Represented spatial structure of error uncertainty by error covariance matrix and represented temporal structure by time lag correlation coefficient, an ensemble QPE is generated in order to improve the effect of estimation of the Quantitative Precipitation Estimation(QPE) in Jiangsu Meteorological Observatory. The ensemble in this paper is generated by using the data from Jiangsu Meteorological Observatory from May to August 2019 and May to August 2020 whose deterministic and probabilistic were then verified by corresponding observed precipitation. It is found that the number of members has little effect on the ensemble QPE and can control member numbers between 16 and 50. The deterministic verification results show that ensemble QPE aggravates the underestimation of precipitation in some areas, but reduces the absolute error and root mean square error of precipitation in general. Ensemble mean can improve the accuracy and reduce the rate of false positives, but it will also increase the number of false positives. The ensemble has a good Brier score for precipitation of various magnitudes. The larger the precipitation magnitudes, the better the estimation effect. The dispersion of the ensemble is small, and after the members of the set are sorted, the frequency of observations falling at both ends is higher, which also reflects the small dispersion. In addition, the observed values are more frequent than the maximum values of ensemble members, which indicates that ensemble QPE tends to underestimate precipitation. With the increase of probability threshold, the hit rate (POD) and false alarm rate (POFD) of ensemble precipitation estimation gradually increase, but the degree of POD increase is much greater than that of POFD, which makes the ROC curve in the form of broken line. POD and POFD with different probability thresholds show that ensemble QPE has high estimation skills for all levels of precipitation, and light rain and moderate rain have the best resolution. It is more serious that the occurrence probability of light rain and heavy rain estimated by ensemble is less than the actual frequency, and the occurrence probability of moderate rain and heavy rain estimated by ensemble is very close to the actual frequency of precipitation, which has high reliability, but on the whole, ensemble QPE still tends to underestimate the occurrence probability of precipitation.