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Ensemble-based satellite-derived carbon dioxide and methane column-averaged dry-air mole fraction data sets (2003-2018) for carbon and climate applications

Reuter, Maximilian and Buchwitz, Michael and Schneising, Oliver and Noël, Stefan and Bovensmann, Heinrich and Burrows, John P. and Boesch, Hartmut and Di Noia, Antonio and Anand, Jasdeep and Parker, Robert J. and Somkuti, Peter and Wu, Lianghai and Hasekamp, Otto P. and Aben, Ilse and Kuze, Akihiko and Suto, Hiroshi and Shiomi, Kei and Yoshida, Yukio and Morino, Isamu and Crisp, David and O'Dell, Christopher W. and Notholt, Justus and Petri, Christof and Warneke, Thorsten and Velazco, Voltaire A. and Deutscher, Nicholas M. and Griffith, David W. T. and Kivi, Rigel and Pollard, David F. and Hase, Frank and Sussmann, Ralf and Té, Yao V. and Strong, Kimberly and Roche, Sébastien and Sha, Mahesh K. and De Mazière, Martine and Feist, Dietrich G. and Iraci, Laura T. and Roehl, Coleen M. and Retscher, Christian and Schepers, Dinand (2020) Ensemble-based satellite-derived carbon dioxide and methane column-averaged dry-air mole fraction data sets (2003-2018) for carbon and climate applications. Atmospheric Measurement Techniques, 13 (2). pp. 789-819. ISSN 1867-8548.

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Satellite retrievals of column-averaged dry-air mole fractions of carbon dioxide (CO₂) and methane (CH₄), denoted XCO₂ and XCH₄, respectively, have been used in recent years to obtain information on natural and anthropogenic sources and sinks and for other applications such as comparisons with climate models. Here we present new data sets based on merging several individual satellite data products in order to generate consistent long-term climate data records (CDRs) of these two Essential Climate Variables (ECVs). These ECV CDRs, which cover the time period 2003–2018, have been generated using an ensemble of data products from the satellite sensors SCIAMACHY/ENVISAT and TANSO-FTS/GOSAT and (for XCO₂) for the first time also including data from the Orbiting Carbon Observatory 2 (OCO-2) satellite. Two types of products have been generated: (i) Level 2 (L2) products generated with the latest version of the ensemble median algorithm (EMMA) and (ii) Level 3 (L3) products obtained by gridding the corresponding L2 EMMA products to obtain a monthly 5∘×5∘ data product in Obs4MIPs (Observations for Model Intercomparisons Project) format. The L2 products consist of daily NetCDF (Network Common Data Form) files, which contain in addition to the main parameters, i.e., XCO₂ or XCH₄, corresponding uncertainty estimates for random and potential systematic uncertainties and the averaging kernel for each single (quality-filtered) satellite observation. We describe the algorithms used to generate these data products and present quality assessment results based on comparisons with Total Carbon Column Observing Network (TCCON) ground-based retrievals. We found that the XCO₂ Level 2 data set at the TCCON validation sites can be characterized by the following figures of merit (the corresponding values for the Level 3 product are listed in brackets) – single-observation random error (1σ): 1.29 ppm (monthly: 1.18 ppm); global bias: 0.20 ppm (0.18 ppm); and spatiotemporal bias or relative accuracy (1σ): 0.66 ppm (0.70 ppm). The corresponding values for the XCH₄ products are single-observation random error (1σ): 17.4 ppb (monthly: 8.7 ppb); global bias: −2.0 ppb (−2.9 ppb); and spatiotemporal bias (1σ): 5.0 ppb (4.9 ppb). It has also been found that the data products exhibit very good long-term stability as no significant long-term bias trend has been identified. The new data sets have also been used to derive annual XCO₂ and XCH₄ growth rates, which are in reasonable to good agreement with growth rates from the National Oceanic and Atmospheric Administration (NOAA) based on marine surface observations. The presented ECV data sets are available (from early 2020 onwards) via the Climate Data Store (CDS,, last access: 10 January 2020) of the Copernicus Climate Change Service (C3S,, last access: 10 January 2020).

