mean precipitation band, the seasonal march of major precipitation bands, and the daily variability of regional-averaged time series, show much more consistency with observations than those of the CTL runs.