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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

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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 CO2 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 CO2 observations. Finally, the simulated background atmospheric CO2 concentrations in the experiment with the nesting domain in Asia were more consistent with the observed CO2 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.

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References

  • 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.

    Article  Google Scholar 

  • Baker, D. F., S. C. Doney, and D. S. Schimel, 2006a: Variational data assimilation for atmospheric CO2. Tellus, 58B, 359–365.

    Article  Google Scholar 

  • ____, and Coauthors, 2006b: TransCom 3 inversion intercomparison: Impact of transport model error on the interannual variability of regional CO2 fluxes, 1988–2003. Global Biogeochem. Cycles, 20, GB1002, doi:10.1029/2004GB002439.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • ____, S. Maksyutov, P. Bousquet, F.-M. Bréon, R. Saito, Y. Yoshida, and T. Yokota, 2009b: On the accuracy of the CO2 surface fluxes to be estimated from the GOSAT observations. Geophys. Res. Lett., 36, L19807, doi:10.1029/2009GL040108.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Engelen R. J., and P. Bauer, 2011: The use of variable CO2 in the data assimilation of AIRS and IASI radiances. Quart. J. Roy. Meteor. Soc., doi:10.1002/qj.919.

    Google Scholar 

  • ____, S. Serrar, and F. Chevallier, 2009: Four-dimensional data assimilation of atmospheric CO2 using AIRS observations. J. Geophys. Res., 114, D03303, doi:10.1029/2008JD010739.

    Google Scholar 

  • Enting, I., 2002: Inverse Problems in Atmospheric Constituent Transport. Cambridege Univ. Press, New York, doi:10.1017/CBO9780511535741.

    Book  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Feng, L., P. I. Palmer, H. Bosch, and S. Dance, 2009: Estimating surface CO2 fluxes from space-born CO2 dry air mole fraction observations using an ensemble Kalman Filter. Atmos. Chem. Phys., 9, 2619–2633.

    Article  Google Scholar 

  • Friedlingstein, P., and Coauthors, 2010: Update on CO2 emissions. Nat. Geosci., 3, 811–812, doi:10.1038/ngeo01022.

    Article  Google Scholar 

  • Gregg, J., S. Andres, and G. Marland, 2008: China: emissions pattern of the world leader in CO2 emissions from fossil fuel consumption and cement production. Geophys. Res. Lett., 35, doi:10.1029/2007GL032887.

    Google Scholar 

  • Gurney, K. R., and Coauthors, 2002: Towards robust regional estimates of CO2 sources and sinks using atmospheric transport models. Nature, 415, 626–630.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Google Scholar 

  • 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.

    Google Scholar 

  • ____, _____, 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.

    Google Scholar 

  • 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)

    Article  Google Scholar 

  • Knorr, W., N. Gobron, M. Scholze, T. Kaminski, R. Schnur, and B. Pinty, 2007: Impact of terrestrial biosphere carbon exchanges on the anomalous CO2 increase in 2002–2003. Geophys. Res. Lett., 34, L09703, doi:10.1029/2006GL029019.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Le Quéré, and Coauthors, 2009: Trends in the sources and sinks of carbon dioxide. Nat. Geosci., 2, 831–836, doi:10.1038/ngeo689.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Maksyutov, S., T. Machida, H. Mukai, P. K. Patra, T. Nakazawa, and G. Inoue, 2003: Effect of recent observations on Asian CO2 flux estimates by transport model inversions. Tellus, 55B, 522–529.

    Article  Google Scholar 

  • Masarie, K. A., and Coauthors, 2011: Impact of CO2 measurement bias on carbontracker surface flux estimates. J. Geophys. Res., 116, D17305, doi:10.1029/2011JD016270.

    Article  Google Scholar 

  • Miyazaki, K., T. Maki, P. Patra, and T. Nakazawa, 2011: Assesing the impact of satellite, aircraft, and surface observations on CO2 flux estimation using an ensemble-based 4-D data assimilation system. J. Geophys. Res., 116, D16306, doi:10.1029/2010JD015366.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • NOAA ESRL, cited 2013: Documentation CT2010. [Available online at http://www.esrl.noaa.gov/gmd/ccgg/carbontracker/CT2010/documentation_CT2010.pdf.]

  • 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.

    Google Scholar 

  • 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.

    Article  Google Scholar 

  • Patra, P. K., and Coauthors, 2008: TrasnCom model simulations of hourly atmospheric CO2: analysis of synoptic-scale variations for the period 2002–2003. Global Biogeochem. Cycles, 22, GB4013, doi:10.1029/2007GB003081.

    Article  Google Scholar 

  • Peters, W., and Coauthors, 2005: An ensemble data assimilation system to estimate CO2 surface fluxes from atmospheric trace gas observations. J. Geophys. Res., 110, D24304, doi:10.1029/2005JD006157.

    Article  Google Scholar 

  • ____, and Coauthors, 2007: An atmospheric perspective on North American carbon dioxide exchange: CarbonTracker. Proc. Nat. Acad. Sci. U.S.A., 104, 18925–18930.

    Article  Google Scholar 

  • ____, 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

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Stephens B. B., and Coauthors, 2007: Weak northern and strong tropical land carbon uptake from vertical profiles of atmospheric CO2. Science, 316, 1732–1735, doi:10.1126/science.1137004.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Turnbull, J. C., and Coauthors, 2011: Atmospheric observations of carbon monoxide and fossil fuel CO2 emissions from East Asia. J. Geophys. Res., 116, D24306, doi:10.1029/2011JD016691.

    Google Scholar 

  • 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Whitaker, J. S., and T. M. Hamill, 2002: Ensemble data assimilation without perturbed observations. Mon. Wea. Rev., 130, 1913–1924.

    Article  Google Scholar 

  • ____, _____, 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Yokota, T., Y. Yoshida, N. Eguchi, Y. Ota, T. Tanaka, H. Watanabe, S. Maksyutov, 2004: Global concentrations of CO2 and CH4 retrieved from GOSAT: First preliminary results. Sci. Online Lett. Atmos., 5, 160–163, doi:10.2151/sola.2009-041.

    Google Scholar 

  • Zeng, N., H. Qian, C. Rödenbeck, 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.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

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Kim, J., Kim, H.M. & Cho, CH. 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. Asia-Pacific J Atmos Sci 50, 327–344 (2014). https://doi.org/10.1007/s13143-014-0020-y

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