A Method for the Recovery of Aura Satellite Remote Sensing Ozone Products

Total ozone data plays is essential for monitoring the spatial distribution and temporal change in the total ozone. However, since late 2006, total ozone production from OMI (ozone monitoring instrument) aboard on Aura OMTO3e satellite began show defects resulting from an OMI instrument anomaly. The missing parts accounting for one third or even more of one set data, which is a serious obstacle for normal usage. Therefore, the recovery pf missing OMTO3e data is necessary. In this paper, a multi-temporal fitting model, based on the characteristics of OMTO3e data, is proposed to reconstruct the missing data. Experimental results and comparitive quantitative evaluation, verify that the proposed method has higher feasibility and superior to traditional methods.