As part of the TCCON, the Karlsruhe Institute of Technology (KIT) operates a high-resolution ground-based spectrometer at KIT, Campus North (CN) near Karlsruhe (49.100∘ N, 8.439∘ E, 112 m a.s.l.). Standard TCCON instruments have been described in great detail elsewhere . The Karlsruhe instrument, in the following called HR125, is the first demonstration of synchronized recordings of TCCON near-infrared (NIR) and NDACC mid-infrared (MIR) spectra using a dedicated dichroic beamsplitter (BS) arrangement (Optics Balzers Jena GmbH, Germany) with a cut-off wavenumber of 5250 cm-1. It uses an InGaAs (indium–gallium–arsenide) detector in conjunction with an InSb (indium–antimonide) detector; details can be found in . By the TCCON measurements, the relevant wavenumber region 4000–11000 cm-1, corresponding to wavelengths λ between 0.9 and 2.5 µm, is covered so that, among other species, O2, CO2, CH4, CO and H2O can be retrieved. A figure showing the spectral range of TCCON and the EM27/SUN can be found in , Fig. 1. The TCCON measurements were chosen as reference measurements because these gases are also measured by the EM27/SUN spectrometer. For TCCON measurements in the NIR the HR125 records single-sided interferograms with a resolution of 0.014 cm-1 (Δλ=3.5 pm) or 0.0075 cm-1 (Δλ=1.9 pm), corresponding to a maximum optical path difference (MOPD) of 64 and 120 cm. The recording time for a typical measurement consisting of two forward and two backward scans is 212 and 388 s, respectively. The applied scanner velocity is 20 kHz. TCCON site Karlsruhe participated in the Infrastructure for Measurement of the European Carbon Cycle (IMECC) aircraft campaign . The spectrometer has been used for calibrating all gas cells used by TCCON for instrumental line shape (ILS) monitoring .

TCCON data processing is performed using the GGG Suite software package . In this study, the current release version, GGG 2014, is used . The software package includes a pre-processor correcting for solar brightness fluctuations and performing a fast Fourier transform including a phase error correction routine to convert recorded interferograms into solar absorption spectra. Note that forward and backward scans are split by the preprocessing software and analyzed separately. The central part of the software package is nonlinear least-squares retrieval algorithm GFIT. It performs a scaling retrieval with respect to an a priori profile, and then integrates the scaled profile over height to calculate the total column of the gas of interest. The software package additionally uses meteorological data from the National Center for Environmental Protection and National Center for Atmospheric Research (NCEP/NCAR) and provides daily a priori gas profiles. TCCON converts the retrieved total column abundances VCgas of the measured gases into column-averaged dry air mole fractions (DMFs), where the DMF of a gas is denoted as Xgas=VCgasVCO2×0.2095. In this representation several errors cancel out that affect both the target gas and O2. However, residual bias with respect to in situ measurements still persists, as well as a residual spurious dependence of retrieval results on the apparent airmass. Therefore the GGG suite also includes a post-processing routine applying an empirical airmass-dependent correction factor (ADCF) and airmass-independent correction factor (AICF). The AICF is deduced from comparisons with in situ instrumentation on aircrafts .

In addition to the afore-mentioned TCCON data product, a second data product from the HR125 will be used in this work, in the following called HR125 LR. For this product the raw interferograms are first truncated to the resolution of the EM27/SUN, 0.5 cm-1. At 0.5 cm-1 resolution, the ILS of the HR125 is expected to be nearly nominal. However, to avoid any systematic bias of the HR125 LR data with respect to the EM27/SUN results, the same procedure for ILS determination from H2O signatures in open path lab air spectra was applied and the resulting ILS parameters adopted for the trace gas analysis. The analysis procedure will be explained in detail in Sect. ; the retrieval software used for this data set is PROFFIT Version 9.6 . The reason for the construction of this HR125 LR data set is that with this approach the analysis for the two instruments can be performed in exactly the same way. The resolution is harmonized; the averaging kernels for a given airmass are nearly identical. Differences between the EM27/SUN and the HR125 LR data set can then be attributed to instrumental features alone and do not need to be disentangled from retrieval software, resolution and airmass dependency differences. Note that for the low-resolution data set, forward and backward scans are averaged and then analyzed, whereas they are analyzed separately for the TCCON data set. Therefore the number of coincident measurements with the EM27/SUN data set compared to the TCCON data set is lower.

