The ACOS CO<sub>2</sub> retrieval algorithm – Part II: Global X<sub>CO<sub>2</sub></sub> data characterization

Abstract

Abstract. Here, we report preliminary estimates of the column averaged carbon dioxide (CO 2 ) dry air mole fraction, X CO 2 , retrieved from spectra recorded over land by the Greenhouse gases Observing Satellite, GOSAT (nicknamed "Ibuki"), using retrieval methods originally developed for the NASA Orbiting Carbon Observatory (OCO) mission. After screening for clouds and other known error sources, these retrievals reproduce much of the expected structure in the global X CO 2 field, including its variation with latitude and season. However, low yields of retrieved X CO 2 over persistently cloudy areas and ice covered surfaces at high latitudes limit the coverage of some geographic regions, even on seasonal time scales. Comparisons of early GOSAT X CO 2 retrievals with X CO 2 estimates from the Total Carbon Column Observing Network (TCCON) revealed a global, −2 % (7-8 parts per million, ppm, with respect to dry air) X CO 2 bias and 2 to 3 times more variance in the GOSAT retrievals. About half of the global X CO 2 bias is associated with a systematic, 1 % overestimate in the retrieved air mass, first identified as a global +10 hPa bias in the retrieved surface pressure. This error has been attributed to errors in the O 2 A-band absorption cross sections. Much of the remaining bias and spurious variance in the GOSAT X CO 2 retrievals has been traced to uncertainties in the instrument's calibration, oversimplified methods for generating O 2 and CO 2 absorption cross sections, and other subtle errors in the implementation of the retrieval algorithm. Many of these deficiencies have been addressed in the most recent version (Build 2.9) of the retrieval algorithm, which produces negligible bias in X CO 2 on global scales as well as a ∼30 % reduction in variance. Comparisons with TCCON measurements indicate that regional scale biases remain, but these could be reduced by applying empirical corrections like those described by Wunch et al. (2011b). We recommend that such corrections be applied before these data are used in source sink inversion studies to minimize spurious fluxes associated with known biases. These and other lessons learned from the analysis of GOSAT data are expected to accelerate the delivery of high quality data products from the Orbiting Carbon Observatory-2 (OCO-2), once that satellite is successfully launched and inserted into orbit.

Simulated retrievals for the remote sensing of CO<sub>2</sub>, CH<sub>4</sub>, CO, and H<sub>2</sub>O from geostationary orbit

“…This is mainly due to different smoothing errors based on different a priori values. As expected, our simulation results show smaller biases and better precisions than those in real retrievals (e.g., Fu et al, 2014;Crisp et al, 2012), partly because of the assumptions discussed in Sect. 2.2.1 and the different spectral bands used.…”

“…The Greenhouse gases Observing SATellite (GOSAT), developed by the Japan Aerospace Exploration Agency and launched in January 2009, is the world's first mission dedicated to the monitoring of CO 2 and CH 4 (Yokota et al, 2009;Butz et al, 2011;Yoshida et al, 2011). In addition, the Orbiting Carbon Observatory (OCO)-2 mission, successfully launched in July 2014, now provides high-quality and worldwide column abundances of CO 2 (Crisp et al, 2004(Crisp et al, , 2012.…”

“…This method for retrieval has been widely used for GOSAT (Yoshida et al, 2011), Tropospheric Emission Spectrometer, and OCO-2 (Kuang et al, 2002;Connor et al, 2008;O'Dell et al, 2012;Crisp et al, 2012). The state vector x, model parameters b, and error e are related to the measurement vector y by a forward model F:…”

A method for colocating satellite <i>X</i><sub>CO<sub>2</sub></sub> data to ground-based data and its application to ACOS-GOSAT and TCCON

“…understanding of the instrument's calibration, uncertainties in the O 2 and CO 2 absorption cross sections, and subtle errors in the implementation of the retrieval algorithm (Crisp et al, 2012).…”

Bias corrections of GOSAT SWIR XCO<sub>2</sub> and XCH<sub>4</sub> with TCCON data and their evaluation using aircraft measurement data

“…Consequently, several studies have described bias corrections of the satellite retrieval data by using linear regression (e.g., Wunch et al, 2011b;Cogan et al, 2012;Guerlet et al, 2013;Schneising et al, 2013;Nguyen et al, 2014). Wunch et al (2011b) have attempted to correct spatially and temporally varying biases in the Atmospheric CO 2 Observations from Space retrievals of the GOSAT (ACOS-GOSAT; O'Dell et al, 2012;Crisp et al, 2012) data obtained over land using an empirical linear regression model with which they correlated variabilities in XCO 2 retrievals with surface albedo, the difference between the retrieved and a priori surface pressure, airmass, and the oxygen A-band spectral radiance. They used the GOSAT data in the Southern Hemisphere as the reference values for the linear regression and evaluated the bias correction against the Total Carbon Column Observing Network (TCCON) data from the Northern Hemisphere.…”