Articles | Volume 13, issue 2
https://doi.org/10.5194/amt-13-789-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-13-789-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
19 Feb 2020
Research article |
| 19 Feb 2020
| 19 Feb 2020
Ensemble-based satellite-derived carbon dioxide and methane column-averaged dry-air mole fraction data sets (2003–2018) for carbon and climate applications
Maximilian Reuter
Institute of Environmental Physics (IUP), University of Bremen, 28334
Bremen, Germany
Institute of Environmental Physics (IUP), University of Bremen, 28334
Bremen, Germany
Oliver Schneising
Institute of Environmental Physics (IUP), University of Bremen, 28334
Bremen, Germany
Stefan Noël
Institute of Environmental Physics (IUP), University of Bremen, 28334
Bremen, Germany
Heinrich Bovensmann
Institute of Environmental Physics (IUP), University of Bremen, 28334
Bremen, Germany
John P. Burrows
Institute of Environmental Physics (IUP), University of Bremen, 28334
Bremen, Germany
Hartmut Boesch
Earth Observation Science, University of Leicester, LE1 7RH,
Leicester, UK
NERC National Centre for Earth Observation, LE1 7RH, Leicester, UK
Antonio Di Noia
Earth Observation Science, University of Leicester, LE1 7RH,
Leicester, UK
NERC National Centre for Earth Observation, LE1 7RH, Leicester, UK
Jasdeep Anand
Earth Observation Science, University of Leicester, LE1 7RH,
Leicester, UK
NERC National Centre for Earth Observation, LE1 7RH, Leicester, UK
Robert J. Parker
Earth Observation Science, University of Leicester, LE1 7RH,
Leicester, UK
NERC National Centre for Earth Observation, LE1 7RH, Leicester, UK
Peter Somkuti
Earth Observation Science, University of Leicester, LE1 7RH,
Leicester, UK
NERC National Centre for Earth Observation, LE1 7RH, Leicester, UK
Cooperative Institute for Research in the Atmosphere, Colorado State
University (CSU), Fort Collins, CO 80523, USA
Lianghai Wu
SRON Netherlands Institute for Space Research, 3584 CA Utrecht, the
Netherlands
Otto P. Hasekamp
SRON Netherlands Institute for Space Research, 3584 CA Utrecht, the
Netherlands
Ilse Aben
SRON Netherlands Institute for Space Research, 3584 CA Utrecht, the
Netherlands
Akihiko Kuze
Japan Aerospace Exploration Agency (JAXA), 305-8505, Tsukuba, Japan
Hiroshi Suto
Japan Aerospace Exploration Agency (JAXA), 305-8505, Tsukuba, Japan
Kei Shiomi
Japan Aerospace Exploration Agency (JAXA), 305-8505, Tsukuba, Japan
Yukio Yoshida
National Institute for Environmental Studies (NIES), 305-8506,
Tsukuba, Japan
Isamu Morino
National Institute for Environmental Studies (NIES), 305-8506,
Tsukuba, Japan
David Crisp
Jet Propulsion Laboratory (JPL), Pasadena, CA 91109, USA
Christopher W. O'Dell
Cooperative Institute for Research in the Atmosphere, Colorado State
University (CSU), Fort Collins, CO 80523, USA
Justus Notholt
Institute of Environmental Physics (IUP), University of Bremen, 28334
Bremen, Germany
Christof Petri
Institute of Environmental Physics (IUP), University of Bremen, 28334
Bremen, Germany
Thorsten Warneke
Institute of Environmental Physics (IUP), University of Bremen, 28334
Bremen, Germany
Voltaire A. Velazco
Centre for Atmospheric Chemistry, School of Earth, Atmospheric and
Life Sciences, University of Wollongong, NSW, 2522, Australia
Nicholas M. Deutscher
Centre for Atmospheric Chemistry, School of Earth, Atmospheric and
Life Sciences, University of Wollongong, NSW, 2522, Australia
David W. T. Griffith
Centre for Atmospheric Chemistry, School of Earth, Atmospheric and
Life Sciences, University of Wollongong, NSW, 2522, Australia
Rigel Kivi
Space and Earth Observation Centre, Finnish Meteorological Institute (FMI), 99600 Sodankylä, Finland
David F. Pollard
National Institute of Water and Atmospheric Research (NIWA), Lauder,
New Zealand
Frank Hase
Karlsruhe Institute of Technology (KIT), Institute of Meteorology and
Climate Research (IMK), IMK-ASF, 76021 Karlsruhe, Germany
Ralf Sussmann
Karlsruhe Institute of Technology (KIT), Institute of Meteorology and
Climate Research (IMK), IMK-IFU, 82467 Garmisch-Partenkirchen, Germany
Yao V. Té
Laboratoire d'Etudes du Rayonnement et de la Matière en
Astrophysique et Atmosphéres (LERMA-IPSL), Sorbonne Université,
CNRS, Observatoire de Paris, PSL Université, 75005 Paris, France
Kimberly Strong
Department of Physics, University of Toronto, Toronto, ON, M5S 1A7,
Canada
Sébastien Roche
Department of Physics, University of Toronto, Toronto, ON, M5S 1A7,
Canada
Mahesh K. Sha
Royal Belgian Institute for Space Aeronomy (BIRA-IASB), 1180 Brussels,
Belgium
Martine De Mazière
Royal Belgian Institute for Space Aeronomy (BIRA-IASB), 1180 Brussels,
Belgium
Dietrich G. Feist
Max Planck Institute for Biogeochemistry, 07745 Jena, Germany
