Toward a long-term atmospheric CO2 inversion for elucidating natural carbon fluxes: technical notes of NISMON-CO2 v2021.1

Abstract

Abstract Accurate estimates of the carbon dioxide (CO2) fluxes at the earth’s surface are imperative for comprehending the carbon cycle mechanisms and providing reliable global warming predictions. Furthermore, they can also provide valuable science-based information that will be helpful in reducing human-induced CO2 emissions. Inverse analysis is a prominent method of quantitatively estimating spatiotemporal variations in CO2 fluxes; however, it involves a certain level of uncertainty and requires technical refinement, specifically to improve the horizontal resolution so that local fluxes can be compared with other estimates made at the regional or national level. In this study, a novel set of inversion schemes was incorporated into a state-of-the-art inverse analysis system named NISMON-CO2. The introduced schemes include a grid conversion, observational weighting, and anisotropic prior error covariance, the details of which are described. Moreover, pseudo-observation experiments were performed to examine the effect of the new schemes and to assess the reliability of NISMON-CO2 for long-term analysis with practical inhomogeneous observations. The experiment results evidently demonstrate the advantages of the grid conversion scheme for high-resolution flux estimates (1° × 1°), with notable improvements being achieved through the observational weighting and anisotropic prior error covariance. Furthermore, the estimated seasonal and interannual variations in regional CO2 fluxes were confirmed to be reliable, although some potential bias in terms of global land–ocean partitioning was observed. Thus, these results are useful for interpreting the flux variations that result from real-observation inverse analysis by NISMON-CO2 ver. 2021.1.

Keywords

• Inverse analysis
• Carbon dioxide
• Carbon cycle
• Atmospheric transport model
• Data assimilation