Preprints
https://doi.org/10.5194/acp-2021-299
https://doi.org/10.5194/acp-2021-299

  20 Apr 2021

20 Apr 2021

Review status: this preprint is currently under review for the journal ACP.

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

Bharat Rastogi1,2, John B. Miller2, Micheal Trudeau1,2, Arlyn E. Andrews2, Lei Hu1,2, Marikate Mountain3, Thomas Nehrkorn3, John Mund2, Kaiyu Guan4, and Caroline B. Alden1,2 Bharat Rastogi et al.
  • 1Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado Boulder, CO, 80309
  • 2Global Monitoring Laboratory, National Oceanic and Atmospheric Administration, Boulder, CO 80305
  • 3Atmospheric and Environmental Research, Lexington, MA 02041
  • 4Department of Natural Resources and Environmental Sciences, College of Agriculture, Consumer, and Environmental Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 60801

Abstract. Feedbacks between the climate system and the carbon cycle represent a key source of uncertainty in model projections of Earth’s climate, in part due to our inability to directly measure large scale biosphere-atmosphere carbon fluxes. In-situ measurements of CO2 mole fraction from surface flasks, towers and aircraft are used in inverse models to infer fluxes, but measurement networks remain sparse, with limited or no coverage over large parts of the planet. Satellite retrievals of total column CO2 (XCO2), such as those from NASA’s Orbiting Carbon Observatory-2 (OCO-2), can potentially provide unprecedented global information about CO2 spatiotemporal variability. However, for use in inverse modeling, data need to be extremely stable, highly precise and unbiased to distinguish abundance changes emanating from surface fluxes from those associated with variability in weather. Systematic errors in XCO2 have been identified and, while bias correction algorithms are applied globally, inconsistencies persist at regional and smaller scales that may complicate or confound flux estimation. To evaluate XCO2 retrievals and assess potential biases, we compare OCO-2 v10 retrievals with in-situ data-constrained XCO2 simulations over North America estimated using surface fluxes and boundary conditions optimized with observations that are rigorously calibrated relative to the WMO X2007 CO2 scale. Systematic errors in simulated atmospheric transport are independently evaluated using unassimilated aircraft and AirCore profiles. We find that the global OCO-2 v10 bias correction shifts the distribution of retrievals closer to the simulated XCO2, as intended. Comparisons between bias corrected and simulated XCO2 reveal differences that vary seasonally. Importantly, the difference between simulations and retrievals is of the same magnitude as the imprint of recent surface flux in the total column. This work demonstrates that systematic errors in OCO-2v10 retrievals of XCO2 over land can be large enough to confound reliable surface flux estimation and that further improvements in retrieval and bias correction techniques are essential. Finally, we show that independent observations, especially vertical profile data, such as from NOAA’s aircraft and AirCore programs are critical for evaluating errors in both satellite retrievals and carbon-cycle models.

Bharat Rastogi et al.

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Bharat Rastogi et al.

Bharat Rastogi et al.

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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 in these data is necessary.
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