Articles | Volume 15, issue 11
https://doi.org/10.5194/amt-15-3401-2022
© Author(s) 2022. 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-15-3401-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
09 Jun 2022
Research article |
| 09 Jun 2022
| 09 Jun 2022
Retrieval of greenhouse gases from GOSAT and GOSAT-2 using the FOCAL algorithm
Stefan Noël
CORRESPONDING AUTHOR
Institute of Environmental Physics, University of Bremen,
FB 1, P.O. Box 330440, 28334 Bremen, Germany
Maximilian Reuter
Institute of Environmental Physics, University of Bremen,
FB 1, P.O. Box 330440, 28334 Bremen, Germany
Michael Buchwitz
Institute of Environmental Physics, University of Bremen,
FB 1, P.O. Box 330440, 28334 Bremen, Germany
Jakob Borchardt
Institute of Environmental Physics, University of Bremen,
FB 1, P.O. Box 330440, 28334 Bremen, Germany
Michael Hilker
Institute of Environmental Physics, University of Bremen,
FB 1, P.O. Box 330440, 28334 Bremen, Germany
Oliver Schneising
Institute of Environmental Physics, University of Bremen,
FB 1, P.O. Box 330440, 28334 Bremen, Germany
Heinrich Bovensmann
Institute of Environmental Physics, University of Bremen,
FB 1, P.O. Box 330440, 28334 Bremen, Germany
John P. Burrows
Institute of Environmental Physics, University of Bremen,
FB 1, P.O. Box 330440, 28334 Bremen, Germany
Antonio Di Noia
Earth Observation Science, University of Leicester, LE1 7RH,
Leicester, UK
Robert J. Parker
Earth Observation Science, University of Leicester, LE1 7RH,
Leicester, UK
National Centre for Earth Observation, University of Leicester, Leicester, UK
Hiroshi Suto
Japan Aerospace Exploration Agency (JAXA), 305-8505, Tsukuba, Japan
Yukio Yoshida
National Institute for Environmental Studies (NIES), Onogawa 16-2, Tsukuba, Ibaraki 305-8506, Japan
Matthias Buschmann
Institute of Environmental Physics, University of Bremen,
FB 1, P.O. Box 330440, 28334 Bremen, Germany
Nicholas M. Deutscher
Centre for Atmospheric Chemistry, School of Earth, Atmospheric and Life Sciences, University of Wollongong, NSW 2522, Wollongong, Australia
Dietrich G. Feist
Max Planck Institute for Biogeochemistry, 07745 Jena, Germany
Deutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, 82234 Oberpfaffenhofen, Germany
Ludwig-Maximilians-Universität München, Lehrstuhl für Physik der Atmosphäre, 80539 Munich, Germany
David W. T. Griffith
Centre for Atmospheric Chemistry, School of Earth, Atmospheric and Life Sciences, University of Wollongong, NSW 2522, Wollongong, Australia
Frank Hase
Karlsruhe Institute of Technology, IMK-ASF, 76021 Karlsruhe, Germany
Rigel Kivi
Finnish Meteorological Institute, Space and Earth Observation Centre, Tähteläntie 62, 99600 Sodankylä, Finland
Cheng Liu
Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, 230026 Hefei, China
Isamu Morino
National Institute for Environmental Studies (NIES), Onogawa 16-2, Tsukuba, Ibaraki 305-8506, Japan
Justus Notholt
Institute of Environmental Physics, University of Bremen,
FB 1, P.O. Box 330440, 28334 Bremen, Germany
Young-Suk Oh
Global Atmosphere Watch Team, Innovative Meteorological Research Department, National Institute of Meteorological Sciences, 3 Seohobuk-ro, Seogwipo-si, Jeju-do, Republic of Korea
Hirofumi Ohyama
National Institute for Environmental Studies (NIES), Onogawa 16-2, Tsukuba, Ibaraki 305-8506, Japan
Christof Petri
Institute of Environmental Physics, University of Bremen,
FB 1, P.O. Box 330440, 28334 Bremen, Germany
David F. Pollard
National Institute of Water and Atmospheric Research Ltd (NIWA), Lauder, Private Bag 50061, Omakau 9352, New Zealand
Markus Rettinger
