NASA's Orbiting Carbon Observatory-2 (OCO-2) has been measuring carbon dioxide column-averaged dry-air mole fraction, X CO ₂ , in the Earth's atmosphere for over 2 years. In this paper, we describe the comparisons between the first major release of the OCO-2 retrieval algorithm (B7r) and X CO ₂ from OCO-2's primary ground-based validation network: the Total Carbon Column Observing Network (TCCON). The OCO-2 X CO ₂ retrievals, after filtering and bias correction, agree well when aggregated around and coincident with TCCON data in nadir, glint, and target observation modes, with absolute median differences less than 0.4 ppm and RMS differences less than 1.5 ppm. After bias correction, residual biases remain. These biases appear to depend on latitude, surface properties, and scattering by aerosols. It is thus crucial to continue measurement comparisons with TCCON to monitor and evaluate the OCO-2 X CO ₂ data quality throughout its mission.

Since September 2014, NASA's Orbiting Carbon Observatory-2 (OCO-2) satellite has been taking measurements of reflected solar spectra and using them to infer atmospheric carbon dioxide levels. This work provides details of the OCO-2 retrieval algorithm, versions 7 and 8, used to derive the column-averaged dry air mole fraction of atmospheric CO₂ (XCO₂) for the roughly 100 000 cloud-free measurements recorded by OCO-2 each day. The algorithm is based on the Atmospheric Carbon Observations from Space (ACOS) algorithm which has been applied to observations from the Greenhouse Gases Observing SATellite (GOSAT) since 2009, with modifications necessary for OCO-2. Because high accuracy, better than 0.25 %, is required in order to accurately infer carbon sources and sinks from XCO₂, significant errors and regional-scale biases in the measurements must be minimized. We discuss efforts to filter out poor-quality measurements, and correct the remaining good-quality measurements to minimize regional-scale biases. Updates to the radiance calibration and retrieval forward model in version 8 have improved many aspects of the retrieved data products. The version 8 data appear to have reduced regional-scale biases overall, and demonstrate a clear improvement over the version 7 data. In particular, error variance with respect to TCCON was reduced by 20 % over land and 40 % over ocean between versions 7 and 8, and nadir and glint observations over land are now more consistent. While this paper documents the significant improvements in the ACOS algorithm, it will continue to evolve and improve as the CO₂ data record continues to expand.

In a 3.5-year long study, the long-term performance of a mobile, solar absorption Bruker EM27/SUN spectrometer, used for greenhouse gas observations, is checked with respect to a co-located reference Bruker IFS 125HR spectrometer, which is part of the Total Carbon Column Observing Network (TCCON). We find that the EM27/SUN is stable on timescales of several years; the drift per year between the EM27/SUN and the official TCCON product is 0.02 ppmv for XCO₂ and 0.9 ppbv for XCH₄, which is within the 1σ precision of the comparison, 0.6 ppmv for XCO₂ and 4.3 ppbv for XCH₄. The bias between the two data sets is 3.9 ppmv for XCO₂ and 13.0 ppbv for XCH₄. In order to avoid sensitivity-dependent artifacts, the EM27/SUN is also compared to a truncated IFS 125HR data set derived from full-resolution TCCON interferograms. The drift is 0.02 ppmv for XCO₂ and 0.2 ppbv for XCH₄ per year, with 1σ precisions of 0.4 ppmv for XCO₂ and 1.4 ppbv for XCH₄, respectively. The bias between the two data sets is 0.6 ppmv for XCO₂ and 0.5 ppbv for XCH₄. With the presented long-term stability, the EM27/SUN qualifies as an useful supplement to the existing TCCON network in remote areas. To achieve consistent performance, such an extension requires careful testing of any spectrometers involved by application of common quality assurance measures. One major aim of the COllaborative Carbon Column Observing Network (COCCON) infrastructure is to provide these services to all EM27/SUN operators. In the framework of COCCON development, the performance of an ensemble of 30 EM27/SUN spectrometers was tested and found to be very uniform, enhanced by the centralized inspection performed at the Karlsruhe Institute of Technology prior to deployment. Taking into account measured instrumental line shape parameters for each spectrometer, the resulting average bias across the ensemble with respect to the reference EM27/SUN used in the long-term study in XCO₂ is 0.20 ppmv, while it is 0.8 ppbv for XCH₄. The average standard deviation of the ensemble is 0.13 ppmv for XCO₂ and 0.6 ppbv for XCH₄. In addition to the robust metric based on absolute differences, we calculate the standard deviation among the empirical calibration factors. The resulting 2σ uncertainty is 0.6 ppmv for XCO₂ and 2.2 ppbv for XCH₄. As indicated by the executed long-term study on one device presented here, the remaining empirical calibration factor deduced for each individual instrument can be assumed constant over time. Therefore the application of these empirical factors is expected to further improve the EM27/SUN network conformity beyond the scatter among the empirical calibration factors reported above.

