Global-Scale Evaluation of XCO2 Products from GOSAT, OCO-2 and CarbonTracker Using Direct Comparison and Triple Collocation Method

Abstract

Triple collocation (TC) shows potential in estimating the errors of various geographical data in the absence of the truth. In this study, the TC techniques are first applied to evaluate the performances of multiple column-averaged dry air CO2 mole fraction (XCO2) estimates derived from the Greenhouse Gases Observing Satellite (GOSAT), the Orbiting Carbon Observatory 2 (OCO-2) and the CarbonTracker model (CT2019B) at a global scale. A direct evaluation with the Total Carbon Column Observing Network (TCCON) measurements is also employed for comparison. Generally, the TC-based evaluation results are consistent with the direct evaluation results on the overall performances of three XCO2 products, in which the CT2019B performs best, followed by OCO-2 and GOSAT. Correlation coefficient estimates of the TC show higher consistency and stronger robustness than root mean square error estimates. TC-based error estimates show that most of the terrestrial areas have larger error than the marine areas overall, especially for the GOSAT and CT2019B datasets. The OCO-2 performs well in areas where CT2019B or GOSAT have large errors, such as most of China except the northwest, and Russia. This study provides a reference for characterizing the performances of multiple CO2 products from another perspective.