Statistic Retrieval Method of Carbon Dioxide Based on Principal Component Analysis

Abstract

Abstract:

In the satellite remote sensing of carbon dioxide (CO2), atmospheric environmental factor is the important factor affecting the inversion accuracy. The inversion conditions 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.

Key words: optical remote sensing, CO2 retrieval; principal component analysis, statistical retrieval, greenhouse gas

CLC Number:

P407

SANG Hao, WANG Xian-Hua, XIE Han-Han, JIANG Yun. Statistic Retrieval Method of Carbon Dioxide Based on Principal Component Analysis[J]. Journal of Atmospheric and Environmental Optics, 2017, 12(3): 202-209.

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