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Regional Measurements and Modelling of Carbon Exchange

  • A. Johannes Dolman
  • Joel Noilhan
  • Lieselotte Tolk
  • Thomas Lauvaux
  • Michiel van der Molen
  • Christoph Gerbig
  • Franco Miglietta
  • Gorka Pérez-Landa
Part of the Ecological Studies book series (ECOLSTUD, volume 203)

Atmospheric measurements of CO2 mixing ratios at a number of locations around the globe have helped significantly to quantify the source—sink distribution of carbon at the global and sub-hemispheric scales (e.g. Rödenbeck et al. 2003, chapter 3 and 11). The techniques that achieve this (e.g. Gurney et al. 2002), use a globally distributed network of atmospheric concentration observations of CO2 and other trace gasses together with an atmospheric transport model that back calculates an ‘optimal’ source—sink distribution. So far, this global inversion approach has yielded estimates of regional sinks and sources at scales of the order of a few hundreds of kilometres. For example, the distribution of the Northern Hemisphere carbon uptake in longitude between the oceans, North America, Europe and Asia is subject to many investigations but also to many uncertainties (e.g. Peylin et al. 2002; Fan et al. 1998). Stephens et al. (2007) question the common understanding of a large Northern Hemispheric sink, by comparing modelled profiles against observed ones from a few locations, and conclude that transport errors in the models may have contributed to putting too much of the global sink in the Northern Hemisphere transport.

At the local scale (1 km2), direct flux measurements by the eddy covariance technique (Baldocchi et al. 2001; Valentini et al. 2000, chapter 11) constrain the net ecosystem exchange (NEE) to within 20%, comparable to the uncertainty estimated from inverse models (e.g. Janssens et al. 2003). In parallel, intensive field studies can determine the changes in vegetation and soil carbon stocks using biometric techniques, which allow independent quantification of the average carbon balance of ecosystems, albeit also with significant errors (Schulze et al. 2000; Wirth et al. 2002; Curtis et al. 2002). How the two scales, the global and local, interact at the regional level is unknown. It remains a major challenge to quantify the carbon balance at this ‘missing scale’. Understanding the link between the local and global scale will add significant value to the existing local and global networks and will ultimately help to improve the constraints on the dynamics and vulnerability of the continental scale carbon balance.

Keywords

Geophysical Research Surface Flux Convective Boundary Layer Carbon Exchange Regional Atmospheric Modeling System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. André, J.-C., Goutorbe, J.-P., and Perrier, A. 1986. HAPEX-MOBILHY: A hydrologic atmos-pheric experiment for the study of water budget and evaporation flux at the climatic scale.Bulletin of the American Meteorological Society 67, 138-144.CrossRefGoogle Scholar
  2. Bakwin, P. S., Tans, P. P., Hurst, D. F., and Zhao, C. 1998. Measurements of carbon dioxide on very tall towers: Results of the NOAA/CMDL program. Tellus 50B, 401-415.Google Scholar
  3. Baldocchi, D. D., Falge, E., Gu, L., Olson, R., Hollinger, D., Running, S., Anthoni, P., ChBernhofer, Davis, K., Fuentes, J., Goldstein, A., Katul, G., Law, B., Lee, X., Malhi, Y., Meyers, T., Munger, J. W., Oechel, W., Pilegaard, K., Schmid, H. P., Valentini, R., Verma, S., Vesala, T., Wilson, K., and , Wofsy, S. 2001. FLUXNET: A new tool to study the temporal and spatial variability of ecosystem-scale carbon dioxide, water vapor and energy flux densities. Bulletin of the American Meteorological Society 82, 2415-2435.CrossRefGoogle Scholar
