The precipitation forecasts of three prediction ensemble systems (ECMWF, NCEP and CMA) from the TIGGECMA archiving center (TIGGE, THORPEX Interactive Grand Global Ensemble) were assessed against observations of 19 stations located in the DapolingWangjiaba subcatchment of Huaihe Basin. It covers a period of 37day beginning on July 1st, 2008. The Threat Scores（TS）, the Brier Score and a percentile method were employed to assess the performance of the three ensemble prediction systems (EPSs) and their grand ensemble . The skills of probabilistic prediction of the heavy rain events occurring during 22-23 July 2008 were also investigated. The verifications of TS and Brier Scores showed that grand ensemble usually gives the best scores in any of the three EPSs. The verification of Brier Scores showed some members of any three EPSs captured the extreme events even a lead of 10 days. However, the probability skills were usually decreased by a simple ensemble mean. Grand ensemble increased the skill of probabilistic precipitation prediction. Whereas the simulation tends to more underestimate in comparison to the observation as the lead days range from 1 to 10 days. That means the probability forecasts are more skillful with a grand ensemble in comparison to a single EPS. The skills of probabilistic prediction with the grand ensemble were improved not only in space distribution of precipitation, but also in the intensity of it.