Articles | Volume 14, issue 5
https://doi.org/10.5194/amt-14-3837-2021
© Author(s) 2021. 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-14-3837-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
26 May 2021
Research article |
| 26 May 2021
| 26 May 2021
XCO2 retrieval for GOSAT and GOSAT-2 based on 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
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
Hiroshi Suto
Japan Aerospace Exploration Agency (JAXA), 305-8505, Tsukuba, Japan
Yukio Yoshida
National Institute for Environmental Studies (NIES), 305-8506, Tsukuba, 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, 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, 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
Isamu Morino
National Institute for Environmental Studies (NIES), 305-8506, Tsukuba, Japan
Justus Notholt
Institute of Environmental Physics, University of Bremen, FB 1, P.O. Box 330440, 28334 Bremen, Germany
Hirofumi Ohyama
National Institute for Environmental Studies (NIES), 305-8506, Tsukuba, Japan
Christof Petri
Institute of Environmental Physics, University of Bremen, FB 1, P.O. Box 330440, 28334 Bremen, Germany
James R. Podolske
NASA Ames Research Center, Atmospheric Science Branch, Moffett Field, CA 94035, USA
David F. Pollard
National Institute of Water and Atmospheric Research Ltd (NIWA), Lauder,Private Bag 50061, Omakau 9352, New Zealand
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
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, Australia
now at: Deutscher Wetterdienst, Meteorological Observatory, 82383 Hohenpeissenberg, Germany
Thorsten Warneke
Institute of Environmental Physics, University of Bremen, FB 1, P.O. Box 330440, 28334 Bremen, Germany
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- Global estimates of gap-free and fine-scale CO2 concentrations during 2014–2020 from satellite and reanalysis data L. Zhang et al. 10.1016/j.envint.2023.108057
- A long-term global XCO2 dataset: Ensemble of satellite products C. Jin et al. 10.1016/j.atmosres.2022.106385
- 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
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- Atmospheric Greenhouse Gas Distributions: Satellite-Based Measurements A. Uspensky 10.1134/S0001433823140141
- Atmospheric CO2retrieval from satellite spectral measurements by a two-step machine learning approach Z. Zhao et al. 10.1016/j.jqsrt.2021.108006
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- Can a regional-scale reduction of atmospheric CO<sub>2</sub> during the COVID-19 pandemic be detected from space? A case study for East China using satellite XCO<sub>2</sub> retrievals M. Buchwitz et al. 10.5194/amt-14-2141-2021
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- Spectroscopic techniques conceptualized with the remote sensing of atmospheric carbon dioxide and other greenhouse gases B. Raychaudhuri 10.1080/05704928.2024.2326527
- Spectral Calibration of the Spectrometer on Board the Colombian FACSAT-2 Satellite Mission L. Cárdenas Espinosa et al. 10.3390/rs16193674
- Global estimates of gap-free and fine-scale CO2 concentrations during 2014–2020 from satellite and reanalysis data L. Zhang et al. 10.1016/j.envint.2023.108057
- A long-term global XCO2 dataset: Ensemble of satellite products C. Jin et al. 10.1016/j.atmosres.2022.106385
- 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
- Review of Satellite Remote Sensing of Carbon Dioxide Inversion and Assimilation K. Hu et al. 10.3390/rs16183394
- Generating daily high-resolution and full-coverage XCO2 across China from 2015 to 2020 based on OCO-2 and CAMS data T. Li et al. 10.1016/j.scitotenv.2023.164921
- Mapping the CO2 total column retrieval performance from shortwave infrared measurements: synthetic impacts of the spectral resolution, signal-to-noise ratio, and spectral band selection M. Dogniaux & C. Crevoisier 10.5194/amt-17-5373-2024
- Update on the GOSAT TANSO–FTS SWIR Level 2 retrieval algorithm Y. Someya et al. 10.5194/amt-16-1477-2023
- Spatio-temporal variation of atmospheric CO2 and its association with anthropogenic, vegetation, and climate indices over the state of Bihar, India A. Dass et al. 10.1016/j.envadv.2024.100513
- The importance of digital elevation model accuracy in XCO2 retrievals: improving the Orbiting Carbon Observatory 2 Atmospheric Carbon Observations from Space version 11 retrieval product N. Jacobs et al. 10.5194/amt-17-1375-2024
- An assessment of China's industrial emission characteristics using satellite observations of XCO2, SO2, and NO2 Y. Fu et al. 10.1016/j.apr.2022.101486
- Retrieval of greenhouse gases from GOSAT and GOSAT-2 using the FOCAL algorithm S. Noël et al. 10.5194/amt-15-3401-2022
- Atmospheric Greenhouse Gas Distributions: Satellite-Based Measurements A. Uspensky 10.1134/S0001433823140141
- Atmospheric CO2retrieval from satellite spectral measurements by a two-step machine learning approach Z. Zhao et al. 10.1016/j.jqsrt.2021.108006
- 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
- Potential of solar-induced chlorophyll fluorescence (SIF) to access long-term dynamics of soil salinity using OCO-2 satellite data and machine learning method R. Du et al. 10.1016/j.geoderma.2024.116855
- 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
Latest update: 23 Nov 2024
Short summary
We present the first GOSAT and GOSAT-2 XCO2 data derived with the FOCAL retrieval algorithm. Comparisons of the GOSAT-FOCAL product with other data reveal long-term agreement within about 1 ppm over 1 decade, differences in seasonal variations of about 0.5 ppm, and a mean regional bias to ground-based TCCON data of 0.56 ppm with a mean scatter of 1.89 ppm. GOSAT-2-FOCAL data are preliminary only, but first comparisons show that they compare well with the GOSAT-FOCAL results and TCCON.
We present the first GOSAT and GOSAT-2 XCO2 data derived with the FOCAL retrieval algorithm....
