The Chinese Academy of Meteorological Sciences Lightning Nowcasting and Warning System (CAMS_LNWS) was designed to predict lightning within the upcoming 0-1 h and provide lightning activity potential and warning products. Multiple remote sensing data and numerical simulation of an electrification and discharge model were integrated in the system. Two core algorithms were implemented: (1) an area identification, tracking, and extrapolating algorithm and (2) a decision tree algorithm. The system was designed using a framework and modular structure, and integrated warning methods were applied in the warning program. Two new algorithms related to the early warning of the first lightning and thunderstorm dissipation were also introduced into the system during the upgrade process. Thunderstorms occurring in Beijing, Tianjin, and Hebei during 2016-2017 were used to evaluate the CAMS_LNWS by the low-frequency cloud to ground lightning detection data, and the results showed that the system has good forecasting and warning ability for local lightning activities. The TS score in 0-1 h ranged from 0.11 to 0.32, with a mean of 0.20. Operational experiments and promotional work for the CAMS_LNWS are now in progress.