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Effect of Data Assimilation Parameters on The Optimized Surface CO2 Flux in Asia

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Abstract

In this study, CarbonTracker, an inverse modeling system based on the ensemble Kalman filter, was used to evaluate the effects of data assimilation parameters (assimilation window length and ensemble size) on the estimation of surface CO2 fluxes in Asia. Several experiments with different parameters were conducted, and the results were verified using CO2 concentration observations. The assimilation window lengths tested were 3, 5, 7, and 10 weeks, and the ensemble sizes were 100, 150, and 300. Therefore, a total of 12 experiments using combinations of these parameters were conducted. The experimental period was from January 2006 to December 2009. Differences between the optimized surface CO2 fluxes of the experiments were largest in the Eurasian Boreal (EB) area, followed by Eurasian Temperate (ET) and Tropical Asia (TA), and were larger in boreal summer than in boreal winter. The effect of ensemble size on the optimized biosphere flux is larger than the effect of the assimilation window length in Asia, but the importance of them varies in specific regions in Asia. The optimized biosphere flux was more sensitive to the assimilation window length in EB, whereas it was sensitive to the ensemble size as well as the assimilation window length in ET. The larger the ensemble size and the shorter the assimilation window length, the larger the uncertainty (i.e., spread of ensemble) of optimized surface CO2 fluxes. The 10-week assimilation window and 300 ensemble size were the optimal configuration for CarbonTracker in the Asian region based on several verifications using CO2 concentration measurements.

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References

  • Andrews, A. E., and Coauthors, 2014: CO2, CO, and CH4 measurements from tall towers in the NOAA Earth System Research Laboratory’s Global Greenhouse Gas Reference Network: instrumentation, uncertainty analysis, and recommendations for future high-accuracy greenhouse gas monitoring efforts. Atmos. Meas. Tech., 7, 647–687, doi: 10.5194/amt-7-647-2014.

    Article  Google Scholar 

  • Babenhauserheide, A., S. Basu, S. Houweling, W. Peters, and A. Butz, 2015: Comparing the CarbonTracker and TM5-4DVar data assimilation systems for CO2 surface flux inversions. Atmos. Chem. Phys., 15, 9747–9763, doi:10.5194/acp-15-9747-2015.

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Ballav, S., and Coauthors, 2012: Simulation of CO2 concentration over East Asia using the regional transport model WRF-CO2. J. Meteor. Soc. Japan, 90, 959–976, doi:10.2151/jmsj.2012-607.

    Article  Google Scholar 

  • Basu, S., and Coauthors, 2013: Global CO2 fluxes estimated from GOSAT retrievals of total column CO2. Atmos. Chem. Phys., 13, 8695–8717, doi:10.5194/acp-13-8695-2013.

    Article  Google Scholar 

  • Battle, M., M. L. Bender, P. P. Tans, J. W. C. White, J. T. Ellis, T. Conway, and R. J. Francey, 2000: Global carbon sinks and their variability inferred from atmospheric O2 and δ13C. Science, 287, 2467–2470.

    Article  Google Scholar 

  • Betts, R. A., C. D. Jones, J. R. Knight, R. F. Keeling, and J. J. Kennedy, 2016: El Niño and a record CO2 rise. Nat. Clim. Change, 6, 806–810, doi:10.1038/nclimate3063.

    Article  Google Scholar 

  • Bhattacharya, S. K., and Coauthors, 2009: Trace gases and CO2 isotope records from Cabo de Rama, India. Curr. Sci., 97, 1336–1344.

    Google Scholar 

  • Biraud, S. C., M. S. Torn, J. R. Smith, C. Sweeney, W. J. Riley, and P. P. Tans, 2013: A multi-year record of airborne CO2 observations in the US Southern Great Plains. Atmos. Meas. Tech., 6, 751, doi:10.5194/amt-6-751-2013.

    Article  Google Scholar 

  • Boden, T. A., G. Marland, and R. Andres, 2010: Global, regional, and national fossil-fuel CO2 emissions, Carbon Dioxide Information Analysis Center, doi:10.3334/CDIAC/00001_V2010, 10. [Available online at http://cdiac.ornl.gov/trends/emis/overview_2007.html.]

    Google Scholar 

  • Bruhwiler, L. M. P., A. M. Michalak, and P. P. Tans, 2011: Spatial and temporal resolution of carbon flux estimates for 1983-2002. Biogeosci., 8, 1309–1331, doi:10.5194/bg-8-1309-2011.

