Abstract:The weather radar has a strong ability of monitoring and early warning for small and medium-scale disastrous weather, which is of great help to study the cloud-rain structure of small and medium-scale convective systems and understand the thermodynamics and dynamics processes inside the precipitation. The single-site ground-based radars are subject to such effects as the attenuation of electromagnetic waves and the interference of ground objects, and there are some limitations in detection. In order to extend the weather radar detection area, multiple weather radar networks are needed for joint detection. However, there is no uniform calibration among radars of the radar network, which affects the data consistency of radar network, the networking mosaic, and limits the application of radar data in numerical model assimilation. In this paper, the accurately calibrated Precipitation Radar (PR) data product on the Tropical Rainfall Measuring Mission (TRMM) satellite is used as a standard reference source to correct the reflectivity factor deviation of the Ground-based Radar (GR). In order to reduce the inconsistency between the observed values of PR and GR, the Available Best Comparable Dataset (ABCD) method is used to correct the reflectivity factor deviation of six GRs in Jiangsu Province (Nanjing, Changzhou, Lianyungang, Nantong, Xuzhou, Yancheng) from January 2008 to September 2014. Finally, the application scope, existing problems and future prospects of the method are discussed.