CaltechAUTHORS
Published June 9, 2022 | Version Published
Journal Article Open

Retrieval of greenhouse gases from GOSAT and GOSAT-2 using the FOCAL algorithm

Creators

  • 1. ROR icon University of Bremen
  • 2. ROR icon University of Leicester
  • 3. ROR icon Japan Aerospace Exploration Agency
  • 4. ROR icon National Institute for Environmental Studies
  • 5. ROR icon University of Wollongong
  • 6. ROR icon Max Planck Institute for Biogeochemistry
  • 7. ROR icon German Aerospace Center
  • 8. ROR icon Ludwig-Maximilians-Universität München
  • 9. ROR icon Karlsruhe Institute of Technology
  • 10. ROR icon Finnish Meteorological Institute
  • 11. ROR icon University of Science and Technology of China
  • 12. ROR icon National Institute of Meteorological Sciences
  • 13. ROR icon National Institute of Water and Atmospheric Research
  • 14. ROR icon California Institute of Technology
  • 15. ROR icon Cyprus Institute
  • 16. ROR icon Royal Belgian Institute for Space Aeronomy
  • 17. ROR icon University of Toronto
  • 18. ROR icon German Meteorological Service

Abstract

We show new results from an updated version of the Fast atmOspheric traCe gAs retrievaL (FOCAL) retrieval method applied to measurements of the Greenhouse gases Observing SATellite (GOSAT) and its successor GOSAT-2. FOCAL was originally developed for estimating the total column carbon dioxide mixing ratio (XCO₂) from spectral measurements made by the Orbiting Carbon Observatory-2 (OCO-2). However, depending on the available spectral windows, FOCAL also successfully retrieves total column amounts for other atmospheric species and their uncertainties within one single retrieval. The main focus of the current paper is on methane (XCH₄; full-physics and proxy product), water vapour (XH₂O) and the relative ratio of semi-heavy water (HDO) to water vapour (δD). Due to the extended spectral range of GOSAT-2, it is also possible to derive information on carbon monoxide (XCO) and nitrous oxide (XN2O) for which we also show first results. We also present an update on XCO₂ from both instruments. For XCO₂, the new FOCAL retrieval (v3.0) significantly increases the number of valid data compared with the previous FOCAL retrieval version (v1) by 50 % for GOSAT and about a factor of 2 for GOSAT-2 due to relaxed pre-screening and improved post-processing. All v3.0 FOCAL data products show reasonable spatial distribution and temporal variations. Comparisons with the Total Carbon Column Observing Network (TCCON) result in station-to-station biases which are generally in line with the reported TCCON uncertainties. With this updated version of the GOSAT-2 FOCAL data, we provide a first total column average XN₂O product. Global XN2O maps show a gradient from the tropics to higher latitudes on the order of 15 ppb, which can be explained by variations in tropopause height. The new GOSAT-2 XN₂O product compares well with TCCON. Its station-to-station variability is lower than 2 ppb, which is about the magnitude of the typical N₂O variations close to the surface. However, both GOSAT-2 and TCCON measurements show that the seasonal variations in the total column average XN₂O are on the order of 8 ppb peak-to-peak, which can be easily resolved by the GOSAT-2 FOCAL data. Noting that only few XN₂O measurements from satellites exist so far, the GOSAT-2 FOCAL product will be a valuable contribution in this context.

