We present first GOSAT and GOSAT-2 XCO2 data derived with the FOCAL retrieval algorithm.
Comparisons of the GOSAT FOCAL product with other data reveal a long-term agreement within about 1 ppm over one 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 considered to be preliminary only, but first comparisons show that they compare well with the GOSAT FOCAL results.
We present first GOSAT and GOSAT-2 XCO2 data derived with the FOCAL retrieval...
Review status: this preprint is currently under review for the journal AMT.
XCO2 retrieval for GOSAT and GOSAT-2 based on the FOCAL algorithm
Stefan Noël1,Maximilian Reuter1,Michael Buchwitz1,Jakob Borchardt1,Michael Hilker1,Heinrich Bovensmann1,John P. Burrows1,Antonio Di Noia2,Hiroshi Suto3,Yukio Yoshida4,Matthias Buschmann1,Nicholas M. Deutscher5,Dietrich G. Feist6,7,8,David W. T. Griffith5,Frank Hase9,Rigel Kivi10,Isamu Morino4,Justus Notholt1,Hirofumi Ohyama4,Christof Petri1,James R. Podolske11,David F. Pollard12,Mahesh Kumar Sha13,Kei Shiomi3,Ralf Sussmann14,Yao Té15,Voltaire A. Velazco5,and Thorsten Warneke1Stefan Noël et al.Stefan Noël1,Maximilian Reuter1,Michael Buchwitz1,Jakob Borchardt1,Michael Hilker1,Heinrich Bovensmann1,John P. Burrows1,Antonio Di Noia2,Hiroshi Suto3,Yukio Yoshida4,Matthias Buschmann1,Nicholas M. Deutscher5,Dietrich G. Feist6,7,8,David W. T. Griffith5,Frank Hase9,Rigel Kivi10,Isamu Morino4,Justus Notholt1,Hirofumi Ohyama4,Christof Petri1,James R. Podolske11,David F. Pollard12,Mahesh Kumar Sha13,Kei Shiomi3,Ralf Sussmann14,Yao Té15,Voltaire A. Velazco5,and Thorsten Warneke1
1Institute of Environmental Physics, University of Bremen, FB 1, P.O. Box 330440, 28334 Bremen, Germany
2Earth Observation Science, University of Leicester, LE1 7RH, Leicester, UK
3Japan Aerospace Exploration Agency (JAXA), 305-8505, Tsukuba, Japan
4National Institute for Environmental Studies (NIES), 305-8506, Tsukuba, Japan
5Centre for Atmospheric Chemistry, School of Earth, Atmospheric and Life Sciences, University of Wollongong NSW 2522 Australia
6Max Planck Institute for Biogeochemistry, Jena, Germany
7Deutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
8Ludwig-Maximilians-Universität München, Lehrstuhl für Physik der Atmosphäre, Munich, Germany
9Karlsruhe Institute of Technology, IMK-ASF, Karlsruhe, Germany
10Finnish Meteorological Institute, Space and Earth Observation Centre, Tähteläntie 62, 99600 Sodankylä, Finland
11NASA Ames Research Center, Atmospheric Science Branch, Moffett Field, CA 94035, USA
12National Institute of Water and Atmospheric Research Ltd (NIWA), Lauder, New Zealand
13Royal Belgian Institute for Space Aeronomy (BIRA-IASB), Brussels, Belgium
14Karlsruhe Institute of Technology, IMK-IFU, Garmisch-Partenkirchen, Germany
15Laboratoire 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
1Institute of Environmental Physics, University of Bremen, FB 1, P.O. Box 330440, 28334 Bremen, Germany
2Earth Observation Science, University of Leicester, LE1 7RH, Leicester, UK
3Japan Aerospace Exploration Agency (JAXA), 305-8505, Tsukuba, Japan
4National Institute for Environmental Studies (NIES), 305-8506, Tsukuba, Japan
5Centre for Atmospheric Chemistry, School of Earth, Atmospheric and Life Sciences, University of Wollongong NSW 2522 Australia
6Max Planck Institute for Biogeochemistry, Jena, Germany
7Deutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
8Ludwig-Maximilians-Universität München, Lehrstuhl für Physik der Atmosphäre, Munich, Germany
9Karlsruhe Institute of Technology, IMK-ASF, Karlsruhe, Germany
10Finnish Meteorological Institute, Space and Earth Observation Centre, Tähteläntie 62, 99600 Sodankylä, Finland
