A Method for Estimating the Background Column Concentration of CO2 Using the Lagrangian Approach

With the rapid growth of greenhouse gas (GHG) monitoring satellites, more and more studies focused on the issue of inversion/optimization of carbon dioxide (CO2) fluxes using satellite-derived XCO2 observations in recent years. A common and critical challenge in this framework is the separation of background and anomalies from XCO2 observations, which directly affect the performance of the CO2 fluxes' inversion. We proposed a novel method to accurately extract background XCO2 from satellite observations. A series of observing system simulation experiments (OSSEs) were performed to test the performance of the method. We found that the bias and uncertainty of the background concentration are below 0.01 and 0.05 ppm in the given cases, respectively. Based on this method, we selected five overpasses from 2014 to 2016 to demonstrate a regional-scale flux inversion near Riyadh. The comparison with the two previous methods shows that the posterior simulated XCO2 by the method proposed in this article can match better with the observed XCO2 from Orbiting Carbon Observatory-2 (OCO-2).

Automated summary

With the increasing use of GHG monitoring satellites, researchers have been focusing on the inversion/optimization of CO2 fluxes using satellite-derived XCO2 observations. One major challenge in this field is how to accurately separate background and anomalies from the XCO2 observations. This study proposes a novel method to extract background XCO2 accurately and tests its performance through simulation experiments.