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.

Here, we report preliminary estimates of the column averaged carbon dioxide (CO₂) dry air mole fraction, X_CO2, 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_CO2 field, including its variation with latitude and season. However, low yields of retrieved X_CO2 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_CO2 retrievals with X_CO2 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_CO2 bias and 2 to 3 times more variance in the GOSAT retrievals. About half of the global X_CO2 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 O₂ A-band absorption cross sections. Much of the remaining bias and spurious variance in the GOSAT X_CO2 retrievals has been traced to uncertainties in the instrument's calibration, oversimplified methods for generating O₂ and CO₂ 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_CO2 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. (2011). 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 Observeratory-2 (OCO-2), once that satellite is successfully launched and inserted into orbit

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OCO-2 (Orbiting Carbon Observatory-2) is the first NASA (National Aeronautics and Space Administration) mission dedicated to studying atmospheric carbon dioxide, specifically to identify sources (emitters) and sinks (absorbers) on a regional (1000 km x 1000 km) scale. The mission is designed to meet a science imperative by providing critical and urgent measurements needed to improve understanding of the carbon cycle and global climate change processes. The single instrument consisting of three grating spectrometers was built at the Jet Propulsion Laboratory, but is based on the design co-developed with Hamilton Sundstrand Corporation for the original OCO mission. The instrument underwent an extensive ground test program. This was generally made possible through the use of a thermal vacuum chamber with a window/port that allowed optical ground support equipment to stimulate the instrument. The instrument was later delivered to Orbital Sciences Corporation for integration and test with the LEOStar-2 spacecraft. During the overall ground test campaign, proper function and performance in simulated launch, ascent, and space environments were verified. The observatory was launched into space on 02 July 2014. Initial indications are that the instrument is meeting functional and performance specifications, and there is every expectation that the spatially-order, geo-located, calibrated spectra of reflected sunlight and the science retrievals will meet the Level 1 science requirements.