Abstract:

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