A Method for Estimating the Background Column Concentration of CO<sub>2</sub> Using the Lagrangian Approach
Zhipeng Pei, Ge Han, Xin Ma, Tianqi Shi, Wei Gong
Abstract
With the rapid growth of GHG monitoring satellites, more and more studies focused on the issue of inversion/optimization of 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 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 were performed to test the performance of the method. We found that the bias and uncertainty of the background concentration are below 0.01 ppm 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 paper can match better with the observed XCO2 from OCO-2.