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Journal of Meteorological Research

, Volume 32, Issue 3, pp 433–443 | Cite as

Validation of Column-Averaged Dry-Air Mole Fraction of CO2 Retrieved from OCO-2 Using Ground-Based FTS Measurements

  • Yanmeng Bi
  • Qian Wang
  • Zhongdong Yang
  • Jie Chen
  • Wenguang Bai
Article
  • 4 Downloads

Abstract

In order to correctly use the column-averaged atmospheric CO2 dry-air mole fraction (XCO2) data in the CO2 flux studies, XCO2 measurements retrieved from the Orbiting Carbon Observatory-2 (OCO-2) in 2015 were compared with those obtained from the global ground-based high-resolution Fourier Transform Spectrometer (FTS) participating in the Total Carbon Column Observing Network (TCCON). The XCO2 retrieved from three observing modes adopted by OCO-2, i.e., nadir, target, and glint, were separately validated by the FTS measurements at up to eight TCCON stations located in different areas. These comparisons show that OCO-2 glint mode yields the best qualitative estimations of CO2 concentration among the three operational approaches. The overall results regarding the glint mode show no obvious systematic biases. These facts may indicate that the glint concept is appropriate for not only oceans but also land regions. Negative systematic biases in nadir and target modes have been found at most TCCON sites. The standard deviations of XCO2 retrieved from target and nadir modes within the observation period are similar, and larger than those from glint mode. We also used the FTS site in Beijing, China, to assess the OCO-2 XCO2 in 2016. This site is located in a typical urban area, which has been absent in previous studies. Overall, OCO-2 XCO2 agrees well with that from FTS at this site. Such a study will benefit the validation of the newly launched TanSat products in China.

Key words

Orbiting Carbon Observatory-2 (OCO-2) Fourier Transform Spectrometer (FTS) carbon dioxide (CO2validation 

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Notes

Acknowledgments

The OCO-2 data were produced by the OCO-2 project at the Jet Propulsion Laboratory, California Institute of Technology, and obtained from the OCO-2 data archive maintained at the NASA Goddard Earth Science Data and Information Services Center. TCCON data were obtained from the TCCON Data Archive, hosted by the Carbon Dioxide Information Analysis Center (CDIAC) before September 2017 and has now been transitioned to tccon.caltech.edu. We thank S. Arnold and D. Feist from the Max Planck Institute for Biogeochemistry in Jena, Germany, for helpful comments.