The EM27/SUN spectrometer, which was developed by KIT in collaboration with Bruker Optics^™, is utilized for the acquisition of solar spectra. The instrument has been described in great detail in ; in the following a short overview is given. The central part of this Fourier transform spectrometer (FTS) is a RockSolid^™ pendulum interferometer with two cube corner mirrors and a CaF2 beamsplitter. The EM27/SUN routinely records double-sided interferograms; the compensated BS design minimizes the curvature in the phase spectrum. This setup achieves high stability against thermal influences and vibrations. The retroreflectors are gimbal-mounted, which results in frictionless and wear-free movement. In this aspect the EM27/SUN is more stable than the HR125 high-resolution FTS, which suffers from wear because of the use of friction bearings on the moving retroreflector. Over time this leads to shear misalignment and requires regular realignment . The gimbal-mounted retroreflectors move a geometrical distance of 0.45 cm, leading to an optical path difference of 1.8 cm which corresponds to a spectral resolution of 0.5 cm-1.

In a first pre-processing step, a solar brightness fluctuation correction is performed similarly to . Furthermore, the recorded interferograms are Fourier transformed using the Norton–Beer medium apodization function . This apodization is useful for reducing sidelobes around the spectral lines, an undesired feature in low-resolution spectra, which would complicate the further analysis. A quality control, which filters interferograms with intensity fluctuations above 10 % and intensities below 10 % of the maximal signal range, is also applied.

In this work, spectra were analyzed utilizing PROFFIT Version 9.6, a nonlinear least-squares spectral fitting algorithm, which gives the user the opportunity to provide the measured ILS as an input parameter, an option chosen for this study . This code is in wide use and has been thoroughly tested in the past for the HR125 as well as the EM27/SUN, e.g., , , , and . Due to the low resolution of the EM27/SUN, the atmospheric spectra were fitted by scaling of a priori trace gas profiles, although PROFFIT has the ability to perform a full profile retrieval . As the source of the a priori profiles, the TCCON daily profiles introduced in Sect.  are utilized to be consistent with the TCCON analysis. Also for the daily temperature and pressure profiles, the approach from TCCON was adopted, using NCEP model data together with on-site ground pressure data from a meteorological tall tower (http://www.imk.kit.edu/messmast/; last access: 4 March 2019).

For the evaluation of the O2 column the 7765–8005 cm-1 spectral region is used, which is also applied in the TCCON analysis . For CO2 we combine the two spectral windows used by TCCON into one larger window ranging from 6173 to 6390 cm-1. CH4 is evaluated in the 5897–6145 cm-1 spectral domain. For H2O the 8353–8463 cm-1 region is used. This differs from TCCON, which deploys several narrow spectral windows, a strategy which is more in line with high-resolution spectral observations. For consistency reasons, and to reference the results to the WMO scale, the EM27/SUN retrieval also performs a post-processing. The AICFs from TCCON are adopted, and similarly to , an airmass dependency correction is performed, although other numerical values for the correction parameters are used. Details can be found in and .

