Preprints
https://doi.org/10.5194/amt-2022-322
https://doi.org/10.5194/amt-2022-322
 
07 Dec 2022
07 Dec 2022
Status: this preprint is currently under review for the journal AMT.

Inferring the vertical distribution of CO and CO2 from TCCON total column values using the TARDISS algorithm

Harrison A. Parker1, Joshua L. Laughner2, Geoffrey C. Toon2, Debra Wunch3, Coleen M. Roehl1, Laura T. Iraci4, James R. Podolske4, Kathryn McKain5,6, Bianca Baier5,7, and Paul O. Wennberg1,8 Harrison A. Parker et al.
  • 1Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, USA
  • 2Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
  • 3Department of Physics, University of Toronto, Toronto, ON, Canada
  • 4Atmospheric Science Branch, NASA Ames Research Center, Moffett Field, CA, USA
  • 5Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado, Boulder, CO, USA
  • 6Earth System Research Laboratory, National Oceanic and Atmospheric Administration, Boulder, CO, USA
  • 7Global Monitoring Laboratory, National Oceanic and Atmospheric Administration, Boulder, CO, USA
  • 8Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA, USA

Abstract. We describe an approach for determining limited information about the vertical distribution of carbon monoxide (CO) and carbon dioxide (CO2) from total column observations from ground-based TCCON observations. For long-lived trace gases, such as CO and CO2, it has been difficult to retrieve information about their vertical distribution from spectral line shapes in the shortwave infrared (SWIR) spectra because of the large doppler widths at 6000 cm-1, and errors in the spectroscopy and in the atmospheric temperature profile which mask the effects of variations in their mixing ratio with altitude in the troposphere. For CO2 the challenge is especially difficult given that these variations are typically 2 % or less. Nevertheless, if sufficient accuracy can be obtained, such information would be highly valuable for evaluation of retrievals from satellites and more generally for improving the estimate of surface sources and sinks of these trace gases. We present here the Temporal Atmospheric Retrieval Determining Information from Secondary Scaling (TARDISS) retrieval algorithm. TARDISS uses several simultaneously obtained total column observations of the same gas from different absorption bands with distinctly different vertical averaging kernels. Since TARDISS avoids spectral re-fitting by ingesting retrieved column abundances, it is very fast and processes years of data in minutes. The different total column retrievals are combined using a Bayesian approach where the weights and temporal covariance applied to the different retrievals include additional constraints on the diurnal variation in the vertical distribution for these gases. We assume that only the near surface is influenced by local sources and sinks, while variations in the distribution in the middle and upper troposphere result primarily from advection that can be independently constrained using reanalysis data about the variation in mid-tropospheric potential temperature. Using measurements from five North American TCCON sites, we find that the retrieved lower partial column (between the surface and ~800 hPa) of the CO and CO2 dry mole fractions (DMF) have slopes of 1.001±0.002 and 1.007±0.002 with respect to lower column DMF from integrated in situ data measured by aircraft and AirCore. The average error for our CO retrieval is 0.857 ppb (~1 %) while the average error for our CO2 retrieval is 3.55 ppm (~0.8 %). We calculate degrees of freedom from signal of 0.218 per measurement for lower partial column CO on average and of 0.353 per measurement for lower partial column CO2 on average. Compared with classical line-shape-derived vertical profile retrievals, our algorithm reduces the influence of forward model errors such as imprecision in spectroscopy (line shapes and intensities) and in the instrument line shape. We anticipate that this approach will find broad application for use in carbon cycle science.

Harrison A. Parker et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2022-322', Anonymous Referee #1, 14 Jan 2023
  • RC2: 'Comment on amt-2022-322', Anonymous Referee #2, 22 Jan 2023

Harrison A. Parker et al.

Harrison A. Parker et al.

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Short summary
We describe a retrieval algorithm for determining limited information about the vertical distribution of carbon monoxide (CO) and carbon dioxide (CO2) from total column observations from ground-based observations. Our retrieved partial column values compare well with integrated in situ data. The average error for our retrieval is 0.857 ppb (~1 %) for CO and 3.55 ppm (~0.8 %) for CO2. We anticipate that this approach will find broad application for use in carbon cycle science