Atmosphere (대기)

Korean Meteorological Society (한국기상학회)
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A Comparison of the Atmospheric CO2 Concentrations Obtained by an Inverse Modeling System and Passenger Aircraft Based Measurement

인버스 모델링 방법을 통해 추정된 대기 중 이산화탄소 농도와 항공 관측 자료 비교

  • Kim, Hyunjung (Atmospheric Predictability and Data Assimilation Laboratory, Department of Atmospheric Sciences, Yonsei University) ;
  • Kim, Hyun Mee (Atmospheric Predictability and Data Assimilation Laboratory, Department of Atmospheric Sciences, Yonsei University) ;
  • Kim, Jinwoong (Atmospheric Predictability and Data Assimilation Laboratory, Department of Atmospheric Sciences, Yonsei University) ;
  • Cho, Chun-Ho (National Institute of Meteorological Research)
  • 김현정 (연세대학교 대기과학과, 대기예측성 및 자료동화 연구실) ;
  • 김현미 (연세대학교 대기과학과, 대기예측성 및 자료동화 연구실) ;
  • 김진웅 (연세대학교 대기과학과, 대기예측성 및 자료동화 연구실) ;
  • 조천호 (국립기상과학원)
  • Received : 2016.03.25
  • Accepted : 2016.06.21
  • Published : 2016.09.30
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Abstract

In this study, the atmospheric $CO_2$ concentrations estimated by CT2013B, a recent version of CarbonTracker, are compared with $CO_2$ measurements from the Comprehensive Observation Network for Trace gases by Airliner (CONTRAIL) project during 2010-2011. CarbonTracker is an inversion system that estimates surface $CO_2$ fluxes using atmospheric $CO_2$ concentrations. Overall, the model results represented the atmospheric $CO_2$ concentrations well with a slight overestimation compared to observations. In the case of horizontal distribution, variations in the model and observation difference were large in northern Eurasia because most of the model and data mismatch were located in the stratosphere where the model could not represent $CO_2$ variations well enough due to low model resolution at high altitude and existing phase shift from the troposphere. In addition, the model and observation difference became larger in boreal summer. Despite relatively large differences at high latitudes and in boreal summer, overall, the modeled $CO_2$ concentrations fitted well to observations. Vertical profiles of modeled and observed $CO_2$ concentrations showed that the model overestimates the observations at all altitudes, showing nearly constant differences, which implies that the surface $CO_2$ concentration is transported well vertically in the transport model. At Narita, overall differences were small, although the correlation between modeled and observed $CO_2$ concentrations decreased at higher altitude, showing relatively large differences above 225 hPa. The vertical profiles at Moscow and Delhi located on land and at Hawaii on the ocean showed that the model is less accurate on land than on the ocean due to various effects (e.g., biospheric effect) on land compared to the homogeneous ocean surface.

