Articles | Volume 8, issue 7
https://doi.org/10.5194/amt-8-2961-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-8-2961-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
24 Jul 2015
Research article |
| 24 Jul 2015
Consistent satellite XCO2 retrievals from SCIAMACHY and GOSAT using the BESD algorithm
J. Heymann
CORRESPONDING AUTHOR
Institute of Environmental Physics (IUP), University of Bremen, Bremen, Germany
M. Reuter
Institute of Environmental Physics (IUP), University of Bremen, Bremen, Germany
M. Hilker
Institute of Environmental Physics (IUP), University of Bremen, Bremen, Germany
M. Buchwitz
Institute of Environmental Physics (IUP), University of Bremen, Bremen, Germany
O. Schneising
Institute of Environmental Physics (IUP), University of Bremen, Bremen, Germany
H. Bovensmann
Institute of Environmental Physics (IUP), University of Bremen, Bremen, Germany
J. P. Burrows
Institute of Environmental Physics (IUP), University of Bremen, Bremen, Germany
Japan Aerospace Exploration Agency (JAXA), Tsukuba, Japan
H. Suto
Japan Aerospace Exploration Agency (JAXA), Tsukuba, Japan
N. M. Deutscher
Centre for Atmospheric Chemistry, University of Wollongong, Wollongong, Australia
Institute of Environmental Physics (IUP), University of Bremen, Bremen, Germany
M. K. Dubey
Los Alamos National Laboratory, Los Alamos, USA
D. W. T. Griffith
Centre for Atmospheric Chemistry, University of Wollongong, Wollongong, Australia
F. Hase
IMK-ASF, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
S. Kawakami
Japan Aerospace Exploration Agency (JAXA), Tsukuba, Japan
Finnish Meteorological Institute, Sodankylä, Finland
I. Morino
National Institute for Environmental Studies (NIES), Tsukuba, Japan
Institute of Environmental Physics (IUP), University of Bremen, Bremen, Germany
C. Roehl
California Institute of Technology, Pasadena, USA
M. Schneider
IMK-ASF, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
V. Sherlock
National Institute of Water and Atmospheric Research, Wellington, New Zealand
now at: Laboratoire de Météorologie Dynamique, Palaiseau, France
R. Sussmann
IMK-IFU, Karlsruhe Institute of Technology (KIT), Garmisch-Partenkirchen, Germany
V. A. Velazco
Centre for Atmospheric Chemistry, University of Wollongong, Wollongong, Australia
T. Warneke
Institute of Environmental Physics (IUP), University of Bremen, Bremen, Germany
California Institute of Technology, Pasadena, USA
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44 citations as recorded by crossref.
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- Evaluation of OCO‐2 X Variability at Local and Synoptic Scales using Lidar and In Situ Observations from the ACT‐America Campaigns E. Bell et al. 10.1029/2019JD031400
- Reviews and syntheses: Systematic Earth observations for use in terrestrial carbon cycle data assimilation systems M. Scholze et al. 10.5194/bg-14-3401-2017
- Thermal and near-infrared sensor for carbon observation Fourier transform spectrometer-2 (TANSO-FTS-2) on the Greenhouse gases Observing SATellite-2 (GOSAT-2) during its first year in orbit H. Suto et al. 10.5194/amt-14-2013-2021
- Monitoring greenhouse gases (GHGs) in China: status and perspective Y. Sun et al. 10.5194/amt-15-4819-2022
- Spatio-Temporal Mapping of Multi-Satellite Observed Column Atmospheric CO2 Using Precision-Weighted Kriging Method Z. He et al. 10.3390/rs12030576
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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 M. Reuter et al. 10.5194/amt-13-789-2020
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- Retrieval of greenhouse gases from GOSAT and GOSAT-2 using the FOCAL algorithm S. Noël et al. 10.5194/amt-15-3401-2022
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- The TanSat mission: preliminary global observations Y. Liu et al. 10.1016/j.scib.2018.08.004
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Latest update: 23 Nov 2024
Short summary
Long-term data sets of global atmospheric carbon dioxide concentrations based on observations from different satellite instruments may suffer from inconsistencies originating from the use of different retrieval algorithms. This issue has been addressed by applying the Bremen Optimal Estimation DOAS retrieval algorithm to SCIAMACHY and TANSO-FTS observations. Detailed comparisons with TCCON and CarbonTracker show good consistency between the SCIAMACHY and TANSO-FTS data sets.
Long-term data sets of global atmospheric carbon dioxide concentrations based on observations...
