Constructing reliable precipitation datasets with high spatial and temporal resolution to reveal the temporal and spatial variation characteristics of precipitation in the context of global warming is crucial for water resources management and soil erosion prevention and governance. In this paper, a Combinedly Interpolated Precipitation (CIP) method was proposed. Using the daily precipitation data observed at more than 400 sites in Fujian Province from 1979 to 2018 as the data source, a 0.05°×0.05° high spatial resolution daily precipitation grid point dataset was produced in the study area. Based on this data set, eight extreme precipitation indices and three precipitation concentration indices were calculated, and the temporal and spatial variation characteristics of precipitation in Fujian Province were analyzed. The results showed that the CIP method proposed in this paper could effectively improve the accuracy of daily precipitation interpolation, and the data accuracy was far higher than that of the commonly used reanalysis and satellite remote sensing precipitation data products. The five extreme precipitation indicators of the maximum one-day precipitation, the maximum five-day precipitation, the heavy precipitation, the total precipitation and precipitation intensity in Fujian coastal areas and the lower reaches of the Minjiang River, had significant upward trend in a large area. The precipitation concentration period (PCP) in the whole region was bounded by the Jiufeng Mountains-the lower reaches of the Minjiang River-Daiyun Mountains strip, that was, PCP on the northwest side of the strip was before June 11, whereas the southeastern side was after June 11, which was basically consistent with the first rainy season in Fujian Province. The first rainy season in the northwest region had a backward trend, while the rainfall of the second rainy season in the southeast region had increasing trend.