Abstract: The paper outlines research achievements of Chinese Academy of Meteorological Sciences (CAMS) in the development of new multi-band weather radar detection technologies, field experiments, radar data quality control, generation of secondary products, and studies of cloud-precipitation processes and structures. In response to scientific frontiers and national requirements, CAMS has successively developed a C-band transportable dual-polarization radar, an X-band phased-array weather radar, a multi-band cloud radar observation system, and a C-band continuous-wave vertically pointing radar. Cloud-precipitation observation bases and severe convective weather observation bases have been established at Longmen, Shenzhen, and Foshan in Guangdong Province, as well as cloud-precipitation observation bases at Naqu and Mêdog on the Tibetan Plateau. Long-term field experiments are carried out focusing on rainstorms, typhoons, and the microphysical structures of clouds and precipitation at these sites. Utilizing these field experiment data together with observations from the national weather radar network, studies have been conducted on data quality control methods for W/Ka/Ku multi-band cloud radars, C-band vertically pointing continuous-wave radar, wind profiler radars, dual-polarization weather radars, and phased-array dual-polarization weather radars, aiming to remove non-meteorological echoes, reduce attenuation effects, and mitigate systematic biases in radar measurements. Mosaic and integration methods for S-, C-, and X-band weather radars have been developed to extend the spatial coverage of radar data, reduce biases in X-band radar data, and produce high-quality gridded radar data with high spatiotemporal resolution. Employing dual-band Doppler power spectrum analysis technique, methods have been investigated for retrieving vertical air velocity, raindrop size distributions, and drop size distributions of solid precipitation particles of different shapes, as well as vertical profiles of water content and rainfall intensity from multi-band cloud radars. Quantitative precipitation estimation, hydrometeor classification, tornado and mesocyclone identification, and networking approaches for multi-band weather radars have also been studied. Furthermore, nowcasting research based on artificial intelligence has been conducted, thereby enhancing the capability of radar systems to detect cloud and precipitation microphysical and dynamical parameters. Using field experiment data, the fine microphysical structure and evolution of clouds and precipitation in regions such as South China and the Tibetan Plateau have been investigated, providing more detailed data and products for cloud physics and severe weather monitoring and early warning. Many of these research results have been operationally applied to severe weather monitoring and warning services in China. Enhancing the detection capabilities, optimizing the accuracy of observation modes, and expanding the application of phased array weather radar technology, as well as advancing detection techniques using shorter wavelengths and their application in cloud process observation, will remain key research directions for CAMS in the future.