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Ishizawa, Misa; Chan, Douglas; Higuchi, Kaz; Maksyutov, Shamil; Yuen, Chiu-Wai; Chen, Jin; Worthy, Douglas (2011)
Publisher: Tellus B
Journal: Tellus B
Languages: English
Types: Article
Atmospheric CO2 measurements show strong synoptic variability. To understand the contribution of the synoptic signals on atmospheric CO2 inversion, we simulate the cases of biospheric fluxes with and without synoptic variations (referred to as ‘Synoptic’ and ‘Reference’, respectively) using an atmospheric transport model, and then perform inversion analyses with these biospheric CO2concentration fields.Results show the monthly and annually averaged CO2 concentration anomalies (Synoptic–Reference) are functions of the distance from the continental biospheric source regions. Remote sites (like Mauna Loa) show averaged monthly amplitude of ∼0.2 ppm, while continental sites show averaged monthly amplitudes of 1–2 ppm with maximum monthly amplitudes up to 7 ppm. Spatial scales of these monthly mean synoptic anomaly patterns may exceed 1000 km. These CO2 concentration patterns are the results of the interaction of the synoptic CO2 flux field and atmospheric transport, and may be referred to as the synoptic Rectifier Effect.Inversion CO2 fluxes for 1992–1995 are obtained using biospheric background fields with and without synoptic biospheric flux variations. The maximum magnitude differences in estimated monthly flux for land and ocean regions are ∼0.4 and ∼0.2 GtC month−1, respectively. The average land sink increases by 0.19 GtC yr−1 while the average ocean sink decreases by 0.30 GtC yr−1.DOI: 10.1111/j.1600-0889.2006.00219.x
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    • Andres, R. J., Marland, G. and Bischoff, S. 1996. Carbon dioxide emissions from fossil fuel combustion and cement manufacture 1751- 1991 and an estimate of their isotopic composition and latitudinal distribution. In: 1993 Global Change Institute (eds. T. Wigley and D. Schimel). Cambridge Univ. Press, New York, pp. 419- 429.
    • Baker, D. F., Law, R. M., Gurney, K. R., Rayner, P., Peylin, P. and co-authors. 2006. TransCom3 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.
    • Brenkert, A. L. 1998. Carbon dioxide emission estimates from fossil-fuel burning, hydraulic cement production, and gas flaring for 1995 on a one degree grid cell basis. NDP-058A, CDIAC, ORNL, Oak Ridge, Tenn., USA.
    • Chan, D., Yuen, C. W., Higuchi, K., Shashkov, A., Liu, J. and co-authors. 2004. On the CO2 exchange between the atmosphere and the biosphere: the role of synoptic and mesoscale processes. Tellus 56B, 194-212.
    • Denning, A. S., Fung, I. and Randall, D. 1995. Latitudinal gradient of atmospheric CO2 due to seasonal exchange with land biota. Nature 376, 240-243.
    • Denning, A. S., Collatz, J. G., Zhang, C., Randall, D. A., Berry, J. A. and co-authors. 1996a. Simulations of terrestrial carbon metabolism and atmospheric CO2 in a general circulation model. Part 1: surface carbon fluxes. Tellus 48B, 521-542.
    • Denning, A. S., Randall, D. A., Collatz, G. J. and Sellers, P. J. 1996b. Simulations of terrestrial carbon metabolism and atmospheric CO2 in a general circulation model. Part 2: spatial and temporal variations of atmospheric CO2. Tellus 48B, 543-567.
    • Enting, I. G. 2002. Inverse Problems in Atmospheric Constituent Transport. Cambridge Univ. Press, New York.
    • Fujita, D., Ishizawa, M., Maksyutov, S., Thornton, P., Saeki, T. and co-authors 2003. Inter-annual variability of the atmospheric carbon dioxide concentrations as simulated with global terrestrial biosphere models and atmospheric transport model. Tellus 55B, 530- 546.
    • GLOBALVIEW-CO2. 2000. Cooperative Atmospheric Data Integration Project-Carbon Dioxide [CD-ROM], NOAA Clim. Model. And Diag. Lab., Boulder, Colo., USA.
    • Grell, G., Dudhia, J. and Stauffer, D. 1995. Description of the FifthGeneration Penn State/NCAR Mesoscale Model (MM5), NCAR/TN398. NCAR, Boulder, Colo., USA.
