Sensitivity of atmospheric CO2 inversions to seasonal and interannual variations in fossil fuel emissions

• Published in: Journal of Geophysical Research. D. Atmospheres 2005-05, Vol.110 (D10), p.D10308.1-n/a
• Main Authors: Gurney, Kevin Robert, Chen, Yu-Han, Maki, Takashi, Kawa, S. Randy, Andrews, Arlyn, Zhu, Zhengxin
• Format: Article
• Language: English
• Subjects: atmospheric inversion; Earth sciences; Earth, ocean, space; Exact sciences and technology; fossil fuel emissions; global carbon cycle
• ISSN: 0148-0227; 2156-2202
• DOI: 10.1029/2004JD005373

Estimates of fossil fuel CO2 are a critical component in atmospheric CO2 inversions. Rather than solving for this portion of the atmospheric CO2 budget, inversions typically include estimates of fossil fuel CO2 as a known quantity. However, this assumption may not be appropriate, particularly as inversions continue to solve for fluxes at reduced space and timescales. In this study, two different alterations are made to widely used fossil fuel CO2 emissions estimates, and these altered emissions are run through a series of atmospheric inversion experiments. The first alteration is the inclusion of a seasonal cycle which depends upon both season and latitude. The other alteration is the inclusion of year‐by‐year changes in the spatial distribution of fossil fuel CO2 emissions. All but the interannual inversion experiments are run with three models from the TransCom 3 atmospheric inversion intercomparison. These three models span the key components of atmospheric transport and hence can be expected to capture the range of potential bias caused by assumed fossil fuel CO2 emission estimates when interacting with transport processes. Key findings include the lack of seasonal rectification of the seasonally varying fossil fuel CO2 emissions in the annual mean. Examination of monthly fluxes in the seasonal inversion, however, indicates that significant bias is likely occurring and may be as large as 50% of the residual flux during certain times of the year. In this study, interannual variations were little effected by shifts in the spatial pattern of fossil fuel CO2 emissions. However, as the spatial scale of inversions is reduced, potential bias will likely increase.