Articles | Volume 12, issue 4
https://doi.org/10.5194/essd-12-3383-2020
© 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/essd-12-3383-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
14 Dec 2020
Data description paper |
| 14 Dec 2020
| 14 Dec 2020
A decade of GOSAT Proxy satellite CH4 observations
National Centre for Earth Observation, University of Leicester, Leicester, UK
Earth Observation Science, School of Physics and Astronomy, University of Leicester, Leicester, UK
Alex Webb
National Centre for Earth Observation, University of Leicester, Leicester, UK
Earth Observation Science, School of Physics and Astronomy, University of Leicester, Leicester, UK
Hartmut Boesch
National Centre for Earth Observation, University of Leicester, Leicester, UK
Earth Observation Science, School of Physics and Astronomy, University of Leicester, Leicester, UK
Peter Somkuti
Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO, USA
Rocio Barrio Guillo
National Centre for Earth Observation, University of Leicester, Leicester, UK
Earth Observation Science, School of Physics and Astronomy, University of Leicester, Leicester, UK
Antonio Di Noia
Earth Observation Science, School of Physics and Astronomy, University of Leicester, Leicester, UK
Nikoleta Kalaitzi
National Centre for Earth Observation, University of Leicester, Leicester, UK
Earth Observation Science, School of Physics and Astronomy, University of Leicester, Leicester, UK
Jasdeep S. Anand
Earth Observation Science, School of Physics and Astronomy, University of Leicester, Leicester, UK
Peter Bergamaschi
European Commission Joint Research Centre, Ispra (Va), Italy
Frederic Chevallier
Laboratoire des Sciences du Climat et de L'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
Paul I. Palmer
School of GeoSciences, University of Edinburgh, Edinburgh, Scotland, UK
National Centre for Earth Observation, University of Edinburgh, Edinburgh, Scotland, UK
Liang Feng
School of GeoSciences, University of Edinburgh, Edinburgh, Scotland, UK
National Centre for Earth Observation, University of Edinburgh, Edinburgh, Scotland, UK
Nicholas M. Deutscher
Centre for Atmospheric Chemistry, School of Earth, Atmospheric and Life Sciences, University of Wollongong, Wollongong, NSW 2522, Australia
Dietrich G. Feist
Ludwig-Maximilians-Universität München, Lehrstuhl für Physik der Atmosphäre, Munich, Germany
Deutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
Max Planck Institute for Biogeochemistry, Jena, Germany
David W. T. Griffith
Centre for Atmospheric Chemistry, School of Earth, Atmospheric and Life Sciences, University of Wollongong, Wollongong, NSW 2522, Australia
Frank Hase
Karlsruhe Institute of Technology, IMK-ASF, Karlsruhe, Germany
Rigel Kivi
Space and Earth Observation Centre, Finnish Meteorological Institute, Sodankylä, Finland
Isamu Morino
National Institute for Environmental Studies (NIES), Tsukuba, Japan
Justus Notholt
Institute of Environmental Physics, University of Bremen, Bremen, Germany
Young-Suk Oh
Climate Research Division, National Institute of Meteorological Sciences (NIMS), Jeju-do 63568, Republic of Korea
Hirofumi Ohyama
National Institute for Environmental Studies (NIES), Tsukuba, Japan
Christof Petri
Institute of Environmental Physics, University of Bremen, Bremen, Germany
David F. Pollard
National Institute of Water and Atmospheric Research Ltd (NIWA), Lauder, New Zealand
Coleen Roehl
California Institute of Technology, Pasadena, CA 91125, USA
Mahesh K. Sha
Royal Belgian Institute for Space Aeronomy (BIRA-IASB), Brussels, Belgium
Kei Shiomi
Earth Observation Research Center, Japan Aerospace Exploration Agency, Tsukuba, Japan
Kimberly Strong
Department of Physics, University of Toronto, Toronto, ON M5S 1A7, Canada
Ralf Sussmann
Karlsruhe Institute of Technology, IMK-IFU, Garmisch-Partenkirchen, Germany
Laboratoire d'Etudes du Rayonnement et de la Matière en Astrophysique et Atmosphères (LERMA-IPSL), Sorbonne Université, CNRS, Observatoire de Paris, PSL Université, 75005 Paris, France
Voltaire A. Velazco
Centre for Atmospheric Chemistry, School of Earth, Atmospheric and Life Sciences, University of Wollongong, Wollongong, NSW 2522, Australia
Thorsten Warneke
