Inversion of tropospheric ozone over China based on OMI data

doi:10.13878/j.cnki.jnuist.2021.06.009

2025-5-28- 15

Home > Archive>Volume 13, Issue 6, 2021 >707-719. DOI:10.13878/j.cnki.jnuist.2021.06.009

Inversion of tropospheric ozone over China based on OMI data
DOI:
                        10.13878/j.cnki.jnuist.2021.06.009
                    
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                        XU JunXU Jun
Key Lab of Spatial Data Mining & Information Sharing, Ministry of Education, Fuzhou University, Fuzhou 350108;National Engineering Research Center of Geospatial Information Technology, Fuzhou University, Fuzhou 350108;Academy of Digital China (Fujian), Fuzhou 350116
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LU YiminLU Yimin
Key Lab of Spatial Data Mining & Information Sharing, Ministry of Education, Fuzhou University, Fuzhou 350108;National Engineering Research Center of Geospatial Information Technology, Fuzhou University, Fuzhou 350108;Academy of Digital China (Fujian), Fuzhou 350116
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Abstract:

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.

Key words:ozone monitoring instrument(OMI);data repair;spatial-temporal weighting method;tropospheric ozone;satellite remote sensing data;inversion

Reference

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XU Jun, LU Yimin. Inversion of tropospheric ozone over China based on OMI data[J]. Journal of Nanjing University of Information Science & Technology,2021,13(6):707-719

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Received:January 31,2021
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Online: January 21,2022
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