The Orbiting Carbon Observatory-2 (OCO-2) carries and points a three-channel imaging grating spectrometer designed to collect high-resolution, co-boresighted spectra of reflected sunlight within the molecular oxygen (O₂) A-band at 0.765 microns and the carbon dioxide (CO₂) bands at 1.61 and 2.06 microns. These measurements are calibrated and then combined into soundings that are analyzed to retrieve spatially resolved estimates of the column-averaged CO₂ dry-air mole fraction, XCO₂. Variations of XCO₂ in space and time are then analyzed in the context of the atmospheric transport to quantify surface sources and sinks of CO₂. This is a particularly challenging remote-sensing observation because all but the largest emission sources and natural absorbers produce only small (< 0.25 %) changes in the background XCO₂ field. High measurement precision is therefore essential to resolve these small variations, and high accuracy is needed because small biases in the retrieved XCO₂ distribution could be misinterpreted as evidence for CO₂ fluxes. To meet its demanding measurement requirements, each OCO-2 spectrometer channel collects 24 spectra s⁻¹ across a narrow (< 10 km) swath as the observatory flies over the sunlit hemisphere, yielding almost 1 million soundings each day. On monthly timescales, between 7 and 12 % of these soundings pass the cloud screens and other data quality filters to yield full-column estimates of XCO₂. Each of these soundings has an unprecedented combination of spatial resolution (< 3 km²/sounding), spectral resolving power (λ∕Δλ > 17 000), dynamic range (∼ 10⁴), and sensitivity (continuum signal-to-noise ratio > 400). The OCO-2 instrument performance was extensively characterized and calibrated prior to launch. In general, the instrument has performed as expected during its first 18 months in orbit. However, ongoing calibration and science analysis activities have revealed a number of subtle radiometric and spectroscopic challenges that affect the yield and quality of the OCO-2 data products. These issues include increased numbers of bad pixels, transient artifacts introduced by cosmic rays, radiance discontinuities for spatially non-uniform scenes, a misunderstanding of the instrument polarization orientation, and time-dependent changes in the throughput of the oxygen A-band channel. Here, we describe the OCO-2 instrument, its data products, and its on-orbit performance. We then summarize calibration challenges encountered during its first 18 months in orbit and the methods used to mitigate their impact on the calibrated radiance spectra distributed to the science community.

Since September 2014, NASA's Orbiting Carbon Observatory-2 (OCO-2) satellite has been taking measurements of reflected solar spectra and using them to infer atmospheric carbon dioxide levels. This work provides details of the OCO-2 retrieval algorithm, versions 7 and 8, used to derive the column-averaged dry air mole fraction of atmospheric CO₂ (XCO₂) for the roughly 100 000 cloud-free measurements recorded by OCO-2 each day. The algorithm is based on the Atmospheric Carbon Observations from Space (ACOS) algorithm which has been applied to observations from the Greenhouse Gases Observing SATellite (GOSAT) since 2009, with modifications necessary for OCO-2. Because high accuracy, better than 0.25 %, is required in order to accurately infer carbon sources and sinks from XCO₂, significant errors and regional-scale biases in the measurements must be minimized. We discuss efforts to filter out poor-quality measurements, and correct the remaining good-quality measurements to minimize regional-scale biases. Updates to the radiance calibration and retrieval forward model in version 8 have improved many aspects of the retrieved data products. The version 8 data appear to have reduced regional-scale biases overall, and demonstrate a clear improvement over the version 7 data. In particular, error variance with respect to TCCON was reduced by 20 % over land and 40 % over ocean between versions 7 and 8, and nadir and glint observations over land are now more consistent. While this paper documents the significant improvements in the ACOS algorithm, it will continue to evolve and improve as the CO₂ data record continues to expand.

The Orbiting Carbon Observatory-2 (OCO-2) is the first National Aeronautics and Space Administration (NASA) satellite designed to measure atmospheric carbon dioxide (CO₂) with the accuracy, resolution, and coverage needed to quantify CO₂ fluxes (sources and sinks) on regional scales. OCO-2 was successfully launched on 2 July 2014 and has gathered more than 2 years of observations. The v7/v7r operational data products from September 2014 to January 2016 are discussed here. On monthly timescales, 7 to 12 % of these measurements are sufficiently cloud and aerosol free to yield estimates of the column-averaged atmospheric CO₂ dry air mole fraction, XCO₂, that pass all quality tests. During the first year of operations, the observing strategy, instrument calibration, and retrieval algorithm were optimized to improve both the data yield and the accuracy of the products. With these changes, global maps of XCO₂ derived from the OCO-2 data are revealing some of the most robust features of the atmospheric carbon cycle. This includes XCO₂ enhancements co-located with intense fossil fuel emissions in eastern US and eastern China, which are most obvious between October and December, when the north–south XCO₂ gradient is small. Enhanced XCO₂ coincident with biomass burning in the Amazon, central Africa, and Indonesia is also evident in this season. In May and June, when the north–south XCO₂ gradient is largest, these sources are less apparent in global maps. During this part of the year, OCO-2 maps show a more than 10 ppm reduction in XCO₂ across the Northern Hemisphere, as photosynthesis by the land biosphere rapidly absorbs CO₂. As the carbon cycle science community continues to analyze these OCO-2 data, information on regional-scale sources (emitters) and sinks (absorbers) which impart XCO₂ changes on the order of 1 ppm, as well as far more subtle features, will emerge from this high-resolution global dataset.

