Atmospheric Chemistry and Physics
Atmospheric Chemistry and Physics
ACP
Articles | Volume 21, issue 18
Articles | Volume 21, issue 18
https://doi.org/10.5194/acp-21-14385-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-21-14385-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 21, issue 18
Research article
 | 
28 Sep 2021
Research article |  | 28 Sep 2021

Evaluating consistency between total column CO2 retrievals from OCO-2 and the in situ network over North America: implications for carbon flux estimation

Bharat Rastogi, John B. Miller, Micheal Trudeau, Arlyn E. Andrews, Lei Hu, Marikate Mountain, Thomas Nehrkorn, Bianca Baier, Kathryn McKain, John Mund, Kaiyu Guan, and Caroline B. Alden

Supplement

https://doi.org/10.5194/acp-21-14385-2021-supplement

Data sets

Source code and model output for constructing synthetic OCO-2 columns and evaluation of bias Bharat Rastogi, John B. Miller, Micheal Trudeau, Arlyn Andrews, Lei Hu, Marikate Mountain, Thomas Nehrkorn, Bianca Baier, Kathryn McKain, John Mund, Kaiyu Guan, and Caroline B. Alden https://doi.org/10.15138/cbz1-t443

OCO-2 Level 2 bias-corrected XCO2 and other select fields from the full-physics retrieval aggregated as daily files, Retrospective processing V10r, Greenbelt, MD, USA OCO-2 Science Team, Michael Gunson, and Annmarie Eldering https://doi.org/10.5067/E4E140XDMPO2

NOAA AirCore atmospheric sampling system profiles Bianca Baier, Colm Sweeney, Tim Newberger, Jack Higgs, and Sonja Wolter https://doi.org/10.15138/6AV0-MY81

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Short summary
Predicting Earth's climate is difficult, partly due to uncertainty in forecasting how much CO2 can be removed by oceans and plants, because we cannot measure these exchanges directly on large scales. Satellites such as NASA's OCO-2 can provide part of the needed information, but data need to be highly precise and accurate. We evaluate these data and find small biases in certain months that are similar to the signals of interest. We argue that continued improvement of these data is necessary.
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