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In recent years, ozone has become the primary air pollution in major cities of China. Therefore, tropospheric ozone products are very important for monitoring near surface ozone concentration. However, existing ozone products cannot meet the requirements of high spatial & temporal resolution monitoring. Here, we use a spatial & temporal fitting method to repair the total ozone data from OMI, and then inverse the tropospheric ozone distribution by a residual approach. The results show that the spatial & temporal fitting method is qualitatively and quantitatively superior to both Kriging interpolation and inverse distance weighted interpolation, indicated by its smaller RMSE and MAE. The tropospheric ozone profile obtained by the proposed method is consistent with official ozone products of OMI/MLS according to their correlation coefficient (R) up to 0. 82. [ABSTRACT FROM AUTHOR]

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