  4. Bousquet, P., Peylin, P., Ciais, P., Le Quéré, C., Friedlingstein, P., and Tans, P. 2000. Regional changes in carbon dioxide fluxes of land and oceans since 1980. Science 290, 1342-1346.CrossRefGoogle Scholar
  5. Brooks, S. B., Dumas, E. J., and Verfaillie, J. 2001. Development of the SkyArrow surface/atmosphere flux aircraft for global ecosystem research. American Institute of Aeronautics and Astronautics Journal and Proceedings, 39th Aerospace Sciences Meeting & Exhibit, January 8-11, 2001, Reno Nevada, 10 pp.Google Scholar
  6. Carouge, C. 2006. Vers une estimation des flux de CO2 journaliers européens à haute résolution par inversion du transport atmosphérique. PhD thesis University Paris 6.Google Scholar
  7. Champeaux, J.-L., Fortin, H., and Han, K.-S., 2005. Spatio-temporal characterization of biomes over SW France using SPOT/VEGETATION and Corinne Land Cover datasets. IGARRS proceedings.Google Scholar
  8. Chevallier, F., Viovy, N., Reichstein, M., and Ciais, P. 2006. On the assignment of prior errors in Bayesian inversions of CO2 surface fluxes. Geophysical Research Letters 33.Google Scholar
  9. Chou, W. W., Wofsy, S. C., Harriss, R. C., Lin, J. C., Gerbig, C., and Sachse, G. W., 2002. Net fluxes of CO2 in Amazonia derived from aircraft observations. Journal of Geophysical Research-Atmospheres 107 (D22), 4614, doi: 10.1029/2001JD001295.CrossRefGoogle Scholar
  10. Crawford, T. L., and Dobosy, R. J. 1992. A sensitive fast response probe to measure turbulence and heat flux from any airplane. Boundary Layer Meteorology 59, 257-278.CrossRefGoogle Scholar
  11. Crawford, T. L., Dobosy, R. J., McMillen, R. T., Vogel, C. A., and Hicks, B. B. 1996. Air-surface exchange measurement in heterogeneous regions: Extending tower observations with spatial structure observed from small aircraft. Global Change Biology 2, 275-285.CrossRefGoogle Scholar
  12. Culf, A. D., Fiosch, G., Mahli, Y., and Nobre, C. A. 1997. The influence of the atmospheric boundary layer on carbon dioxide concentrations over a tropical rain forest. Agricultural and Forest Meteorology 85, 149-158.CrossRefGoogle Scholar
  13. Curtis, P. S., Hanson, P. J., Bolstad, P., Barford, C., Randolf, J. C., Scmid, H. P., and Wilson, K. B. 2002. Biomertix and eddy covariance based estimates of annual carbon storage in five eastern North American deciduous forests. Agricultural and Forest Meteorology 113, 3-19.CrossRefGoogle Scholar
  14. Desjardins, R. L., Brach, E. J., Alno, P., and Schuepp, P. H. 1982. Aircraft monitoring of surface carbon dioxide exchange. Science 216, 733-735.CrossRefGoogle Scholar
  15. Desjardins, R. L., MacPherson, J. I., Mahrt, L., et al. 1997. Scaling up flux measurements for the boreal forest using aircraft-tower combinations. Journal of Geophysical Research-Atmospheres 102 (D24), 29125-29133.CrossRefGoogle Scholar
  16. Dolman A.J., Ronda, R., Miglietta, F., and Ciais, P. 2005. Regional measurement and modelling of carbon balances. In Griffith H and Jarvis, P.G. (Eds). The carbon balance of forest biomes. Taylor Francis, Abingdon UK., p 93-108.Google Scholar
