The Orbiting Carbon Observatory (OCO) mission

Crisp, David; Atlas, Robert; Bréon, F. M.; Brown, L.R.; Burrows, J. P.; Ciais, P.; Connor, B. J.; Doney, Scott C.; Fung, I.; Jacob, D.; Miller, CE; O’Brien, D. M.; Pawson, Steven; Randerson, J. T.; Rayner, P. J.; Salawitch, R. J.; Sander, S.; Sen, B.; Stephens, G. L.; Tans, P. P.; Toon, G. C.; Wennberg, P. O.; Wofsy, S. C.; Yung, Y. L.; Kuang, Z.; Chudasama, Bijal; Sprague, G.; Weiss, B. P.; Pollock, Randy; Kenyon, D.; Schroll, S

doi:10.1016/j.asr.2003.08.062

Cited by 656 publications

(508 citation statements)

References 41 publications

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“…The Thermal And Near infrared Sensor for carbon Observations Fourier Transform Spectrometer (TANSO-FTS) onboard the Greenhouse gases Observing SATellite (GOSAT) (Kuze et al, 2009), launched in January 2009, and the Orbiting Carbon Observatory-2 (OCO-2) (Crisp et al, 2004), launched in July 2014, are currently the only satellite instruments yielding XCO 2 with high near-surface sensitivity. Both satellite missions are specifically designed to observe XCO 2 .…”

Section: Introductionmentioning

confidence: 99%

Consistent satellite XCO2 retrievals from SCIAMACHY and GOSAT using the BESD algorithm

et al. 2015

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Abstract. Consistent and accurate long-term data sets of global atmospheric concentrations of carbon dioxide (CO 2 ) are required for carbon cycle and climate-related research. However, global data sets based on satellite observations may suffer from inconsistencies originating from the use of products derived from different satellites as needed to cover a long enough time period. One reason for inconsistencies can be the use of different retrieval algorithms. We address this potential issue by applying the same algorithm, the Bremen Optimal Estimation DOAS (BESD) algorithm, to different satellite instruments, SCIAMACHY on-board ENVISAT (March 2002-April 2012 and TANSO-FTS onboard GOSAT (launched in January 2009), to retrieve XCO 2 , the column-averaged dry-air mole fraction of CO 2 . BESD has been initially developed for SCIAMACHY XCO 2 retrievals. Here, we present the first detailed assessment of the new GOSAT BESD XCO 2 product. GOSAT BESD XCO 2 is a product generated and delivered to the MACC project for assimilation into ECMWF's Integrated Forecasting System. We describe the modifications of the BESD algorithm needed in order to retrieve XCO 2 from GOSAT and present detailed comparisons with ground-based observations of XCO 2 from the Total Carbon Column Observing Network (TC-CON). We discuss detailed comparison results between all three XCO 2 data sets (SCIAMACHY, GOSAT and TC-CON). The comparison results demonstrate the good consistency between SCIAMACHY and GOSAT XCO 2 . For example, we found a mean difference for daily averages of −0.60±1.56 ppm (mean difference ± standard deviation) for GOSAT-SCIAMACHY (linear correlation coefficient r = 0.82), −0.34±1.37 ppm (r = 0.86) for GOSAT-TCCON and 0.10±1.79 ppm (r = 0.75) for SCIAMACHY-TCCON. The remaining differences between GOSAT and SCIAMACHY are likely due to non-perfect collocation (± 2 h, 10• around TCCON sites), i.e. the observed air masses are not exactly identical but likely also due to a still non-perfect BESD retrieval algorithm, which will be continuously improved in the future. Our overarching goal is to generate a satellitederived XCO 2 data set appropriate for climate and carbon cycle research covering the longest possible time period. We therefore also plan to extend the existing SCIAMACHY and Published by Copernicus Publications on behalf of the European Geosciences Union. J. Heymann et al.: SCIAMACHY and GOSAT BESD XCO 2 retrievalsGOSAT data set discussed here by also using data from other missions (e.g. OCO-2, GOSAT-2, CarbonSat) in the future.

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Section: Introductionmentioning

confidence: 99%

Consistent satellite XCO2 retrievals from SCIAMACHY and GOSAT using the BESD algorithm

et al. 2015

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“…As illustrated by Kuang et al (Kuang et al, 2002) and D. Crisp et al (Crisp et al, 2004), three bands in the visual and nearinfrared solar-reflected spectra are required to accurately measure atmospheric CO 2 and to efficiently eliminate the impacts of aerosols and clouds (Cressie et al, 2016). Table 1 shows a summary of the ACGS spectral requirements, including the spectral ranges and resolutions.…”

Section: Spectral Performance Requirementsmentioning

confidence: 99%

Laboratory Spectral Calibration of the TanSat Atmospheric Carbon Dioxide Grating Spectrometer

