Abstract: TRMM satellite precipitation radar (PR) can provide complete and accurate data with high vertical resolution, but it has a weakness of low sensitivity. Ground-based radar (GR) has a relatively good capability to detect weak precipitation and its horizontal resolution is high, but it has a weakness of low vertical resolution. We propose to combine PR and GR data by three-dimensional (3D) fusion of reflectivity factor to get optimal images. Integrating PR and GR reflectivity data mainly includes following steps: Preprocessing of PR and GR data such as clutter removing and attenuation correction, spatial-temporal matchup of PR and GR data, image fusion algorithms selection and application, and quality evaluation of the fused images. It is found from the reflectivity factor image fusion that the fused images have improved 3D spatial resolution and gain finer precipitation structure, have a higher sensitivity to detect precipitation and effectively increase the amount of information, and the data are more complete and reliable as a whole. Besides, rainfall from the radar data and the rain gauge are compared in this study, and the rainfall estimation from the fused reflectivity factor images are evaluated.