  17. Dolman, A. J., Noilhan, J., Durand, P., Sarrat, C., Brut, A., Piguet, B., Butet, A., Jarosz, N., Brunet, Y., Loustau, D., Lamaud, E., Tolk, L., Ronda, R., Miglietta, F., Gioli, B., Magliulo, V., Esposito, M., Gerbig, C., Körner, S., Galdemard, P., Ramonet, M., Ciais, P., Neininger, B., Hutjes, R. W. A., Elbers, J. A., Macatangay, R., Schrems, O., Pérez-Landa, G., Sanz, M. J., Scholz, Y., Facon, G., Ceschia, E., and Beziat, P. 2006. CERES, the CarboEurope regional experiment strategy in Les Landes, South West France, May-June 2005. Bulletin of the American Meteorological Society 87 (10), 1367-1379.CrossRefGoogle Scholar
  18. Fan, S., Gloor, M., Mahlman, J., Pacala, S., Sarmiento, J., Takahashi, T., and Tans, P. 1998. A large terrestrial carbon sink in North America implied by atmospheric and oceanic carbon dioxide and models. Science 282, 53-74.CrossRefGoogle Scholar
  19. Gerbig, C., Lin, J. C., Wofsy, S. C., Daube, B. C., Andrews, A. E., Stephens, B. B., Bakwin, P. S., and Grainger, C. A. 2003a. Toward constraining regional-scale fluxes of CO2 with atmospheric observations over a continent: 1. Observed spatial variability from airborne platforms. Journal of Geophysical Research 108 (D24), 4756, doi:10.1029/2002JD003018.CrossRefGoogle Scholar
  20. Gerbig, C., Lin, J. C., Wofsy, S. C., Daube, B. C., Andrews, A. E., Stephens, B. B., Bakwin, P. S., and Grainger, C. A. 2003b. Toward constraining regional-scale fluxes of CO2 with atmospheric observations over a continent: 2. Analysis of COBRA data using a receptor-oriented frame-work. Journal of Geophysical Research 108 (D24), 4757, doi:10.1029/2003JD003770.CrossRefGoogle Scholar
  21. Gerbig, C., Lin, J. C., Munger, J. W., and Wofsy, S. C. 2006. What can tracer observations in the continental boundary layer tell us about surface-atmosphere fluxes? Atmospheric Chemistry and Physics 6, 539-554.Google Scholar
  22. Gioli, B., Miglietta, F., De Martino, B., Hutjes, R. W. A., Dolman, A. J., Lindroth, A., Lloyd, J., Sanz, M. J., Valentini, R., and Dumas, E. 2004. Comparison of tower and aircraft-based eddy correlation fluxes at five sites in Europe. Agricultural and Forest Meteorology 127, 1-16.CrossRefGoogle Scholar
  23. Gurney, K., Law, R. M., Denning, A. S., et al. 2002. Towards robust regional estimates of CO2 sources and sinks using atmospheric transport models. Nature 415, 626-630.CrossRefGoogle Scholar
  24. Hurwitz, M. D., Ricciuto, D. M., Davis, K. J., Wang, W., Yi, C., Butler, M. P., and Bakwin, P. S. 2004. Advection of carbon dioxide in the presence of storm systems over a northern Wisconsin forest. Journal of the Atmospheric Sciences 61, 607-618.CrossRefGoogle Scholar
  25. Isaac, P. R., McAneney, J., Coppin, P., and Hacker, J. 2004. Comparison of aircraft and ground-based flux measurements during OASIS95. Boundary Layer Meteorology 110, 39-67.CrossRefGoogle Scholar
  26. Janssens, I. A., Freibauer, A., Ciais, P., Smith, P., Nabuurs, G.-J., Folberth, G., Schlamadinger, B., Hutjes, R. W. A., Ceulemans, R., Schulze, E.-D., Valentini, R., and ,Dolman, A. J. 2003. Europe’s biosphere absorbs 7-12% of anthropogenic carbon emissions. Science 300, 1538-1542.CrossRefGoogle Scholar
  27. Karstens U., Gloor, M., Heimann, M., and Rödenbeck, C. 2006. Insights from simulations with high-resolution transport and process models on sampling of the atmosphere for constraining midlatitude land carbon sinks. Journal of Geophysical Research 111,  D12301, doi:10.1029/2005JD006278.CrossRefGoogle Scholar
  28. Laubach, J., and Fritsch, H. 2002. Convective boundary layer budgets derived from aircraft data. Agricultural and Forest Meteorology 111, 237-263.CrossRefGoogle Scholar