Five portable Bruker EM27/SUN FTIR (Fourier transform infrared) spectrometers have been used for the accurate and precise observation of column-averaged abundances of CO₂ and CH₄ around the major city Berlin. In the work by Frey et al. (2015), a calibration procedure is developed and applied to the set of spectrometers used for the Berlin campaign. Here, we describe the observational setup of the campaign and aspects of the data analysis, and we present the recorded time series of XCH₄ and XCO₂. We demonstrate that the CO₂ emissions of Berlin can be clearly identified in the observations. A simple dispersion model is applied which indicates a total strength of the Berlin source of about 0.8 t CO₂ s⁻¹. In the Supplement of this work, we provide the measured data set and auxiliary data. We hope that the model community will exploit this unique data set for state-of-the art inversion studies of CO₂ and CH₄ sources in the Berlin area.

All measurements of XCO₂ from space have systematic errors. To reduce a large fraction of these errors, a bias correction is applied to XCO₂ retrieved from GOSAT and OCO-2 spectra using the ACOS retrieval algorithm. The bias correction uses, among other parameters, the surface pressure difference between the retrieval and the meteorological reanalysis. Relative errors in the surface pressure estimates, however, propagate nearly 1:1 into relative errors in bias-corrected XCO₂. For OCO-2, small errors in the knowledge of the pointing of the observatory (up to ∼ 130 arcsec) introduce a bias in XCO₂ in regions with rough topography. Erroneous surface pressure estimates are also caused by a coding error in ACOS version 8, sampling meteorological analyses at wrong times (up to 3 h after the overpass time). Here, we derive new geolocations for OCO-2's eight footprints and show how using improved knowledge of surface pressure estimates in the bias correction reduces errors in OCO-2's v9 XCO₂ data.

The Total Carbon Column Observing Network (TCCON) measures column-average mole fractions of several greenhouse gases (GHGs), beginning in 2004, from over 30 current or past measurement sites around the world using solar absorption spectroscopy in the near-infrared (near-IR) region. TCCON GHG data have been used extensively for multiple purposes, including in studies of the carbon cycle and anthropogenic emissions, as well as to validate and improve observations from space-based sensors. Here, we describe an update to the retrieval algorithm used to process the TCCON near-IR solar spectra and to generate the associated data products. This version, called GGG2020, was initially released in April 2022. It includes updates and improvements to all steps of the retrieval, including but not limited to the conversion of the original interferograms into spectra, the spectroscopic information used in the column retrieval, post hoc air mass dependence correction, and scaling to align with the calibration scales of in situ GHG measurements. All TCCON data are available through https://tccondata.org/ (last access: 22 April 2024) and are hosted on CaltechDATA (https://data.caltech.edu/, last access: 22 April 2024). Each TCCON site has a unique DOI for its data record. An archive of all the sites' data is also available with the DOI https://doi.org/10.14291/TCCON.GGG2020 (Total Carbon Column Observing Network (TCCON) Team, 2022). The hosted files are updated approximately monthly, and TCCON sites are required to deliver data to the archive no later than 1 year after acquisition. Full details of data locations are provided in the “Code and data availability” section.