INTRODUCTION: Earth’s carbon cycle involves large fluxes of carbon dioxide (CO₂) between the atmosphere, land biosphere, and oceans. Over the past several decades, net loss of CO₂from the atmosphere to the land and oceans has varied considerably from year to year, equaling 20 to 80% of CO₂emissions from fossil fuel combustion and land use change. On average, the uptake is about 50%. The imbalance between CO₂emissions and removal is seen in increasing atmospheric CO₂concentrations. In recent years, an increase of 2 to 3 parts per million (ppm) per year in the atmospheric mole fraction, which is currently about 400 ppm, has been observed.Almost a quarter of the CO₂emitted by human activities is being absorbed by the ocean, and another quarter is absorbed by processes on land. The identity and location of the terrestrial sinks are poorly understood. This absorption has been attributed by some to tropical or Eurasian temperate forests, whereas others argue that these regions may be net sources of CO₂. The efficiency of these land sinks appears to vary dramatically from year to year. Because the identity, location, and processes controlling these natural sinks are not well constrained, substantial additional uncertainty is added to projections of future CO₂levels.RATIONALE: The NASA satellite, the Orbiting Carbon Observatory-2 (OCO-2), which was launched on 2 July 2014, is designed to collect global measurements with sufficient precision, coverage, and resolution to aid in resolving sources and sinks of CO₂on regional scales. Since 6 September 2014, the OCO-2 mission has been producing about 2 million estimates of the column-averaged CO₂dry-air mole fraction (XCO2) each month after quality screening, with spatial resolution of <3 km²per sounding. Solar-induced chlorophyll fluorescence (SIF), a small amount of light emitted during photosynthesis, is detected in remote sensing measurements of radiance within solar Fraunhofer lines and is another data product from OCO-2.RESULTS: The measurements from OCO-2 provide a global view of the seasonal cycles and spatial patterns of atmospheric CO₂, with the anticipated year-over-year growth rate. The buildup of CO₂in the Northern Hemisphere during winter and its rapid decrease in concentration as spring arrives (and the SIF increases) is seen in unprecedented detail. The enhanced CO₂in urban areas relative to nearby background areas is observed with a single overpass of OCO-2. Increases in CO₂due to the biomass burning in Africa are also clearly observed. The dense, global,XCO2and SIF data sets from OCO-2 are combined with other remote sensing data sets and used to disentangle the processes driving the carbon cycle on regional scales during the recent 2015–2016 El Niño event. This analysis shows more carbon release in 2015 relative to 2011 over Africa, South America, and Southeast Asia. Now, the fundamental driver for the change in carbon release can be assessed continent by continent, rather than treating the tropics as a single, integrated region. Small changes inXCO2were also observed early in the El Niño over the equatorial eastern Pacific, due to less upwelling of cold, carbon-rich water than is typical.CONCLUSION: NASA’s OCO-2 mission is collecting a dense, global set of high-spectral resolution measurements that are used to estimateXCO2and SIF. The OCO-2 mission data set can now be used to assess regional-scale sources and sinks of CO₂around the globe. The papers in this collection present early scientific findings from this new data set. El Niño impact on carbon flux in 2015 relative to 2011, detected from Greenhouse Gases Observing Satellite (GOSAT) and OCO-2 data.: OCO-2 uses reflected sunlight to deriveXCO2and SIF. This shows OCO-2XCO2data over North America from 12 August 2015 to 26 August 2015.

A data set containing more than 6 years (February 2009 to present) of radiance spectra for carbon dioxide (CO₂) and methane (CH₄) observations has been acquired by the Greenhouse gases Observing SATellite (GOSAT, available at http://data.gosat.nies.go.jp/GosatUserInterfaceGateway/guig/GuigPage/open.do), nicknamed “Ibuki”, Thermal And Near infrared Sensor for carbon Observation Fourier Transform Spectrometer (TANSO-FTS). This paper provides updates on the performance of the satellite and TANSO-FTS sensor and describes important changes to the data product, which has recently been made available to users. With these changes the typical accuracy of retrieved column-averaged dry air mole fractions of CO₂ and CH₄ (XCO₂ and XCH₄, respectively) are 2 ppm or 0.5 % and 13 ppb or 0.7 %, respectively. Three major anomalies of the satellite system affecting TANSO-FTS are reported: a failure of one of the two solar paddles in May 2014, a switch to the secondary pointing system in January 2015, and most recently a cryocooler shutdown and restart in August 2015. The Level 1A (L1A) (raw interferogram) and the Level 1B (L1B) (radiance spectra) of version V201 described here have long-term uniform quality and provide consistent retrieval accuracy even after the satellite system anomalies. In addition, we discuss the unique observation abilities of GOSAT made possible by an agile pointing mechanism, which allows for optimization of global sampling patterns.

We present an analysis of uncertainties in global measurements of the column averaged dry-air mole fraction of CO₂ (XCO₂) by the NASA Orbiting Carbon Observatory-2 (OCO-2). The analysis is based on our best estimates for uncertainties in the OCO-2 operational algorithm and its inputs, and uses simulated spectra calculated for the actual flight and sounding geometry, with measured atmospheric analyses. The simulations are calculated for land nadir and ocean glint observations. We include errors in measurement, smoothing, interference, and forward model parameters. All types of error are combined to estimate the uncertainty in XCO₂ from single soundings, before any attempt at bias correction has been made. From these results we also estimate the "variable error" which differs between soundings, to infer the error in the difference of XCO₂ between any two soundings. The most important error sources are aerosol interference, spectroscopy, and instrument calibration. Aerosol is the largest source of variable error. Spectroscopy and calibration, although they are themselves fixed error sources, also produce important variable errors in XCO₂. Net variable errors are usually < 1 ppm over ocean and ∼ 0.5–2.0 ppm over land. The total error due to all sources is ∼ 1.5–3.5 ppm over land and ∼ 1.5–2.5 ppm over ocean.