  29. Lauvaux, T., Uliasz, M., Sarrat, C., Chevallier, F., Bousquet, P., Lac, C., Davis, K. J., Ciais, P., Denning, A. S., and Rayner, P. J. 2007. Mesoscale inversion: First results from the CERES campaign with synthetic data, ACPD submitted.Google Scholar
  30. Lenschow, D. H., Pearson, Jr. R., and Stankov, B. B. 1981. Estimating the ozone budget in the boundary layer by use of aircraft measurements of ozone eddy flux and mean concentration. Journal of Geophysical Research 86, 7291-7297.CrossRefGoogle Scholar
  31. Levy, P., et al. 1999. Regional scale CO2 fluxes over central Sweden by a boundary layer budget method. Agricultural and Forest Meteorology 99, 159-167.CrossRefGoogle Scholar
  32. Lin, J. C., Gerbig, C., Wofsy, S. C., Andrews, A. E., Daube, B. C., Grainger, C. A., Stephens, B. B., Bakwin, P. S., and Hollinger, D. Y. 2004. Measuring fluxes of trace gases at regional scales by Lagrangian observations: Application to the CO2 Budget and Rectification Airborne (COBRA) study. Journal of Geophysical Research 109, D15304, doi:10.1029/2004 JD004754.CrossRefGoogle Scholar
  33. Lin, J. C., Gerbig, C., Wofsy, S. C., Daube, B. C., Andrews, A. E., Bakwin, P. S., Davis, K. J., Stith, J., and Grainger, A. 2003. A near-field tool for simulating the upstream influence of atmospheric observations: The Stochastic Time-Inverted Lagrangian Transport (STILT) model. Journal of Geophysical Research 108 (D16), 4493, doi:10.1029/2002JD003161.CrossRefGoogle Scholar
  34. Lloyd, J., Francey, R., Mollicone, D., Raupach, M. R., Sogachev, A., Arneth, A., Byers, J. N., Kelliher, F. M., Rebmann, C., Valentini, R., Chin-Wong, S., Bauer, G., and Schulze, E.-D. 2001. Vertical profiles, boundary layer budgets, and regional flux estimates for CO2 and its 13C/12C ratio and for water vapor above a forest/bog mosaic in central Siberia. Global Biogeochemical Cycles 15, 267-284.CrossRefGoogle Scholar
  35. Lu, L., Denning, A. S., Silva-Dias, M. A., Silva-Dias, P., Longo, M., Freitas, S. R., and Saatchi, S. 2005. Mesoscale circulations and atmospheric CO2 variations in the Tapajós Region, Pará, Brazil. Journal of Geophysical Research, in press.Google Scholar
  36. Michalak, A. M., Bruhwiler, L., and Tans, P. P. 2004. A geostatistical approach to surface flux estimation of atmospheric trace gases. Journal of Geophysical Research-Atmospheres 109, D14109, doi:10.1029/2003JD004422.CrossRefGoogle Scholar
  37. Miglietta, F., Gioli, B., Hutjes, R. W. A., and Reichstein, M. 2007. Net regional ecosystem CO2 exchange from airborne and ground-based eddy covariance, land-use maps and weather obser-vations. Global Change Biology 13, 548-550. doi:10.1111/j./1365-2486.2006.01219.x.CrossRefGoogle Scholar
  38. Nicholls, M. E., Denning, A. S., Prihodko, L., Vidale, P.-L., Davis, K., and Bakwin, P. 2004. A multiple-scale simulation of variations in atmospheric carbon dioxide using a coupled biosphere-atmospheric model. Journal of Geophysical Research, 109, D18117, doi:10.1029/2003JD004482.CrossRefGoogle Scholar
  39. Oechel, W. C., Vourlitis, G. L., Brooks, S. B., Crawford, T. L., and Dumas, E. J. 1998. Intercomparison between chamber, tower, and aircraft net CO2 exchange and energy fluxes measured during the Arctic system sciences land-atmosphere-ice interaction (ARCSS-LAII) flux study. Journal of Geophysical Research 103, 28993-29003.CrossRefGoogle Scholar
  40. Pérez-Landa, G., Ciais, P., Sanz, M. J., Gioli, B., Miglietta, F., Palau, J. L., Gangoiti, G., and Millán, M. M. 2006a. Mesoscale circulations over complex terrain in the Valencia coastal region, Spain, Part 1: Simulation of diurnal circulation regimes. Atmospheric Chemistry and Physics Discussions 6, 2809-2852.CrossRefGoogle Scholar
