Abstract: Landfalling and offshore typhoons often result in significant casualties and property damage due to associated hazards such as torrential rainfall, strong winds, and storm surges. Three key scientific challenges related to typhoons, namely rapid intensification, sudden track changes, and formation mechanisms, remain poorly understood because of the lack of high spatiotemporal resolution in situ observational data covering internal dynamics and environmental factors throughout the complete lifecycle of typhoons. To address the scarcity of marine typhoon observation data, the unmanned surface vehicle (USV) team from the Institute of Atmospheric Physics, Chinese Academy of Sciences, independently developed two long-endurance, semi-submersible USVs and conducted multiple sea trials. This paper presents the novel concept of networked unmanned vehicle observation systems for obtaining comprehensive meteorological and oceanic multi-element field information during typhoon evolution processes. For long-term typhoon observation, a network observation system employing an automatically deployed solar-powered USV and oil-electric powered USV with sounding equipment is being proposed across the typhoon-active South China Sea and western Pacific transit regions. The highly maneuverable solar-powered USVs can acquire multi-element observational data, including meteorology and hydrology data at the sea surface, while the oil-electric powered USV equipped with rocket-based sounding technology can obtain vertical profiles of the atmospheric boundary layer within typhoons. The UAV networked observation system can enable real-time in situ collection of observational data from the internal structure of marine tropical cyclones and their ambient environmental fields. The collected data will be validated through comparative analysis against concurrently acquired satellite observation products and reanalysis data to provide a comprehensive observational dataset for multiple South China Sea tropical cyclones. This first-hand dataset will support data assimilation and forecast verification for numerical prediction models, ultimately enhancing their capability in forecasting typhoon track typhoons, intensity, as well as heavy rainfall and gale-force winds.