Abstract. 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.

Abstract. We use 2009-2011 space-borne methane observations from the Greenhouse Gases Observing SATellite (GOSAT) to estimate global and North American methane emissions with 4 • × 5 • and up to 50 km × 50 km spatial resolution, respectively. GEOS-Chem and GOSAT data are first evaluated with atmospheric methane observations from surface and tower networks (NOAA/ESRL, TCCON) and aircraft (NOAA/ESRL, HIPPO), using the GEOS-Chem chemical transport model as a platform to facilitate comparison of GOSAT with in situ data. This identifies a high-latitude bias between the GOSAT data and GEOS-Chem that we correct via quadratic regression. Our global adjoint-based inversion yields a total methane source of 539 Tg a −1 with some important regional corrections to the EDGARv4.2 inventory used as a prior. Results serve as dynamic boundary conditions for an analytical inversion of North American methane emissions using radial basis functions to achieve high resolution of large sources and provide error characterization. We infer a US anthropogenic methane source of 40.2-42.7 Tg a −1 , as compared to 24.9-27.0 Tg a −1 in the EDGAR and EPA bottom-up inventories, and 30.0-44.5 Tg a −1 in recent inverse studies. Our estimate is supported by independent surface and aircraft data and by previous inverse studies for California. We find that the emissions are highest in the southern-central US, the Central Valley of California, and Florida wetlands; large isolated point sources such as the US Four Corners also contribute. Using prior information on source locations, we attribute 29-44 % of US anthropogenic methane emissions to livestock, 22-31 % to oil/gas, Published by Copernicus Publications on behalf of the European Geosciences Union.

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 XCO 2 and 0.9 ppbv for XCH 4 , which is within the 1σ precision of the comparison, 0.6 ppmv for XCO 2 and 4.3 ppbv for XCH 4 . The bias between the two data sets is 3.9 ppmv for XCO 2 and 13.0 ppbv for XCH 4 . 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 XCO 2 and 0.2 ppbv for XCH 4 per year, with 1σ precisions of 0.4 ppmv for XCO 2 and 1.4 ppbv for XCH 4 , respectively. The bias between the two data sets is 0.6 ppmv for XCO 2 and 0.5 ppbv for XCH 4 . 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 COC-CON 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 XCO 2 is 0.20 ppmv, while it is 0.8 ppbv for XCH 4 . The average standard deviation of the ensemble is 0.13 ppmv for XCO 2 and 0.6 ppbv for XCH 4 . 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 XCO 2 and 2.2 ppbv for XCH 4 . 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.

Abstract. We use 2009–2011 space-borne methane observations from the Greenhouse Gases Observing SATellite (GOSAT) to constrain global and North American inversions of methane emissions with 4° × 5° and up to 50 km × 50 km spatial resolution, respectively. The GOSAT data are first evaluated with atmospheric methane observations from surface networks (NOAA, TCCON) and aircraft (NOAA/DOE, HIPPO), using the GEOS-Chem chemical transport model as a platform to facilitate comparison of GOSAT with in situ data. This identifies a high-latitude bias between the GOSAT data and GEOS-Chem that we correct via quadratic regression. The surface and aircraft data are subsequently used for independent evaluation of the methane source inversions. Our global adjoint-based inversion yields a total methane source of 539 Tg a−1 and points to a large East Asian overestimate in the EDGARv4.2 inventory used as a prior. Results serve as dynamic boundary conditions for an analytical inversion of North American methane emissions using radial basis functions to achieve high resolution of large sources and provide full error characterization. We infer a US anthropogenic methane source of 40.2–42.7 Tg a−1, as compared to 24.9–27.0 Tg a−1 in the EDGAR and EPA bottom-up inventories, and 30.0–44.5 Tg a−1 in recent inverse studies. Our estimate is supported by independent surface and aircraft data and by previous inverse studies for California. We find that the emissions are highest in the South-Central US, the Central Valley of California, and Florida wetlands, large isolated point sources such as the US Four Corners also contribute. We attribute 29–44% of US anthropogenic methane emissions to livestock, 22–31% to oil/gas, 20% to landfills/waste water, and 11–15% to coal with an additional 9.0–10.1 Tg a−1 source from wetlands.