AbstractTotal ozone data from the Aura Ozone Monitoring Instrument (OMI) play an important role in the monitoring of the spatial distribution and temporal change of total ozone. However, since September 2005, and especially after mid‐2006, due to row anomalies in the OMI instrument, one third to one half of the OMI total ozone data has been missing. In this study, we generate a spatially continuous and daily global total ozone product (2004–2014) by quantitatively reconstructing the level 3 (gridded) total ozone data via a new two‐step method, which takes full advantage of the temporal and spatial correlation characteristics. First, a preliminary prediction is made based on an adaptive weighted temporal fitting method. Residual correction based on an anisotropic kriging method is then proposed to further improve the prediction accuracy. To assess the efficacy of the proposed method, a comparison of different gap filling algorithms through a series of simulated experiments was performed. On this basis, we further evaluated the proposed product with Brewer spectrophotometers' total ozone columns. The evaluation results suggest that the proposed method outperforms the other algorithms, and its product is better able to capture total ozone variation than the MERRA‐2 assimilated ozone product. The total ozone product produced in this study can be freely downloaded fromhttp://sendimage.whu.edu.cn/send‐resource‐download/.