Karlsruhe Institute of Technology, IMK-IFU, 82467 Garmisch-Partenkirchen, Germany
Coleen Roehl
California Institute of Technology, Global Environmental
Center, Pasadena, CA 91125, USA
Constantina Rousogenous
Climate and Atmosphere Research Center (CARE-C), The Cyprus Institute, Nicosia, Cyprus
Mahesh Kumar Sha
Royal Belgian Institute for Space Aeronomy (BIRA-IASB), 1180 Brussels, Belgium
Kei Shiomi
Japan Aerospace Exploration Agency (JAXA), 305-8505, Tsukuba, Japan
Kimberly Strong
Department of Physics, University of Toronto, Toronto, ON, M5S 1A7, Canada
Ralf Sussmann
Karlsruhe Institute of Technology, IMK-IFU, 82467 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, NSW 2522, Wollongong, Australia
Deutscher Wetterdienst, Meteorological Observatory, 82383 Hohenpeissenberg, Germany
Mihalis Vrekoussis
Climate and Atmosphere Research Center (CARE-C), The Cyprus Institute, Nicosia, Cyprus
Institute of Environmental Physics, University of Bremen,
FB 1, P.O. Box 330440, 28334 Bremen, Germany
Center of Marine Environmental Sciences (MARUM), University of Bremen, Bremen, Germany
Thorsten Warneke
Institute of Environmental Physics, University of Bremen,
FB 1, P.O. Box 330440, 28334 Bremen, Germany
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Cited
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- Evaluating the performance of carbon dioxide and methane observations from carbon-monitoring satellite products over China X. Hong et al. 10.1016/j.scitotenv.2024.176896
- Methane Retrieval Algorithms Based on Satellite: A Review Y. Jiang et al. 10.3390/atmos15040449
- Global carbon monoxide retrieval from the hyperspectral infrared atmospheric sounder-II onboard FengYun-3E in a dawn-dusk sun-synchronous orbit Z. Zeng 10.1016/j.jqsrt.2024.109336
- Predictions of failed satellite retrieval of air quality using machine learning E. Malina et al. 10.5194/amt-18-1689-2025
- Seasonal and Diurnal Variations in XCO2 Characteristics in China as Observed by OCO‐2/3 Satellites: Effects of Land Cover and Local Meteorology H. Zhao et al. 10.1029/2023JD038841
- Improving Methane Point Sources Detection Over Heterogeneous Land Surface for Satellite Hyperspectral Imagery E. Sun et al. 10.1109/JSTARS.2024.3482278
- Local and regional enhancements of CH4, CO, and CO2 inferred from TCCON column measurements K. Mottungan et al. 10.5194/amt-17-5861-2024
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- First TanSat CO2 retrieval over land and ocean using both nadir and glint spectroscopy X. Hong et al. 10.1016/j.rse.2024.114053
- Updating the carbon dioxide line list in HITEMP R. Hargreaves et al. 10.1016/j.jqsrt.2024.109324
- 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
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- Retrieving the atmospheric concentrations of carbon dioxide and methane from the European Copernicus CO2M satellite mission using artificial neural networks M. Reuter et al. 10.5194/amt-18-241-2025
- A nonlinear data-driven approach to bias correction of XCO2 for NASA's OCO-2 ACOS version 10 W. Keely et al. 10.5194/amt-16-5725-2023
- TROPESS-CrIS CO single-pixel vertical profiles: intercomparisons with MOPITT and model simulations for 2020 western US wildfires M. Luo et al. 10.5194/amt-17-2611-2024
- The Greenhouse gas Observations of Biospheric and Local Emissions from the Upper sky (GOBLEU): a mission overview, instrument description, and results from the first flight H. Suto et al. 10.1186/s13021-024-00273-1
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24 citations as recorded by crossref.
