Ozone and methane are important atmospheric trace gases,which have an important impact on climate change.In order to improve their forecast accuracy in the climate model,anassimilation system based on the ensemble square root filter (EnSRF)assimilation method and the community earth system model (CESM)has been built.We have designed experiments to assess the performance of this system by assimilating the observation data from the atmospheric infrared sounder(AIRS).The results showed that:①The ensemble mean bias and root mean square error of ozone and methane in the analysis fields are both lower than those in the background fields.②In the re-forecast experiment,the bias and root mean square error of ozone and methane are lower than those in the control experiment,except the ozone obove 5 hPa.③The improvement rates(IRs)of ozone and methanein the stratosphere are improving by the data cycling assimilation at the beginning,andstabilizedgradually.In the troposphere,the IRs are stabilized during the whole experimental period.These results indicatethat the assimilation system can improve the rationality ofozone and methane in the background field by assimilatingthe observation data.And it can improve the reforecast accuracy of ozone and methane in the model.However,the ozone photochemistry performance of the model is more important than assimilating observation dataabove 5 hPa.In addition,the data cycling assimilation is more effective in improving the reforecast accuracyof ozone at 5~ 150 hPa,and methane at 1~ 200 hPa in the CESM.