Item Type:Article
Related URLs:
URLURL TypeDescription ItemTCCON Data Archive
Reuter, Maximilian0000-0001-9141-3895
Buchwitz, Michael0000-0001-7616-1837
Schneising, Oliver0000-0003-1725-8246
Bovensmann, Heinrich0000-0001-8882-4108
Burrows, John P.0000-0003-1547-8130
Di Noia, Antonio0000-0002-5052-0763
Parker, Robert J.0000-0002-0801-0831
Wu, Lianghai0000-0001-7797-1719
Kuze, Akihiko0000-0001-5415-3377
Yoshida, Yukio0000-0002-3515-1488
Morino, Isamu0000-0003-2720-1569
Crisp, David0000-0002-4573-9998
Petri, Christof0000-0002-7010-5532
Velazco, Voltaire A.0000-0002-1376-438X
Deutscher, Nicholas M.0000-0002-2906-2577
Griffith, David W. T.0000-0002-7986-1924
Kivi, Rigel0000-0001-8828-2759
Pollard, David F.0000-0001-9923-2984
Strong, Kimberly0000-0001-9947-1053
Roche, Sébastien0000-0003-2474-4744
Sha, Mahesh K.0000-0003-1440-1529
Feist, Dietrich G.0000-0002-5890-6687
Iraci, Laura T.0000-0002-2859-5259
Roehl, Coleen M.0000-0001-5383-8462
Additional Information:© 2020 Author(s). This work is distributed under the Creative Commons Attribution 4.0 License. Published by Copernicus Publications on behalf of the European Geosciences Union. Received: 21 Oct 2019 – Discussion started: 30 Oct 2019 – Revised: 16 Jan 2020 – Accepted: 20 Jan 2020 – Published: 19 Feb 2020. The generation of the EMMA Level 2 and OBS4MIPS Level 3 data sets and the corresponding data analysis has been funded primarily by the European Union (EU) via the Copernicus Climate Change Service (C3S,, last access: 10 January 2020) managed by the European Centre for Medium-Range Weather Forecasts (ECMWF). The work presented here strongly benefited from additional funding by the European Space Agency (ESA) via ESA's Climate Change Initiative (CCI,, last access: 10 January 2020) projects GHG-CCI/GHG-CCI+. The further development of the FOCAL retrieval algorithm used to generate the OCO-2/FOCAL XCO2 input data product would not have been possible without cofunding from the European Union (EU) Horizon 2020 (H2020) research and innovation program projects CHE (grant agreement no. 776186) and VERIFY (grant agreement no. 776810). The generation of the XCO2_OBS4MIPS product also benefited from cofunding from EU H2020 project CCiCC (grant agreement no. 821003). We thank several space agencies for making available satellite Level 1 (L1) input data: ESA/DLR for SCIAMACHY L1 data, JAXA for GOSAT Level 1B data, and NASA for the OCO-2 L1 data product. We also thank ESA for making the GOSAT L1 product available via the ESA Third Party Mission (TPM) archive. We thank NIES for the operational GOSAT XCO2 and XCH4 Level 2 products (obtained from:, last access: 4- September 2019) and the NASA team for the GOSAT and OCO-2 ACOS Level 2 XCO2 products (the NASA GOSAT L2 data product was obtained from:, last access: 4 September 2019; the NASA OCO-2 data product was obtained from:, last access: 4 September 2019). TCCON data were obtained from the TCCON Data Archive, hosted by CaltechDATA, California Institute of Technology (, last access: 15 July 2019). The TCCON stations Ascension Island, Bremen, Garmisch, Karlsruhe, and Ny-Ålesund have been supported by the German Bundesministerium für Wirtschaft und Energie (BMWi) via the DLR under grants 50EE1711A-E. We thank the ESA Ariane tracking station at North East Bay, Ascension Island, for hosting and local support. Nicholas M. Deutscher is supported by an ARC Future Fellowship, FT180100327. The TCCON site at Réunion island is operated by the Royal Belgian Institute for Space Aeronomy with financial support in 2014, 2015, 2016, 2017, 2018, and 2019 under the EU project ICOS-Inwire and the ministerial decree for ICOS (FR/35/IC2) and local activities supported by LACy/UMR8105 – Université de La Réunion. The TCCON stations at Tsukuba and Burgos are supported in part by the GOSAT series project. Local support for Burgos is provided by the Energy Development Corporation (EDC, Philippines). The