04 Aug 2021

04 Aug 2021

Review status: this preprint is currently under review for the journal ESSD.

An eleven year record of XCO2 estimates derived from GOSAT measurements using the NASA ACOS version 9 retrieval algorithm

Thomas E. Taylor1, Christopher W. O'Dell1, David Crisp2, Akhiko Kuze3, Hannakaisa Lindqvist4, Paul O. Wennberg5, Abhishek Chatterjee6,7, Michael Gunson2, Annmarie Eldering2, Brendan Fisher2, Matthäus Kiel2, Robert R. Nelson2, Aronne Merrelli8, Greg Osterman2, Frédéric Chevallier9, Paul I. Palmer10, Liang Feng10, Nicholas M. Deutscher11, Manvendra K. Dubey12, Dietrich G. Feist13,14,15, Omaira E. Garcia16, David Griffith11, Frank Hase17, Laura T. Iraci18, Rigel Kivi19, Cheng Liu20, Martine De Mazière21, Isamu Morino22, Justus Notholt23, Young-Suk Oh24, Hirofumi Ohyama22, David F. Pollard25, Markus Rettinger26, Coleen M. Roehl27, Matthias Schneider26, Mahesh Kumar Sha28, Kei Shiomi3, Kimberly Strong29, Ralf Sussmann26, Yao Té30, Voltaire A. Velazco11,31, Mihalis Vrekoussis32,23, Thorsten Warneke23, and Debra Wunch29 Thomas E. Taylor et al.
  • 1Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO, USA
  • 2Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
  • 3Japan Aerospace Exploration Agency, Tsukuba-City, Ibaraki, Japan
  • 4Finnish Meteorological Institute, Helsenki, Finland
  • 5California Institute of Technology, Pasadena, CA, USA
  • 6Universities Space Research Association, Columbia, MD, USA
  • 7Goddard Space Flight Center, Greenbelt, MD, USA
  • 8Space Science and Engineering Center, University of Wisconsin - Madison, Madison WI, 53706, USA
  • 9Laboratoire des Sciences du Climat et de l’Environnement/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, 91198 Gif-sur-Yvette, France
  • 10National Centre for Earth Observation, University of Edinburgh, Edinburgh, UK
  • 11Centre for Atmospheric Chemistry, School of Earth, Atmospheric and Life Sciences, University of Wollongong, Wollongong, Australia
  • 12Los Alamos National Laboratory, Los Alamos, NM 87545, USA
  • 13Max Planck Institute for Biogeochemistry, Jena, Germany
  • 14Ludwig-Maximilians-Universität München, Lehrstuhl für Physik der Atmosphäre, Munich, Germany
  • 15Deutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
  • 16Izaña Atmospheric Research Centre (IARC), State Meteorological Agency of Spain (AEMET), Santa Cruz de Tenerife, Spain
  • 17Karlsruhe Institute of Technology, IMK-ASF, Karlsruhe, Germany
  • 18NASA Ames Research Center, Moffett Field, CA, USA
  • 19Finnish Meteorological Institute, FMI, Sodankylä, Finland
  • 20Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, China
  • 21Royal Belgian Institute for Space Aeronomy (BIRA-IASB), Brussels, Belgium
  • 22National Institute for Environmental Studies (NIES), Tsukuba, Japan
  • 23Institute of Environmental Physics, University of Bremen, Bremen, Germany
  • 24Global Atmosphere Watch Team, Innovative Meteorological Research Department, National Institute of Meteorological Sciences, Jeju-do, Republic of Korea
  • 25National Institute of Water and Atmospheric Research Ltd (NIWA), Lauder, New Zealand
  • 26Karlsruhe Institute of Technology, IMK-IFU, Garmisch-Partenkirchen, Germany
  • 27Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, USA
  • 28SRON Netherlands Institute for Space Research, Utrecht, the Netherlands
  • 29Department of Physics, University of Toronto, Toronto, Ontario, Canada
  • 30Laboratoire d’Etudes du Rayonnement et de la Matière en Astrophysique et Atmosphères (LERMA-IPSL), Sorbonne Université, CNRS, Observatoire de Paris, PSL Université, Paris, France
  • 31Deutscher Wetterdienst, Meteorological Observatory Hohenpeissenberg, 82383 Germany
  • 32Climate and Atmosphere Research Center (CARE-C), The Cyprus Institute, Nicosia, Cyprus

