Asia-Pacific Journal of Atmospheric Sciences

Korean Meteorological Society (한국기상학회)
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The Effect of Optimization and the Nesting Domain on Carbon Flux Analyses in Asia Using a Carbon Tracking System Based on the Ensemble Kalman Filter

  • Kim, Jinwoong (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) ;
  • Cho, Chun-Ho (National Institute of Meteorological Research)
  • Received : 2013.07.18
  • Accepted : 2013.11.29
  • Published : 2014.05.31
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Abstract

To estimate the surface carbon flux in Asia and investigate the effect of the nesting domain on carbon flux analyses in Asia, two experiments with different nesting domains were conducted using the CarbonTracker developed by the National Oceanic and Atmospheric Administration. CarbonTracker is an inverse modeling system that uses an ensemble Kalman filter (EnKF) to estimate surface carbon fluxes from surface $CO_2$ observations. One experiment was conducted with a nesting domain centered in Asia and the other with a nesting domain centered in North America. Both experiments analyzed the surface carbon fluxes in Asia from 2001 to 2006. The results showed that prior surface carbon fluxes were underestimated in Asia compared with the optimized fluxes. The optimized biosphere fluxes of the two experiments exhibited roughly similar spatial patterns but different magnitudes. Weekly cumulative optimized fluxes showed more diverse patterns than the prior fluxes, indicating that more detailed flux analyses were conducted during the optimization. The nesting domain in Asia produced a detailed estimate of the surface carbon fluxes in Asia and exhibited better agreement with the $CO_2$ observations. Finally, the simulated background atmospheric $CO_2$ concentrations in the experiment with the nesting domain in Asia were more consistent with the observed $CO_2$ concentrations than those in the experiment with the nesting domain in North America. The results of this study suggest that surface carbon fluxes in Asia can be estimated more accurately using an EnKF when the nesting domain is centered in Asian regions.

