The Total Ozone Unit (TOU) on board the second-generation polar orbiting meteorological satellite of China, Fengyun-3A (FY-3A), provides once-daily global total ozone observations. To apply the TOU ozone data in numerical weather prediction, a quality control scheme is developed, viewed from the assimilation point. In the first step, a daily updated linear regression model, which links the total column ozone to the mean potential vorticity (MPV), is established. Following this step, the biweight algorithm is applied to remove the outliers. Numerical results implementing the proposed quality control scheme in typhoon Tembin (2012) and Isaac (2012) reflect daily variations of correlation between total ozone and MPV. The total percentage of outliers identified by this scheme is highly stable with the change of time, and the main information of ozone data is maintained whereas the standard deviation is reduced significantly. In addition, the ozone data after quality control are more consistent with the statistical fitting variable. The distribution of the observed-minus-fitting Probability Density Function becomes nearly Gaussian, which is conducive to data assimilation.