The Adaptable 4A Inversion (5AI): description and first X_(CO₂) retrievals from Orbiting Carbon Observatory-2 (OCO-2) observations

Creators: Dogniaux, Matthieu; Crevoisier, Cyril; Armante, Raymond; Capelle, Virginie; Delahaye, Thibault; Cassé, Vincent; De Mazière, Martine; Deutscher, Nicholas M.; Feist, Dietrich G.; Garcia, Omaira E.; Griffith, David W. T.; Hase, Frank; Iraci, Laura T.; Kivi, Rigel; Morino, Isamu; Notholt, Justus; Pollard, David F.; Roehl, Coleen M.; Shiomi, Kei; Strong, Kimberly; Té, Yao; Velazco, Voltaire A.; Warneke, Thorsten

Abstract

A better understanding of greenhouse gas surface sources and sinks is required in order to address the global challenge of climate change. Space-borne remote estimations of greenhouse gas atmospheric concentrations can offer the global coverage that is necessary to improve the constraint on their fluxes, thus enabling a better monitoring of anthropogenic emissions. In this work, we introduce the Adaptable 4A Inversion (5AI) inverse scheme that aims to retrieve geophysical parameters from any remote sensing observation. The algorithm is based on the Optimal Estimation algorithm, relying on the Operational version of the Automatized Atmospheric Absorption Atlas (4A/OP) radiative transfer forward model along with the Gestion et Étude des Informations Spectroscopiques Atmosphériques: Management and Study of Atmospheric Spectroscopic Information (GEISA) spectroscopic database. Here, the 5AI scheme is applied to retrieve the column-averaged dry air mole fraction of carbon dioxide (X_(CO₂)) from a sample of measurements performed by the Orbiting Carbon Observatory-2 (OCO-2) mission. Those have been selected as a compromise between coverage and the lowest aerosol content possible, so that the impact of scattering particles can be neglected, for computational time purposes. For air masses below 3.0, 5AI X_(CO₂) retrievals successfully capture the latitudinal variations of CO₂ and its seasonal cycle and long-term increasing trend. Comparison with ground-based observations from the Total Carbon Column Observing Network (TCCON) yields a bias of 1.30±1.32 ppm (parts per million), which is comparable to the standard deviation of the Atmospheric CO₂ Observations from Space (ACOS) official products over the same set of soundings. These nonscattering 5AI results, however, exhibit an average difference of about 3 ppm compared to ACOS results. We show that neglecting scattering particles for computational time purposes can explain most of this difference that can be fully corrected by adding to OCO-2 measurements an average calculated–observed spectral residual correction, which encompasses all the inverse setup and forward differences between 5AI and ACOS. These comparisons show the reliability of 5AI as an optimal estimation implementation that is easily adaptable to any instrument designed to retrieve column-averaged dry air mole fractions of greenhouse gases.

Additional Information

© Author(s) 2021. This work is distributed under the Creative Commons Attribution 4.0 License. Published by Copernicus Publications on behalf of the European Geosciences Union. Received: 5 October 2020 – Discussion started: 10 November 2020; Revised: 22 March 2021 – Accepted: 18 April 2021 – Published: 24 June 2021. The authors would like to thank the ACOS team and NASA for OCO-2 data availability. We thank the AERONET team for the whole database availability and especially Jochen Stutz, Brent Holben, Toshihiko Takemura, Rigel Kivi, Veijo Aaltonen, Francois Ravetta, and Jacques Pelon for their effort in establishing and maintaining Caltech, Ascension Island, Saint-Denis, Réunion, Fukuoka, Sodankylä, and Paris AERONET sites. Finally, we would like to thank the two anonymous referees whose comments and advice significantly improved the quality of this paper. The TCCON site at Réunion is operated by the Royal Belgian Institute for Space Aeronomy, with financial support, since 2014, from the EU project ICOS-INWIRE and the ministerial decree for ICOS (grant nos. FR/35/IC1 to FR/35/C5) and local activities supported by LACy/UMR8105 at Université de La Réunion. The TCCON stations at 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 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 Ascension Island TCCON station has been supported by the European Space Agency (ESA; grant no. 4000120088/17/I-EF) and by the German Bundesministerium für Wirtschaft und Energie (BMWi; grant nos. 50EE1711C and 50EE1711E). We thank the ESA Ariane Tracking Station at North East Bay, Ascension Island, for hosting and local support. Nicholas M. Deutscher is funded by an ARC Future Fellowship (grant no. FT180100327). Darwin and Wollongong TCCON stations are supported by ARC (grant nos. DP160100598, LE0668470, DP140101552, DP110103118, and DP0879468) and NASA (grant nos. NAG5-12247 and NNG05-GD07G). This work has received funding from CNES and CNRS. Matthieu Dogniaux has been funded by Airbus Defence and Space in the framework of a scientific collaboration with École polytechnique. Review statement: This paper was edited by Abhishek Chatterjee and reviewed by two anonymous referees. Data availability: For this work, we use the B8r of OCO-2 data that were produced by the OCO-2 project at the Jet Propulsion Laboratory, California Institute of Technology, and obtained from the OCO-2 data archive maintained at the NASA Goddard Earth Science Data and Information Services Center (NASA GES-DISC). All TCCON references are given in Table 2. AERONET data are available from the AERONET website (https://aeronet.gsfc.nasa.gov/new_web/download_all_v3_aod.html, last access: 25 May 2021, Stutz et al., 2021). 5AI retrieval results presented in this work are available, upon emailed request, from Matthieu Dogniaux (matthieu.dogniaux@lmd.ipsl.fr). Author contributions: MD developed 5AI and tested it on the OCO-2 soundings under the supervision of CC, with input and support from CC, RA, VirC, TD, and VinC. MDM, NMD, DGF, OEG, DWTG, FH, LTI, RK, IM, JN, DFP, CMR, KS, KS, YT, VAV, and TW provided the TCCON data. MD wrote this article, with feedback from all co-authors. The authors declare that they have no conflict of interest.

Attached Files

Published - amt-14-4689-2021.pdf

Files

amt-14-4689-2021.pdf

Files (6.0 MB)

Name	Size	Download all
amt-14-4689-2021.pdf md5:76b9cef6c1731c9c53236adba616d95f	6.0 MB	Preview Download

Additional details

	All versions	This version
Views	0	0
Downloads	0	0
Data volume	0 Bytes	0 Bytes