Comparing simulated atmospheric carbon dioxide concentration with GOSAT retrievals

Abstract

Satellite observations of atmospheric carbon dioxide (CO 2 ) provide a useful way to improve the understanding of global carbon cycling. In this paper, we present a comparison between simulated CO 2 concentrations from an inversion model of the CarbonTracker Data Assimilation System (CTDAS) and satellite-based CO 2 measurements of column-averaged dry air mole fraction (denoted XCO 2 ) derived from version 3.3 Atmospheric CO 2 Observations from Space retrievals of the Greenhouse Gases Observing SATellite (ACOS-GOSAT) L2 data products. We examine the differences of CTDAS and GOSAT to provide important guidance for the further investigation of CTDAS in order to quantify the corresponding flux estimates with satellite-based CO 2 observations. We find that the mean point-by-point difference (CTDAS-GOSAT) between CTDAS and GOSAT XCO 2 is -0.11 ± 1.81 ppm, with a high agreement (correlation r = 0.77, P \ 0.05) over the studied period. The latitudinal zonal variations of CTDAS and GOSAT are in general agreement with clear seasonal fluctuations. The major exception occurs in the zonal band of 0°-15°N where the difference is approximately 4 ppm, indicating that large uncertainty may exist in the assimilated CO 2 for the lowlatitude region of the Northern Hemisphere (NH). Additionally, we find that the hemispherical/continental differences between CTDAS and GOSAT are typically less than 1 ppm, but obvious discrepancies occur in different hemispheres/continents, with high consistency (point-bypoint correlation r = 0.79, P \ 0.05) in the NH and a weak correlation (point-by-point correlation r = 0.65, P \ 0.05) in the Southern Hemisphere. Overall, the difference of CTDAS and GOSAT is small, and the comparison of CTDAS and GOSAT will further instruct the inverse modeling of CO 2 fluxes using GOSAT.

Impact of Prior Terrestrial Carbon Fluxes on Simulations of Atmospheric CO2 Concentrations

“…This suggests that the GEOS-Chem CO 2 simulation performs better in summer than in other seasons. This finding is consistent with the results from previous studies (Lei, Guan, et al, 2014;Li et al, 2017;H. Zhang et al, 2015).…”

“…In addition, GOSAT may capture the spatial heterogeneity and temporal variations in CO 2 caused by changes in carbon sources and sinks better than the CTM model, which is constrained by emissions inventories (Li et al, 2017). The GOSAT measurements have a constant sensitivity to 10.1029/2021JD034794 10 of 22 the entire atmospheric column and show the maximum sensitivity to changes in CO 2 concentrations near the surface (H. Zhang et al, 2015).…”

Global Atmospheric CO2 Concentrations Simulated by GEOS-Chem: Comparison with GOSAT, Carbon Tracker and Ground-Based Measurements

“…This phenomenon is similar to the result shown in Figure 2. The reason for more discrete variations of GOSAT/ACOS XCO 2 may be that, on the one hand, the GEOS-Chem model is not better to capture complicated dynamic variations of XCO 2 than satellite observations [15]. On the other hand, the retrieval errors on satellite observations [23,26] could lead to large uncertainties in the GOSAT/ACOSv7.3 XCO 2 .…”

“…Morino et al [14] pointed out that only about 10% of the GOSAT data points can be used for the XCO 2 retrievals. Consequently, these limited CO 2 observations could bring additional uncertainties into atmospheric inversion models [15].…”

“…To better estimate the uncertainty in CO 2 model inversion, several studies have also assessed the differences between observations and models [15,18,19]. Li et al [18] compared the differences of atmospheric CO 2 concentration in East Asia between the Community Multiscale Air Quality Modeling System (CMAQ) and GOSAT observations to evaluate the uncertainties in model simulation.…”