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References

  1. Basu, S., and Coauthors, 2011: The seasonal cycle amplitude of total column $CO_2$: Factors behind the modelobservation mismatch. J. Geophys. Res., 116, D23306, doi:10.1029/2011JD016124.
  2. Chevallier, F., and Coauthors, 2010: $CO_2$ surface fluxes at grid point scale estimated from a global 21 year reanalysis of atmospheric measurements. J. Geophys. Res., 115, D21307, doi:10.1029/2010JD013887.
  3. Crevoisier, C., A. Chedin, H. Matsueda, T. Machida, R. Armante, and N. A. Scott, 2009: First year of upper tropospheric integrated content of $CO_2$ from IASI hyperspectral infrared observations. Atmos. Chem. Phys., 9, 4797-4810. https://doi.org/10.5194/acp-9-4797-2009
  4. Crevoisier, C., and Coauthors, 2013: The 2007-2011 evolution of tropical methane in the mid-troposphere as seen from space by MetOp-A/IASI. Atmos. Chem. Phys., 13, 4279-4289. https://doi.org/10.5194/acp-13-4279-2013
  5. Evensen, G., 1994: Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics. J. Geophys. Res., 99, 10143-10162. https://doi.org/10.1029/94JC00572
  6. Feng, L., P. I. Palmer, H. Bosch, and S. Dance, 2009: Estimating surface $CO_2$ fluxes from space-born $CO_2$ dry air mole fraction observations using an ensemble Kalman Filter. Atmos. Chem. Phys., 9, 2619-2633. https://doi.org/10.5194/acp-9-2619-2009
  7. Feng, L., P. I. Palmer, Y. Yang, R. M. Yantosca, S. R. Kawa, J.-D. Paris, H. Matsueda, and T. Machida, 2011: Evaluating a 3-D transport model of atmospheric $CO_2$ using ground-based, aircraft, and space-borne data. Atmos. Chem. Phys., 11, 2789-2803, doi:10.5194/acp-11-2789-2011.
  8. Frankenberg, C., S. S. Kulawik, S. Wofsy, F. Chevallier, B. Daube, E. A. Kort, C. O'Dell, E. T. Olsen, and G. Osterman, 2016: Using airborne HIAPER Pole-to- Pole Observations (HIPPO) to evaluate model and remote sensing estimates of atmospheric carbon dioxide. Atmos. Chem. Phys. Discuss., doi:10.5194/acp-2015-961.
  9. Goody, R. M., and Y. L. Yung, 1989: Atmospheric radiation: theoretical basis. 2nd ed. Oxford University Press, 544 pp.
  10. Gurney, K. R., and Coauthors, 2002: Towards robust regional estimates of $CO_2$ sources and sinks using atmospheric transport models. Nature, 415, 626-630. https://doi.org/10.1038/415626a
  11. Heymann, J., and Coauthors, 2015: Consistent satellite $XCO_2$ retrievals from SCIAMACHY and GOSAT using the BESD algorithm. Atmos. Meas. Tech., 8, 2961-2980. https://doi.org/10.5194/amt-8-2961-2015
  12. Houweling, S., and Coauthors, 2015: An intercomparison of inverse models for estimating sources and sinks of $CO_2$ using GOSAT measurements. J. Geophys. Res. Atmos., 120, 5253-5266, doi:10.1002/2014JD022962.
  13. Inoue, M., and Coauthors, 2013: Validation of $XCO_2$ derived from SWIR spectra of GOSAT TANSO-FTS with aircraft measurement data. Atmos. Chem. Phys., 13, 9771-9788, doi:10.5194/acp-13-9771-2013.
  14. Jacobson, A. R., S. E. M. Fletcher, N. Gruber, J. L. Sarmiento, and M. Gloor, 2007: A joint atmosphereocean inversion for surface fluxes of carbon dioxide: 2. Regional results. Glob. Biogeochem. Cycles., 21, GB1019, doi:10.1029/2006GB002703.
  15. Jiang, X., Q. Li, M.-C. Liang, R.-L. Shia, M. T. Chahine, E. T. Olsen, L. L. Chen, and Y. L. Yung, 2008: Simulation of upper tropospheric $CO_2$ from chemistry and transport models. Global Biogeochem. Cy., 22, GB4025, doi:10.1029/2007GB003049.
  16. Jiang, F., H. M. Wang, J. M. Chen, T. Machida, L. X. Zhou, W. M. Ju, H. Matsueda, and Y. Sawa, 2014: Carbon balance of China constrained by CONTRAIL aircraft $CO_2$ measurements. Atmos. Chem. Phys., 14, 10133-10144, doi:10.5194/acp-14-10133-2014.
  17. Kim, J., H. M. Kim, and C.-H. Cho, 2014: The effect of optimization and the nesting domain on carbon flux analysis in Asia using a carbon tracking system based on the ensemble Kalman filter. Asia-Pac. Atmos. Sci., 50, 327-344, doi:10.1007/s13143-014-0020-y.
  18. Kim, J., H. M. Kim, C.-H. Cho, K.-O. Boo, A. R. Jacobson, M. Sasakawa, T. Machida, M. Arshinov, and N. Fedoseev, 2016: Impact of Siberian observations on the optimization of surface $CO_2$ flux. Atmos. Chem. Phys. Discuss., doi:10.5194/acp-2015-875.
  19. Krol, M. C., S. Houweling, B. Bregman, M. van den Broek, A. Segers, P. van Velthoven, W. Peters, F. Dentener, and P. Bergamaschi, 2005: The two-way nested global chemistry-transport zoom model TM5: Algorithm and applications. Atmos. Chem. Phys., 5, 417-432. https://doi.org/10.5194/acp-5-417-2005
  20. Kulawik, S. S., and Coauthors, 2010: Characterization of tropospheric emission spectrometer (TES) $CO_2$ for carbon cycle science. Atmos. Chem. Phys., 10, 5601- 5623, doi:10.5194/acp-10-5601-2010.
