Articles | Volume 5, issue 8
https://doi.org/10.5194/amt-5-1935-2012
© Author(s) 2012. 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-5-1935-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
SCIAMACHY WFM-DOAS XCO2: comparison with CarbonTracker XCO2 focusing on aerosols and thin clouds
J. Heymann
Institute of Environmental Physics – IUP, University of Bremen FB1, Otto-Hahn-Allee 1, P.O. Box 33 04 40, 28334 Bremen, Germany
O. Schneising
Institute of Environmental Physics – IUP, University of Bremen FB1, Otto-Hahn-Allee 1, P.O. Box 33 04 40, 28334 Bremen, Germany
M. Reuter
Institute of Environmental Physics – IUP, University of Bremen FB1, Otto-Hahn-Allee 1, P.O. Box 33 04 40, 28334 Bremen, Germany
M. Buchwitz
Institute of Environmental Physics – IUP, University of Bremen FB1, Otto-Hahn-Allee 1, P.O. Box 33 04 40, 28334 Bremen, Germany
V. V. Rozanov
Institute of Environmental Physics – IUP, University of Bremen FB1, Otto-Hahn-Allee 1, P.O. Box 33 04 40, 28334 Bremen, Germany
V. A. Velazco
Institute of Environmental Physics – IUP, University of Bremen FB1, Otto-Hahn-Allee 1, P.O. Box 33 04 40, 28334 Bremen, Germany
now at: School of Chemistry, University of Wollongong, Wollongong, New South Wales, Australia
H. Bovensmann
Institute of Environmental Physics – IUP, University of Bremen FB1, Otto-Hahn-Allee 1, P.O. Box 33 04 40, 28334 Bremen, Germany
J. P. Burrows
Institute of Environmental Physics – IUP, University of Bremen FB1, Otto-Hahn-Allee 1, P.O. Box 33 04 40, 28334 Bremen, Germany
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Cited
16 citations as recorded by crossref.
- Estimating regional methane surface fluxes: the relative importance of surface and GOSAT mole fraction measurements A. Fraser et al. https://doi.org/10.5194/acp-13-5697-2013
- Consistent satellite XCO2 retrievals from SCIAMACHY and GOSAT using the BESD algorithm J. Heymann et al. https://doi.org/10.5194/amt-8-2961-2015
- Ground-based remote sensing of atmospheric total column CO2and CH4by direct sunlight in Hefei S. Cheng et al. https://doi.org/10.1088/1674-1056/22/12/129201
- Global land mapping of satellite-observed CO2 total columns using spatio-temporal geostatistics Z. Zeng et al. https://doi.org/10.1080/17538947.2016.1156777
- The Greenhouse Gas Climate Change Initiative (GHG-CCI): comparative validation of GHG-CCI SCIAMACHY/ENVISAT and TANSO-FTS/GOSAT CO2 and CH4 retrieval algorithm products with measurements from the TCCON B. Dils et al. https://doi.org/10.5194/amt-7-1723-2014
- Anthropogenic carbon dioxide source areas observed from space: assessment of regional enhancements and trends O. Schneising et al. https://doi.org/10.5194/acp-13-2445-2013
- Analysis of spatiotemporal patterns of atmospheric CO2 concentration in the Yellow River Basin over the past decade based on time-series remote sensing data Y. Lv et al. https://doi.org/10.1007/s11356-023-30553-1
- Carbon Monitoring Satellite (CarbonSat): assessment of atmospheric CO2 and CH4 retrieval errors by error parameterization M. Buchwitz et al. https://doi.org/10.5194/amt-6-3477-2013
- The Greenhouse Gas Climate Change Initiative (GHG-CCI): Comparison and quality assessment of near-surface-sensitive satellite-derived CO2 and CH4 global data sets M. Buchwitz et al. https://doi.org/10.1016/j.rse.2013.04.024
- SCIAMACHY WFM-DOAS XCO2: reduction of scattering related errors J. Heymann et al. https://doi.org/10.5194/amt-5-2375-2012
- Global satellite observations of column-averaged carbon dioxide and methane: The GHG-CCI XCO2 and XCH4 CRDP3 data set M. Buchwitz et al. https://doi.org/10.1016/j.rse.2016.12.027
- Interpreting seasonal changes of low-tropospheric CO 2 over China based on SCIAMACHY observations during 2003–2011 W. Xi et al. https://doi.org/10.1016/j.atmosenv.2014.12.053
- A Data-Driven Assessment of Biosphere-Atmosphere Interaction Impact on Seasonal Cycle Patterns of XCO2 Using GOSAT and MODIS Observations Z. He et al. https://doi.org/10.3390/rs9030251
- Spatiotemporal evaluation of atmospheric CO2 fluctuations in Shaanxi Province (2013–2022) utilizing multi-source satellite remote sensing data Y. Li et al. https://doi.org/10.1186/s13021-025-00294-4
- A Review of Anthropogenic Ground-Level Carbon Emissions Based on Satellite Data K. Hu et al. https://doi.org/10.1109/JSTARS.2024.3355549
- An Analysis Method of Gas Absorption Spectrum Characteristics Based on Fuzzy Comprehensive Evaluation Z. Wu et al. https://doi.org/10.1109/JSTARS.2023.3322640
16 citations as recorded by crossref.