    • Gurney, K., Law, R., Rayner, P. and Denning, A. S. 2000. TransCom 3 Experimental Protocol. Department of Atmospheric Science, Colorado State University, USA. Paper No. 707. (Available at http://transcom.colostate.edu/TransCom 3/transcom 3.html) Gurney, K. R., Law, R. M., Denning, A. S., Rayner, P. J., Baker, D. and co-authors. 2002. Towards robust regional estimates of CO2 sources and sinks using atmospheric transport models. Nature 415, 626-630.
    • Gurney, K. R., Law, R. M., Denning, A. S., Rayner, P. J., Pak, B. C. and co-authors. 2004. Transcom 3 inversion intercomparison: Model mean results for the estimation of seasonal carbon sources and sinks. Global Biogeochem. Cycles 18, GB1010, doi:10.1029/2003/GB002111.
    • Gurney, K. R., Chen, Y.-H., Maki, T., Kawa, S. R., Andrews, A. and coauthors. 2005. Sensitivity of atmospheric CO2 inversinos to seasonal and interannual variations in fossil fuel emissions. J. Geophys. Res. 110, D10308, doi:10.1029/2004JD005373.
    • Hack, J. J., Boville, B. A., Briegleb, B. P., Kiehl, J. T., Rasch, P. J. and co-authors. 1993. Description of the NCAR community climate model (CCM2), NCAR/TN-382, NCAR, Boulder, Colo., USA.
    • Higuchi, K., Worthy, D. E. J., Chan, D. and Shashkov, A. 2003. Regional source/sink impact on the diurnal, seasonal and inter-annual variations in atmospheric CO2 at a boreal forest site in Canada. Tellus 55B, 115- 125.
    • Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D. and co-authors. 1996. The NCEP/NCAR 40-year reanalysis project. Bull. Am.Meteorol. Soc. 77, 437-471.
    • Maksyutov, S. and Inoue, G. 2000. Vertical profiles of radon and CO2 simulated by the global atmospheric transport model. In: CGER Supercomputer activity report, I039-2000 7, CGER NIES, Tsukuba, Japan, pp. 39-41.
    • Nakazawa, T., Ishizawa, M., Higuchi, K. and Trivett, N. B. A. 1997. Two curve fitting methods applied to CO2 flask data. Environmetrics 8, 197-218.
    • Randerson, J. T., Matthew, M. V., Conway, T. J., Fung, I. Y. and Field, C. B. 1997. The contribution of terrestrial sources and sinks to trends in the seasonal cycles of atmospheric carbon dioxide. Global Biogeochem. Cycles 11, 553-560.
    • Rayner, P. J., Enting, I. G., Francey, R. J. and Langenfelds, R. 1999. Reconstructing the recent carbon cycle from atmospheric CO2, 13C and O2/N2 observations. Tellus 51B, 213-232.
    • Takahashi, T., Wanninkhof, R. H., Feely, R. A., Weiss, R. F., Chipman, D. W., and co-authors. 1999. Net sea-air CO2 flux over the global oceans: An improved estimate based on the sea-air pCO2 difference. In: Proceedings of the 2nd International Symposium: CO2 in the Oceans (ed Y. Nojiri). Tsukuba, Japan.
    • Tarantola, A. 1987. Inverse Problem Theory: Methods for Data Fitting and Model Parameter Estimation. Elsevier Sci., New York.
    • Thornton, P. E., Law, B. E., Gholz, H. L., Clark, K. L., Falge, E. and co-authors. 2002. Modeling and measuring the effects of disturbance history and climate on carbon and water budgets in evergreen needleleaf forests. Agric. For. Meteorol. 113, 185-222.
    • Thoning, K. W., Tans, P. P. and Komhyr, W. D. 1989. Atmospheric carbon dioxide at Mauna Loa Observatory, 2. Analysis of the NOAA/GMCC data, 1974-1985. J. Geophys. Res. 94, 8549-8565.
    • Tiedtke, M. 1989. A comprehensive mass flux scheme for cumulus parameterization in large-scale models. Mon. Wea. Rev. 117, 1779-1800.
    • Trivett, N. B. A. and Higuchi, K. 1989. Trends and seasonal cycles of atmospheric CO2 over Alert, Sable Island, and Cape St. James, as analyzed by forward stepwise regression technique. pp. 27-42. In: The Statistical Treatment of CO2 Data Records (ed W. P. Elliott). Air Resources Laboratory, Silver Spring, Maryland, USA.
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