  21. Kulawik, S. S., and Coauthors, 2016: Consistent evaluation of GOSAT, SCIAMACHY, CarbonTracker, and MACC through comparisons to TCCON. Atmos. Meas. Tech., 9, 683-709, doi:10.5194/amt-9-683-2016.
  22. Lindqvist, H., and Coauthors, 2015: Does GOSAT capture the true seasonal cycle of carbon dioxide? Atmos. Chem. Phys., 15, 13023-13040, doi:10.5194/acp-15-13023-2015.
  23. Machida, T., H. Matsueda, Y. Sawa, Y. Nakagawa, K. Hirotani, N. Kondo, K. Goto, K. Ishikawa, T. Nakazawa, and T. Ogawa, 2008: Worldwide measurements of atmospheric $CO_2$ and other trace gas species using commercial airlines. J. Atmos. Oceanic Technol., 25, 1744-1754, doi:10.1175/2008JTECHA1082.1.
  24. Machida, T., Y. Tohjima, K. Katsumata, and H. Mukai, 2011: A new $CO_2$ calibration scale based on gravimetric onestep dilution cylinders in National Institute for Environmental Studies-NIES 09 $CO_2$ scale. Report of the 15th WMO Meeting of Experts on Carbon Dioxide Concentration and Related Tracer Measurement Techniques, Switzerland: Geneva, 7-10.
  25. Masarie, K. A., W. Peters, A. R. Jacobson, and P. P. Tans, 2014: ObsPack: a framework for the preparation, delivery, and attribution of atmospheric greenhouse gas measurements, Earth Syst. Sci. Data, 6, 375-384, doi:10.5194/essd-6-375-2014.
  26. Matsueda, H., and H. Y. Inoue, 1996: Measurements of atmospheric $XCO_2$ and $CH_4$ using a commercial airliner from 1993 to 1994. Atmos. Environ., 30, 1647- 1655, doi:10.1016/1352-2310(95)00374-6.
  27. Matsueda, H., H. Y. Inoue, and M. Ishii, 2002: Aircraft observation of carbon dioxide at 8-13 km altitude over the western Pacific from 1993 to 1999. Tellus, 54B, 1-21.
  28. Matsueda, H., T. Machida, Y. Sawa, Y. Nakagawa, K. Hirotani, H. Ikeda, N. Kondo, and K. Goto, 2008: Evaluation of atmospheric $CO_2$ measurements from new flask sampling of JAL airliner observations. Pap. Meteorol. Geophys., 59, 1-17, doi:10.2467/mripapers.59.1.
  29. Niwa, Y., and Coauthors, 2011: Three-dimensional variations of atmospheric $CO_2$: aircraft measurements and multi-transport model simulations. Atmos. Chem. Phys., 11, 13359-13375. https://doi.org/10.5194/acp-11-13359-2011
  30. Niwa, Y., T. Machida, Y. Sawa, H. Matsueda, T. J. Schuck, C. A. M. Brenninkmeijer, R. Imasu, and M. Satoh, 2012: Imposing strong constraints on tropical terrestrial $CO_2$ fluxes using passenger aircraft based measurements. J. Geophys. Res.-Atmos., 117, D11303, doi:10.1029/2012JD01747.
  31. Patra, P. K., Y. Niwa, T. J. Schuck, C. A. M. Brenninkmeijer, T. Machida, H. Matsueda, and Y. Sawa, 2011: Carbon balance of South Asia constrained by passenger aircraft $CO_2$ measurements. Atmos. Chem. Phys., 11, 4163-4175, doi:10.5194/acp-11-4163-2011.
  32. Peters, W., and Coauthors, 2007: An atmospheric perspective on North American carbon dioxide exchange: CarbonTracker. Proc. Nat. Acad. Sci. U.S.A., 104, 18925-18930.
  33. Peters, W., and Coauthors, 2010: Seven years of recent European net terrestrial carbon dioxide exchange constrained by atmospheric observations. Glob. Change Biol., 16, 1317-1337, doi:10.1111/j.1365-2486.2009.02078.x.
  34. Sawa, Y., T. Machida, and H. Matsueda, 2008: Seasonal variations of $CO_2$ near the tropopause observed by commercial aircraft. J. Geophys. Res., 113, D23301, doi:10.1029/2008JD010568.
  35. Sawa, Y., T. Machida, and H. Matsueda, 2012: Aircraft observation of the seasonal variation in the transport of $CO_2$ in the upper atmosphere. J. Geophys. Res., 117, D05305, doi:10.1029/2011JD016933.
  36. Stephens, B. B., and Coauthors, 2007: Weak Northern and strong tropical land carbon uptake from vertical profiles of atmospheric $CO_2$. Science, 316, 1732-1735. https://doi.org/10.1126/science.1137004
  37. van der Werf, G. R., J. T. Randerson, L. Giglio, G. J. Collatz, M. Mu, P. S. Kasibhatla, D. C. Morton, R. S. DeFries, Y. Jin, and T. T. van Leeuwen, 2010: Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997- 2009). Atmos. Chem. Phys., 10, 11707-11735. https://doi.org/10.5194/acp-10-11707-2010
  38. Whitaker, J. S., and T. M. Hamill, 2002: Ensemble Data Assimilation without Perturbed Observations. Mon. Wea. Rev., 130, 1913-1924. https://doi.org/10.1175/1520-0493(2002)130<1913:EDAWPO>2.0.CO;2
  39. Zhang, H. F., and Coauthors, 2014: Estimating Asian terrestrial carbon fluxes from CONTRAIL aircraft and surface $CO_2$ observations for the period 2006-2010. Atmos. Chem. Phys., 14, 5807-5824. https://doi.org/10.5194/acp-14-5807-2014

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