Articles | Volume 8, issue 11
https://doi.org/10.5194/amt-8-4785-2015
© 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-8-4785-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
17 Nov 2015
Research article |
| 17 Nov 2015
Assessing 5 years of GOSAT Proxy XCH4 data and associated uncertainties
Earth Observation Science, Department of Physics and Astronomy, University of Leicester, Leicester, UK
National Centre for Earth Observation, Department of Physics and Astronomy, University of Leicester, Leicester, UK
H. Boesch
Earth Observation Science, Department of Physics and Astronomy, University of Leicester, Leicester, UK
National Centre for Earth Observation, Department of Physics and Astronomy, University of Leicester, Leicester, UK
K. Byckling
Earth Observation Science, Department of Physics and Astronomy, University of Leicester, Leicester, UK
A. J. Webb
Earth Observation Science, Department of Physics and Astronomy, University of Leicester, Leicester, UK
P. I. Palmer
School of GeoSciences, University of Edinburgh, Edinburgh, UK
National Centre for Earth Observation, School of GeoSciences, University of Edinburgh, Edinburgh, UK
L. Feng
School of GeoSciences, University of Edinburgh, Edinburgh, UK
National Centre for Earth Observation, School of GeoSciences, University of Edinburgh, Edinburgh, UK
P. Bergamaschi
European Commission Joint Research Centre, Institute for Environment and Sustainability, Ispra, Italy
F. Chevallier
Lab. des Sciences du Climat et de l'Environnement, CNRS, Gif-sur-Yvette, France
J. Notholt
Institute of Environmental Physics, University of Bremen, Bremen, Germany
N. Deutscher
Institute of Environmental Physics, University of Bremen, Bremen, Germany
School of Chemistry, University of Wollongong, Wollongong, Australia
T. Warneke
Institute of Environmental Physics, University of Bremen, Bremen, Germany
F. Hase
Karlsruhe Institut für Technologie, Karlsruhe, Germany
R. Sussmann
Karlsruhe Institut für Technologie, Karlsruhe, Germany
S. Kawakami
Japan Aerospace Exploration Agency (JAXA), Tsukuba, Japan
Finnish Meteorological Institute, Arctic Research, Sodankylä, Finland
D. W. T. Griffith
School of Chemistry, University of Wollongong, Wollongong, Australia
V. Velazco
School of Chemistry, University of Wollongong, Wollongong, Australia
Viewed
Total article views: 6,105 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 17 Jun 2015)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 3,620 | 2,319 | 166 | 6,105 | 173 | 179 |
- HTML: 3,620
- PDF: 2,319
- XML: 166
- Total: 6,105
- BibTeX: 173
- EndNote: 179
Total article views: 4,939 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 17 Nov 2015)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 3,079 | 1,721 | 139 | 4,939 | 156 | 164 |
- HTML: 3,079
- PDF: 1,721
- XML: 139
- Total: 4,939
- BibTeX: 156
- EndNote: 164
Total article views: 1,166 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 17 Jun 2015)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 541 | 598 | 27 | 1,166 | 17 | 15 |
- HTML: 541
- PDF: 598
- XML: 27
- Total: 1,166
- BibTeX: 17
- EndNote: 15
Cited
54 citations as recorded by crossref.