Accurate knowledge of the real ILS of a spectrometer is extremely important because errors in the ILS lead to systematic errors in the trace gas retrieval. For this reason regular ILS measurements were performed from the beginning of this study 4 years ago to detect possible misalignments and alignment drifts. The source of a de-adjustment is mostly mechanical shock, due to, e.g., impacts or vibrations especially due to transportation of the instruments. For the analysis of the measured data, version 14.5 of retrieval software LINEFIT is used. Due to the fact that the EM27/SUN is equipped with a circular field stop aperture, the ILS is nearly nominal. Therefore, to keep the treatment concise, we use the simple two-parameter ILS model offered by LINEFIT. A detailed description of the ILS analysis is given in . The time series of the ILS measurements is shown in Fig. ; the modulation efficiency (ME) at maximum optical path difference (MOPD) ranges between 0.9835 and 0.9896, with a mean value of 0.9862 and a standard deviation of 0.0015. The phase error is close to zero for the whole time series, with a mean value of 0.0019±0.0018. This modulation efficiency is significantly different from nominal, which is surprising, as great care was taken to align the instrument. Therefore open path measurements were also performed for the HR125 at a resolution of 0.5 cm-1 to investigate whether this method shows a bias. For this small optical path difference, the alignment of the HR125 should be very close to nominal. However, the LINEFIT analysis shows a ME of 0.9824 at MOPD. From this result it is concluded that this method shows an overall low bias of around 1.5 %–2 %, probably due to a slight underestimate of the pressure-broadening parameters of H2O in the selected spectral region.

There is no overall trend apparent in the time series; the remaining differences in the modulation efficiency are probably due to the remaining uncertainty of the measurement technique. As is indicated by the more frequent measurements in 2017, there is also no seasonality in the results of the open path measurements. It should be noted that the measurement routine was refined in the course of this work. In particular, in the beginning (2014) it was assumed that the inside of the EM27/SUN is free of water vapor, so the instrument was not vented during the lamp measurements. However, sensitivity studies as presented in revealed that the influence of the water vapor column inside the spectrometer can not always be neglected. After this discovery the instrument was vented during the open path measurements. This is why the 2014 calculations show larger scatter, as here the amount of water vapor inside the spectrometer is not known. For this analysis it was assumed that also for the 2014 measurements the total pressure inside the spectrometer is the same as of the surrounding air, which is a sensible assumption as the spectrometer is not evacuated. This also explains why the deviations become smaller in 2017. A further test to verify the stability of the instrument is the Xair parameter, which is the surface pressure divided by the measured column of air. This test will be shown in Sect. .

The grey lines in Fig.  denote transportation of the spectrometer over longer distances for field campaigns in Berlin (northeastern Germany), Oldenburg (northern Germany) and Paris (France) and for maintenance at Bruker Optics. Note that no realignment of the interferometer was performed during this maintenance. Only the reference HeNe laser was exchanged due to sampling instabilities during interferogram recordings. More specifically, the laser wavelength was unstable, resulting in a corruption of parts of the measured spectra. Later in 2016 and 2017 this instrument was not used for campaigns since it has been chosen as the reference EM27/SUN for comparison measurements next to the HR125 spectrometer in order to take measurements at Karlsruhe as continuously as possible. The instrument was not realigned during the whole comparison study.

An error estimation for the open path measurements is given in Table . For the temperature and pressure error, the stated accuracies of the data logger manufacturer were used. For the other potential error sources reasonable estimates were made. The total error, given by the root-squares sum of the individual errors, is 0.29 % in ME amplitude, consisting of several errors of approximately the same magnitude.

In this section the total column measurements from the EM27/SUN are compared to the reference HR125 spectrometer. For the measurements, the EM27/SUN was moved to a terrace on the top floor of the IMK-ASF, building 435 KIT CN (49.094∘ N, 8.436∘ E; 133 m a.s.l.) on a daily basis if weather conditions were favorable. The spectrometer was moved from the lab on the fourth floor to the roof terrace on the seventh floor, thus being exposed to mechanical stress. The instrument was coarsely oriented north, without effort for levelling. If further orientation was needed, the spectrometer was manually rotated so that the solar beam was centered onto the entrance window. The CamTracker program was then able to track the sun. The spectrometer was operated at ambient temperatures. During summer, the spectrometer heated up to temperatures above 40 ∘C. In order to protect the electronics from the heat, a sun cover for the EM27/SUN was built, which reduced the temperatures inside the spectrometer by about 10 ∘C. In winter the temperatures were as low as -4 ∘C at the start of measurements. Double-sided interferograms with 0.5 cm-1 resolution were recorded. With 10 scans and a scanner velocity of 10 kHz, one measurement takes about 58 s. For precise time recording, a GPS receiver was used.