- Diurnal Carbon Monoxide Retrieval from FY-4B/GIIRS Using a Novel Machine Learning Method Z. Liang et al. 10.34133/remotesensing.0289
- Multi-sensor integrated mapping of global XCO2 from 2015 to 2021 with a local random forest model J. Chen et al. 10.1016/j.isprsjprs.2024.01.009
- Quantification of CO2 Emissions from Three Power Plants in China Using OCO-3 Satellite Measurements Y. Yang et al. 10.1007/s00376-024-3293-9
- Advances in retrieving XCH4 and XCO from Sentinel-5 Precursor: improvements in the scientific TROPOMI/WFMD algorithm O. Schneising et al. 10.5194/amt-16-669-2023
- Evaluating the performance of carbon dioxide and methane observations from carbon-monitoring satellite products over China X. Hong et al. 10.1016/j.scitotenv.2024.176896
- Methane Retrieval Algorithms Based on Satellite: A Review Y. Jiang et al. 10.3390/atmos15040449
- Global carbon monoxide retrieval from the hyperspectral infrared atmospheric sounder-II onboard FengYun-3E in a dawn-dusk sun-synchronous orbit Z. Zeng 10.1016/j.jqsrt.2024.109336
- Predictions of failed satellite retrieval of air quality using machine learning E. Malina et al. 10.5194/amt-18-1689-2025
- Seasonal and Diurnal Variations in XCO2 Characteristics in China as Observed by OCO‐2/3 Satellites: Effects of Land Cover and Local Meteorology H. Zhao et al. 10.1029/2023JD038841
- Improving Methane Point Sources Detection Over Heterogeneous Land Surface for Satellite Hyperspectral Imagery E. Sun et al. 10.1109/JSTARS.2024.3482278
- Local and regional enhancements of CH4, CO, and CO2 inferred from TCCON column measurements K. Mottungan et al. 10.5194/amt-17-5861-2024
- Quantifying methane emissions from the global scale down to point sources using satellite observations of atmospheric methane D. Jacob et al. 10.5194/acp-22-9617-2022
- 基于国产碳卫星的在轨光谱性能评估及大气二氧化碳的高精度反演（特邀） 洪. Hong Xinhua et al. 10.3788/AOS241153
- Diurnal carbon monoxide observed from a geostationary infrared hyperspectral sounder: first result from GIIRS on board FengYun-4B Z. Zeng et al. 10.5194/amt-16-3059-2023
- Based on the Feedforward Inputs Obtained by the Intelligent Algorithm the Moving Mirror Control System of the Fourier Transform Spectrometer Y. Huang et al. 10.3390/electronics12224568
- First TanSat CO2 retrieval over land and ocean using both nadir and glint spectroscopy X. Hong et al. 10.1016/j.rse.2024.114053
- Updating the carbon dioxide line list in HITEMP R. Hargreaves et al. 10.1016/j.jqsrt.2024.109324
- 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
- 大气环境监测卫星星载IPDA激光雷达的大气二氧化碳柱浓度反演及多源数据对比验证 赖. Lai Kaijie et al. 10.3788/AOS231797
- Retrieving the atmospheric concentrations of carbon dioxide and methane from the European Copernicus CO2M satellite mission using artificial neural networks M. Reuter et al. 10.5194/amt-18-241-2025
- A nonlinear data-driven approach to bias correction of XCO2 for NASA's OCO-2 ACOS version 10 W. Keely et al. 10.5194/amt-16-5725-2023
- TROPESS-CrIS CO single-pixel vertical profiles: intercomparisons with MOPITT and model simulations for 2020 western US wildfires M. Luo et al. 10.5194/amt-17-2611-2024
- The Greenhouse gas Observations of Biospheric and Local Emissions from the Upper sky (GOBLEU): a mission overview, instrument description, and results from the first flight H. Suto et al. 10.1186/s13021-024-00273-1
- Greenhouse gas retrievals for the CO2M mission using the FOCAL method: first performance estimates S. Noël et al. 10.5194/amt-17-2317-2024
Latest update: 23 Apr 2025
Short summary
We present a new version (v3) of the GOSAT and GOSAT-2 FOCAL products.
In addition to an increased number of XCO2 data, v3 also includes products for XCH4 (full-physics and proxy), XH2O and the relative ratio of HDO to H2O (δD). For GOSAT-2, we also present first XCO and XN2O results. All FOCAL data products show reasonable spatial distribution and temporal variations and agree well with TCCON. Global XN2O maps show a gradient from the tropics to higher latitudes on the order of 15 ppb.
We present a new version (v3) of the GOSAT and GOSAT-2 FOCAL products.
In addition to an...
