• Journal of Atmospheric and Environmental Optics
  • Vol. 12, Issue 3, 202 (2017)
Hao SANG, Xianhua WANG*, Hanhan YE, and Yun JIANG
Author Affiliations
  • [in Chinese]
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    DOI: 10.3969/j.issn.1673-6141.2017.03.006 Cite this Article
    SANG Hao, WANG Xianhua, YE Hanhan, JIANG Yun. Statistic Retrieval Method of Carbon Dioxide Based on Principal Component Analysis[J]. Journal of Atmospheric and Environmental Optics, 2017, 12(3): 202 Copy Citation Text show less

    Abstract

    In the satellite remote sensing of carbon dioxide (CO2), atmospheric environmental factor is the important factor affecting the inversion accuracy. The inversion condition is usually limited to the situation of the aerosol optical thickness less than 0.3. The higher requirement of the atmospheric conditions will seriously affect the application ability of our country’s CO2 satellite remote sensing data. For this kind of situation, based on principal component analysis (PCA), atmospheric CO2 of Beijing and Tianjin areas of China is inversed of high aerosol optical thickness, the CO2 column concentration obtained is compared with the product of GOSAT-Level2 in 2013, 2014. The root mean square error is 0.65% and 0.46%, respectively, and the correlation is 0.77 and 0.93, respectively.
    SANG Hao, WANG Xianhua, YE Hanhan, JIANG Yun. Statistic Retrieval Method of Carbon Dioxide Based on Principal Component Analysis[J]. Journal of Atmospheric and Environmental Optics, 2017, 12(3): 202
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