Boundary-Layer Meteorology

, Volume 146, Issue 1, pp 1–15 | Cite as

Concurrency of Coherent Structures and Conditionally Sampled Daytime Sub-canopy Respiration

  • Matthias J. ZeemanEmail author
  • Werner Eugster
  • Christoph K. Thomas


We investigated an alternative means for quantifying daytime ecosystem respiration from eddy-covariance data in three forests with different canopy architecture. Our hypothesis was that the turbulent transport by coherent structures is the main pathway for carrying detectable sub-canopy respiration signals through the canopy. The study extends previously published work by incorporating state-of-the-art wavelet decomposition techniques for the detection of coherent structures. Further, we investigated spatial and temporal variability of the respiration signal and coherent exchange at multiple heights, for three mature forest sites with varying canopy and terrain properties for one summer month. A connection between the coherent structures and identified sub-canopy respiration signal was clearly determined. Although not always visible in signals collected above the canopy, certain cases showed a clear link between conditionally sampled respiration events and coherent structures. The dominant time scales of the coherent structure ejection phase (20–30 s), relative timing of maximum coincidence between respiration events and the coherent structure ejection phase (at approximately −10 s from detection) and vertical transport upward through the canopy were shown to be consistent in time, across measurement heights and across the different forest sites. Best results were observed for an open canopy pine site. We conclude that the presented method is likely to be applicable at more open rather than dense (closed) canopies. The results provided a confirmation of the connection between below- and above-canopy scalar time series, and may help the development or refinement of direct methods for the determination of component fluxes from observations above the canopy.


