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As an important greenhouse gas (GHG) in the atmosphere, Carbon dioxide (CO 2 ) has a great impact on global climate change. Accurate knowledge of the spatio-temporal variations of CO 2 is of great significance for understanding the carbon cycle and evaluating the effectiveness of carbon emission reduction. In recent years, several satellites with CO 2 sensors have been launched and a series of atmospheric CO 2 concentration products have been developed using different retrieval algorithms. This study validated nine satellite XCO 2 products derived from Greenhouse gases Observing SATellite (GOSAT), GOSAT-2, Orbiting Carbon Observatory-2 (OCO-2) and OCO-3: including ACOS-GOSAT, NIES-GOSAT, BESD-GOSAT, OCFP-GOSAT, SRFP-GOSAT, EMMA, GOSAT-2, OCO-2, and OCO-3 XCO 2 . The remotely sensed XCO 2 products were compared with the XCO 2 observations from six Total Carbon Column Observing Network (TCCON) stations in East Asia for validation. The results showed that the OCO-2 XCO 2 product outperformed other products, with the highest R 2 of 0.94 and the lowest MAE of 1.24 ppm. The ACOS-GOSAT and EMMA-GOSAT XCO 2 products also showed favorable accuracies, both achieving the R 2 of 0.93 and corresponding MAE values of 1.29 and 1.31 ppm, respectively. The GOSAT-2 XCO 2 product showed the poorest accuracy, with an R 2 of 0.77 and an MAE of 3.28 ppm. There was a significant overestimation of the bias-uncorrected GOSAT-2 XCO 2 product in East Asia, and it indicated that bias correction must be performed for this XCO 2 product. The accuracy of TCCON XCO 2 was not consistent with remotely sensed XCO 2 at different stations. The RJ, JS, AN, and TK TCCON stations generally showed better agreements between satellite estimates and TCCON observations, except for the GOSAT-2 XCO 2 product.
Ji et al. (Mon,) studied this question.
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