The Orbiting Carbon Observatory-2 (OCO-2), scheduled to launch in July 2014, is a NASA mission designed to measure atmospheric CO 2 . Its main purpose is to allow inversions of net flux estimates of CO 2 on regional to continental scales using the total column CO 2 retrieved using high-resolution spectra in the 0.76, 1.6, and 2.0 μm ranges. Recently, it was shown that solar-induced chlorophyll fluorescence (SIF), a proxy for gross primary production (GPP, carbon uptake through photosynthesis), can be accurately retrieved from space using high spectral resolution radiances in the 750 nm range from the Japanese GOSAT and European GOME-2 instruments. Here, we use real OCO-2 thermal vacuum test data as well as a full repeat cycle (16 days) of simulated OCO-2 spectra under realistic conditions to evaluate the potential of OCO-2 for retrievals of chlorophyll fluorescence and also its dependence on clouds and aerosols. We find that the single-measurement precision is 0.3-0.5 Wm (15-25% of typical peak values), better than current measurements from space but still difficult to interpret on a single-sounding basis. The most significant advancement will come from smaller ground-pixel sizes and increased measurement frequency, with a 100-fold increase compared to GOSAT (and about 8 times higher than GOME-2). This will largely decrease the need for coarse spatial and temporal averaging in data analysis and pave the way to accurate local studies. We also find that the lack of full global mapping from the OCO-2 only incurs small representativeness errors on regional averages. Eventually, the combination of net ecosystem exchange (NEE) derived from CO 2 source/sink inversions and SIF as proxy for GPP from the same satellite will provide a more process-based understanding of the global carbon cycle.

Abstract. 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.

Abstract. The Orbiting Carbon Observatory-2 (OCO-2) is the first National Aeronautics and Space Administration (NASA) satellite designed to measure atmospheric carbon dioxide (CO 2 ) with the accuracy, resolution, and coverage needed to quantify CO 2 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 CO 2 dry air mole fraction, X CO 2 , 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 X CO 2 derived from the OCO-2 data are revealing some of the most robust features of the atmospheric carbon cycle. This includes X CO 2 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 X CO 2 gradient is small. Enhanced X CO 2 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 X CO 2 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 X CO 2 across the Northern Hemisphere, as photosynthesis by the land biosphere rapidly absorbs CO 2 . As the carbon cycle science community continues to analyze these OCO-2 data, information on regional-scale sources (emitters) and sinks (absorbers) which impart X CO 2 changes on the order of 1 ppm, as well as far more subtle features, will emerge from this high-resolution global dataset.

Abstract. A data set containing more than 6 years (February 2009 to present) of radiance spectra for carbon dioxide (CO 2 ) and methane (CH 4 ) 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 CO 2 and CH 4 (X CO 2 and X CH 4 , 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 longterm 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.

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This work describes the radiometric calibration of the short-wave infrared (SWIR) bands of two instruments aboard the Greenhouse gases Observing SATellite (GOSAT), the Thermal And Near infrared Sensor for carbon Observations Fourier Transform Spectrometer (TANSO-FTS) and the Cloud and Aerosol Imager (TANSO-CAI). Four vicarious calibration campaigns (VCCs) have been performed annually since June 2009 at Railroad Valley, NV, USA, to estimate changes in the radiometric response of both sensors. While the 2009 campaign (VCC 2009 ) indicated significant initial degradation in the sensors compared to the prelaunch values, the results presented here show that the stability of the sensors has improved with time. The largest changes were seen in the 0.76 μm oxygen A-band for TANSO-FTS and in the 0.380 and 0.674 μm bands for TANSO-CAI. This paper describes techniques used to optimize the vicarious calibration of the GOSAT SWIR sensors. We discuss error reductions, relative to previous work, achieved by using higher quality and more comprehensive in situ measurements and proper selection of reference remote sensing Manuscript products from the Moderate Resolution Imaging Spectroradiometer used in radiative transfer calculations to model top-of-theatmosphere radiances. In addition, we present new estimates of TANSO-FTS radiometric degradation factors derived by combining the new vicarious calibration results with the time-dependent model provided by Yoshida et al. (2012), which is based on analysis of on-board solar diffuser data. We conclude that this combined model provides a robust correction for TANSO-FTS Level 1B spectra. A detailed error budget for TANSO-FTS vicarious calibration is also provided. Index Terms-Carbon dioxide (CO 2 ), Greenhouse gases Observing SATellite (GOSAT), short-wave infrared (SWIR), Thermal And Near infrared Sensor for carbon Observations (TANSO), vicarious calibration.

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