- Global satellite observations of column-averaged carbon dioxide and methane: The GHG-CCI XCO2 and XCH4 CRDP3 data set M. Buchwitz et al. 10.1016/j.rse.2016.12.027
- MethaNet – An AI-driven approach to quantifying methane point-source emission from high-resolution 2-D plume imagery S. Jongaramrungruang et al. 10.1016/j.rse.2021.112809
- Global distribution of methane emissions, emission trends, and OH concentrations and trends inferred from an inversion of GOSAT satellite data for 2010–2015 J. Maasakkers et al. 10.5194/acp-19-7859-2019
- 煤炭行业甲烷排放卫星遥感研究进展与展望 秦. Qin Kai et al. 10.3788/AOS231293
- 大气甲烷卫星传感器和遥感算法研究综述 何. He Zhuo et al. 10.3788/AOS230429
- Characterizing model errors in chemical transport modeling of methane: using GOSAT XCH<sub>4</sub> data with weak-constraint four-dimensional variational data assimilation I. Stanevich et al. 10.5194/acp-21-9545-2021
- CH4 concentrations over the Amazon from GOSAT consistent with in situ vertical profile data A. Webb et al. 10.1002/2016JD025263
- The added value of satellite observations of methane forunderstanding the contemporary methane budget P. Palmer et al. 10.1098/rsta.2021.0106
- Evaluating year-to-year anomalies in tropical wetland methane emissions using satellite CH4 observations R. Parker et al. 10.1016/j.rse.2018.02.011
- Sustained methane emissions from China after 2012 despite declining coal production and rice-cultivated area J. Sheng et al. 10.1088/1748-9326/ac24d1
- Satellite and ground-based measurements of XCO<sub>2</sub> in a remote semiarid region of Australia V. Velazco et al. 10.5194/essd-11-935-2019
- Spatiotemporal analysis of atmospheric XCH4 as related to fires in the Amazon biome during 2015–2020 L. de Souza Maria et al. 10.1016/j.rsase.2023.100967
- Methane retrieval from MethaneAIR using the CO2 proxy approach: a demonstration for the upcoming MethaneSAT mission C. Chan Miller et al. 10.5194/amt-17-5429-2024
- Decadal Methane Emission Trend Inferred from Proxy GOSAT XCH4 Retrievals: Impacts of Transport Model Spatial Resolution S. Zhu et al. 10.1007/s00376-022-1434-6
- Information content analysis: the potential for methane isotopologue retrieval from GOSAT-2 E. Malina et al. 10.5194/amt-11-1159-2018
- 2010–2016 methane trends over Canada, the United States, and Mexico observed by the GOSAT satellite: contributions from different source sectors J. Sheng et al. 10.5194/acp-18-12257-2018
- Interannual Variability of Atmospheric CH4 and Its Driver Over South Korea Captured by Integrated Data in 2019 S. Kenea et al. 10.3390/rs13122266
- Characterizing model errors in chemical transport modeling of methane: impact of model resolution in versions v9-02 of GEOS-Chem and v35j of its adjoint model I. Stanevich et al. 10.5194/gmd-13-3839-2020
- Bias Correction of the Ratio of Total Column CH4 to CO2 Retrieved from GOSAT Spectra H. Oshio et al. 10.3390/rs12193155
- An integrated analysis of contemporary methane emissions and concentration trends over China using in situ and satellite observations and model simulations H. Tan et al. 10.5194/acp-22-1229-2022
- Attribution of the accelerating increase in atmospheric methane during 2010–2018 by inverse analysis of GOSAT observations Y. Zhang et al. 10.5194/acp-21-3643-2021
- A decade of GOSAT Proxy satellite CH<sub>4</sub> observations R. Parker et al. 10.5194/essd-12-3383-2020
- A simple and quick sensitivity analysis method for methane isotopologues detection with GOSAT-TANSO-FTS E. Malina et al. 10.14324/111.444/ucloe.000013
- Evaluation of wetland CH4in the Joint UK Land Environment Simulator (JULES) land surface model using satellite observations R. Parker et al. 10.5194/bg-19-5779-2022
- A new algorithm to generate a priori trace gas profiles for the GGG2020 retrieval algorithm J. Laughner et al. 10.5194/amt-16-1121-2023
- Assimilation of GOSAT Methane in the Hemispheric CMAQ; Part I: Design of the Assimilation System S. Voshtani et al. 10.3390/rs14020371
- Consistent regional fluxes of CH<sub>4</sub> and CO<sub>2</sub> inferred from GOSAT proxy XCH<sub>4</sub> : XCO<sub>2</sub> retrievals, 2010–2014 L. Feng et al. 10.5194/acp-17-4781-2017