The full time series from March 2014 to November 2017 is shown in Fig.  for the three data sets. For better visibility only coincident data points measured within 1 min between EM27/SUN and the other data sets are shown. There are 8349 paired measurements between EM27/SUN and TCCON and 4624 between EM27/SUN and HR125 LR; in total there are 50 550 EM27/SUN and 25 361 TCCON measurements.

All gases show a pronounced seasonal cycle, where the variability in water vapor is strongest with values below 1×1026 molec. m-2 in winter and up to 14×1026 molec. m-2 in summer. Furthermore, the seasonal cycle of water vapor is shifted with respect to the other species. Another feature seen is that there is an offset in the EM27/SUN (red squares) and HR125 LR (blue squares) total column data with respect to the TCCON data (black squares). The occurrence of a systematic bias when reducing the spectral resolution has been observed by several investigators . The observed offset between EM27/SUN and HR125 LR measurements is smaller. The remaining difference can be attributed to the different measurement heights of the HR125 (112 m) and EM27/SUN (133 m). For a quantitative analysis we do not utilize the total column measurements, but rather use the XGas, as in this representation systematic errors, e.g., ILS errors, timing errors, tracking errors and nonlinearities, mostly cancel out. Furthermore, the height dependence largely cancels out in this representation. The comparison will be presented in the following sections.

First, a sensitivity study is provided demonstrating the effect of changes in the ILS on the gas retrieval. For this 1 h of measurements around solar noon on 1 August 2016 and 15 February 2017, corresponding to solar elevation angles (SEAs) of 60 and 30∘, were analyzed with artificially altered ILS values. The results are shown in Table . An increase of 1 % in the modulation efficiency leads to a decrease of 0.35 % (0.37 %) in the retrieved O2 column, 0.31 % (0.31 %) in H2O, 0.26 % (0.28 %) in CH4 and 0.50 % (0.57 %) in CO2 for an SEA of 60∘ (30∘). So the change in the retrieved total column is not alike, but a unique characteristic of each species, and also slightly airmass-dependent. As the decrease in the CO2 column is larger than the decrease in the O2 column, XCO2 decreases with an increasing ME, 0.16 % (0.19 %) for 1 % ILS increase, whereas XCH4 increases 0.10 % (0.09 %). This is opposed to prior studies reporting an increase in XCO2 and decrease in XCH4 for an increase in the modulation efficiency, albeit in agreement with the findings from for the HR125 spectrometer, reporting that a change in the modulation efficiency results in a larger relative decrease in the CO2 column than in the O2 column.

In this section the column-averaged amount of dry air (Xair) is investigated. This quantity is a sensitive test of the stability of a spectrometer because for Xair there is no compensation of possible instrumental problems, in contrast to the DMFs, where errors can partially cancel out. Xair compares the measured oxygen column (VCO2) with surface pressure measurements (PS): Xair=0.2095VCO2⋅μ‾⋅PSg-VCH2O⋅μH2O,

Here μ‾ and μH2O denote the molecular masses of dry air and water vapor, respectively, g is the column-averaged gravitational acceleration and VCH2O is the total column of water vapor. The correction with VCH2O is necessary as the surface pressure instruments measure the pressure of the total air column, including water vapor. For an ideal measurement and retrieval with accurate O2 and H2O spectroscopy, as well as accurate surface pressure, Xair would be 1. However, due to insufficiencies in the oxygen spectroscopy, this value is not obtained. For TCCON measurements Xair is typically ∼0.98 . For the EM27/SUN prior studies showed a factor of ∼0.97 . Large deviations (∼1 %) from these values indicate severe problems, e.g., errors with the surface pressure, pointing errors, timing errors or changes in the optical alignment of the instrument. As mentioned in Sect. , here Xair is used to check whether the small changes in the modulation efficiency indicated by the open path measurements are due to actual alterations in the alignment of the EM27/SUN or due to the residual uncertainty of the calibration method.

