Using the WRF (Weather Research and Forecasting) model and it's 3Dvar (3-Dimentional Variational) data assimilation (DA) system, a local rainstorm event in middle Shandong on 8 May 2011 is studied adopting 3-h assimilation cycle of 36 km, 12 km, and 4 km nested grid and comparative experiments of different microphysics and cumulus convective parameterization schemes. The results are as follows. Rapid update cycle of surface observation data is a key factor for the model forecast of precipitation area. Different microphysics and cumulus convective parameterization schemes mainly affect the precipitation intensity forecast. Comparative experiments of different microphysics and cumulus convective parameterization schemes show that LIN scheme and WSM6 (WRF Single-Moment 6-class) microphysics schemes are both good for precipitation forecast and the LIN scheme performs better. The precipitation forecast of 4 km nested grid both performs better with K-F (Kain-Fritsch) cumulus convective parameterization schemes or without cumulus convective parameterization schemes. The 4 km grid forecast with the previous K-F cumulus convective parameterization schemes indicates that the weak surface wind field leads to weak lifting motion and the precipitation of model forecast is weaker.