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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Volume 9, issue 5 | Copyright

Special issue: Twenty-five years of operations of the Network for the Detection...

Atmos. Meas. Tech., 9, 2223-2239, 2016
https://doi.org/10.5194/amt-9-2223-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 20 May 2016

Research article | 20 May 2016

Comparison of XCO abundances from the Total Carbon Column Observing Network and the Network for the Detection of Atmospheric Composition Change measured in Karlsruhe

Matthäus Kiel1, Frank Hase1, Thomas Blumenstock1, and Oliver Kirner2 Matthäus Kiel et al.
  • 1Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Karlsruhe, Germany
  • 2Steinbuch Centre for Computing (SCC), Karlsruhe Institute of Technology, Karlsruhe, Germany

Abstract. We present a comparison of Karlsruhe XCO records (April 2010–December 2014) from the Total Carbon Column Observing Network (TCCON) and from the spectral region covered by the Network for the Detection of Atmospheric Composition Change (NDACC). The Karlsruhe TCCON Fourier transform infrared (FTIR) spectrometer allows us to record spectra in the mid-infrared (MIR) and near-infrared (NIR) spectral region simultaneously, which makes Karlsruhe a favourable FTIR site to directly compare measurements from both spectral regions. We compare XCO retrieved from the fundamental absorption band at 4.7µm (as used by NDACC) and first overtone absorption band at 2.3µm (TCCON-style measurements). We observe a bias of (4.47±0.17)ppb between both data sets with a standard deviation of 2.39ppb in seasonal variation. This corresponds to a relative bias of (4.76±0.18)% and a standard deviation of 2.28%. We identify different sources which contribute to the observed bias (air-mass-independent correction factor, air-mass-dependent correction factor, isotopic identities, differing a priori volume mixing ratio profiles) and quantify their contributions. We show that the seasonality in the residual of NDACC and TCCON XCO can be largely explained by the smoothing effect caused by differing averaging kernel sensitivities between the MIR and NIR spectral region. This study aims to improve the comparability of NDACC and TCCON XCO validation data sets as desired for potential future satellite missions and model studies.

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