Keywords

References

  1. Anderson, J. L., 2009: Spatially and temporally varying adaptive covariance inflation for ensemble filters. Tellus, 61A, 72-83, doi: 10.1111/j.1600-0870.2008.00361.x.
  2. Baker, D. F., S. C. Doney, and D. S. Schimel, 2006a: Variational data assimilation for atmospheric $CO_2$. Tellus, 58B, 359-365.
  3. Baker, D. F., and Coauthors, 2006b: TransCom 3 inversion intercomparison: Impact of transport model error on the interannual variability of regional $CO_2$ fluxes, 1988-2003. Global Biogeochem. Cycles, 20, GB1002, doi:10.1029/2004GB002439.
  4. Bowler, N. E., A. Arribas, K. R. Mylne, K. B. Robertson, and S. E. Beare, 2008: The MOGREPS short-range ensemble prediction system. Quart. J. Roy. Meteor. Soc., 134, 703-722. https://doi.org/10.1002/qj.234
  5. Chevallier, F., R. J. Engelen, C. Carouge, T. J. Conway, P. Peylin, C. Pickett-Heaps, M. Ramonet, P. J. Rayner, and I. Xueref-Remy, 2009a: AIRS-based versus flask-based estimation of carbon surface fluxes. J. Geophys. Res., 114, D20303, doi:10.1029/2009JD012311.
  6. Chevallier, F., S. Maksyutov, P. Bousquet, F.-M. Breon, R. Saito, Y. Yoshida, and T. Yokota, 2009b: On the accuracy of the $CO_2$ surface fluxes to be estimated from the GOSAT observations. Geophys. Res. Lett., 36, L19807, doi:10.1029/2009GL040108.
  7. Ciais, P., and Coauthors, 2005: Europe-wide reduction in primary productivity caused by the heat and drought in 2003. Nature, 437, 529-533, doi:10.1038/nature03972.
  8. Engelen R. J., and P. Bauer, 2011: The use of variable $CO_2$ in the data assimilation of AIRS and IASI radiances. Quart. J. Roy. Meteor. Soc., doi:10.1002/qj.919.
  9. Engelen R. J., S. Serrar, and F. Chevallier, 2009: Four-dimensional data assimilation of atmospheric $CO_2$ using AIRS observations. J. Geophys. Res., 114, D03303, doi:10.1029/2008JD010739.
  10. Enting, I., 2002: Inverse Problems in Atmospheric Constituent Transport. Cambridege Univ. Press, New York, doi:10.1017/CBO9780511535741.
  11. Evensen, G., 1994: Sequential data assimilation with a nonlinear quasigeostrophic model using Monte Carlo methods to forecast error statistics. J. Geophys. Res., 99, 10143-10162. https://doi.org/10.1029/94JC00572
  12. 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
  13. Friedlingstein, P., and Coauthors, 2010: Update on $CO_2$ emissions. Nat. Geosci., 3, 811-812, doi:10.1038/ngeo01022.
  14. Gregg, J., S. Andres, and G. Marland, 2008: China: Emissions pattern of the world leader in $CO_2$ emissions from fossil fuel consumption and cement production. Geophys. Res. Lett., 35, doi:10.1029/2007GL032887.
  15. 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
  16. Houghton, R. A., and J. L. Hackler., 2003: Sources and sinks of carbon from land-use change in China. Global Biogeochem. Cycles, 17(2), 1034, doi:10.1029/2002GB001970.
  17. Huang, S., F. Siegert, J. G. Goldammer, and A. I. Sukhinin, 2009: Satellitederived 2003 wildfires in southern Siberia and their potential influence on carbon sequestration. Int. J. Remote Sens., 30(6), 1479-1492, doi:10.1080/01431160802541549.
  18. Huijnen, J., and Coauthors, 2010: The global chemistry model TM5: description and evaluation of the tropospheric chemistry version 3.0. Geosci. Model Dev., 3, 445-473, doi:10.5194/gmd-3-445-2010.
  19. Jacobson, A. R., S. E. M. Fletcher, N. Gruber, J. L. Sarmiento, and M. Gloor, 2007: A joint atmosphere-ocean inversion for surface fluxes of carbon dioxide: 2. Regional results. Glob. Biogeochem. Cycles, 21, GB1019, doi:10.1029/2006GB002703.
  20. Kang, J. S., E. Kalnay, J. Liu, I. Fung, T. Miyoshi, and K. Ide, 2011: "Variable localization" in an ensemble Kalman filter: Application to the carbon cycle data assimilation. J. Geophys. Res., 116, D09110, doi: 10.1029/2010JD014673.
  21. Kang, J. S., E. Kalnay, T. Miyoshi, J. Liu, and I. Fung, 2012: Estimation of surface carbon flxues with an advanced data assimilation methodology. J. Geophys. Res., 117, D24101, doi:10.1029/2012JD018259.
  22. Kim, J., H. M. Kim, and C.-H. Cho, 2012: Application of carbon tracking system based on ensemble Kalman filter on the diagnosis of carbon cycle in Asia. Atmosphere, 22, 415-247. (in Korean with English abstract) https://doi.org/10.14191/Atmos.2012.22.4.415
  23. Knorr, W., N. Gobron, M. Scholze, T. Kaminski, R. Schnur, and B. Pinty, 2007: Impact of terrestrial biosphere carbon exchanges on the anomalous $CO_2$ increase in 2002-2003. Geophys. Res. Lett., 34, L09703, doi:10.1029/2006GL029019.
  24. Krol, M., S. Houweling, B. Bregman, M. Broek, A. van der Segers, P. V. Velthoven, W. Peters, F. Dentener, and P. Bergamaschi, 2005: The twoway 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
  25. Le Quere, and Coauthors, 2009: Trends in the sources and sinks of carbon dioxide. Nat. Geosci., 2, 831-836, doi:10.1038/ngeo689.
  26. Li, H., E. Kalnay, and T. Miyoshi, 2009: Simultaneous estimation of covariance inflation and observation errors within an ensemble Kalman filter. Quart. J. Roy. Meteor. Soc., 135, 523-533. https://doi.org/10.1002/qj.371
  27. Lüthi, D., and Coauthors, 2008: High-resolution carbon dioxide concentration record 650,000-800,000 years before present. Nature, 453, 379-382, doi:10.1038/natures06969.