- Atmospheric data support a multi-decadal shift in the global methane budget towards natural tropical emissions A. Drinkwater et al. 10.5194/acp-23-8429-2023
- Estimating 2010–2015 anthropogenic and natural methane emissions in Canada using ECCC surface and GOSAT satellite observations S. Baray et al. 10.5194/acp-21-18101-2021
- Satellite observations of atmospheric methane and their value for quantifying methane emissions D. Jacob et al. 10.5194/acp-16-14371-2016
- Methane point source quantification using MethaneAIR: a new airborne imaging spectrometer A. Chulakadabba et al. 10.5194/amt-16-5771-2023
- Role of regional wetland emissions in atmospheric methane variability J. McNorton et al. 10.1002/2016GL070649
- Exploring constraints on a wetland methane emission ensemble (WetCHARTs) using GOSAT observations R. Parker et al. 10.5194/bg-17-5669-2020
- Inverse modeling of GOSAT-retrieved ratios of total column CH<sub>4</sub> and CO<sub>2</sub> for 2009 and 2010 S. Pandey et al. 10.5194/acp-16-5043-2016
- Quantifying sources of Brazil's CH<sub>4</sub> emissions between 2010 and 2018 from satellite data R. Tunnicliffe et al. 10.5194/acp-20-13041-2020
- 2010–2015 North American methane emissions, sectoral contributions, and trends: a high-resolution inversion of GOSAT observations of atmospheric methane J. Maasakkers et al. 10.5194/acp-21-4339-2021
- A measurement-based verification framework for UK greenhouse gas emissions: an overview of the Greenhouse gAs Uk and Global Emissions (GAUGE) project P. Palmer et al. 10.5194/acp-18-11753-2018
- Attribution of recent increases in atmospheric methane through 3-D inverse modelling J. McNorton et al. 10.5194/acp-18-18149-2018
- Advancing Scientific Understanding of the Global Methane Budget in Support of the Paris Agreement A. Ganesan et al. 10.1029/2018GB006065
- Reevaluating the Use of O2 a1Δg Band in Spaceborne Remote Sensing of Greenhouse Gases K. Sun et al. 10.1029/2018GL077823
- Atmospheric CH<sub>4</sub> and CO<sub>2</sub> enhancements and biomass burning emission ratios derived from satellite observations of the 2015 Indonesian fire plumes R. Parker et al. 10.5194/acp-16-10111-2016
- Global inverse modeling of CH<sub>4</sub> sources and sinks: an overview of methods S. Houweling et al. 10.5194/acp-17-235-2017
- Remote sensing of methane plumes: instrument tradeoff analysis for detecting and quantifying local sources at global scale S. Jongaramrungruang et al. 10.5194/amt-14-7999-2021
- Tropical methane emissions explain large fraction of recent changes in global atmospheric methane growth rate L. Feng et al. 10.1038/s41467-022-28989-z
- Global height-resolved methane retrievals from the Infrared Atmospheric Sounding Interferometer (IASI) on MetOp R. Siddans et al. 10.5194/amt-10-4135-2017
- Accelerating methane growth rate from 2010 to 2017: leading contributions from the tropics and East Asia Y. Yin et al. 10.5194/acp-21-12631-2021
- East Asian methane emissions inferred from high-resolution inversions of GOSAT and TROPOMI observations: a comparative and evaluative analysis R. Liang et al. 10.5194/acp-23-8039-2023
- Reduced-cost construction of Jacobian matrices for high-resolution inversions of satellite observations of atmospheric composition H. Nesser et al. 10.5194/amt-14-5521-2021
- Satellite-derived methane hotspot emission estimates using a fast data-driven method M. Buchwitz et al. 10.5194/acp-17-5751-2017
- An increase in methane emissions from tropical Africa between 2010 and 2016 inferred from satellite data M. Lunt et al. 10.5194/acp-19-14721-2019
- Toward High Precision XCO2Retrievals From TanSat Observations: Retrieval Improvement and Validation Against TCCON Measurements D. Yang et al. 10.1029/2020JD032794
- Atmospheric observations show accurate reporting and little growth in India’s methane emissions A. Ganesan et al. 10.1038/s41467-017-00994-7
- Evaluation of column-averaged methane in models and TCCON with a focus on the stratosphere A. Ostler et al. 10.5194/amt-9-4843-2016
- Comparison of Satellite-Observed XCO2 from GOSAT, OCO-2, and Ground-Based TCCON A. Liang et al. 10.3390/rs9101033
53 citations as recorded by crossref.