Yang¹,

Zhen²,

Yin³

et al. 2018

Preprint

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Abstract. TanSat is a key satellite mission in the Chinese Earth Observation program and is designed to measure the global atmospheric column-averaged dry-air CO 2 mole fraction by measuring the visible and near-infrared solar-reflected spectra.The first Chinese super-high-resolution grating spectrometer for measuring atmospheric CO 2 is aboard TanSat. This spectrometer is a suite incorporating three grating spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO 2 band near 1.61 and 2.06 micrometers and in the molecular oxygen (O 2 ) A band at 0.76 micrometers. Their 5 spectral resolving power (λ/∆λ) are ∼19000, ∼12800 and ∼12250 in O 2 A-band, WCO 2 and SCO 2 band respectively. This paper describes the prelaunch spectral calibration of the Atmospheric Carbon dioxide Grating Spectrometer aboard TanSat.Several critical aspects of the spectrometer, including the spectral resolution, spectral dispersion and the instrument line shape function of each channel, that are directly related to producing the Level 1 products were evaluated in this paper. The instrument line shape function of the spectrometer is notably symmetric and perfectly consistent across all channels in three bands. 10The variations resulting in spectral calibrations and radiometric response errors are negligible. The spectral resolution characterizations meet the mission requirements. The spectral dispersions have excellent consistency in the spatial dimension of each band, and there is good linearity in the spectral dimension of each band. Taken together, these results suggest that the spectral characterizations of the spectrometer aboard TanSat meet the mission requirements.

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“…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.…”

Section: XI Et Al: Simulated Retrievals From Geostationary Orbitmentioning

confidence: 99%

“…Band 1A is used for retrievals of CH 4 , CO, and H 2 O and Band 1B for CH 4 , CO 2 , and H 2 O. Band 2 is the O 2 A-band, which provides information about surface pressure, aerosols, and clouds (Crisp et al, 2004).…”

Section: Design Of the Geofts Observing Systemmentioning

confidence: 99%

Simulated retrievals for the remote sensing of CO2, CH4, CO, and H2O from geostationary orbit

Natraj

Shia

et al. 2015

Atmos. Meas. Tech.

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Abstract. The Geostationary Fourier Transform Spectrometer (GeoFTS) is designed to measure high-resolution spectra of reflected sunlight in three near-infrared bands centered around 0.76, 1.6, and 2.3 µm and to deliver simultaneous retrievals of column-averaged dry air mole fractions of CO 2 , CH 4 , CO, and H 2 O (denoted XCO 2 , XCH 4 , XCO, and XH 2 O, respectively) at different times of day over North America. In this study, we perform radiative transfer simulations over both clear-sky and all-sky scenes expected to be observed by GeoFTS and estimate the prospective performance of retrievals based on results from Bayesian error analysis and characterization.We find that, for simulated clear-sky retrievals, the average retrieval biases and single-measurement precisions are < 0.2 % for XCO 2 , XCH 4 , and XH 2 O, and < 2 % for XCO, when the a priori values have a bias of 3 % and an uncertainty of 3 %. In addition, an increase in the amount of aerosols and ice clouds leads to a notable increase in the retrieval biases and slight worsening of the retrieval precisions. Furthermore, retrieval precision is a strong function of signal-to-noise ratio and spectral resolution. This simulation study can help guide decisions on the design of the GeoFTS observing system, which can result in cost-effective measurement strategies while achieving satisfactory levels of retrieval precisions and biases. The simultaneous retrievals at different times of day will be important for more accurate estimation of carbon sources and sinks on fine spatiotemporal scales and for studies related to the atmospheric component of the water cycle.

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The Orbiting Carbon Observatory (OCO) mission

Cited by 656 publications

References 41 publications

Consistent satellite XCO<sub>2</sub> retrievals from SCIAMACHY and GOSAT using the BESD algorithm

Consistent satellite XCO<sub>2</sub> retrievals from SCIAMACHY and GOSAT using the BESD algorithm

Laboratory Spectral Calibration of the TanSat Atmospheric Carbon Dioxide Grating Spectrometer

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

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The Orbiting Carbon Observatory (OCO) mission

Cited by 656 publications

References 41 publications

Consistent satellite XCO&lt;sub&gt;2&lt;/sub&gt; retrievals from SCIAMACHY and GOSAT using the BESD algorithm

Consistent satellite XCO&lt;sub&gt;2&lt;/sub&gt; retrievals from SCIAMACHY and GOSAT using the BESD algorithm

Laboratory Spectral Calibration of the TanSat Atmospheric Carbon Dioxide Grating Spectrometer

Simulated retrievals for the remote sensing of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt;, CO, and H&lt;sub&gt;2&lt;/sub&gt;O from geostationary orbit

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Consistent satellite XCO<sub>2</sub> retrievals from SCIAMACHY and GOSAT using the BESD algorithm

Consistent satellite XCO<sub>2</sub> retrievals from SCIAMACHY and GOSAT using the BESD algorithm

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