Abstract: Based on WRF four-dimensional data assimilation and forecast (WRF-FDDA), a cloud-resolving weather modification model (CR-WMM) is developed for modeling and forecasting cloud microphysical and cloud-seeding processes in Northwest China. The microphysical parameterization (CAMS-MP) and the silver iodide (AgI) cloud-seeding schemes, developed by the Chinese Academy of Meteorological Sciences, are transplanted into CR-WMM. The model permits simultaneously nested-grid LES (Large-Eddy Simulation) simulation of transportation and dispersion of AgI particles released from aircrafts or ground burner stoves. Precipitation cases are simulated to evaluate the data assimilation, CAMS-MP and AgI nucleation scheme in CR-WMM and the result demonstrated the general reliability of these components. CR-WMM is been developed for continuously assimilating diverse observational datasets, including conventional and intensive ground and upper-air meteorological observations, satellite cloud observations, and special cloud-radar and aircraft in-situ observations during weather modification operations as well. The system produces integrated analysis of thermodynamic, dynamic and microphysical analysis fields of cloud and precipitation processes, which can be used to support cloud and weather modification theoretical studies and field cloud-seeding operations.Finally, several challenges with the CR-WMM developments are identified, which should be addressed in the next 5-10 years.