Conditional sampling Eddy covariance Flux partitioning Wavelet decomposition 


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  1. Baldocchi D (2008) ‘Breathing’ of the terrestrial biosphere: lessons learned from a global network of carbon dioxide flux measurement systems. Aust J Bot 56(1): 1–26. doi: 10.1071/BT07151 CrossRefGoogle Scholar
  2. Bergström H, Högström U (1989) Turbulent exchange above a pine forest. 2. Organized structures. Boundary-Layer Meteorol 49(3): 231–263CrossRefGoogle Scholar
  3. Blackwelder RF, Kaplan RE (1976) On the wall structure of the turbulent boundary layer. J Fluid Mech 76(01): 89–112. doi: 10.1017/S0022112076003145 CrossRefGoogle Scholar
  4. Burkard R, Bützberger P, Eugster W (2003) Vertical fogwater flux measurements above an elevated forest canopy at the lägeren research site, Switzerland. Atmos Environ 37(21): 2979–2990. doi: 10.1016/S1352-2310(03)00254-1 CrossRefGoogle Scholar
  5. Cantwell BJ (1981) Organized motion in turbulent-flow. Annu Rev Fluid Mech 13: 457–515CrossRefGoogle Scholar
  6. Cava D, Katul G, Sempreviva A, Giostra U, Scrimieri A (2008) On the anomalous behaviour of scalar flux–variance similarity functions within the canopy sub-layer of a dense alpine forest. Boundary-Layer Meteorol 128: 33–57. doi: 10.1007/s10546-008-9276-z CrossRefGoogle Scholar
  7. Collineau S, Brunet Y (1993a) Detection of turbulent coherent motions in a forest canopy. 1. Wavelet analysis. Boundary-Layer Meteorol 65(4): 357–379. doi: 10.1007/BF00707033 Google Scholar
  8. Collineau S, Brunet Y (1993b) Detection of turbulent coherent motions in a forest canopy. 2. Time-scales and conditional averages. Boundary-Layer Meteorol 66(1): 49–73. doi: 10.1007/BF00705459 CrossRefGoogle Scholar
  9. De Ridder K (2010) Bulk transfer relations for the roughness sublayer. Boundary-Layer Meteorol 134(2): 257–267. doi: 10.1007/s10546-009-9450-y CrossRefGoogle Scholar
  10. Denmead OT, Bradley EF (1987) On scalar transport in plant canopies. Irrigation Sci 8(2): 131–149. doi: 10.1007/BF00259477 CrossRefGoogle Scholar
  11. Etzold S, Buchmann N, Eugster W (2010) Contribution of advection to the carbon budget measured by eddy covariance at a steep mountain slope forest in Switzerland. Biogeosci Discuss 7(2): 1633–1673. doi: 10.5194/bgd-7-1633-2010 CrossRefGoogle Scholar
  12. Eugster W, Zeyer K, Zeeman M, Michna P, Zingg A, Buchmann N, Emmenegger L (2007) Methodical study of nitrous oxide eddy covariance measurements using quantum cascade laser spectrometry over a Swiss forest. Biogeosciences 4(5): 927–939CrossRefGoogle Scholar
  13. Farge M (1992) Wavelet transforms and their applications to turbulence. Annu Rev Fluid Mech 24(1): 395–458. doi: 10.1146/annurev.fl.24.010192.002143 CrossRefGoogle Scholar
  14. Finnigan JJ (1979a) Turbulence in waving wheat. 1. Mean statistics and honami. Boundary-Layer Meteorol 16(2): 181–211. doi: 10.1007/BF02350511 CrossRefGoogle Scholar
  15. Finnigan JJ (1979b) Turbulence in waving wheat. 2. Structure of momentum-transfer. Boundary-Layer Meteorol 16(2): 213–236CrossRefGoogle Scholar
  16. Finnigan J (2000) Turbulence in plant canopies. Annu Rev Fluid Mech 32: 519–571CrossRefGoogle Scholar
  17. Foken T (2006) 50 years of the Monin–Obukhov similarity theory. Boundary-Layer Meteorol 119(3): 431–447. doi: 10.1007/s10546-006-9048-6 CrossRefGoogle Scholar
  18. Gao W, Shaw RH, Paw U KT (1989) Observation of organized structure in turbulent flow within and above a forest canopy. Boundary-Layer Meteorol 47(1): 349–377. doi: 10.1007/BF00122339 CrossRefGoogle Scholar
  19. Goeckede M, Foken T, Aubinet M, Aurela M, Banza J, Bernhofer C, Bonnefond JM, Brunet Y, Carrara A, Clement R, Dellwik E, Elbers J, Eugster W, Fuhrer J, Granier A, Grunwald T, Heinesch B, Janssens IA, Knohl A, Koeble R, Laurila T, Longdoz B, Manca G, Marek M, Markkanen T, Mateus J, Matteucci G, Mauder M, Migliavacca M, Minerbi S, Moncrieff J, Montagnani L, Moors E, Ourcival JM, Papale D, Pereira J, Pilegaard K, Pita G, Rambal S, Rebmann C, Rodrigues A, Rotenberg E, Sanz MJ, Sedlak P, Seufert G, Siebicke L, Soussana JF, Valentini R, Vesala T, Verbeeck H, Yakir D (2008) Quality control of CarboEurope flux data. 1. Coupling footprint analyses with flux data quality assessment to evaluate sites in forest ecosystems. Biogeosciences 5(2): 433–450CrossRefGoogle Scholar
  20. Kobayashi N, Hiyama T (2011) Stability dependence of canopy flows over a flat larch forest. Boundary-Layer Meteorol 139: 97–120. doi: 10.1007/s10546-010-9572-2 CrossRefGoogle Scholar
  21. Lasslop G, Reichstein M, Papale D, Richardson AD, Arneth A, Barr A, Stoy P, Wohlfahrt G (2010) Separation of net ecosystem exchange into assimilation and respiration using a light response curve approach: critical issues and global evaluation. Global Change Biol 16(1): 187–208. doi: 10.1111/j.1365-2486.2009.02041.x CrossRefGoogle Scholar
  22. McNaughton KG, Brunet Y (2002) Townsend’s hypothesis, coherent structures and Monin–Obukhov similarity. Boundary-Layer Meteorol 102(2): 161–175CrossRefGoogle Scholar
  23. Misson L, Baldocchi D, Black T, Blanken P, Brunet Y, Yuste JC, Dorsey J, Falk M, Granier A, Irvine M, Jarosz N, Lamaud E, Launiainen S, Law B, Longdoz B, Loustau D, McKay M, Paw U K, Vesala T, Vickers D, Wilson K, Goldstein A (2007) Partitioning forest carbon fluxes with overstory and understory eddy-covariance measurements: a synthesis based on FLUXNET data. Agric For Meteorol 144(1–2):14–31. doi: 10.1016/j.agrformet.2007.01.006