Panel (a) of Fig.  shows the Xair time series of TCCON, the EM27/SUN and HR125 LR. For clarity, only coincident data points that were measured within 1 min between the different data sets are shown. Grey areas denote periods where the EM27/SUN was moved over long distances for campaigns or maintenance. The absolute values of Xair differ for the data sets, with 0.9805±0.0012 for TCCON, 0.9669±0.0010 for the EM27/SUN and 0.9670±0.0011 for HR125 LR. The difference between the EM27/SUN and the HR125 LR is within 1σ precision. The difference between the EM27/SUN and TCCON data set, which is commonly observed as previously noted, is a consequence of the different resolution together with the different retrieval algorithm . It can be seen that all data sets exhibit a seasonal variability, which is more prominent in the TCCON data, as can also be seen from the higher standard deviation. From this higher variability it can be concluded that the airmass dependency in the official TCCON O2 retrieval is higher than for the PROFFIT retrieval on reduced-resolution TCCON measurements, a finding also observed by between the TCCON retrieval and the PROFFIT retrieval at full resolution. For the PROFFIT retrieval, it is suspected that part of the variability stems from insufficiencies in the utilized HITRAN 2008 H2O linelist. It was reported by that in the 8000–9200 cm-1 region, line intensities are low by up to 20 % compared to other wavenumber regions. This in return will lead to a systematic overestimation of the water column, which also affects Xair. To test the sensitivity of Xair with respect to the measured H2O column, in panel (b) of Fig.  the original EM27/SUN time series is compared to a data set where the H2O column is artificially reduced by 20 %. This approach is further justified by a study from the Romanian National Institute for Research and Development in Optoelectronics (INOE) conducted in 2017, where we compared total column amounts of water vapor from an EM27/SUN and a radiometer. We found that the EM27/SUN values were systematically higher by 20 %. And indeed, the standard deviation, which is here used as a measure of the seasonal variability, of the modified time series (0.0009) is lower when compared to the original time series (0.0010).

There are no obvious steps and there is no significant drift between the EM27/SUN and the HR125 LR data sets, so that it can be concluded that the EM27/SUN is stable during the complete course of the over 3-year long comparison, and differences seen in the modulation efficiency are introduced by the remaining uncertainty in the calibration method.

In Fig.  XCO2 time series of the three data sets are shown together with the offsets between the data sets. The general characteristics of the data sets are similar. The yearly increase in XCO2 due to anthropogenic emissions of about 2 ppmv can be seen as well as the seasonal cycle with a decrease in XCO2 of approximately 10 ppmv during summer due to photosynthesis, characteristic of mid-latitude stations. Despite these agreements in the general trend, there are also differences between the data sets. Relative to the TCCON data the EM27/SUN and the HR125 LR data sets are biased high (0.98 % and 0.84 %, respectively). The scaling factors are calculated by taking the mean of all individual coincident point ratios (EM27/SUN/TCCON and EM27/SUN/HR125 LR). Together with these ratios a standard deviation is also derived; see Table . A high bias was also observed by , albeit with smaller absolute differences. This is due to the fact that (1) in the Gisi et al. paper the TCCON data were retrieved with an earlier version of GFIT (GGG2012) and (2) after the publication of the Frey et al. paper the Karlsruhe TCCON data were reprocessed with a customized GFIT retrieval accounting for baseline variations . The offset between EM27/SUN and TCCON shows a seasonal variability. The reasons for this are mainly the differences in airmass correction, averaging kernels and retrieval algorithm. These effects have been investigated before . The averaging kernels of the EM27/SUN have been previously presented and compared to TCCON in a study by .

