Interpolation of XCO₂ retrieved from GOSAT in China using fixed rank kriging

The Greenhouse Gases Observing Satellite (GOSAT) can provide high accuracy column-averaged dry air mole fractions of carbon dioxide (XCO₂). However, the observations have large gaps due to the impact of the cloud and observational modes. Although kriging interpolation yields the best linear unbiased predictor, it would be computationally expensive for a large dataset. Fixed Rank Kriging (FRK) is based on the Spatial Random Effect (SRE) model and it assumes that the process of interest can be expressed as a linear combination of spatial basis functions, plus a fine-scale-variation component. The FRK predictors and standard errors can be computed rapidly. This paper analyzes the FRK prediction of GOSAT Level 2 XCO₂ data over China and shows that the FRK prediction is consistent with other kriging methods (e.g., ordinary kriging). In addition, the result agrees well with the CO₂ measurements from the stations at Mt. Waliguan and Shangdianzi.