    Article  Google Scholar 

  • Chatterjee, A., and A, M. Michalak, 2013: Technical Note: Comparison of ensemble Kalman filter and variational approaches for CO2 data assimilation. Atmos. Chem. Phys., 13, 11643–11660, doi:10.5194/acp-13-11643-2013.

    Article  Google Scholar 

  • ---, A. M. Michalak, J. L. Anderson, K. L. Mueller, and V. Yadav, 2012: Toward reliable ensemble Kalman filter estimates of CO2 fluxes. J. Geophys. Res., 117, D22306, doi:10.1029/2012JD018176.

    Article  Google Scholar 

  • Chevallier, F., M. Fisher, P. Peylin, S. Serrar, P. Bousquet, F.-M. Bréon, A. Chédin, and P. Ciais, 2005: Inferring CO2 sources and sinks from satellite observations: Method and application to TOVS data. J. Geophys. Res., 110, D24309, doi:10.1029/2005JD006390.

    Article  Google Scholar 

  • ---, S. Maksyutov, P. Bousquet, F.-M. Bréon, R. Saito, Y. Yoshida, and T. Yokota, 2009: 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 

  • ---, and Coauthors, 2010: CO2 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.

    Article  Google Scholar 

  • Conway, T.J., P. M. Lang, and K. A. Masarie, cited 2011: Atmospheric Carbon Dioxide Dry Air Mole Fractions from the NOAA ESRL Carbon Cycle Cooperative Global Air Sampling Network, 1968-2010.

    Google Scholar 

  • Engelen, R. J., 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.

    Article  Google Scholar 

  • Enting, I. G., 2002: Inverse Problems in Atmospheric Constituent Transport. Cambridge University Press, 392 pp, doi:10.1017/CBO9780511-535741.

    Book  Google Scholar 

  • European Commission, 2009: Emission Database for Global Atmospheric Research (EDGAR), release version 4.0. [Available online at http://edgar.jrc.ec.europa.eu/.]

    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. Bösch, 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 

  • ---, 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 CO2 using ground-based, aircraft, and space-borne data. Atmos. Chem. Phys., 11, 2789–2803, doi:10.5194/acp-11-2789-2011.

    Article  Google Scholar 

  • Fujii, Y., 1990: An Assessment of the Responsibility for the Increase in the CO2 Concentration and Inter-generational Carbon Accounts. IIASA Working Paper, WP-90-055, 31 pp.

    Google Scholar 

  • Gatti, L. V., J. B. Miller, M. T. S. D’amelio, A. Martinewski, L. S. Basso, M. E. Gloor, S. Wofsy, and P. Tans, 2010: Vertical profiles of CO2 above eastern Amazonia suggest a net carbon flux to the atmosphere and balanced biosphere between 2000 and 2009. Tellus, 62, 581–594, doi:10.1111/j.1600-0889.2010.00484.x.

    Article  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 

  • Hamill, T. M., 2001: Interpretation of rank histograms for verifying ensemble forecasts. Mon. Wea. Rev., 129, 550–560.

    Article  Google Scholar 

  • Houtekamer, P. L., and H. L. Mitchell, 1998: Data assimilation using an Ensemble Kalman Filter technique. Mon. Wea. Rev., 126, 796–811.

    Article  Google Scholar 

  • Houweling, S., and Coauthors, 2015: An intercomparison of inverse models for estimating sources and sinks of CO2 using GOSAT measurements. J. Geophys. Res., 120, 5253–5266, doi:10.1002/2014JD022962.

    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 

  • Ju, O.-J., J.-S. Cha, D.-W. Lee, Y.-M. Kim, J.-Y. Lee, and I.-S. Park, 2007: Analysis of variation characteristics of greenhouse gases in the background atmosphere measured at Gosan, Jeju. J. Korean Soc. Atmos. Environ., 23, 487–497 (in Korean with English abstract).

    Article  Google Scholar 

  • Kim, H., H. M. Kim, J. Kim, and C.-H. Cho, 2016: A comparison of the atmospheric CO2 concentrations obtained by an inverse modeling system and passenger aircraft based measurement. Atmosphere, 26, 387–400, doi:10.14191/Atmos.2016.26.3.387 (in Korean with English abstract).

    Article  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, 415–427, doi:10.14191/Atmos.2012.22.4.415 (in Korean with English abstract).

    Article  Google Scholar 

  • ---, ---, and ---, 2014a: 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. J. of Atmos. Sci., 50, 327–344, doi:10.1007/s13143-014-0020-y.