  41. Pérez-Landa, G., Ciais, P., Gangoiti, G., Palau, J. L., Carrara, A., Gioli, B., Miglietta, F., Schumacher, M., Millán, M. M., and Sanz, M. J. 2006b. Mesoscale circulations over complex terrain in the Valencia coastal region, Spain, Part 2: Linking CO2 surface fluxes with observed concentrations. Atmospheric Chemistry and Physics Discussions 6, 2853-2895.Google Scholar
  42. Peters, W., Miller, J. B., Whitaker, J., Denning, A. S., Hirsch, A., Krol, M. C., Zupanski, D., Bruhwiler, L., and Tans, P. P. 2005. An ensemble data assimilation system to estimate CO2 surface fluxes from atmospheric trace gas observations. Journal of Geophysical Research-Atmospheres 110, D24304, doi:10.1029/2005JD006157.CrossRefGoogle Scholar
  43. Peylin, P., Baker, D., Sarmiento, J., Cias, P., and Bousquet, P. 2002. Influence of transport uncer-tainty on annual mean and seasonal inversions of atmospheric CO2 data. Journal of Geophysical Research 107, 10.1029/2001JD000 857.Google Scholar
  44. PielkeR. A.,Cotton, W. R.,Walko, R. L. Tremback, C. J., Lyons, W. A., Grasso, L. D., Nicholis, M. E., Moran, M. D., Wesley, D. A.Lee, T. J., and Copeland, J. H. 1992. A comprehensive meteorological modelling system-RAMS. Meteorology and Atmospheric Physics 49, 69-91.CrossRefGoogle Scholar
  45. Rayner, P. J., and Law, R. M. 1999. The interannual variability of the global carbon cycle. Tellus Series B-Chemical and Physical Meteorology 51, 210-212.CrossRefGoogle Scholar
  46. Rödenbeck, C., Houweling, S., Gloor, M., and Heimann, M. 2003. CO2 flux history 1982-2001 inferred from atmospheric data using a global inversion of atmospheric transport. Atmospheric Chemistry and Physics 3, 1919-1964.CrossRefGoogle Scholar
  47. Sarrat, C., et al. (2007). Atmospheric CO2 modeling at the regional scale: Application to the CarboEurope Regional Experiment. J. Geophys. Res., 112, D12105, doi:10.1029/2006JD008107.CrossRefGoogle Scholar
  48. Schmitgen, S., Ciais, P., Geiss, H., Kley, D., Voz-Thomas, A., Neiniger, B., Baeumle, M., and Brunet, Y. 2004. Carbon dioxide uptake of a forested region in southwest France derived from airborne CO2 and CO observations in a Lagrangian budget approach. Journal of Geophysical Research 109, D14, doi:10.1029/2003JD004335.CrossRefGoogle Scholar
  49. Schulze, E. D., Hoegberg, P., Van Oene, H., Persson, T., Harrison, A. F., Read, D., Kjoller, A., and Matteucci, G. 2000. Interactions between the carbon and nitrogen cycles and the role of biodi-versity: A synopsis of a study along a north-south transect through Europe. In: Carbon and Nitrogen Cycling in European Forest Ecosytems, pp 468-491.Google Scholar
  50. Stephens, B., et al. 2007. Weak northern and strong tropical land carbon uptake from vertical pro-files of atmospheric CO2. Science 316, 1732-1735.CrossRefGoogle Scholar
  51. Styles, J.M., Lloyd, Zolotukhin, D., Lawton, K.A., Tchebakova, N., Francey, R.J., Arneth, A., Salamakho, D., Kolle, O., Schulze, E-D., 2002. Estimates of regional surface carbon dioxide exchange and carbon and oxygen isotope discrimination during photosynthesis from concen-tration profiles in the atmospheric boundary layer. Tellus B 54:5 768.Google Scholar
  52. Uliasz, M. 2003. A modelling framework to evaluate feasibility of deriving mesoscale surface fluxes of trace gases from concentration data. Available at http://biocycle.atmos.colostate.edu/ marek.mesoinversion7c.pdf.