It has to be noted that the level of uncertainty for XCO2 is significantly higher between COCCON and TCCON compared to the internal EM27/SUN consistency. According to Table , a current calibration uncertainty with respect to TCCON of 0.6 ppmv is estimated.

For the long-term stability of the EM27/SUN the focus lies on the comparison with the HR125 LR data set, where the above-mentioned differences cancel out. There is a small offset between the two data sets, resulting in a calibration factor of 1.0014, which is constant over time in the analyzed time period. To test this assumption a linear fit was applied to the XCO2 ratios; see panel (b) of Fig. . In Table  the slope coefficient is depicted. For both comparisons the yearly trend in the ratio is well within the 1σ precision (0.44 ppmv) of the data set. In absolute numbers the slope per year is ≈-0.02 ppmv for both ratios, or a drift smaller than 0.1 ppmv over the whole comparison period of around 3.5 years.

Figure  shows the data sets in a different representation. In panel (a) the EM27/SUN is compared to the HR125 LR; the colorbar indicates the date of measurement and the dashed line is the 1:1 line. It can be seen that there is no trend in the data apart from the overall increase in time due to anthropogenic emissions. In panel (b) the EM27/SUN is compared to the TCCON data set; the colorbar shows the SEA. This representation is chosen so that the remaining airmass dependency of the ratio can be seen. It is also interesting to note that omitting the TCCON AICF for our analysis would move the data set significantly closer to the 1:1 line. The scaling factor would change from 1.0098 to 0.9995. As this finding is not true for XCH4 and is probably coincidental, we maintain the AICF.

Figure  shows the XCH4 time series of the different data sets. As for XCO2, the general features are in agreement for all data sets. There is a slight annual increase of about 10 ppbv. Also, there is a seasonal cycle with a variability of ≈30 ppbv; however, compared to XCO2 the interannual seasonality strength and phase vary significantly between the years due to the many different variable sinks and sources of methane, e.g., . The differences between the data sets largely resemble the differences observed for XCO2. The bias between EM27/SUN and TCCON is 0.72 %; see Table . This bias is close to the bias observed by , 0.75 %, where they used the GGG software package for the analysis of EM27/SUN spectra. Although a single bias is reported, as was observed for XCO2 the offset is not constant, but rather shows a seasonality. The calibration uncertainty between COCCON and TCCON is estimated to amount to 5 ppbv for XCH4; see Table . The retrievals between EM27/SUN and HR125 LR agree within 1σ precision (0.9997±0.0008). Panel (a) of Fig.  shows the ratio between EM27/SUN and HR125 LR color-coded with the observation date. As for XCO2, no trend is apparent. An explicit linear fit to the XCH4 ratio produces a slope coefficient of 0.0001, 1 order of magnitude smaller than the 1σ precision of the ratio (0.0008).

An interesting feature is observed in the ratio between EM27/SUN and TCCON data sets; see panel (b) of Fig. . In general the pattern is similar to that of XCO2, with a slight dependence on the SEA. The ratio in the figure is color-coded with the date of observation rather than the SEA. It can be seen that for 1 and 14 March 2016 (shaded area in Fig. ), the XCH4 ratio significantly differs from the other observations. Previous work by has shown that stratospheric intrusion, caused for example by the subsidence of the polar vortex, has a different effect on MIR and NIR retrievals, even when using the same a priori profile. This is due to the differing sensitivity of the retrievals with respect to altitude. Therefore, differences between the true atmospheric profile and the assumed a priori profiles on these days could cause the differences seen. This effect will also lead to larger differences between EM27/SUN and TCCON XCH4 because of the different impact on the retrieved columns due to differing sensitivities. A spread of the polar vortex to mid-latitudes could lead to significantly altered CH4 profiles compared to the a priori profiles, explaining the observed differences in the XCH4 ratio.

