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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Volume 6, issue 2 | Copyright
Atmos. Meas. Tech., 6, 397-418, 2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 20 Feb 2013

Research article | 20 Feb 2013

First intercalibration of column-averaged methane from the Total Carbon Column Observing Network and the Network for the Detection of Atmospheric Composition Change

R. Sussmann1, A. Ostler1, F. Forster1, M. Rettinger1, N. M. Deutscher2,3, D. W. T. Griffith2, J. W. Hannigan4, N. Jones2, and P. K. Patra5 R. Sussmann et al.
  • 1Karlsruhe Institute of Technology, IMK-IFU, Garmisch-Partenkirchen, Germany
  • 2School of Chemistry, University of Wollongong, Wollongong, New South Wales, Australia
  • 3Institute of Environmental Physics, University of Bremen, Bremen, Germany
  • 4Atmospheric Chemistry Division, National Center for Atmospheric Research, Boulder, Colorado, USA
  • 5Research Institute for Global Change, JAMSTEC, Yokohama, 236-0001, Japan

Abstract. We present the first intercalibration of dry-air column-averaged mole fractions of methane (XCH4) retrieved from solar Fourier transform infrared (FTIR) measurements of the Network for the Detection of Atmospheric Composition Change (NDACC) in the mid-infrared (MIR) versus near-infrared (NIR) soundings from the Total Carbon Column Observing Network (TCCON). The study uses multi-annual quasi-coincident MIR and NIR measurements from the stations Garmisch, Germany (47.48° N, 11.06° E, 743 m a.s.l.), and Wollongong, Australia (34.41° S, 150.88° E, 30 m a.s.l.).

Direct comparison of the retrieved MIR and NIR XCH4 time series for Garmisch shows a quasi-periodic seasonal bias leading to a standard deviation (stdv) of the difference time series (NIR–MIR) of 7.2 ppb. After reducing time-dependent a priori impact by using realistic site- and time-dependent ACTM-simulated profiles as a common prior, the seasonal bias is reduced (stdv = 5.2 ppb). A linear fit to the MIR/NIR scatter plot of monthly means based on same-day coincidences does not show a y-intercept that is statistically different from zero, and the MIR/NIR intercalibration factor is found to be close to ideal within 2-σ uncertainty, i.e. 0.9996(8). The difference time series (NIR–MIR) do not show a significant trend. The same basic findings hold for Wollongong. In particular an overall MIR/NIR intercalibration factor close to the ideal 1 is found within 2-σ uncertainty. At Wollongong the seasonal cycle of methane is less pronounced and corresponding smoothing errors are not as significant, enabling standard MIR and NIR retrievals to be used directly, without correction to a common a priori.

Our results suggest that it is possible to set up a harmonized NDACC and TCCON XCH4 data set which can be exploited for joint trend studies, satellite validation, or the inverse modeling of sources and sinks.

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