Investigating the Impact of Modern Absorption Cross-Section Databases on CO2 Retrievals

Current spectrometers provide high-quality absorption spectra from both ground-based direct sun measurements and spaceborne backscatter measurements. Accurate retrievals of atmospheric CO₂ concentrations from these measured spectra are fundamental for modelling large-scale atmosphere-surface exchange fluxes. When retrieving CO₂ concentrations from measured spectra, high-quality spectroscopic reference data are essential to drive radiative transfer simulations and to enable accurate retrievals. Here, we investigate how various modern molecular absorption cross-section datasets affect CO₂ retrievals in the 1.6 μm and 2 μm regions. This includes recent parameter sets derived from laboratory measurements at the German Aerospace Center (DLR e.V.) for line-mixing parameterizations (Birk et al., 2024) with separate continuum data, which were obtained in the frame of the ESA-funded project ISOGG (Improved Spectroscopy for satellite measurements Of Greenhouse Gases). We compare these new data to those from HITRAN 2020 (Gordon et al., 2022) with and without speed-dependent Voigt profile extension as well as to the ABSCO tables (Devi et al., 2016).

To evaluate the quality of the spectroscopic databases, we submit high-resolution direct-sun spectra collected by the TCCON (Total Carbon Column Observing Network) spectrometer at Karlsruhe to our RemoTeC retrieval algorithm under variation of the driving spectroscopic parameters. We evaluate the goodness of fit, systematic spectral residuals as well as spurious dependencies of the retrieved CO₂ concentrations on slant airmass. We further use one year of GOSAT satellite measurements to assess whether and how differences in CO₂ concentrations retrieved under variation of the spectroscopic parameters show dependencies on geophysical parameters such as latitude, season or surface type. Our analyses show that the new DLR cross sections and the HITRAN 2020 with speed dependence lead to noticeable improvements in spectral line modelling which in turn affects airmass dependencies as well as latitudinal and seasonal biases. Including the CO₂ continuum from the DLR dataset further improves the fit quality. In contrast, using the ABSCO tables results in larger residuals and poorer fits compared to the standard HITRAN 2020 cross sections, particularly in the 2 μm region.

 

Birk, M., Röske, C., Wagner, G., & Hodges, J. T. (2024, June). New spectroscopic database of CO2 in the 1.6 and 2.0 µm spectral regions for remote sensing. The 17th International HITRAN Conference, Cambridge (MA), United States. https://elib.dlr.de/208834/

Devi, V. M., Benner, D. C., Sung, K., Brown, L. R., Crawford, T. J., Miller, C. E., Drouin, B. J., Payne, V. H., Yu, S., Smith, M. A. H., Mantz, A. W., & Gamache, R. R. (2016). Line parameters including temperature dependences of self- and air-broadened line shapes of 12C16O2: 1.6-μm region. Journal of Quantitative Spectroscopy and Radiative Transfer, 177, 117–144. https://doi.org/10.1016/j.jqsrt.2015.12.020

Gordon, I. E., Rothman, L. S., Hargreaves, R. J., Hashemi, R., Karlovets, E. V., Skinner, F. M., Conway, E. K., Hill, C., Kochanov, R. V., Tan, Y., Wcisło, P., Finenko, A. A., Nelson, K., Bernath, P. F., Birk, M., Boudon, V., Campargue, A., Chance, K. V., Coustenis, A., … Yurchenko, S. N. (2022). The HITRAN2020 molecular spectroscopic database. Journal of Quantitative Spectroscopy and Radiative Transfer, 277, 107949. https://doi.org/10.1016/j.jqsrt.2021.107949