  53. Valentini, R., Matteucci, G., Dolman, A. J., et al. 2000. Respiration as the main determinant of carbon balance in European forests. Nature 404, 861-865.CrossRefGoogle Scholar
  54. Van der Molen, M. K., and Dolman, A. J. 2007. Regional carbon fluxes and the effect of topogra-phy on the variability of atmospheric CO2. Journal of Geophysical Research-Atmosphères 112, D01104. doi:10.1029/2006JD007649. http://dx.doi.org/10.1029/2006JD007649 Google Scholar
  55. Van Ek, M. B., and Holtslag, A. A. M. 2004. Influence of soil moisture on boundary layer cloud development. Journal of Hydrometeorology 5, 86-99.CrossRefGoogle Scholar
  56. Vila-Guerau de Arellano, J., Gioli, B., Miglietta, F., Jonker, H. J. J., Klein Baltink, H., Hutjes, R. W. A., and Holtslag, A.A.M. 2004. Entrainment process of carbon dioxide in the atmospheric boundary layer. Journal of Geophysical Research 109D, 18110, doi:10.1029/2004JD004725.CrossRefGoogle Scholar
  57. Walko,R. L.,Tremback, C. J., and Bell, M. J. 2001. HYPACT Hybrid Particle and Concentration Transport Model, Users Guide. Mission Research Corporation, Fort Collins, CO.Google Scholar
  58. Wirth, C., Czimczik, C. I., and Schulze, E.-D. 2002. Beyond annual budgets: Carbon flux at dif-ferent temporal scales in fire-prone Siberian S cots pine forests. Tellus, 54 B, 611-630.Google Scholar
  59. Wofsy, S. C., Harriss, R. C., and Kaplan, W. A. 1988. Carbon dioxide in the atmosphere over the Amazon basin. Journal of Geophysical Research-Atmospheres 93, 1377-1387.CrossRefGoogle Scholar
  60. Zupanski, D., and Zupanski, M. 2006. Model error estimation employing an ensemble data assimilation approach. Monthly Weather Review 134, 1337-1354.CrossRefGoogle Scholar

Copyright information

© Springer Science + Business Media, LLC 2008

Authors and Affiliations

  • A. Johannes Dolman
    • 1
  • Joel Noilhan
    • 2
  • Lieselotte Tolk
    • 1
  • Thomas Lauvaux
    • 2
    • 3
  • Michiel van der Molen
    • 1
  • Christoph Gerbig
    • 4
    • 5
  • Franco Miglietta
    • 6
  • Gorka Pérez-Landa
    • 7
  1. 1.Department of Hydrology and Geo-Environmental SciencesVU University AmsterdamAmsterdamNetherlands
  2. 2.Météo-France CNRM/GMMEToulouseFrance
  3. 3.LSCEParisFrance
  4. 4.Max-Planck-Institute for BiogeochemistryJena
  5. 5.JenaGermany
  6. 6.CNR IBIMETFlorenceItaly
  7. 7.CEAMValenciaSpain

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