Institute of Environmental Physics, University of Bremen, Bremen, Germany
Paul O. Wennberg
California Institute of Technology, Pasadena, CA 91125, USA
Debra Wunch
Department of Physics, University of Toronto, Toronto, Canada
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- Methane emissions in the United States, Canada, and Mexico: evaluation of national methane emission inventories and 2010–2017 sectoral trends by inverse analysis of in situ (GLOBALVIEWplus CH4 ObsPack) and satellite (GOSAT) atmospheric observations X. Lu et al. 10.5194/acp-22-395-2022
- Global distribution of methane emissions: a comparative inverse analysis of observations from the TROPOMI and GOSAT satellite instruments Z. Qu et al. 10.5194/acp-21-14159-2021
- Observed changes in China’s methane emissions linked to policy drivers Y. Zhang et al. 10.1073/pnas.2202742119
- New evidence for CH4 enhancement in the upper troposphere associated with the Asian summer monsoon M. Tao et al. 10.1088/1748-9326/ad2738
- Short-term trend and temporal variations in atmospheric methane at an Atlantic coastal site in Southwestern Europe R. Padilla et al. 10.1016/j.atmosenv.2024.120665
- Integrated Methane Inversion (IMI) 2.0: an improved research and stakeholder tool for monitoring total methane emissions with high resolution worldwide using TROPOMI satellite observations L. Estrada et al. 10.5194/gmd-18-3311-2025
- 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
- Retrieval of Atmospheric XCH4 via XGBoost Method Based on TROPOMI Satellite Data W. Zhang et al. 10.3390/atmos16030279
- Interannual Variability of Atmospheric CH4 and Its Driver Over South Korea Captured by Integrated Data in 2019 S. Kenea et al. 10.3390/rs13122266
- Satellite quantification of methane emissions and oil–gas methane intensities from individual countries in the Middle East and North Africa: implications for climate action Z. Chen et al. 10.5194/acp-23-5945-2023
- Global Methane Budget 2000–2020 M. Saunois et al. 10.5194/essd-17-1873-2025
- 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
- Accounting for the effect of aerosols in GHGSat methane retrieval Q. Yu et al. 10.5194/amt-17-3347-2024
- Where to place methane monitoring sites in China to better assist carbon management X. Zhang et al. 10.1038/s41612-023-00359-6
- Monitoring greenhouse gases (GHGs) in China: status and perspective Y. Sun et al. 10.5194/amt-15-4819-2022
- 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
- Rain-fed pulses of methane from East Africa during 2018–2019 contributed to atmospheric growth rate M. Lunt et al. 10.1088/1748-9326/abd8fa
- Influences of Uncertainties in the STT Flux on Modeled Tropospheric Methane Z. Wang 10.1029/2023JD039107
6 citations as recorded by crossref.
- A decade of GOSAT Proxy satellite CH4 observations R. Parker et al. 10.5194/essd-12-3383-2020
- Methane Growth Rate Estimation and Its Causes in Western Canada Using Satellite Observations S. Islam et al. 10.1029/2020JD033948
- 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
- Exploring constraints on a wetland methane emission ensemble (WetCHARTs) using GOSAT observations R. Parker et al. 10.5194/bg-17-5669-2020
- Decadal Changes in Atmospheric Methane Emissions in the Eastern Himalayan Region: Source Apportionment and Impact Assessment A. Saikia et al. 10.1007/s41742-022-00501-x
- Satellite Constraints on the Latitudinal Distribution and Temperature Sensitivity of Wetland Methane Emissions S. Ma et al. 10.1029/2021AV000408
Latest update: 09 Jul 2025
Short summary
This work presents the latest release of the University of Leicester GOSAT methane data and acts as the definitive description of this dataset. We detail the processing, validation and evaluation involved in producing these data and highlight its many applications. With now over a decade of global atmospheric methane observations, this dataset has helped, and will continue to help, us better understand the global methane budget and investigate how it may respond to a future changing climate.
This work presents the latest release of the University of Leicester GOSAT methane data and acts...
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