11NASA Ames Research Center, Atmospheric Science Branch, Moffett Field, CA 94035, USA
12National Institute of Water and Atmospheric Research Ltd (NIWA), Lauder, New Zealand
13Royal Belgian Institute for Space Aeronomy (BIRA-IASB), Brussels, Belgium
14Karlsruhe Institute of Technology, IMK-IFU, Garmisch-Partenkirchen, Germany
15Laboratoire 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
Received: 11 Nov 2020 – Accepted for review: 12 Dec 2020 – Discussion started: 15 Dec 2020
Abstract. Since 2009, the Greenhouse gases Observing SATellite (GOSAT) performs radiance measurements in the shortwave-infrared (SWIR) spectral region. From February 2019 onward, data from GOSAT-2 are also available.
We present first results from the application of the Fast atmOspheric traCe gAs retrieval (FOCAL) algorithm to derive column-averaged dry-air mole fractions of carbon dioxide (XCO2) from GOSAT and GOSAT-2 radiances and their validation. FOCAL has initially been developed for OCO-2 XCO2 retrievals and allows simultaneous retrievals of several gases over both land and ocean. Because FOCAL is accurate and numerically very fast it is currently considered as a candidate algorithm for the forthcoming European anthropogenic CO2 Monitoring (CO2M) mission, to be launched in 2025.
We present the adaptation of FOCAL to GOSAT and discuss the changes made and GOSAT specific additions. This includes particularly modifications in pre-processing (e.g. cloud detection) and post-processing (bias correction and filtering).
A feature of the new application of FOCAL to GOSAT/GOSAT-2 is the independent use of both S and P polarisation spectra in the retrieval. This is not possible for OCO-2, which measures only one polarisation direction. Additionally, we make use of GOSAT’s wider spectral coverage compared to OCO-2 and derive not only XCO2, water vapour (H2O) and solar induced fluorescence (SIF) but also methane (XCH4), with the potential for further atmospheric constituents and parameters like semiheavy water vapour (HDO) and (in the case of GOSAT-2) also carbon monoxide (CO) total columns and possibly nitrous oxide (XN2O).
Here, we concentrate on the new FOCAL XCO2 data products. We describe the generation of the products as well as applied filtering and bias correction procedures. GOSAT-FOCAL XCO2 data have been produced for the time interval 2009 to 2019. Comparisons with other independent GOSAT data sets reveal an agreement of long-term temporal variations within about 1 ppm over one decade; differences in seasonal variations of about 0.5 ppm are observed. Furthermore, we obtain a mean regional bias of the new GOSAT-FOCAL product to the ground based Total Carbon Column Observing Network (TCCON) of 0.56 ppm with a mean scatter of 1.89 ppm.
The GOSAT-2-FOCAL XCO2 product is generated in a similar way as the GOSAT-FOCAL product, but with adapted settings. All GOSAT-2 data until end of 2019 have been processed. Because of this limited time interval, the GOSAT-2 results are considered to be preliminary only, but first comparisons show that these data compare well with the GOSAT-FOCAL results.
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Short summary
We present first GOSAT and GOSAT-2 XCO2 data derived with the FOCAL retrieval algorithm.
Comparisons of the GOSAT FOCAL product with other data reveal a long-term agreement within about 1 ppm over one 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 considered to be preliminary only, but first comparisons show that they compare well with the GOSAT FOCAL results.
We present first GOSAT and GOSAT-2 XCO2 data derived with the FOCAL retrieval...