Lehrstuhl für Physik der Atmosphäre,
Ludwig-Maximilians-Universität München, 80333 Munich, Germany
Institut für Physik der Atmosphäre, Deutsches Zentrum für
Luft- und Raumfahrt Oberpfaffenhofen, 82234 Weßling, Germany
Laura T. Iraci
Atmospheric Science Branch, National Aeronautics and Space
Administration (NASA), Moffett Field, CA 94035, USA
Coleen M. Roehl
California Institute of Technology, Pasadena, CA 91125, USA
Christian Retscher
Directorate of Earth Observation Programmes, European Space Agency (ESA), ESRIN, 00044 Frascati, Italy
Dinand Schepers
European Centre for Medium-Range Weather Forecasts (ECMWF), Reading
RG2 9AX, UK
Viewed
Total article views: 5,910 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 30 Oct 2019)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 4,366 | 1,438 | 106 | 5,910 | 113 | 110 |
- HTML: 4,366
- PDF: 1,438
- XML: 106
- Total: 5,910
- BibTeX: 113
- EndNote: 110
Total article views: 4,937 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 19 Feb 2020)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 3,902 | 937 | 98 | 4,937 | 103 | 97 |
- HTML: 3,902
- PDF: 937
- XML: 98
- Total: 4,937
- BibTeX: 103
- EndNote: 97
Total article views: 973 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 30 Oct 2019)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 464 | 501 | 8 | 973 | 10 | 13 |
- HTML: 464
- PDF: 501
- XML: 8
- Total: 973
- BibTeX: 10
- EndNote: 13
Viewed (geographical distribution)
Total article views: 5,910 (including HTML, PDF, and XML)
Thereof 5,262 with geography defined
and 648 with unknown origin.
Total article views: 4,937 (including HTML, PDF, and XML)
Thereof 4,575 with geography defined
and 362 with unknown origin.
Total article views: 973 (including HTML, PDF, and XML)
Thereof 687 with geography defined
and 286 with unknown origin.
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
Cited
19 citations as recorded by crossref.
- Global land 1° mapping dataset of XCO2 from satellite observations of GOSAT and OCO-2 from 2009 to 2020 M. Sheng et al. 10.1080/20964471.2022.2033149
- Comparison of Stratospheric CO2 Measurements by Ground- and Satellite-Based Methods A. Nikitenko et al. 10.1134/S1024856022040145
- Study of Climate Change Detection in North-East Africa Using Machine Learning and Satellite Data S. Ibrahim et al. 10.1109/JSTARS.2021.3120987
- Variation patterns and driving factors of regional atmospheric CO2 anomalies in China Y. Fu et al. 10.1007/s11356-021-17139-5
- Can a regional-scale reduction of atmospheric CO<sub>2</sub> during the COVID-19 pandemic be detected from space? A case study for East China using satellite XCO<sub>2</sub> retrievals M. Buchwitz et al. 10.5194/amt-14-2141-2021
- XCO<sub>2</sub> retrieval for GOSAT and GOSAT-2 based on the FOCAL algorithm S. Noël et al. 10.5194/amt-14-3837-2021
- Retrieval of greenhouse gases from GOSAT and GOSAT-2 using the FOCAL algorithm S. Noël et al. 10.5194/amt-15-3401-2022
- European summer weather linked to North Atlantic freshwater anomalies in preceding years M. Oltmanns et al. 10.5194/wcd-5-109-2024
- Monitoring of the Essential Climate Variables of the Atmosphere from Satellite-based Infrared Sounder IKFS-2 A. Uspensky et al. 10.3103/S1068373922110012
- Spatially resolved evaluation of Earth system models with satellite column-averaged CO<sub>2</sub> B. Gier et al. 10.5194/bg-17-6115-2020
- Approximation of multi-year time series of XCO2 concentrations using satellite observations and statistical interpolation methods W. Wefers et al. 10.1016/j.atmosres.2023.106965
- A decade of GOSAT Proxy satellite CH<sub>4</sub> observations R. Parker et al. 10.5194/essd-12-3383-2020
- Can We Measure a COVID-19-Related Slowdown in Atmospheric CO2 Growth? Sensitivity of Total Carbon Column Observations R. Sussmann & M. Rettinger 10.3390/rs12152387
- Modification of Fraser’s Method for the Atmospheric CO2 Mass Estimation by Using Satellite Data M. Pellegrini et al. 10.3390/atmos13060866
- Towards Robust Calculation of Interannual CO2 Growth Signal from TCCON (Total Carbon Column Observing Network) L. Labzovskii et al. 10.3390/rs13193868
- Detection and quantification of CH<sub>4</sub> plumes using the WFM-DOAS retrieval on AVIRIS-NG hyperspectral data J. Borchardt et al. 10.5194/amt-14-1267-2021
- Data driven analysis of atmospheric methane concentrations as function of geographic, land cover type and season C. Karoff & A. Vara-Vela 10.3389/feart.2023.1119977
- Variation of XCO2 anomaly patterns in the Middle East from OCO-2 satellite data F. Golkar & S. Mousavi 10.1080/17538947.2022.2096936
- Zonal variability of methane trends derived from satellite data J. Hachmeister et al. 10.5194/acp-24-577-2024
19 citations as recorded by crossref.