- Estimating regional methane surface fluxes: the relative importance of surface and GOSAT mole fraction measurements A. Fraser et al. https://doi.org/10.5194/acp-13-5697-2013
- Consistent satellite XCO2 retrievals from SCIAMACHY and GOSAT using the BESD algorithm J. Heymann et al. https://doi.org/10.5194/amt-8-2961-2015
- Ground-based remote sensing of atmospheric total column CO2and CH4by direct sunlight in Hefei S. Cheng et al. https://doi.org/10.1088/1674-1056/22/12/129201
- Global land mapping of satellite-observed CO2 total columns using spatio-temporal geostatistics Z. Zeng et al. https://doi.org/10.1080/17538947.2016.1156777
- The Greenhouse Gas Climate Change Initiative (GHG-CCI): comparative validation of GHG-CCI SCIAMACHY/ENVISAT and TANSO-FTS/GOSAT CO2 and CH4 retrieval algorithm products with measurements from the TCCON B. Dils et al. https://doi.org/10.5194/amt-7-1723-2014
- Anthropogenic carbon dioxide source areas observed from space: assessment of regional enhancements and trends O. Schneising et al. https://doi.org/10.5194/acp-13-2445-2013
- Analysis of spatiotemporal patterns of atmospheric CO2 concentration in the Yellow River Basin over the past decade based on time-series remote sensing data Y. Lv et al. https://doi.org/10.1007/s11356-023-30553-1
- Carbon Monitoring Satellite (CarbonSat): assessment of atmospheric CO2 and CH4 retrieval errors by error parameterization M. Buchwitz et al. https://doi.org/10.5194/amt-6-3477-2013
- The Greenhouse Gas Climate Change Initiative (GHG-CCI): Comparison and quality assessment of near-surface-sensitive satellite-derived CO2 and CH4 global data sets M. Buchwitz et al. https://doi.org/10.1016/j.rse.2013.04.024
- SCIAMACHY WFM-DOAS XCO2: reduction of scattering related errors J. Heymann et al. https://doi.org/10.5194/amt-5-2375-2012
- Global satellite observations of column-averaged carbon dioxide and methane: The GHG-CCI XCO2 and XCH4 CRDP3 data set M. Buchwitz et al. https://doi.org/10.1016/j.rse.2016.12.027
- Interpreting seasonal changes of low-tropospheric CO 2 over China based on SCIAMACHY observations during 2003–2011 W. Xi et al. https://doi.org/10.1016/j.atmosenv.2014.12.053
- A Data-Driven Assessment of Biosphere-Atmosphere Interaction Impact on Seasonal Cycle Patterns of XCO2 Using GOSAT and MODIS Observations Z. He et al. https://doi.org/10.3390/rs9030251
- Spatiotemporal evaluation of atmospheric CO2 fluctuations in Shaanxi Province (2013–2022) utilizing multi-source satellite remote sensing data Y. Li et al. https://doi.org/10.1186/s13021-025-00294-4
- A Review of Anthropogenic Ground-Level Carbon Emissions Based on Satellite Data K. Hu et al. https://doi.org/10.1109/JSTARS.2024.3355549
- An Analysis Method of Gas Absorption Spectrum Characteristics Based on Fuzzy Comprehensive Evaluation Z. Wu et al. https://doi.org/10.1109/JSTARS.2023.3322640
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