Abstract. The Thermal And Near infrared Sensor for carbon Observation – Fourier Transform Spectrometer (TANSO-FTS) on the Japanese Greenhouse gases Observing SATellite (GOSAT) has been returning data since April 2009. The version 9 (v9) Atmospheric Carbon Observations from Space (ACOS) Level 2 Full Physics (L2FP) retrieval algorithm (Kiel et al., 2019) was used to derive estimates of carbon dioxide (CO2) dry air mole fraction (XCO2) from the TANSO-FTS measurements collected over it's first eleven years of operation. The bias correction and quality filtering of the L2FP XCO2 product were evaluated using estimates derived from the Total Carbon Column Observing Network (TCCON) as well as values simulated from a suite of global atmospheric inverse modeling systems (models). In addition, the v9 ACOS GOSAT XCO2 results were compared with collocated XCO2 estimates derived from NASA's Orbiting Carbon Observatory-2 (OCO-2), using the version 10 (v10) ACOS L2FP algorithm.

These tests indicate that the v9 ACOS GOSAT XCO2 product has improved throughput, scatter and bias, when compared to the earlier v7.3 ACOS GOSAT product, which extended through mid 2016. Of the 37 million (M) soundings collected by GOSAT through June 2020, approximately 20 % were selected for processing by the v9 L2FP algorithm after screening for clouds and other artifacts. After post-processing, 5.4 % of the soundings (2M out of 37M) were assigned a “good” XCO2 quality flag, as compared to 3.9 % in v7.3 (< 1M out of 24M). After quality filtering and bias correction, the differences in XCO2 between ACOS GOSAT v9 and both TCCON and models have a scatter (one sigma) of approximately 1 ppm for ocean-glint observations and 1 to 1.5 ppm for land observations. Similarly, global mean biases are less than approximately 0.2 ppm. Seasonal mean biases relative to the v10 OCO-2 XCO2 product are of order 0.1 ppm for observations over land. However, for ocean-glint observations, seasonal mean biases relative to OCO-2 range from 0.2 to 0.6 ppm, with substantial variation in time and latitude.

The ACOS GOSAT v9 XCO2 data are available on the NASA Goddard Earth Science Data and Information Services Center (GES-DISC). The v9 ACOS Data User's Guide (DUG) describes best-use practices for the data. This dataset should be especially useful for studies of carbon cycle phenomena that span a full decade or more, and may serve as a useful complement to the shorter OCO-2 v10 dataset, which begins in September 2014.

Thomas E. Taylor et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2021-247', Anonymous Referee #1, 09 Aug 2021
  • RC2: 'Comment on essd-2021-247', Anonymous Referee #2, 28 Sep 2021

Thomas E. Taylor et al.

Data sets

ACOS GOSAT/TANSO-FTS Level 2 bias-corrected XCO2 and other select fields from the full-physics retrieval aggregated as daily files V9r OCO-2 Science Team and Gunson, Michael and Eldering, Annmarie

Thomas E. Taylor et al.


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Short summary
We provide an analysis of an eleven year record of atmospheric carbon dioxide (CO2) concentrations derived using an optimal estimation retrieval algorithm on measurements made by the GOSAT satellite . The new product (version 9) shows improvement over the previous version (v7.3) as evaluated against independent estimates of CO2 from ground-based sensors and atmospheric inversion systems. We also compare the new GOSAT CO2 values to collocated estimates from NASA's Orbiting Carbon Observatory-2.