The ozone,as an important greenhouse gas,has an important influence on global climate change.In order to test the effects of ozone satellite data assimilation on the analysis field and prediction field of ozone, in this study the CESM-ENSRF assimilation system was constructed based on the ensemble square root filter(ENSRF) theory and community earth system model(CESM).Several key problems concerning the data assimilation methodology of the Kalman filter have been considered,namely utilizing random perturbations to achieve the perturbation involving the initial field,combining the regular variance inflation and relax inflation to complete the variance inflation, and using the five order distance correlation function to conduct the variance localization.In order to analyze the effects of the assimilation of the ozone satellite data on the model prediction, the system was then used to assimilate the ozone profile data of the microwave limb sounding(MLS).The results show that the CESM-ENSRF assimilation system is able to effectively assimilate the ozone data,and that the ozone satellite data assimilation achieves a great improvement in the analysis field and prediction field of atmospheric ozone.