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.

Highlights

  • A new era of dedicated satellite observations of greenhouse gases began in 2009, with the successful launch of gases Observing SATellite (GOSAT) (Kuze et al, 2009)

  • The bias correction and quality filtering of the Level 2 Full Physics (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

  • The Atmospheric Carbon Observations from Space (ACOS) GOSAT v9 XCO2 record was characterized in five ways: (i) an analysis of the XCO2 “good quality” data volume, (ii) a spatiotemporal analysis of the XCO2 estimates, (iii) a validation against XCO2 estimates from TCCON, (iv) a comparison of to XCO2 derived from models, and (v) a comparison with collocated XCO2 estimates from the Orbiting Carbon Observatory-2 (OCO-2) v10 product

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Summary

Introduction

A new era of dedicated satellite observations of greenhouse gases began in 2009, with the successful launch of GOSAT (Kuze et al, 2009). While the official GOSAT L2 products are available from the National Institute for Environmental Studies (NIES; http://www.gosat.nies.go.jp/en/about_5_products.html; Yoshida et al, 2013) a number of independent research institutes have developed their own products e.g., Butz et al, 2011; Crisp et al, 2012; Cogan et al, 2012; Heymann et al, 35 2015; Parker et al, 2020 One of these groups, the Atmospheric CO2 Observations from Space (ACOS) team, used an L2FP retrieval algorithm developed for the NASA Orbiting Carbon Observatory (OCO) to derive estimates of XCO2 from the GOSAT data (O’Dell et al, 2012; Crisp et al, 2012).

The GOSAT instrument and measurements
GOSAT TANSO-FTS instrument
ACOS GOSAT v9 L1b measurements
The ACOS v9 L2FP XCO2 retrieval algorithm
ACOS L2FP algorithm updates
Land surface model
ACOS GOSAT v9 XCO2 quality filtering and bias correction
Inverse Method EnKF
ACOS GOSAT v9 “good quality” data volume
ACOS GOSAT v9 XCO2 spatiotemporal analysis
ACOS GOSAT v9 XCO2 versus TCCON
ACOS GOSAT v9 XCO2 versus models
ACOS GOSAT v9 XCO2 versus OCO-2
Summary
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