This study aims to improve the low-level monitoring and fine-scale observation for severe convective weather frequently occurred in Jiangsu Province. The X-band weather radar network located at northern Jiangsu was utilized to implement the adaptive collaborative control technology,including identification technology for clear sky,precipitation,and storms,and corresponding scanning strategies with an adaptive switching mechanism. The Jiangsu Collaborative Adaptive Processing Center for X-band Weather Radar Network (JSCAPC_XNET) was established for this purpose. Results show that JSCAPC_XNET effectively fills local low-level detection gaps in the S-band weather radar network. By focusing on clear sky,precipitation,and storms,the system demostrates comprehensive capabilities for all-weather observation requirements. Within the collaborative network,various storm cells can be distinguished and labeled using a dynamic area method,hailstorms can be detected using a vertical structure concept model,and mesocyclones can be identified through a combined processing technology that integrates multiple radars from the X-band weather radar network. The adaptive switching mechanism ensures precise transitions among the three observation modes. The adaptive cooperative observation mode enhances the observation efficiency of each radar and enables fine-scale monitoring of key targets. Based on observations from the JSCAPC_XNET during the experimental period,various characteristics related to severe thunderstorm were identified,such as strong hail Z_DR column,tornadic cell's low-level Z_DR arc,tornado debris,as well as the characteristics of low reflectivity regions and the descending of reflectivity core in the tornado eye region.These signatures potentially provide valuable insights for improving the monitoring and early warning capabilities for small-scale extreme weather in the future.