In this study, we present column-averaged dry-air mole fractions of
The concentrations of the most important anthropogenic greenhouse gases (GHGs), carbon dioxide (
Satellites like the Greenhouse Gases Observing Satellite (GOSAT)
Recently, in an effort to further improve the global coverage of ground-based observations, the COllaborative Carbon Column Observing Network (COCCON) was established
In 2015, we installed an EM27/SUN spectrometer of the COCCON network at the Gobabeb Namib Research Institute in Namibia (23.561
© Google Earth image (map data: Google, Maxar technologies) of the measurement site at Gobabeb, Namibia. The blue pin denotes the position of the COCCON instrument. The yellow points show the positions of the GOSAT target observation points. A black circle with a radius of 10 km has been drawn around the COCCON site for visual reference. The inset in the upper right corner shows the EM27/SUN spectrometer at Gobabeb.
Global map showing the COCCON Gobabeb, TCCON Réunion Island and Lauder sites used in this study.
The EM27/SUN spectrometer as used by COCCON has been described in great detail in the works of
The retrieved total column abundances of the trace gases are converted into column-averaged dry-air mole fractions (DMFs), where the DMF of a gas is denoted X
The data analysis is performed differently from
This table summarizes the quality filters applied in the FORTRAN-based preprocessing tool.
For the retrieval of the EM27/SUN spectra, we do not use the PROFFIT 9.6 retrieval algorithm
We use the spectroscopic line lists and retrieval windows as described in
Measurement procedures and data analysis at both sites follow TCCON protocol
A detailed description of the GOSAT instrumental features and data analysis is given in
The CAMS model has been described previously in great detail, e.g.,
ILS measurements were carried out seven times since December 2014. This is depicted in Fig.
Time series of the modulation efficiency at MOPD of the EM27/SUN used in this study. ILS measurements were performed during periods when the instrument was in Karlsruhe for maintenance or detector upgrade. Yellow areas denote measurement periods in Gobabeb. The black bar denotes the time of the detector upgrade.
Side-by-side measurements between the reference EM27/SUN and the instrument deployed in Namibia performed between November 2015 and March 2016 in Karlsruhe. From left to right, the panels show correlation plots for
Between November 2015 and March 2016, side-by-side comparison measurements with the reference EM27/SUN were conducted on 8 d to derive calibration factors for the different trace gases for this spectrometer and thereby removing possible instrument-dependent biases. Some data had to be filtered out for different reasons. Because most measurements were performed during winter, the solar elevation was low, which sometimes led to a partially obstructed view due to railings and a metal frame on the terrace where the observations took place. In the morning, the first measurements were omitted due to unusually high scatter caused by the quickly changing temperature of the helium–neon (HeNe) laser, which is not frequency stabilized as already reported by
Additional side-by-side measurements were performed in February and March 2018 after the instrument came back from Namibia as well as between November 2018 and February 2019 after the dual-channel upgrade and mirror exchange. The combined results are shown in Appendix
In order to investigate if the difference in the calibration factors is linked to the upgrade of the EM27/SUN in 2018, we average the ME at MOPD obtained from the ILS measurements before (0.982) and after (0.985) the upgrade. The ME increased by 0.3 %, which is within the uncertainty budget of 0.3 % using this method. Therefore, we conclude that the changes in the instrumental line shape due to the upgrade of the COCCON instrument might contribute to the slightly different scaling factors, but they are not the main reason for the changes.
For the subsequent analysis, only observations with SZAs not exceeding 80
Column-averaged dry-air mole fraction time series for
For
In this section, we compare the results obtained in Gobabeb with results from the TCCON stations at Réunion Island and Lauder. Although this is not a side-by-side comparison, Réunion Island as the second closest TCCON station is approximately 4000 km east of Gobabeb; this comparison will give us a measure of the feasibility of our results. The observations should be comparable qualitatively as the variation of
Column-averaged dry-air mole fraction daily mean time series for
Daily mean
Correlation plots between the COCCON Gobabeb and TCCON Réunion Island stations for
Correlation plots between the COCCON Gobabeb and TCCON Lauder stations for
In a next step, we show correlation plots for the COCCON site with respect to the TCCON sites for
This table presents the results of the comparison between the COCCON station in Gobabeb and the TCCON stations in Lauder and Réunion Island. Difference and SD are given as the mean difference and 1 standard deviation between the coincident daily TCCON and COCCON
In this section, we validate specific target mode observations from the GOSAT satellite around Gobabeb at three distinct points with different surface albedo properties against COCCON Gobabeb observations. Target mode measurements started in 2016 and are ongoing. The time series of the GOSAT observations is shown in Fig.
Column-averaged dry-air mole fraction daily mean time series for
For a quantitative analysis, we analyze coincident observations between GOSAT and COCCON. To make the datasets comparable, we correct for the influence of the different a priori profiles following
Correlation plots between coincident COCCON Gobabeb observations and GOSAT measurements over the gravel plains between 2016 and 2019. For this area, GOSAT only performed M-gain soundings (red dots). The solid red line is the best-fit line through all M-gain data points. The dotted black line is the 1 : 1 line. Error bars denote the 1
Correlation plots between coincident COCCON Gobabeb observations and GOSAT measurements over the COCCON site between 2016 and 2019. For this area, GOSAT performed M-gain (red dots) and H-gain (blue dots) soundings. The solid red line is the best-fit line through all M-gain data points, the solid blue line is the best-fit line through all H-gain data points and the solid black line is the best-fit line through all data points. The dotted black line is the 1 : 1 line. Error bars denote the 1
Same as Fig.