- Global land 1° mapping dataset of XCO2 from satellite observations of GOSAT and OCO-2 from 2009 to 2020 M. Sheng et al. 10.1080/20964471.2022.2033149
- Comparison of Stratospheric CO2 Measurements by Ground- and Satellite-Based Methods A. Nikitenko et al. 10.1134/S1024856022040145
- Study of Climate Change Detection in North-East Africa Using Machine Learning and Satellite Data S. Ibrahim et al. 10.1109/JSTARS.2021.3120987
- Variation patterns and driving factors of regional atmospheric CO2 anomalies in China Y. Fu et al. 10.1007/s11356-021-17139-5
- Can a regional-scale reduction of atmospheric CO<sub>2</sub> during the COVID-19 pandemic be detected from space? A case study for East China using satellite XCO<sub>2</sub> retrievals M. Buchwitz et al. 10.5194/amt-14-2141-2021
- XCO<sub>2</sub> retrieval for GOSAT and GOSAT-2 based on the FOCAL algorithm S. Noël et al. 10.5194/amt-14-3837-2021
- Retrieval of greenhouse gases from GOSAT and GOSAT-2 using the FOCAL algorithm S. Noël et al. 10.5194/amt-15-3401-2022
- European summer weather linked to North Atlantic freshwater anomalies in preceding years M. Oltmanns et al. 10.5194/wcd-5-109-2024
- Monitoring of the Essential Climate Variables of the Atmosphere from Satellite-based Infrared Sounder IKFS-2 A. Uspensky et al. 10.3103/S1068373922110012
- Spatially resolved evaluation of Earth system models with satellite column-averaged CO<sub>2</sub> B. Gier et al. 10.5194/bg-17-6115-2020
- Approximation of multi-year time series of XCO2 concentrations using satellite observations and statistical interpolation methods W. Wefers et al. 10.1016/j.atmosres.2023.106965
- A decade of GOSAT Proxy satellite CH<sub>4</sub> observations R. Parker et al. 10.5194/essd-12-3383-2020
- Can We Measure a COVID-19-Related Slowdown in Atmospheric CO2 Growth? Sensitivity of Total Carbon Column Observations R. Sussmann & M. Rettinger 10.3390/rs12152387
- Modification of Fraser’s Method for the Atmospheric CO2 Mass Estimation by Using Satellite Data M. Pellegrini et al. 10.3390/atmos13060866
- Towards Robust Calculation of Interannual CO2 Growth Signal from TCCON (Total Carbon Column Observing Network) L. Labzovskii et al. 10.3390/rs13193868
- Detection and quantification of CH<sub>4</sub> plumes using the WFM-DOAS retrieval on AVIRIS-NG hyperspectral data J. Borchardt et al. 10.5194/amt-14-1267-2021
- Data driven analysis of atmospheric methane concentrations as function of geographic, land cover type and season C. Karoff & A. Vara-Vela 10.3389/feart.2023.1119977
- Variation of XCO2 anomaly patterns in the Middle East from OCO-2 satellite data F. Golkar & S. Mousavi 10.1080/17538947.2022.2096936
- Zonal variability of methane trends derived from satellite data J. Hachmeister et al. 10.5194/acp-24-577-2024
Latest update: 23 Nov 2024
Short summary
We present new satellite-derived data sets of atmospheric carbon dioxide (CO2) and methane (CH4). The data products are column-averaged dry-air mole fractions of CO2 and CH4, denoted XCO2 and XCH4. The products cover the years 2003–2018 and are merged Level 2 (satellite footprints) and merged Level 3 (gridded at monthly time and 5° x 5° spatial resolution) products obtained from combining several individual sensor products. We present the merging algorithms and product validation results.
We present new satellite-derived data sets of atmospheric carbon dioxide (CO2) and methane...