Figure a shows N2O data from the Microwave Limb Sounder (MLS) on the Aura satellite for several days in February and March 2016 on the 490 K potential temperature level, corresponding to a height of approximately 18 km. N2O is chosen because it serves as a tracer for the position of the polar vortex. Indeed, it seems that beginning in March 2016 the polar vortex stretches out to mid-latitudes. To further test this hypothesis, in Fig. b independent NDACC CH4 profiles from the Jungfraujoch station in 2016 are shown. The station is situated approximately 270 km south of Karlsruhe with a station height of 3580 m. For dates without measurements, the data were interpolated using a weighted average. The dotted black lines denote 1 and 14 March 2016, the dates on which the XCH4 ratio between EM27/SUN and TCCON shows an anomaly. The changed profile shape during that period is clearly visible. As this station is south of Karlsruhe, it is expected that also for Karlsruhe the CH4 profile will show considerable downwelling, explaining the observed anomaly in the XCH4 ratio.

The measurement of the ILS is a valuable diagnostic for detecting misalignments of spectrometers. Differences in the ILS of the EM27/SUN spectrometers due to misalignment can lead to biases in the data products between the instruments. Here the spread of ILS values of all EM27/SUN spectrometers that were checked at KIT in the past 4 years is estimated. Numerical values are given in Table ; the results are shown in Fig. . The black square denotes an ILS measurement of the HR125 spectrometer, also with 1.8 cm MOPD. This test was done to check for an absolute offset of our method. The HR125 would be expected to show an ideal ILS for short optical path differences, but a value of 0.9824 was obtained. From this measurement it is concluded that our method shows an absolute offset and that values between 0.98 and 0.99 are desired.

In general, the agreement between the 30 tested EM27/SUN is good, with an ensemble mean of 0.9851±0.0078, which does not differ significantly from the value obtained for the HR125, but there are exceptions. Instrument SN 44 was checked at KIT only after an upgrade with the second channel was performed at Bruker Optics. Before realignment, the instrument showed a very low ME value of 0.9374. A realignment of the instrument enhanced the ME to 0.9714. This is still significantly low compared to the EM27/SUN ensemble mean, but the difference was drastically reduced. The second instrument showing strong deviations from the ensemble mean is SN76 with an ILS of 1.0160, the only instrument showing overmodulation. The ILS was even higher (1.0350) when the first ILS measurements were performed. Due to our findings, the manufacturer exchanged the beamsplitter, which reduced the overmodulation, but it partly remained. In the meantime it was recognized that the cause of the error was the manufacturer during assembly of the instrument forgetting to insert the foreseen spacer to achieve the correct detector position with respect to the beamsplitter. The beamsplitter is coated, and the coating is applied on both sides of the beamsplitter over half the surface area. If the optical axis of the detector element coincides with the transition region of the two coating areas, detrimental effects occur. For this reason the detector element needs to be raised with respect to the interferometer. This problem occurred for instrument SN 77, but there it was diagnosed and corrected by KIT (ILS before lifting: 1.0340; ILS after correction: 0.9855).

The above-mentioned problems show the benefit of the calibration routine at KIT. Imperfections from nonideal alignments were diagnosed and corrected. Also, other detrimental effects, e.g., double-passing, channeling, nonlinearity issues, solar tracker problems, inaccurate positioning of the second detector, or camera issues, were corrected or minimized for a number of instruments. Finally, we checked whether the linear interpolation method suppressing sampling ghosts was activated.

