Abstract: Based on the dynamic framework of the Lorenz 96 model,the ensemble prediction system(FPS) containing stochastic forcing has been developed.In this system,the model climate state and ensemble mean forecasts are chosen to study the scientific problems of noise-induced drift of FPS effects.The results show that the proper stochastic forcing being introduced into numerical model integration process new computing paradigm by means of the is closer to the true values of the climatic mean and standard deviation than the non-stochastic models.In another word,numerical model integration process with stochastic forcing has positive effect on model climate state, and the effect is found to be positive mainly for the longer lead times.Meanwhile,with respect to ensemble forecast effect yielded by white noise stochastic forcing, most of the results are better than those provided by no-stochastic forcing and improvements pertaining to white noise stochastic forcing vary non-monotonically with the increasing size of white noise.Moreover, the effects made by the identical white noise stochastic forcing also vary from nonlinear system to nonlinear system.Also, With respect to FPS effect yielded by red noise stochastic forcing, most of the results are better than those provided by no-stochastic forcing, but only a part of ensemble forecast influenced by red noise are superior to results influenced by white noise.Finally, improvements pertaining to red noise stochastic forcing vary non-symmetrically and non-monotonically with the distribution of coefficient φ.And the selection of coefficient φ is also dependent on nonlinear models.