Abstract: Quantitative precipitation forecast (QPF) is one of the most important operations in weather forecast. A brief overview is made for current domestic and foreign operational situation and techniques of ensemble probability forecast, short-term forecasting and nowcasting, veri fi cation methods and error corrections. Preliminary conclusions have been made for some research progress, the improvement of QPF accuracy comes from the development of numerical models and the improvement of correction capability for the application of numerical model productions. Based on the numerical ensemble forecast, the probability QPF (PQPF), as a more scienti fi c weather forecast method, can provide us with uncertainty forecasting information. Moreover, the improvement of real-time synoptic veri fi cation and error correction method of numerical model products provide strong support for 'adding forecasters additional value'. Finally, based on this summary of progress, main problems and research fi elds of QPF research have been introduced. (1) Further strengthening the capability of moisture data assimilation and simulation, using a new model to describe the moisture exchange between land surface and boundary layer and cloud and precipitation physical Processes. (2) Precipitation observation and forecast’s random characteristics have not been considered sufficiently yet, the numerical forecast capability of different spatial and temporal scales and QPF correction methods should be made a close study of. (3) It should be considered how to deliver forecast uncertain information to users due to misunderstanding the meaning of PQPF. (4) The techniques of short-term and nowcasting QPF should be exchanged from radar extrapolation to mixed extrapolation combined with numerical model forecast for improving convective precipitation forecast capability. (5) Based on the shortcoming of traditional statistical methods, new veri fi cation methods for QPF should be introduced, but objective explaination and application of the new method takes time to gather experiences.