    Article  Google Scholar 

  • ---, ---, and ---, 2014b: Influence of CO2 observations on the optimized CO2 flux in an ensemble Kalman filter. Atmos. Chem. Phys., 14, 13515–13530, doi:10.5194/acp-14-13515-2014.

    Article  Google Scholar 

  • ---, ---, ---, K.-O. Boo, A. R. Jacobson, M. Sasakawa, T. Machida, M. Arshinov, and N. Fedoseev, 2017: Impact of Siberian observations on the optimization of surface CO2 flux, Atmos. Chem. Phys., 17, 2881–2899, doi:10.5194/acp-17-2881-2017.

    Google Scholar 

  • Krinner, G., N. Viovy, N. de Noblet-Ducoudré, J. Ogée, J. Polcher, P. Friedlingstein, P. Ciais, S. Sitch, and I. Colin Prentice, 2005: A dynamic global vegetation model for studies of the coupled atmosphere-biosphere system. Global Biogeochem. Cycles, 19, GB1015, doi:10.1029/2003 GB002199.

    Article  Google Scholar 

  • Krol, M., S. Houweling, B. Bregman, M. van den Broek, A. Segers, P. van 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 

  • Law, R. M., and Coauthors, 2008: TransCom model simulations of hourly atmospheric CO2: Experimental overview and diurnal cycle results for 2002. Global Biogeochem. Cycles, 22, GB3009, doi:10.1029/2007GB-003050.

    Article  Google Scholar 

  • Langenfelds, R. L., R. J. Francey, B. C. Pak, L. P. Steele, J. Lloyd, C. M. Trudinger, and C. E. Allison, 2002: Interannual growth rate variations of atmospheric CO2 and its δ13C, H2, CH4 and CO between 1992 and 1999 linked to biomass burning. Global Biogeochem. Cycles, 16, doi:10.1029/2001GB001466.

    Google Scholar 

  • Liu, L., L. Zhou, X. C. Zhang, M. Wen, F. Zhang, B. Yao, and S. X. Fang, 2009: The characteristics of atmospheric CO2 concentration variation of four national background stations in China. Sci. China, Ser. D, 52, 1857–1863.

    Article  Google Scholar 

  • Liu, Z., and Coauthors, 2015: Reduced carbon emission estimates from fossil fuel combustion and cement production in China. Nature, 524, 335–338, doi:10.1038/nature1467.

    Article  Google Scholar 

  • Machida, T., and Coauthors, 2008: Worldwide measurements of atmospheric CO2 and other trace gas species using commercial airlines. J. Atmos. Oceanic Technol., 25, 1744–1754, doi:10.1175/2008JTECHA-1082.1.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Meirink, J. F., P. Bergamaschi, and M. C. Krol, 2008: Four-dimensional variational data assimilation for inverse modelling of atmospheric methane emissions: Method and comparison with synthesis inversion. Atmos. Chem. Phys., 8, 6341–6353, doi:10.5194/acp-8-6341-2008.

    Article  Google Scholar 

  • Mukai, H., and Coauthors, 2001: Characterization of atmospheric CO2 observed at two-background air monitoring stations (Hateruma and Ochi-ishi) in Japan. Proc. Sixth International Carbon Dioxide Conference, Sendai, Japan, 1–5.

    Google Scholar 

  • ---, and Coauthors, 2014a: Continuous observational data of atmospheric CO2 mixing ratios on Cape Ochi-ishi, Ver. 1.0. National Institute for Environmental Studies, doi:10.17595/20160901.002.

    Google Scholar 

  • ---, and Coauthors, 2014b: Continuous observational data of atmospheric CO2 mixing ratios on Hateruma island, Ver. 1.0. National Institute for Environmental Studies, doi:10.17595/20160901.001.

    Google Scholar 

  • 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 CO2 fluxes using passenger aircraft based measurements. J. Geophys. Res., 117, D11303. doi:10.1029/2012JD017474.

    Article  Google Scholar 

  • Olson, J. S., J. A. Watts, and L. J. Allison, 1985: Major World Ecosystem Complexes Ranked by Carbon in Live Vegetation: A Database. NDP017, Carbon Dioxide Information Analysis Center, doi:10.3334/CDIAC/lue.ndp017.

    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 

  • Park, J. I., and H. M. Kim, 2010: Typhoon Wukong (200610) prediction based on the ensemble Kalman filter and ensemble sensitivity analysis. Atmosphere, 20, 287–306 (in Korean with English abstract).

    Google Scholar 

  • Patil, D. J., B. R. Hunt, E. Kalnay, J. A. Yorke, and E. Ott, 2001: Local low dimensionality of atmospheric dynamics. Phys. Rev. Lett., 86, 5878–5881.

