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Journal Articles Atmospheric Measurement Techniques Year : 2022

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

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Stefan Noël
  • Function : Author
Maximilian Reuter
  • Function : Author
Michael Buchwitz
  • Function : Author
Jakob Borchardt
  • Function : Author
Michael Hilker
  • Function : Author
Oliver Schneising
  • Function : Author
Heinrich Bovensmann
  • Function : Author
John P. Burrows
  • Function : Author
Antonio Di Noia
  • Function : Author
Robert J. Parker
  • Function : Author
Hiroshi Suto
  • Function : Author
Yukio Yoshida
  • Function : Author
Matthias Buschmann
  • Function : Author
Nicholas M. Deutscher
  • Function : Author
Dietrich G. Feist
  • Function : Author
David W. T. Griffith
  • Function : Author
Frank Hase
  • Function : Author
Rigel Kivi
  • Function : Author
Cheng Liu
  • Function : Author
Isamu Morino
  • Function : Author
Justus Notholt
  • Function : Author
Young-Suk Oh
  • Function : Author
Hirofumi Ohyama
  • Function : Author
Christof Petri
  • Function : Author
David F. Pollard
  • Function : Author
Markus Rettinger
  • Function : Author
Coleen Roehl
  • Function : Author
Constantina Rousogenous
  • Function : Author
Mahesh Kumar Sha
  • Function : Author
Kei Shiomi
  • Function : Author
Kimberly Strong
  • Function : Author
Ralf Sussmann
  • Function : Author
Voltaire A. Velazco
  • Function : Author
Mihalis Vrekoussis
  • Function : Author
Thorsten Warneke
  • Function : Author

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.

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Dates and versions

insu-03717107 , version 1 (09-07-2022)

Licence

Attribution - CC BY 4.0

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Stefan Noël, Maximilian Reuter, Michael Buchwitz, Jakob Borchardt, Michael Hilker, et al.. Retrieval of greenhouse gases from GOSAT and GOSAT-2 using the FOCAL algorithm. Atmospheric Measurement Techniques, 2022, 15, pp.3401-3437. ⟨10.5194/amt-15-3401-2022⟩. ⟨insu-03717107⟩
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