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Proceedings Paper

Validation of the OMI-TOMS and OMI-DOAS total ozone column data using ground-based observations over China
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Paper Abstract

This study evaluates the accuracy of total ozone column derived from Ozone Monitoring Instruments (OMI) with two algorithms: OMI Total Ozone Mapping Spectrometer (OMI-TOMS) and OMI Differential Optical Absorption Spectroscopy (OMI-DOAS), compared to ground-based Brewer and Dobson spectrophotometers located at eight China stations from July 2009 to December 2013, including Xianghe, Kunming, Mt.Waliguan, Lhasa, Taipei, Chengkung, Cape D'Aguilar and Longfengshan. Results showed that the agreement between OMI ozone data and ground-based measurements is excellent. Total ozone columns from both OMI-TOMS and OMI-DOAS data are on average about 1.5% lower than ground-based data. For both OMI ozone data products the SZA dependence of the mean relative differences (RD) between satellite data and the ground-based data is relative obvious when the SZA is larger than 50°. Similar to the SZA, the satellite view zenith angle (VZA) dependence of the mean relative differences (RD) between satellite and ground is relatively markedly when the VZA is smaller than 10° in eight stations. Finally, the dependence of the mean relative differences (RD) (-4.28% to 0.818%) between OMI-DOAS data and ground-based data for the total ozone column is remarkable. While for OMI-TOMS data the dependence is not obvious (the RD value varies from -3.30% to -0.676%).

Paper Details

Date Published: 4 September 2015
PDF: 13 pages
Proc. SPIE 9610, Remote Sensing and Modeling of Ecosystems for Sustainability XII, 961014 (4 September 2015); doi: 10.1117/12.2186782
Show Author Affiliations
Mingliang Ma, East China Normal Univ. (China)
Institute of Remote Sensing and Digital Earth (China)
Runhe Shi, East China Normal Univ. (China)
Institute of Remote Sensing and Digital Earth (China)
Wei Gao, East China Normal Univ. (China)
Institute of Remote Sensing and Digital Earth (China)
Colorado State Univ. (United States)


Published in SPIE Proceedings Vol. 9610:
Remote Sensing and Modeling of Ecosystems for Sustainability XII
Wei Gao; Ni-Bin Chang; Jinnian Wang, Editor(s)

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