- Global satellite observations of column-averaged carbon dioxide and methane: The GHG-CCI XCO2 and XCH4 CRDP3 data set M. Buchwitz et al. 10.1016/j.rse.2016.12.027
- MethaNet – An AI-driven approach to quantifying methane point-source emission from high-resolution 2-D plume imagery S. Jongaramrungruang et al. 10.1016/j.rse.2021.112809
- Global distribution of methane emissions, emission trends, and OH concentrations and trends inferred from an inversion of GOSAT satellite data for 2010–2015 J. Maasakkers et al. 10.5194/acp-19-7859-2019
- 煤炭行业甲烷排放卫星遥感研究进展与展望 秦. Qin Kai et al. 10.3788/AOS231293
- 大气甲烷卫星传感器和遥感算法研究综述 何. He Zhuo et al. 10.3788/AOS230429
- Characterizing model errors in chemical transport modeling of methane: using GOSAT XCH<sub>4</sub> data with weak-constraint four-dimensional variational data assimilation I. Stanevich et al. 10.5194/acp-21-9545-2021
- CH4 concentrations over the Amazon from GOSAT consistent with in situ vertical profile data A. Webb et al. 10.1002/2016JD025263
- The added value of satellite observations of methane forunderstanding the contemporary methane budget P. Palmer et al. 10.1098/rsta.2021.0106
- Evaluating year-to-year anomalies in tropical wetland methane emissions using satellite CH4 observations R. Parker et al. 10.1016/j.rse.2018.02.011
- Sustained methane emissions from China after 2012 despite declining coal production and rice-cultivated area J. Sheng et al. 10.1088/1748-9326/ac24d1
- Satellite and ground-based measurements of XCO<sub>2</sub> in a remote semiarid region of Australia V. Velazco et al. 10.5194/essd-11-935-2019
- Spatiotemporal analysis of atmospheric XCH4 as related to fires in the Amazon biome during 2015–2020 L. de Souza Maria et al. 10.1016/j.rsase.2023.100967
- Methane retrieval from MethaneAIR using the CO2 proxy approach: a demonstration for the upcoming MethaneSAT mission C. Chan Miller et al. 10.5194/amt-17-5429-2024
- Decadal Methane Emission Trend Inferred from Proxy GOSAT XCH4 Retrievals: Impacts of Transport Model Spatial Resolution S. Zhu et al. 10.1007/s00376-022-1434-6
- Information content analysis: the potential for methane isotopologue retrieval from GOSAT-2 E. Malina et al. 10.5194/amt-11-1159-2018
- 2010–2016 methane trends over Canada, the United States, and Mexico observed by the GOSAT satellite: contributions from different source sectors J. Sheng et al. 10.5194/acp-18-12257-2018
- Interannual Variability of Atmospheric CH4 and Its Driver Over South Korea Captured by Integrated Data in 2019 S. Kenea et al. 10.3390/rs13122266
- Characterizing model errors in chemical transport modeling of methane: impact of model resolution in versions v9-02 of GEOS-Chem and v35j of its adjoint model I. Stanevich et al. 10.5194/gmd-13-3839-2020
- Bias Correction of the Ratio of Total Column CH4 to CO2 Retrieved from GOSAT Spectra H. Oshio et al. 10.3390/rs12193155
- An integrated analysis of contemporary methane emissions and concentration trends over China using in situ and satellite observations and model simulations H. Tan et al. 10.5194/acp-22-1229-2022
- Attribution of the accelerating increase in atmospheric methane during 2010–2018 by inverse analysis of GOSAT observations Y. Zhang et al. 10.5194/acp-21-3643-2021
- A decade of GOSAT Proxy satellite CH<sub>4</sub> observations R. Parker et al. 10.5194/essd-12-3383-2020
- A simple and quick sensitivity analysis method for methane isotopologues detection with GOSAT-TANSO-FTS E. Malina et al. 10.14324/111.444/ucloe.000013
- Evaluation of wetland CH4in the Joint UK Land Environment Simulator (JULES) land surface model using satellite observations R. Parker et al. 10.5194/bg-19-5779-2022
- A new algorithm to generate a priori trace gas profiles for the GGG2020 retrieval algorithm J. Laughner et al. 10.5194/amt-16-1121-2023
- Assimilation of GOSAT Methane in the Hemispheric CMAQ; Part I: Design of the Assimilation System S. Voshtani et al. 10.3390/rs14020371
- Consistent regional fluxes of CH<sub>4</sub> and CO<sub>2</sub> inferred from GOSAT proxy XCH<sub>4</sub> : XCO<sub>2</sub> retrievals, 2010–2014 L. Feng et al. 10.5194/acp-17-4781-2017
- Atmospheric data support a multi-decadal shift in the global methane budget towards natural tropical emissions A. Drinkwater et al. 10.5194/acp-23-8429-2023
- Estimating 2010–2015 anthropogenic and natural methane emissions in Canada using ECCC surface and GOSAT satellite observations S. Baray et al. 10.5194/acp-21-18101-2021