The number of coincident measurements with COCCON observations is 13, 18 and 20 for the three specific observation points and the chosen coincidence criterion is that COCCON observations were performed within 30 min of the satellite overpass. Of these coincident measurements, the vast majority occurred in 2016. The correlation graphs for these three target points are presented in Figs.
For the GOSAT observations over the gravel plains, only GOSAT M-gain soundings were performed. The spread of the dataset is relatively large, GOSAT is biased high and we derive a scaling factor with respect to the COCCON observations of 1.0062
This table presents the results of the comparison between the COCCON station in Namibia and the GOSAT M-gain and H-gain specific target observations. Bias and SD are given as the mean difference and 1 standard deviation between the coincident GOSAT and COCCON observations.
Although not always statistically significant at the 1
COCCON and CAMS
Column-averaged dry-air mole fraction daily mean time series for
As was shown in Sect.
This table presents the results of the comparison between the COCCON station in Namibia and the assimilated CAMS model data. Bias and SD are given as the mean difference and 1 standard deviation between the coincident hourly pooled local noon COCCON and CAMS
For
From the end of 2016 until the beginning of 2017, the
Global map showing OCO-2 assimilated CAMS a posteriori surface carbon fluxes for 16 February 2017 at 12:00 UTC.
In Fig.
NOAA HYSPLIT backward trajectory ensemble simulations on 16 February 2017. The endpoint of the backward trajectories is the COCCON Gobabeb station, 5000 m above ground level. The colors and symbols are used to make the different trajectories of the ensemble distinguishable.
In contrast, the backward trajectories for Réunion Island shown in Fig.
Same as Fig.
Same as Fig.
We present measurements from a new ground-based remote-sensing COCCON station in Namibia, the first FTIR site measuring GHGs on the African continent. We performed a thorough calibration scheme carried out in Karlsruhe in order to make the results traceable to TCCON (and thereby the WMO scale), including ILS measurements and side-by-side comparisons with a reference COCCON spectrometer. The results from Namibia show a typical global annual increase rate for both
To put our results in the broader geophysical context, we compare the COCCON Namibia results to measurements from the TCCON stations Réunion Island and Lauder. Given the fact that the stations are spatially far apart, the results are in good agreement. For
We show the usefulness of our station for satellite validation by comparing the COCCON results to GOSAT specific target mode observations at three points with different surface albedos close to or directly at the site. The satellite performed measurements with different gain settings. Ground-based validation of the different gain settings is difficult as very few sites worldwide have the necessary surface characteristics, further supporting the importance of this new station. We find a good agreement between GOSAT H-gain and COCCON observations within the 1
Then we evaluate the performance of the inversion-optimized CAMS model data against our ground-based COCCON data. For
With this work, we show the potential of the COCCON network for satellite validation and atmospheric transport model validation. We expect that the availability of additional COCCON sites in the near future will be a great asset for future satellite and model studies as they are easy to deploy. In the course of the ESA-funded COCCON PROCEEDS project, COCCON data from several sites will be made available via a web portal. We conclude that instruments from the COCCON network offer stable long-term records of GHGs in remote environments and can be used to close gaps in the global distribution of ground-based remote-sensing sites.
In Fig.
Same as Fig.
We examine several measurement days between Gobabeb and Réunion Island, 1 d each year, where data are available for both sites. The results for
Comparisons of intraday
COCCON data will be made available in the near future through a web portal hosted at the Karlsruhe Institute of Technology. TCCON Réunion Island and Lauder data can be obtained via
MMF, TB and FH planned the study. MMF and TB installed the COCCON station in Gobabeb with help from FH, FG and JG. RM, MH and PA performed the day to day COCCON measurements. MKS and MdM provided the TCCON Réunion Island data. DFP provided the TCCON Lauder data. DD provided the COCCON Gobabeb data. IM provided the GOSAT data. KS organized the GOSAT specific target mode observations over Gobabeb. MMF performed the data analysis and wrote the paper. All authors reviewed, edited and approved the paper.
The authors declare that they have no conflict of interest.
Publisher’s note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
CAMS data were generated using Copernicus Atmosphere Monitoring Service Information 2020. The authors acknowledge support by the ACROSS research infrastructure of the Helmholtz Association of German Research Centres (HGF). The authors acknowledge support by the MOSES research infrastructure of the HGF. The Réunion Island station is operated by the Royal Belgian Institute for Space Aeronomy with financial support since 2014 by the EU project ICOS-Inwire and the ministerial decree for ICOS (FR/35/IC1 to FR/35/IC5) and local activities were supported by LACy/UMR8105 – Université de La Réunion. The authors gratefully acknowledge the NOAA Air Resources Laboratory (ARL) for the provision of the HYSPLIT transport and dispersion model used in this publication.
This research has been supported by the European Space Agency (grant agreement no. ESA-IPL-POE-LG-cl-LE-2015-1129; ESA/contract no. 4000127561/19/INS, project FRM4GHG; ESA/contract no. 4000121212/17/I-EF, project COCCON-PROCEEDS; ESA/contract no. 4000121212/17/I-EF CCN1, project COCCON-PROCEEDS II; and ESA/contract no. 4000128426/19/NL/FF/ab, project QA4EO).The article processing charges for this open-access publication were covered by the Karlsruhe Institute of Technology (KIT).
This paper was edited by Ilse Aben and reviewed by two anonymous referees.