Abstract

Abstract. Since 2009, the Greenhouse gases Observing SATellite (GOSAT) has performed radiance measurements in the near-infrared (NIR) and shortwave infrared (SWIR) spectral region. From February 2019 onward, data from GOSAT-2 have also been available. We present the 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 was initially 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 being 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 particularly includes 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 and 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 semi-heavy water vapour (HDO). In the case of GOSAT-2, the retrieval of nitrous oxide (XN2O) and carbon monoxide (CO) may also be possible. 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 agreement of long-term temporal variations within about 1 ppm over 1 decade; differences in seasonal variations of about 0.5 ppm are observed. Furthermore, we obtain a station-to-station 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 the 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 and also TCCON.

Highlights

  • Carbon dioxide (CO2) is the most important greenhouse gas in the context of global warming (e.g. IPCC, 2013)

  • We present the 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 gases Observing SATellite (GOSAT) and GOSAT and OCO-2 (GOSAT-2) radiances and their validation

  • To show the applicability of the FOCAL method to Orbiting Carbon Observatory-2 (OCO-2) and to other satellite sensors, we present in this study a new application of FOCAL to GOSAT and some first results from an application to GOSAT-2

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Summary

Introduction

Carbon dioxide (CO2) is the most important greenhouse gas in the context of global warming (e.g. IPCC, 2013). Retrievals of column-averaged carbon dioxide (XCO2) from the satellite sensors SCIAMACHY (ENVISAT) (Burrows et al, 1995; Bovensmann et al, 1999; Reuter et al, 2010, 2011) and TANSO FTS (GOSAT) (Kuze et al, 2016), as well as from the Orbiting Carbon Observatory-2 (OCO-2) satellite (Crisp et al, 2004; Eldering et al, 2017; O’Dell et al, 2012, 2018) have been used for over a decade to obtain information on natural CO2 sources and sinks In 2009, the Greenhouse gases Observing SATellite (GOSAT; Kuze et al, 2009, 2016) was launched, followed by the Orbiting Carbon Observatory-2 (OCO-2; Crisp et al, 2017; Eldering et al, 2017; O’Dell et al, 2012, 2018) in 2014.

GOSAT and GOSAT-2
Reference spectra and external databases
The reference database
GOSAT Level 2 products
Pre-processing
Noise estimate
Cloud filter
Processing
N2O 8 CO
Post-processing
Basic filter
Random forest filter
Bias correction and filtering
Results
Verification and validation
Direct comparisons
TCCON comparisons
Time series
Conclusions
Full Text
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