    Article  Google Scholar 

  • Patra, P., and Coauthors, 2008: TransCom 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., J. B. Miller, J. Whitaker, A. S. Denning, A. Hirsch, M. C. Krol, D. Zupanski, L. Bruhwiler, and P. P. Tans, 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. USA., 104, 18925–18930, doi:10.1073/pnas.0708986104.

    Article  Google Scholar 

  • ---, 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.

    Article  Google Scholar 

  • Peylin, P., and Coauthors, 2013: Global atmospheric carbon budget: results from an ensemble of atmospheric CO2 inversions. Biogeosci., 10, 6699–6720, doi:10.5194/bg-10-6699-2013.

    Article  Google Scholar 

  • Rayner, P. J., M. Scholze, W. Knorr, T. Kaminski, R. Giering, and H. Widmann, 2005: Two decades of terrestrial carbon fluxes from a carbon cycle data assimilation system (CCDAS). Global Biogeochem. Cycles, 19, GB2026, doi:10.1029/2004GB002254.

    Article  Google Scholar 

  • Sasakawa, M., and Coauthors, 2010: Continuous measurements of methane from a tower network over Siberia. Tellus, 62, 403–416, doi:10.1111/j.1600-0889.2010.00494.x.

    Article  Google Scholar 

  • ---, T. Machida, N. Tsuda, M. Arshinov, D. Davydov, A. Fofonov, and O. Krasnov, 2013: Aircraft and tower measurements of CO2 concentration in the planetary boundary layer and the lower free troposphere over southern taiga in West Siberia: Long-term records from 2002 to 2011. J. Geophys. Res., 118, 9489–9498, doi:10.1002/jgrd.50755.

    Google Scholar 

  • Sheu, G.-R., N.-H. Lin, J.-L. Wang, and C.-T. Lee, 2009: Lulin atmospheric background station: A new high-elevation baseline station in Taiwan. EarozoruKenyu, 24, 84–89, doi:10.11203/jar.24.84 (in Japanese).

    Google Scholar 

  • Stephens, B. B., N. L. Miles, S. J. Richardson, A. S. Watt, and K. J. Davis, 2011: Atmospheric CO2 monitoring with single-cell NDIR-based analyzers. Atmos. Meas. Tech., 4, 2737, doi:10.5194/amt-4-2737-2011.

    Article  Google Scholar 

  • Thompson, R. L., and Coauthors, 2016: Top-down assessment of the Asian carbon budget since the mid 1990s. Nat. Commun., 7, 10724, doi:10. 1038/ncomms10724.

    Article  Google Scholar 

  • Tsutsumi, Y., K. Mori, M. Ikegami, T. Tashiro, and K. Tsuboi, 2006: Longterm trends of greenhouse gases in regional and background events observed during 1998-2004 at Yonagunijima located to the east of the Asian continent. Atmos. Environ., 40, 5868–5879.

    Article  Google Scholar 

  • van der Werf, G. R., and Coauthors, 2010: Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997-2009). Atmos. Chem. Phys., 10, 11707–11735, doi:10.5194/acp-10-11707-2010.

    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 

  • World Meteorological Organization (WMO), 2016: Greenhouse gas bulletin: The state of greenhouse gases in the atmosphere based on global observations through 2015. [Available online at https://library. wmo.int/opac/doc_num.php?explnum_id=3084.]

    Google Scholar 

  • Worthy, D. E. J., A. Platt, R. Kessler, M. Ernst, and S. Racki, 2003: The greenhouse gases measurement program, measurement procedures and data quality. Canadian Baseline Program, Quebec, 97–120.

    Google Scholar 

  • Zhang, H. F., and Coauthors, 2014a: Net terrestrial CO2 exchange over China during 2001-2010 estimated with an ensemble data assimilation system for atmospheric CO2. J. Geophys. Res., 119, 3500–3515, doi:10. 1002/2013JD021297.

    Google Scholar 

  • ---, and Coauthors, 2014b: Estimating Asian terrestrial carbon fluxes from CONTRAIL aircraft and surface CO2 observations for the period 2006–2010. Atmos. Chem. Phys., 14, 5807–5824, doi:10.5194/acp-14-5807-2014.

    Article  Google Scholar 

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Kim, H., Kim, H.M., Kim, J. et al. Effect of Data Assimilation Parameters on The Optimized Surface CO2 Flux in Asia. Asia-Pacific J Atmos Sci 54, 1–17 (2018). https://doi.org/10.1007/s13143-017-0049-9

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