Climate Change Research ›› 2017, Vol. 13 ›› Issue (2): 95-102.doi: 10.12006/j.issn.1673-1719.2016.152

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Study on the Spatial-Temporal Change Characteristics of Global CO2 Concentration Based on SCIAMACHY Retrievals

Zhao Mingwei1, Li Chenchen1, Zhang Xingying2, Wang Chun1, Jiang Ling1, Sun Jinglu3   

  1. 1 Anhui Center for Collaborative Innovation in Geographical Information Integration and Application, Chuzhou University, Chuzhou 239000, China;
    2 National Satellite Meteorology Center, China Meteorological Administration, Beijing 100081, China;
    3 Anhui Institute of Economics, Hefei 230051, China

  • Received:2016-08-01 Revised:2016-09-20 Online:2017-03-30 Published:2017-03-30


Retrieval estimation based on satellite spectrum characteristics is the principle means to observe the global carbon dioxide concentration and analyze its spatial-temporal tendency today. However, only discrete carbon dioxide concentration data can be obtained limited to the observation condition and retrieval technique. So spatial interpolation method is needed to produce continuous carbon dioxide concentration in space. In this study, the XCO2 concentration data released by the SCIAMACHY research team was taken as the basic data, several classical interpolation methods (IDW, Kriging, and Spline) were compared in the XCO2 concentration interpolation, and the error statistical indicators (MAE, Max_AE, RMSE) showed that IDW was the optimal method for this research. Then, spatial distribution data of XCO2 concentration in the global continent from January 2003 to April 2012 were produced based on IDW, and its spatial-temporal tendency was also analyzed. The XCO2 concentration in global scale all showed an increased trend during this period, and on the average level of the global continent, the increase of XCO2 concentration was 17.43×10-6, the average increase rate of XCO2 was about 2×10-6 per year, and the rate of increase in the Northern Hemisphere was higher than that in the Southern Hemisphere.

Key words: SCIAMACHY, XCO2, spatial interpolation, spatial-temporal analysis

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