With the mesoscale operational numerical model GRAPES-MESO V3.0 from National Meteorological Center of China Meteorological Administration and 12 h T213 forecasts as background field, two numerical experiments with (Exp. 3DVAR) and without (Exp. CNTL) assimilating radio-soundings using the nonhydrostatics GRAPES-3DVAR are conducted from June to August 2009 to investigate the performance of GRAPES-3DVAR. The statistical verifications of precipitation, geopotential height, temperature, wind and relative humidity and typical weather events are conducted. The results indicate that: (1) The root mean square errors of initial temperature, geopotential height, relative humidity and wind field on 850, 700 and 500 hPa in Exp. 3DVAR are morer than that of in Exp. CNTL, except for 700 hPa relative humidity. Exp. 3DVAR has a significant negative contribution to initial temperature, geopotential height and relative humidity on 500 hPa. And Exp. 3DVAR has an obvious negative contribution to 500 hPa wind forecast with forecasting time going on. (2) As to the area mean of whole model domain, TS scores at different orders in 0～24 h and 12～36 h rainfall forecasts in Exp. 3DVAR are mostly less than that of in Exp. CNTL. (3) The coverage of light rain and moderate rain forecasted by Exp. CNTL are close to the observation, while that of heavy rain, torrential rain, heavy torrential rain are less than that of the observation. Moreover, with the increase of rainfall, the changing small degree of forecast range is more than the observation. The forecast area of rainfall at different orders in Exp. 3DVAR are worse than that of in Exp. CNTL, especially for those above moderate rain. (4) The distribution, evolution and intensity variations of rain region in Exp. CNTL are better than that of Exp. 3DVAR. (5) The daily evolution, peak and valley values of the simulated average rainfall rate in the mid-lower reaches of Yangtze River, South China, North China, Northeast China, east of Southwest China and East China, can be almost simulated in Exp. CNTL, but the average rain rate is weaker than the observation. The forecast of Exp. 3DVAR is similar to that of Exp. CNTL, but the rainfall is weaker than in Exp. CNTL. Accordingly, the difference between Exp. 3DVAR and the observation is increased. (6) Rainfall forecasts in Exp. CNTL and 3DVAR are both in a good consistency with the observation, with the former is a little better than the latter. For rainfall more (lower) than 1.5 mm·d-1, the two experiments tend to forecast more (less) rainfall than the observation, respectively. The forecasts of two experiments are nearly in a same level for rainfall lower than 1.5 mm·d-1. However, Exp. CNTL gives a better forecast than Exp. 3DVAR for rainfall above 1\^5 mm·d-1. (7) In the period of June to August 2009, the daily rain band location and rainfall intensity in Exp. CNTL are well forecasted and nearly close to the observation. This experiment gives a good simulation for the rainfall produced by different weather systems, such as westerly trough, typhoon, low vortex, wind shear and local system. The results of Exp. 3DVAR are roughly similar to that of Exp. CNTL, but its simulated rainfall intensity is generally weaker than that in Exp. CNTL.
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