第二届未来大气科学论坛

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 < 1.0 ppm), while the largest uncertainties appear in the tropics (20°S–20°N; 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.