Impacts of Different GRAPES-MESO model Spatial Resolutions on Summer Rainfall Forecast in China

The Global/Regional Assimilation and Prediction System (GRAPES) mesoscale model(GRAPES-MESO) V4.0 with a new spatial resolution has been put into formal operation in the Numerical Weather Prediction Centre (NWPC) of China Meteorological Administration (CMA). This paper examines the computational accuracy of GRAPES-MESO with different spatial resolutions. The results show that the refined spatial resolution can be applied for operational forecast. Several sensitivity experiments are then performed to determine the impacts of different spatial resolutions on the forecast skill of summer rainfall in July 2012 in China. The simulation results indicate that GRAPES-MESO V4.0 with a refined spatial resolution can better improve the precipitation maxima forecast compared to precipitation location forecast. The equitable threat score (ETS) of 24 hours accumulated precipitation from the batch experiments of the whole July 2012 shows that heavy rainfall forecast is significantly improved. The verification of geopotential height at the middle and lower levels of the troposphere illustrates that the model with a refined spatial resolution reduces the prediction error of the geopotential height and improves the predictions of synoptic background circulation at the middle levels and systems at lower levels that can trigger precipitation. Finally, the model can increase the accuracy rate of prediction of convective systems at lower levels and improve the ETS of heavy rainfall forecast.