Accurate monitoring of atmospheric carbon dioxide (CO2) is critical for addressing climate change, as CO2 is one of the dominant greenhouse gases. Satellite remote sensing remains the primary method for monitoring column-averaged CO2 (XCO2), yet different satellite missions and retrieval algorithms generate distinct XCO2 products. Thus, recommendations for selecting appropriate XCO2 products remain unclear due to a lack of systematic evaluation of XCO2 products. Here, we present a comprehensive evaluation of eleven XCO2 products from major satellite missions—including the Environmental Satellite (Envisat), Greenhouse Gases Observing Satellite (GOSAT/GOSAT-2), Orbiting Carbon Observatories (OCO-2/OCO-3), and TanSat—alongside one ensemble product based on the ensemble median algorithm (EMMA). We assess their spatiotemporal coverage and performance using Total Carbon Column Observing Network (TCCON) measurements as reference, evaluating both at global and regional scales across seasons. Our results reveal distinct latitudinal and seasonal variations in the evaluation results. Most products show the highest accuracy at 60–80°N in summer (optimal root mean square error 2 ppm). Furthermore, systematic biases are most pronounced during winter, with mean absolute error increasing by 0.3–1.0 ppm compared to other seasons. Among the twelve satellite XCO2 products, the Atmospheric CO2 Observations from Space-Orbiting Carbon Observatory-2 (ACOS-OCO-2) product shows the best overall performance globally. These results provide practical guidelines for the informed selection and application of satellite-derived XCO2 products in climate research.
Ma et al. (Thu,) studied this question.