A spatio-temporal interpolation approach for the FTS SWIR product of XCO2 data from GOSAT

The spatial distribution of carbon dioxide(CO2) column abundance is of importance in analyzing the change of the greenhouse gas. A spatio-temporal interpolation method is proposed in this paper, by analyzing the seasonal change characteristics of CO2 concentration, to generate the spatial distribution of CO2 column abundance based on the GOSAT Level 2 XCO2 data. The variograms of the CO2 data are analyzed to generate the spatio-temporal model. Cross-validation and the comparison between the predicted value and Waliguang ground observation data are implemented to validate the interpolation method. According to the applied case in China, the spatio-temporal interpolation method generates a better result than the GOSAT Level 3 product, which uses the spatial-only Kriging interpolation algorithm.