References

  1. Bi Y. M., Z. D. Yang, S. Y. Gu, et al., 2014: Impacts of aerosol and albedo on TanSat CO2 retrieval using the near infrared CO2 bands. Proceedings Volume 9259, Remote Sensing of the Atmosphere, Clouds, and Precipitation V, 925915 (8 November 2014), SPIE Asia–Pacific Remote Sensing Conference, Beijing, China, doi: 10.1117/12.2066123.Google Scholar
  2. Bösch H., G. C. Toon, B. Sen, et al., 2006: Space-based near-infrared CO2 measurements: Testing the Orbiting Carbon Observatory retrieval algorithm and validation concept using SCIAMACHY observations over Park Falls, Wisconsin. J. Geophys. Res., 111, D23302, doi: 10.1029/2006JD007080.CrossRefGoogle Scholar
  3. Crisp D., 2015: Measuring atmospheric carbon dioxide from space with the Orbiting Carbon Observatory-2 (OCO-2). Proceedings Volume 9607, Earth Observing Systems XX, 960702 (8 September 2015), SPIE Optical Engineering + Applications Conference, San Diego, California, USA, doi: 10. 1117/12.2187291.Google Scholar
  4. Crisp D., R. M. Atlas, F.-M. Breon, et al., 2004: The Orbiting Carbon Observatory (OCO) mission. Adv. Space Res., 34, 700–709, doi: 10.1016/j.asr.2003.08.062.CrossRefGoogle Scholar
  5. Griffith D. W. T., Hurst D. F., Jiménez R., et al., 2010: Calibration of the Total Carbon Column Observing Network using aircraft profile data. Atmos. Meas. Tech., 3, 1351–1362, doi: 10.5194/amt-3-1351-2010.CrossRefGoogle Scholar
  6. Guo L. J., L. P. Lei, and Z. C. Zeng, 2013: Spatiotemporal correlation analysis of satellite-observed CO2: Case studies in China and USA. 2013 IEEE International Geoscience and Remote Sensing Symposium, Melbourne, VIC, Australia, 21–26 July, IEEE, 1835–1838, doi: 10.1109/IGARSS.2013.6723158.Google Scholar
  7. Hammerling D. M., A. M. Michalak, C. O’Dell, et al., 2012: Global CO2 distributions over land from the Greenhouse Gases Observing Satellite (GOSAT). Geophys. Res. Lett., 39, L08804, doi: 10.1029/2012GL051203.CrossRefGoogle Scholar
  8. Hase F., J. W. Hannigan, M. T. Coffey, et al., 2004: Intercomparison of retrieval codes used for the analysis of high-resolution, ground-based FTIR measurements. J. Quant. Spectrosc. Radiat. Transf., 87, 25–52, doi: 10.1016/j.jqsrt.2003.12.008.CrossRefGoogle Scholar
  9. Mandrake L., O’Dell C. W., Wunch, et al., 2015: Orbiting Carbon Observatory-2 (OCO-2) Warn Level, Bias Correction, and Lite File Product Description, Tech. Rep., Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA. 44 pp. Available at https://disc.gsfc.nasa.gov/information/ documents?title=OCO-2%20Documents. Accessed on 10 December 2017.Google Scholar
  10. Merrelli A., R. Bennartz, C. W. O’Dell, et al., 2015: Estimating bias in the OCO-2 retrieval algorithm caused by 3-D radiation scattering from unresolved boundary layer clouds. Atmos. Meas. Tech., 8, 1641–1656, doi: 10.5194/amt-8-1641-2015.CrossRefGoogle Scholar
  11. Miller C. E., D. Crisp, P. L. De Cola, et al., 2007: Precision requirements for space-based XCO2 data. J. Geophys. Res., 112, D10314, doi: 10.1029/2006JD007659.CrossRefGoogle Scholar
  12. Morino I., O. Uchino, M. Inoue, et al., 2011: Preliminary validation of column-averaged volume mixing ratios of carbon dioxide and methane retrieved from GOSAT short-wavelength infrared spectra. Atmos. Meas. Tech., 4, 1061–1076, doi: 10.5194/amt-4-1061-2011.CrossRefGoogle Scholar
  13. Natraj V., H. Boesch, R. J. D. Spurr, et al., 2008: Retrieval of XCO2 from simulated Orbiting Carbon Observatory measurements using the fast linearized R-2OS radiative transfer model. J. Geophys. Res., 113, D11212, doi: 10.1029/2007JD009017.CrossRefGoogle Scholar
  14. O’Dell C. W., B. Connor, H. Bösch, et al., 2012: The ACOS CO2 retrieval algorithm—Part 1: Description and validation against synthetic observations. Atmos. Meas. Tech., 5, 99–121, doi: 10.5194/amt-5-99-2012.CrossRefGoogle Scholar
  15. Osterman G., B. Fisher, D. Wunch, et al., 2015a: OCO-2 observation and validation overview: Observations data modes and target observations taken during the first 15 months of operations. AGU Fall Meeting, San Franciso, 14–18 December.Google Scholar
  16. Osterman G., A. Eldering, C. Avis, et al., 2015b: Orbiting Carbon Observatory-2 (OCO-2) Data Product User’s Guide, Operational L1 and L2 Data Versions 7 and 7R. Tech. Rep., Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA. 73 pp. Available at https://disc.gsfc. nasa.gov/information/documents?title=OCO-2%20Documents. Accessed on 10 December 2017.Google Scholar
  17. Reuter M., H. Bovensmann, M. Buchwitz, et al., 2011: Retrieval of atmospheric CO2 with enhanced accuracy and precision from SCIAMACHY: Validation with FTS measurements and comparison with model results. J. Geophys. Res., 116, D04301, doi: 10.1029/2010JD015047.CrossRefGoogle Scholar
  18. Tadić J. M., X. Qiu, V. Yadav, et al., 2015: Mapping of satellite Earth observations using moving window block kriging. Geosci. Model Dev., 8, 3311–3319, doi: 10.5194/gmd-8-3311-2015.CrossRefGoogle Scholar
  19. Tadić J. M., X. M. Qiu, S. Miller, et al., 2017: Spatio-temporal approach to moving window block kriging of satellite data v1.0. Geosci. Model Dev., 10, 709–720, doi: 10.5194/gmd-10-709-2017.CrossRefGoogle Scholar
  20. Wargan K., and L. Coy, 2016: Strengthening of the tropopause inversion layer during the 2009 sudden stratospheric warming: A MERRA-2 study. J. Atmos. Sci., 73, 1871–1887, doi: 10.1175/JAS-D-15-0333.1.CrossRefGoogle Scholar
  21. Washenfelder R. A., G. C. Toon, J.-F. Blavier, et al., 2006: Carbon dioxide column abundances at the Wisconsin Tall Tower site. J. Geophys. Res., 111, D22305, doi: 10.1029/2006JD007154.CrossRefGoogle Scholar
  22. Worden J. R., G. Doran, S. Kulawik, et al., 2017: Evaluation and attribution of OCO-2 XCO2 uncertainties. Atmos. Meas. Tech., 10, 2759–2771, doi: 10.5194/amt-10-2759-2017.CrossRefGoogle Scholar
  23. Wunch D., G. C. Toon, P. O. Wennberg, et al., 2010: Calibration of the Total Carbon Column Observing Network using aircraft profile data. Atmos. Meas. Tech., 3, 1351–1362, doi: 10.5194/amt-3-1351-2010.CrossRefGoogle Scholar
  24. Wunch D., G. C. Toon, J.-F. L. Blavier, et al., 2011: The Total Carbon Column Observing Network. Philos. Trans. Royal Soc. London A: Math., Phys. Eng. Sci., 369, 2087–2112, doi: 10.1098/rsta.2010.0240.CrossRefGoogle Scholar
  25. Wunch D., P. O. Wennberg, G. Osterman, et al., 2017: Comparisons of the Orbiting Carbon Observatory-2 (OCO-2) XCO2 measurements with TCCON. Atmos. Meas. Tech., 10, 2209–2238, doi: 10.5194/amt-10-2209-2017.CrossRefGoogle Scholar
  26. Yokota T., Y. Yoshida, N. Eguchi, et al., 2009: Global concentrations of CO2 and CH4 retrieved from GOSAT: First preliminary results. SOLA, 5, 160–163, doi: 10.2151/sola.2009-041.CrossRefGoogle Scholar

Copyright information

© The Chinese Meteorological Society and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Yanmeng Bi
    • 1
  • Qian Wang
    • 1
  • Zhongdong Yang
    • 1
  • Jie Chen
    • 1
  • Wenguang Bai
    • 1
  1. 1.National Satellite Meteorological CenterChina Meteorological AdministrationBeijingChina

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