Tropospheric CH<sub>4</sub> signals as observed by NDACC FTIR at globally distributed sites and comparison to GAW surface in situ measurements

Abstract

Abstract. We present lower/middle tropospheric columnaveraged CH 4 mole fraction time series measured by nine globally distributed ground-based FTIR (Fourier transform infrared) remote sensing experiments of the Network for the Detection of Atmospheric Composition Change (NDACC). We show that these data are well representative of the tropospheric regional-scale CH 4 signal, largely independent of the local surface small-scale signals, and only weakly dependent on upper tropospheric/lower stratospheric (UTLS) CH 4 variations. In order to achieve the weak dependency on the UTLS, we use an a posteriori correction method. We estimate a typical precision for daily mean values of about 0.5 % and a systematic error of about 2.5 %. The theoretical assessments are complemented by an extensive empirical study. For this purpose, we use surface in situ CH 4 measurements made within the Global Atmosphere Watch (GAW) network and compare them to the remote sensing data. We briefly discuss different filter methods for removing the local small-scale signals from the surface in situ data sets in order to obtain the in situ regional-scale signals. We find good agreement between the filtered in situ and the remote sensing data. The agreement is consistent for a variety of timescales that are interesting for CH 4 source/sink research: day-to-day, monthly, and inter-annual. The comparison study confirms our theoretical estimations and proves that the NDACC FTIR measurements can provide valuable data for investigating the cycle of CH 4 .Published by Copernicus Publications on behalf of the European Geosciences Union. E. Sepúlveda et al.: NDACC FTIR and GAW surface in situ tropospheric CH 4

Addition of a channel for XCO observations to a portable FTIR spectrometer for greenhouse gas measurements

“…PROFFIT is in wide use in the NDACC (e.g. Sepúlveda et al, 2014;Virolainen et al, 2014;Mengistu Tsidu et al, 2015), is in very good agreement with the official TCCON analysis (Dohe, 2013), and is also successfully applied for the analysis of spectra recorded with the EM27/SUN (Gisi et al, 2012;Frey et al, 2015). For the analysis of the low-resolution spectra, the methane, water vapour, HDO, and CO a priori profiles were adopted from the TC-CON processor.…”

Seasonal variability of stratospheric methane: implications for constraining tropospheric methane budgets using total column observations

“…Information about the vertical tropospheric CH 4 profile directly retrieved from NDACC spectra (Sepúlveda et al, 2014) can also be used to assess whether transport errors differ at different levels of the free troposphere. Ideally, information from these tropospheric products could be integrated to overcome the limitations of each: the sensitivity of X t CH 4 to prior assumptions of STE and the sensitivity of profile retrievals to UTLS variability (Ostler et al, 2014).…”

Consistency and quality assessment of the Metop-A/IASI and Metop-B/IASI operational trace gas products (O<sub>3</sub>, CO, N<sub>2</sub>O, CH<sub>4</sub>, and CO<sub>2</sub>) in the subtropical North Atlantic

“…The theoretical error estimation strongly depends on the assumed uncertainties. In our case, we consider the error sources and values listed in Table A1 for the input parameters, which are the leading error sources affecting the different FTS products, identified from our experience and the literature Sepúlveda et al, 2014, and references therein), while the smoothing error is calculated as (A − I)S a (A − I) T , where S a matrix is the is the covariance matrix of the target gas. Strictly, to estimate the smoothing error contribution, the covariance matrix of a real ensemble of atmospheric states must be known (Rodgers, 2000).…”

“…Moreover, this analysis allows us to quickly detect instrumental issues or inconsistencies. For this purpose, we follow the procedure proposed by Sepúlveda et al (2014) (and references therein), explained in detail in the following. Firstly, for analysing the time series on different timescales the measured TC time series of each target gas ([TC] gas ) is fitted to a time series model, which considers a mean [TC] gas value and [TC] gas variations on two different timescales (see Eq.…”

“…The good quality of these long-term ground-based FTS data sets has been extensively documented by theoretical and empirical validation studies (e.g. Schneider et al, 2006Sepúlveda et al, 2012;García et al, 2012b;Sepúlveda et al, 2014;.…”