After checking the alignment and performing lamp measurements, side-by-side solar calibration measurements were performed on the terrace on top of the KIT-IMK office building with each spectrometer with respect to the reference EM27/SUN and also a co-located HR125 spectrometer. Calibration measurements started in June 2014 and are ongoing, if new spectrometers arrive for testing. The aim is to have at least 1 day of comparison measurements so that the spectrometers can be scaled to TCCON via the reference EM27/SUN. TCCON is extensively compared to measurements on the WMO scale. Dates of the comparison measurements for the different spectrometers as well as number of coincident measurements are given in Table . On 21 January 2016, our reference spectrometer suffered from laser sampling errors after approximately 1 h of measurements. Therefore the number of coincident measurements for SN62 and 63 that were checked on this date are sparse. A typical calibration day is depicted in Fig. .

The calibration factors and standard deviations for all instruments with respect to the reference spectrometer are also depicted in Table . Calibration factors and standard deviations were obtained using the methods described in Sect. . The calibration factors are close to nominal for all species and instruments. For XCO2 the ensemble mean is high compared to the reference EM27/SUN, with a mean calibration factor of 0.9993 and a standard deviation of 0.0007. In Fig.  histograms of the calibration factor distributions are depicted for XCO2, XCH4, and O2, respectively. The histograms are not conspicuous.

Applying the mean calibration factor to all calculated calibration factors centers the data around the ensemble mean. As an estimate for the spread of the calibration factors 1nΣ|XGas factor-1|, we arrive at an average bias between the instruments of 0.20 ppmv. From Table  we can also calculate an average standard deviation 1nΣ|σ| of 0.13 ppmv. For XCH4 the ensemble mean is closer to the reference EM27/SUN (0.9997±0.0006) as compared to XCO2. From this results an average bias of 0.8 ppbv. The average standard deviation is 0.6 ppbv. These values are comparable to results obtained in a study from . They checked the intercomparability of the four United States TCCON sites using an EM27/SUN as a traveling standard. They report average biases of 0.11 ppmv for XCO2 and 1.2 ppbv for XCH4; for the average standard deviations they obtain 0.34 ppmv (XCO2) and 1.8 ppbv (XCH4). It has to be noted that for the study only data within ±2 h of local noon were taken into account, whereas here no constraints regarding the time of measurement were applied. As another sensitive test the O2 total column calibration factors are given. In contrast to XCO2 and XCH4, there is no canceling of errors in this quantity. The ensemble mean is slightly high compared to the reference EM27/SUN (0.9999±0.0014). The average bias is 0.11 % O2 with an average standard deviation of 0.04 % O2.

Note that for our setup this average bias is a worst case scenario. The bias only applies if no calibration factor is used in the subsequent analysis. The strength of this calibration routine is that the computed calibration factors can be used, thereby significantly lowering the bias between different EM27/SUN spectrometers. The remaining bias is then given by the long-term drift of the individual instrument (see Sect.  and ) and sudden alignment drifts due to mechanical strain from, e.g., transport and campaign use. To estimate this drift, we utilize the calibration factors before and after the Berlin campaign performed in 2014. There the drifts between five instruments were below 0.005 % XCO2 and 0.035 % XCH4 .

Ideally, we would expect identical calibration factors as we took the real ILS of the instruments into account. As this is not the case, we investigate whether the remaining differences can be attributed to the uncertainties of the open path measurements, which are summarized in Table . The results are incorporated into Fig. . Panel (a) shows the correlation between O2 and XCO2 calibration factors. Black squares denote the empirical calibration factors derived from the side-by-side measurements. The red squares show calculated calibration factors based on the ME uncertainty budget. The dashed red line is a linear fit through the calculated factors. About half the measured empirical factors are within the bounds of the factors derived from the ME error budget. Furthermore, the slopes of the calculated and empirical factors are in good agreement, confirming that the ME uncertainty is contributing to the uncertainty of the calibration factors. The other contributions for this uncertainty are due to a superposition of various small device-specific imperfections. Panel (b) of Fig.  shows the correlation between O2 and XCH4 calibration factors. The findings mentioned above for the O2 and XCO2 correlation also hold true here.