- Satellite observations of atmospheric methane and their value for quantifying methane emissions D. Jacob et al. 10.5194/acp-16-14371-2016
- Methane point source quantification using MethaneAIR: a new airborne imaging spectrometer A. Chulakadabba et al. 10.5194/amt-16-5771-2023
- Role of regional wetland emissions in atmospheric methane variability J. McNorton et al. 10.1002/2016GL070649
- Exploring constraints on a wetland methane emission ensemble (WetCHARTs) using GOSAT observations R. Parker et al. 10.5194/bg-17-5669-2020
- Inverse modeling of GOSAT-retrieved ratios of total column CH<sub>4</sub> and CO<sub>2</sub> for 2009 and 2010 S. Pandey et al. 10.5194/acp-16-5043-2016
- Quantifying sources of Brazil's CH<sub>4</sub> emissions between 2010 and 2018 from satellite data R. Tunnicliffe et al. 10.5194/acp-20-13041-2020
- 2010–2015 North American methane emissions, sectoral contributions, and trends: a high-resolution inversion of GOSAT observations of atmospheric methane J. Maasakkers et al. 10.5194/acp-21-4339-2021
- A measurement-based verification framework for UK greenhouse gas emissions: an overview of the Greenhouse gAs Uk and Global Emissions (GAUGE) project P. Palmer et al. 10.5194/acp-18-11753-2018
- Attribution of recent increases in atmospheric methane through 3-D inverse modelling J. McNorton et al. 10.5194/acp-18-18149-2018
- Advancing Scientific Understanding of the Global Methane Budget in Support of the Paris Agreement A. Ganesan et al. 10.1029/2018GB006065
- Reevaluating the Use of O2 a1Δg Band in Spaceborne Remote Sensing of Greenhouse Gases K. Sun et al. 10.1029/2018GL077823
- Atmospheric CH<sub>4</sub> and CO<sub>2</sub> enhancements and biomass burning emission ratios derived from satellite observations of the 2015 Indonesian fire plumes R. Parker et al. 10.5194/acp-16-10111-2016
- Global inverse modeling of CH<sub>4</sub> sources and sinks: an overview of methods S. Houweling et al. 10.5194/acp-17-235-2017
- Remote sensing of methane plumes: instrument tradeoff analysis for detecting and quantifying local sources at global scale S. Jongaramrungruang et al. 10.5194/amt-14-7999-2021
- Tropical methane emissions explain large fraction of recent changes in global atmospheric methane growth rate L. Feng et al. 10.1038/s41467-022-28989-z
- Global height-resolved methane retrievals from the Infrared Atmospheric Sounding Interferometer (IASI) on MetOp R. Siddans et al. 10.5194/amt-10-4135-2017
- Accelerating methane growth rate from 2010 to 2017: leading contributions from the tropics and East Asia Y. Yin et al. 10.5194/acp-21-12631-2021
- East Asian methane emissions inferred from high-resolution inversions of GOSAT and TROPOMI observations: a comparative and evaluative analysis R. Liang et al. 10.5194/acp-23-8039-2023
- Reduced-cost construction of Jacobian matrices for high-resolution inversions of satellite observations of atmospheric composition H. Nesser et al. 10.5194/amt-14-5521-2021
- Satellite-derived methane hotspot emission estimates using a fast data-driven method M. Buchwitz et al. 10.5194/acp-17-5751-2017
- An increase in methane emissions from tropical Africa between 2010 and 2016 inferred from satellite data M. Lunt et al. 10.5194/acp-19-14721-2019
- Toward High Precision XCO2Retrievals From TanSat Observations: Retrieval Improvement and Validation Against TCCON Measurements D. Yang et al. 10.1029/2020JD032794
- Atmospheric observations show accurate reporting and little growth in India’s methane emissions A. Ganesan et al. 10.1038/s41467-017-00994-7
- Evaluation of column-averaged methane in models and TCCON with a focus on the stratosphere A. Ostler et al. 10.5194/amt-9-4843-2016
1 citations as recorded by crossref.
Saved (final revised paper)
Saved (preprint)
Latest update: 23 Nov 2024
Short summary
Atmospheric CH4 is an important greenhouse gas. Long-term global observations are necessary to understand its behaviour, with satellite observations playing a key role. The "proxy" retrieval method is one of the most successful but relies on the contribution from atmospheric CO2 models. This work assesses the significance of the uncertainty from the model CO2 within the retrieval and determines that despite this uncertainty the data are still valuable for determining sources and sinks of CH4.
Atmospheric CH4 is an important greenhouse gas. Long-term global observations are necessary to...