  28. Maksyutov, S., T. Machida, H. Mukai, P. K. Patra, T. Nakazawa, and G. Inoue, 2003: Effect of recent observations on Asian $CO_2$ flux estimates by transport model inversions. Tellus, 55B, 522-529.
  29. Masarie, K. A., and Coauthors, 2011: Impact of $CO_2$ measurement bias on carbontracker surface flux estimates. J. Geophys. Res., 116, D17305, doi:10.1029/2011JD016270.
  30. Miyazaki, K., T. Maki, P. Patra, and T. Nakazawa, 2011: Assesing the impact of satellite, aircraft, and surface observations on $CO_2$ flux estimation using an ensemble-based 4-D data assimilation system. J. Geophys. Res., 116, D16306, doi:10.1029/2010JD015366.
  31. Miyoshi, T., 2011: The Gaussian approach to adaptive covariance inflation and its implementation with the local ensemble transform Kalman filter. Mon. Wea. Rev., 139, 1519-1535, doi:10.1175/2010MWR3570.1.
  32. NOAA ESRL, cited 2013: Documentation CT2010. [Available online at http://www.esrl.noaa.gov/gmd/ccgg/carbontracker/CT2010/documentation_CT2010.pdf.]
  33. Olsen, S. C., J. A. Watts, and L. J. Allison, 1985: Major World Ecosystem Complexes Ranked by Carbon in Live Vegetation: A Database, NDP017, Carbon Dioxide Info. Analy. Cent., Oak Ridge Nat. Lab., Oak Rideger, Tenn.
  34. Pan, Y., and Coauthors, 2011: A large and persistent Carbon Sink in the world's forests. Science, 333, 988-993, doi:10.1126/science.1201609.
  35. Patra, P. K., and Coauthors, 2008: TrasnCom model simulations of hourly atmospheric $CO_2$: analysis of synoptic-scale variations for the period 2002-2003. Global Biogeochem. Cycles, 22, GB4013, doi:10.1029/2007GB003081.
  36. Peters, W., and Coauthors, 2005: An ensemble data assimilation system to estimate $CO_2$ surface fluxes from atmospheric trace gas observations. J. Geophys. Res., 110, D24304, doi:10.1029/2005JD006157.
  37. 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. https://doi.org/10.1073/pnas.0708986104
  38. Peters, W., and Coauthors, 2010: Seven years of recent European net terrestrial carbon dioxide exchange constrained by atmospheric observations. Glob. Change Bio., 16, 1317-1337, doi:10.1111/j.1365-2486.2009.02078.x
  39. Quegan, S., and Coauthors, 2011: Estimating the carbon balance of central Siberia using landscape-ecosystem approach, atmospheric inversion and dynamic global vegetation models. Glob. Change Biol., 17, 351-365, doi:10.1111/j.1365-2486.2010.02275.x.
  40. Randerson, J. T., and Coauthors, 2009: Systematic assessment of terrestrial biogeochemistry in coupled climate-carbon models. Glob. Change Biol., 15, 2462-2484, doi:10.1111/j.1365-2486.2009.01912.x.
  41. Schulze, E.-D., and Coauthors, 1999: Productivity of forest in the Eurosiberian boreal region and their potential to act as a carbon sink -- a synthesis. Glob. Change Biol., 5, 703-722, doi:10.1046/j.1365-2486.1999.00266.x.
  42. 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, doi:10.1126/science.1137004.
  43. Tippett, M. K., J. L. Anderson, C. H. Bishop, T. M. Hamill, and J. S. Whitaker, 2003: Ensemble square root filters. Mon. Wea. Rev. 131, 1485-1490. https://doi.org/10.1175/1520-0493(2003)131<1485:ESRF>2.0.CO;2
  44. Turnbull, J. C., and Coauthors, 2011: Atmospheric observations of carbon monoxide and fossil fuel $CO_2$ emissions from East Asia. J. Geophys. Res., 116, D24306, doi:10.1029/2011JD016691.
  45. van der Werf, G. R., J. T. Randerson, L. Giglio, G. J. Collatz, P. S. Kasibhatla, and A. F. Arellano Jr., 2006: Interannual variability of global biomass burning emissions from 1997 to 2004. Atmos. Chem. Phys., 6, 3423-3441. https://doi.org/10.5194/acp-6-3423-2006
  46. Wang, X., and C. H. Bishop, 2003: A comparison of breeding and ensemble transform Kalman filter ensemble forecast schemes. J. Atmos. Sci., 60, 1140-1158. https://doi.org/10.1175/1520-0469(2003)060<1140:ACOBAE>2.0.CO;2
  47. 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
  48. Whitaker, J. S., T. M. Hamill, X. Wei, Y. Song, and Z. Toth, 2008: Ensemble data assimilation with the NCEP global forecast system. Mon. Wea. Rev., 136, 463-482, doi:10.1175/2007MWR2018.1.
  49. Yang, Z., R. A. Washenfelder, G. Keppel-Aleks, N. Y. Krakauer, J. T. Randerson, P. P. Tans, C. Sweeney, and P. O. Wennberg, 2007: New constraints on Northern Hemisphere growing season net flux. Geophys. Res. Lett., 34, L12807, doi:1029/2007GL029742. https://doi.org/10.1029/2007GL029742
  50. Yokota, T., Y. Yoshida, N. Eguchi, Y. Ota, T. Tanaka, H. Watanabe, and S. Maksyutov, 2004: Global concentrations of $CO_2$ and $CH_4$ retrieved from GOSAT: First preliminary results. Sci. Online Lett. Atmos., 5, 160-163, doi:10.2151/sola.2009-041.
  51. Zeng, N., H. Qian, C. Rodenbeck, and M. Heimann, 2005: Impact of 1998-2002 midlatitude drought and warming on terrestrial ecosystem and the global carbon cycle. Geophys. Res. Lett., 32, L22709, doi:10.1029/2005GL024607.
  52. Zhao, M., and S. W. Running, 2010: Drought-induced reduction in global terrestrial net primary production from 2000 through 2009. Science, 329(5994), 940-943, doi:10.1126/science.1192666.

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