Additional Information

© Author(s) 2022. This work is distributed under the Creative Commons Attribution 4.0 License. Received: 08 Feb 2022 – Discussion started: 21 Mar 2022 – Revised: 17 May 2022 – Accepted: 19 May 2022 – Published: 09 Jun 2022. GOSAT and GOSAT-2 spectral data have been provided by JAXA and NIES. CarbonTracker CT2019B and CT-NRT.v2020-1 results were provided by NOAA ESRL, Boulder, Colorado, USA, from the website at http://carbontracker.noaa.gov (last access: 2 June 2022). ABSCO cross sections for CO₂ were provided by NASA and the ACOS/OCO-2 team. GMTED2010 topography data were provided by the U.S. Geological Survey (USGS) and the National Geospatial-Intelligence Agency (NGA). We thank the European Centre for Medium-Range Weather Forecasts (ECMWF) for providing us with analysed meteorological fields (ERA5 data). The GOSAT ACOS v9 Level 2 XCO₂ product from the NASA/OCO-2 team has been obtained from https://oco2.gesdisc.eosdis.nasa.gov/data/GOSAT_TANSO_Level2/ACOS_L2_Lite_FP.9r/, https://doi.org/10.5067/VWSABTO7ZII4 (last access: 16 October 2020). The UoL and SRON GOSAT data products have been obtained from the Copernicus Climate Data Store (https://cds.climate.copernicus.eu/, last assess: 15 October 2020). GOSAT Level 2 data from NIES have been provided by the GOSAT Data Archive Service (GDAS; https://data2.gosat.nies.go.jp/, last access: 17 January 2022). RJP is funded via the UK National Centre for Earth Observation (NE/N018079/1). This research used the ALICE High Performance Computing Facility at the University of Leicester for the UoL GOSAT retrievals. The Paris TCCON site has received funding from Sorbonne Université, the French research centre CNRS, the French space agency CNES and Région Île-de-France. The Réunion station is operated by the Royal Belgian Institute for Space Aeronomy with financial support since 2014 by the EU project ICOS-Inwire and the ministerial decree for ICOS (FR/35/IC1 to FR/35/IC6) as well as local activities supported by LACy/UMR8105 – Université de La Réunion. The TCCON stations at Rikubetsu, Tsukuba and Burgos are supported in part by the GOSAT series project. Local support for Burgos is provided by the Energy Development Corporation (EDC, Philippines). The Eureka measurements were made at the Polar Environment Atmospheric Research Laboratory (PEARL) by the Canadian Network for the Detection of Atmospheric Change (CANDAC), primarily supported by the Natural Sciences and Engineering Research Council of Canada, Environment and Climate Change Canada, and the Canadian Space Agency. The Anmyeondo TCCON station is funded by the Korea Meteorological Administration research and development programme "Development of Monitoring and Analysis Techniques for Atmospheric Composition in Korea" under grant KMA2018-00522. The TCCON Nicosia site has received support from the European Unions' Horizon 2020 research and innovation programme under grant agreement no. 856612 (EMME-CARE), the Cyprus Government, and by the University of Bremen. NMD is supported by an Australian Research Council (ARC) Future Fellowship (FT180100327). The Darwin and Wollongong TCCON sites have been supported by a series of ARC grants, including DP160100598, DP140100552, DP110103118, DP0879468 and LE0668470, and NASA grants NAG5-12247 and NNG05-GD07G. Large parts of the calculations reported here were performed on high-performance computing (HPC) facilities of the IUP, University of Bremen, funded under DFG/FUGG grant INST 144/379-1 and INST 144/493-1. The work was supported by the Copernicus Atmosphere Monitoring Service (CAMS) via project CAMS2-52b. This work has received funding from JAXA (GOSAT and GOSAT-2 support, contracts 19RT000692 and JX-PSPC-527269), EUMETSAT (FOCAL-CO2M study, contract EUM/CO/19/4600002372/RL), ESA (GHG-CCI+ project, contract 4000126450/19/I-NB), and the state and the University of Bremen. This research has been supported by the Japan Aerospace Exploration Agency (grant nos. 19RT000692 and JX-PSPC-527269), the European Organization for the Exploitation of Meteorological Satellites (grant no. EUM/CO/19/4600002372/RL) and the European Space Agency (grant no. 4000126450/19/I-NB). The article processing charges for this open-access publication were covered by the University of Bremen. Author contributions. SN adapted the FOCAL method to GOSAT and GOSAT-2, generated the updated FOCAL data products and performed the validation. MR developed the FOCAL method and provided the XCO2 and XCH4 reference databases and the TCCON validation tools. JPB provided the used Python implementation for the SLIM XCO2 and methane climatology. MH provided the original Python implementation of FOCAL (OCO-2 version). ADN and RJP provided the UoL data, and YY provided the NIES GOSAT data products. The following co-authors provided TCCON data: MB, NMD, DGF, DWTG, FH, RK, CL, YO, IM, JN, HO, CP, DFP, MR, CR, CR, MKS, KS, KS, RS, YT, VAV, MV and TW. All authors provided support in writing the paper. Competing interests. At least one of the (co-)authors is a member of the editorial board of Atmospheric Measurement Techniques. Review statement. This paper was edited by Alexander Kokhanovsky and reviewed by T. E. Taylor and three anonymous referees.

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Additional details

Identifiers

Eprint ID
115728
Resolver ID
CaltechAUTHORS:20220721-8152000

Related works

Describes
https://oco2.gesdisc.eosdis.nasa.gov/data/GOSAT_TANSO_Level2/ACOS_L2_Lite_FP.9r/ (URL)
10.5067/VWSABTO7ZII4 (DOI)
https://cds.climate.copernicus.eu/ (URL)
https://data2.gosat.nies.go.jp/ (URL)

Funding

Natural Environment Research Council (NERC)
NE/N018079/1
Sorbonne Université
Centre National de la Recherche Scientifique (CNRS)
Centre National d'Études Spatiales (CNES)
Région Île-de-France
Université de La Réunion
LACy/UMR8105
Natural Sciences and Engineering Research Council of Canada (NSERC)
Environment and Climate Change Canada
Canadian Space Agency (CSA)
Korea Meteorological Administration
KMA2018-00522
European Research Council (ERC)
856612
Government of Cyprus
University of Bremen
Australian Research Council
FT180100327
Australian Research Council
DP160100598
Australian Research Council
DP140100552
Australian Research Council
DP110103118
Australian Research Council
DP0879468
Australian Research Council
LE0668470
NASA
NAG5-12247
NASA
NNG05-GD07G
Deutsche Forschungsgemeinschaft (DFG)
INST 144/379-1
Deutsche Forschungsgemeinschaft (DFG)
INST 144/493-1
Copernicus Atmosphere Monitoring Service
CAMS2-52b
Japan Aerospace Exploration Agency (JAXA)
19RT000692
Japan Aerospace Exploration Agency (JAXA)
JX-PSPC-527269
European Organization for the Exploitation of Meteorological Satellites
EUM/CO/19/4600002372/RL
European Space Agency (ESA)
4000126450/19/I-NB

Dates

Created
2022-07-22
Created from EPrint's datestamp field
Updated
2022-07-22
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