Abstract: To accurately interpolate the missing precipitation data from meteorological observation stations within a region to obtain a complete precipitation series is of significance in improving the spatial and temporal resolution in analyzing the effects of climate change. By using spatial correlation and stepwise regression techniques, this paper interpolated the missing precipitation data for an individual day or less than 7 days in a month from  the 853 meteorological stations in the  forest region of Eastern China in 1961-2010, as a consequent establishment of  the complete time series precipitation datasets of the observation stations in 1961-2010 established. Based on these, trend analysis approach was applied to analyze the variation characteristics of the annual precipitation, annual precipitation days, and extreme precipitation events in the  region in 1961-2010. During the study period, the annual precipitation in the region presented an insignificant increasing trend, with a tendency of 5.58 mm·(10 a)^-1, but the decadal variation was obvious. The annual precipitation days reduced significantly, while the annual extreme precipitation days and extreme precipitation volumes increased significantly, with a tendency of 0.12 d·(10 a)^-1 and 10.22 mm·(10 a)^-1, respectively. Since the 1990s, the extreme precipitation events became frequently and intensively, and the proportion of the volumes of extreme precipitation to total precipitation increased significantly. Both the extreme precipitation days and the volumes of extreme precipitation had an abrupt change in 1993.