  24. Paw U KT, Brunet Y, Collineau S, Shaw RH, Maitani T, Qiu J, Hipps L (1992) On coherent structures in turbulence above and within agricultural plant canopies. Agric For Meteorol 61(1–2): 55–68. doi: 10.1016/0168-1923(92)90025-Y CrossRefGoogle Scholar
  25. Poggi D, Porporato A, Ridolfi L, Albertson JD, Katul GG (2004) The effect of vegetation density on canopy sub-layer turbulence. Boundary-Layer Meteorol 111(3): 565–587. doi: 10.1023/B:BOUN.0000016576.05621.73 CrossRefGoogle Scholar
  26. Raupach MR, Finnigan JJ, Brunet Y (1996) Coherent eddies and turbulence in vegetation canopies: the mixing-layer analogy. Boundary-Layer Meteorol 78(3–4): 351–382CrossRefGoogle Scholar
  27. Scanlon TM, Albertson JD (2001) Turbulent transport of carbon dioxide and water vapor within a vegetation canopy during unstable conditions: identification of episodes using wavelet analysis. J Geophys Res 106(D7): 7251–7262CrossRefGoogle Scholar
  28. Scanlon TM, Kustas WP (2010) Partitioning carbon dioxide and water vapor fluxes using correlation analysis. Agric For Meteorol 150(1): 89–99CrossRefGoogle Scholar
  29. Scanlon TM, Sahu P (2008) On the correlation structure of water vapor and carbon dioxide in the atmospheric surface layer: A basis for flux partitioning. Water Resour Res 44(10): W10418CrossRefGoogle Scholar
  30. Shaw RH, McCartney HA (1985) Gust penetration into plant canopies. Atmos Environ 19(5): 827–830. doi: 10.1016/0004-6981(85)90073-3 CrossRefGoogle Scholar
  31. Shaw RH, Zhang XJ (1992) Evidence of pressure-forced turbulent-flow in a forest. Boundary-Layer Meteorol 58(3): 273–288CrossRefGoogle Scholar
  32. Shaw RH, Tavangar J, Ward DP (1983) Structure of the Reynolds stress in a canopy layer. J Clim Appl Meteorol 22(11): 1922–1931CrossRefGoogle Scholar
  33. Shaw RH, Paw U KT, Gao W (1989) Detection of temperature ramps and flow structures at a deciduous forest site. Agric For Meteorol 47(2–4): 123–138. doi: 10.1016/0168-1923(89)90091-9 CrossRefGoogle Scholar
  34. Thomas C (2011) Variability of sub-canopy flow, temperature, and horizontal advection in moderately complex terrain. Boundary-Layer Meteorol 139: 61–81. doi: 10.1007/s10546-010-9578-9 CrossRefGoogle Scholar
  35. Thomas C, Foken T (2005) Detection of long-term coherent exchange over spruce forest using wavelet analysis. Theor Appl Climatol 80(2–4): 91–104CrossRefGoogle Scholar
  36. Thomas C, Foken T (2007) Flux contribution of coherent structures and its implications for the exchange of energy and matter in a tall spruce canopy. Boundary-Layer Meteorol 123(2): 317–337CrossRefGoogle Scholar
  37. Thomas C, Mayer JC, Meixner F, Foken T (2006) Analysis of low-frequency turbulence above tall vegetation using a Doppler sodar. Boundary-Layer Meteorol 119: 563–587. doi: 10.1007/s10546-005-9038-0 CrossRefGoogle Scholar
  38. Thomas C, Martin J, Goeckede M, Siqueira M, Foken T, Law B, Loescher H, Katul G (2008) Estimating daytime subcanopy respiration from conditional sampling methods applied to multi-scalar high frequency turbulence time series. Agric For Meteorol 148: 1210–1229. doi: 10.1016/j.agrformet.2008.03.002 CrossRefGoogle Scholar
  39. Thomas CK, Law BE, Irvine J, Martin JG, Pettijohn J, Davis K (2009) Seasonal hydrology explains inter-annual and seasonal variation in carbon and water exchange in a semi-arid mature ponderosa pine forest in central Oregon. J Geophys Res 114: G04006. doi: 10.1029/2009JG001010 CrossRefGoogle Scholar
  40. Vickers D, Mahrt L (1997) Quality control and flux sampling problems for tower and aircraft data. J Atmos Ocean Technol 14(3): 512–526CrossRefGoogle Scholar
  41. Vickers D, Thomas CK, Martin JG, Law B (2009) Self-correlation between assimilation and respiration resulting from flux partitioning of eddy-covariance CO2 fluxes. Agric For Meteorol 149(9): 1552–1555CrossRefGoogle Scholar
  42. Wilczak JM, Businger JA (1984) Large-scale eddies in the unstably stratified atmospheric surface layer. 2. Turbulent pressure fluctuations and the budgets of heat flux, stress and turbulent kinetic energy. J Atmos Sci 41(24): 3551–3567. doi: 10.1175/1520-0469(1984)041<3551:LSEITU>2.0.CO;2 CrossRefGoogle Scholar
  43. Williams CA, Scanlon TM, Albertson JD (2007) Influence of surface heterogeneity on scalar dissimilarity in the roughness sublayer. Boundary-Layer Meteorol 122(1): 149–165CrossRefGoogle Scholar
  44. Zeeman MJ, Tuzson B, Emmenegger L, Knohl A, Buchmann N, Eugster W (2009) Conditional CO2 flux analysis of a managed grassland with the aid of stable isotopes. Biogeosci Discuss 6: 3481–3510. doi: 10.5194/bgd-6-3481-200 CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. (outside the USA)  2012

Authors and Affiliations

  • Matthias J. Zeeman
    • 1
    • 2
    Email author
  • Werner Eugster
    • 3
  • Christoph K. Thomas
    • 1
  1. 1.College of Earth, Ocean, and Atmospheric SciencesOregon State UniversityCorvallisUSA
  2. 2.Institute of Meteorology and Climate Research Atmospheric Environmental Research (IMK-IFU)Karlsruhe Institute of TechnologyGarmisch-PartenkirchenGermany
  3. 3.Institute of Agricultural SciencesETH ZurichZurichSwitzerland

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