Paris TCCON site has received funding from Sorbonne Université, the French research center CNRS, the French space agency CNES, and Région Île-de-France. We also thank NOAA for access to the surface CO2 (file; last access: 30 July 2019) and CH4 (file; last access: 30 July 2019) growth rate data sets. Output from NOAA's CarbonTracker has been used as input for the SECM2018 model. CarbonTracker CT2017 results are provided by NOAA ESRL, Boulder, Colorado, USA, from their website at: (last access: 4 September 2019). We also thank Peter Bergamaschi for providing MACC-II project inversion system CH4 fields, which have been used as input for the SC4C2018 model. This research has been supported by the European Union (Copernicus Climate Change Service project C3S_312b_Lot2, via contract with DLR, contract no. D/565/67260504; CHE, grant agreement no. 776186; VERIFY, grant agreement no. 776810; CCiCC, grant agreement no. 821003) and the European Space Agency (ESA; grant no. Project GHG-CCI+). The article processing charges for this open-access publication were covered by the University of Bremen. Review statement: This paper was edited by John Worden and reviewed by Ray Nassar and two anonymous referees. The EMMA and OBS4MIPS XCO2 and XCH4 version 4.1 data products (but also several data sets used as input; see data sets with CCI/C3S product ID in Tables 1 and 2) are available (from early 2020 onwards) via the Copernicus Climate Change Service (C3S,, ECMWF, 2020a) Climate Data Store (CDS,, ECMWF, 2020b), including documentation such as the product user guides (, Buchwitz et al., 2019c;, Reuter et al., 2019d). Author contributions: MR generated the EMMA and OBS4MIPS XCO2 and XCH4 version 4.1 data sets. MR and MB performed the data analysis. MB wrote the first version of the paper with support of MR. The following authors provided input data or expertise on data sets: MR, MB, OS, SN, HB, JPB, HBoe, ADN, JA, RJP, PS, LW, OPH, IA, AK, HS, KS, YY, IM, DC, CWO'D, JN, CP, TW, VAV, NMD, DWTG, RK, DP, FH, RS, YVT, KS, SR, MKS, MDM, DGF, LTI, CMR, CR, and DS. All authors contributed to significantly improve the paper. The authors declare that they have no conflict of interest.
Funding AgencyGrant Number
European UnionC3S_312b_Lot2
Deutsches Zentrum für Luft- und Raumfahrt (DLR)D/565/67260504
European Research Council (ERC)776186
European Research Council (ERC)776810
European Research Council (ERC)821003
European Space Agency (ESA)GHG-CCI+
University of BremenUNSPECIFIED
Bundesministerium für Wirtschaft und Energie (BMWi)
Deutsches Zentrum für Luft- und Raumfahrt (DLR)50EE1711A-E
Australian Research CouncilFT180100327
European UnionFR/35/IC2
Université de La RéunionLACy/UMR8105
Sorbonne UniversitéUNSPECIFIED
Centre National de la Recherche Scientifique (CNRS)UNSPECIFIED
Centre National d'Études Spatiales (CNES)UNSPECIFIED
Région Île-de-FranceUNSPECIFIED
Issue or Number:2
Record Number:CaltechAUTHORS:20200317-091330389
Persistent URL:
Official Citation:Reuter, M., Buchwitz, M., Schneising, O., Noël, S., Bovensmann, H., Burrows, J. P., Boesch, H., Di Noia, A., Anand, J., Parker, R. J., Somkuti, P., Wu, L., Hasekamp, O. P., Aben, I., Kuze, A., Suto, H., Shiomi, K., Yoshida, Y., Morino, I., Crisp, D., O'Dell, C. W., Notholt, J., Petri, C., Warneke, T., Velazco, V. A., Deutscher, N. M., Griffith, D. W. T., Kivi, R., Pollard, D. F., Hase, F., Sussmann, R., Té, Y. V., Strong, K., Roche, S., Sha, M. K., De Mazière, M., Feist, D. G., Iraci, L. T., Roehl, C. M., Retscher, C., and Schepers, D.: Ensemble-based satellite-derived carbon dioxide and methane column-averaged dry-air mole fraction data sets (2003–2018) for carbon and climate applications, Atmos. Meas. Tech., 13, 789–819,, 2020.
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:101941
Deposited By: Tony Diaz
Deposited On:17 Mar 2020 16:30
Last Modified:17 Mar 2020 16:30

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