Abstract
Inferring the vertical variation of the mean turbulent kinetic energy dissipation rate (ε) inside dense canopies remains a basic research problem to be confronted. Using detailed laser Doppler anemometry (LDA) measurements collected within a densely arrayed rod canopy, traditional and newly proposed methods to infer ε profiles are compared. The traditional methods for estimating ε at a given layer include isotropic relationships applied to the viscous dissipation scales that are resolved by LDA measurements, higher order structure function methods, and residuals of the turbulent kinetic energy budget in which production and transport terms are all independently inferred. The newly proposed method extends earlier approaches based on zero-crossing statistics, which were shown to be promising in a number of laboratory flows. The extension to account for an arbitrary threshold (hereafter referred to as the level-crossing method) instead of zero-crossing minimizes the effects of instrument noise on the inferred ε. While none of the ε methods employed here can be titled as ‘measured’, these methods differ in their underlying assumptions and simplifications. Above the canopy, where a balance between production and dissipation rate of turbulent kinetic energy is expected, the agreement among all the methods is reasonably good. In the lower-to-middle layers of the canopy, all the methods agree except for those based on a structure-function inference of ε. This departure can be attributed to the lack of a well-defined inertial subrange in these layers. In the upper canopy layers, the disagreements between the methods are largest. Even the higher order structure-function methods disagree with each other when ε is inferred from third- and fifth-order moments. However, for all layers within the canopy, the proposed zero- and threshold-crossing methods agree well with estimates of ε derived from the isotropic relationship applied to the viscous dissipation range. Finally, the advantages of introducing thresholds to minimize two types of instrument noises, additive and multiplicative, are briefly discussed.
Similar content being viewed by others
References
Bershadskii A, Niemela JJ, Praskovsky A, Sreenivasan KR (2004) Clusterization and intermittency of temperature fluctuations in turbulent convection. Phys Rev E 69(5): 1–5
Cava D, Katul GG (2008) Spectral short-circuiting and wake production within the canopy trunk space of an alpine hardwood forest. Boundary-Layer Meteorol 126(3): 415–431
Cava D, Katul GG (2009) The effects of thermal stratification on clustering properties of canopy turbulence. Boundary-Layer Meteorol 130(3): 307–325
Chamecki M, Dias NL (2004) The local isotropy hypothesis and the turbulent kinetic energy dissipation rate in the atmospheric surface layer. Q J R Meteorol Soc 130: 2733–2752
Finnigan J (2000) Turbulence in plant canopies. Ann Rev Fluid Mech 32: 519–571
Hinze JO (1959) Turbulence. McGraw-Hill, New York, p 790
Hsieh CI, Katul GG (1997) Dissipation methods, Taylor’s hypothesis, and stability correction functions in the atmospheric surface layer. J Geophys Res Atmos 102(D14): 16391–16405
Juang JY, Katul GG, Siqueira MB, Stoy PC, McCarthy HR (2008) Investigating a hierarchy of Eulerian closure models for scalar transfer inside forested canopies. Boundary-Layer Meteorol 128(1): 1–32
Kailasnath P, Sreenivasan KR (1993) Zero crossings of velocity fluctuations in turbulent boundary layers. Phys Fluids 5(11): 2879–2885
Kaimal JC, Finnigan JJ (1994) Atmospheric boundary layer flows: their structure and measurement. Oxford University Press, New York, p 289
Katul GG, Albertson JD (1998) An investigation of higher-order closure models for a forested canopy. Boundary-Layer Meteorol 89(1): 47–74
Katul G, Hsieh CI, Kuhn G, Ellsworth D, Nie DL (1997) Turbulent eddy motion at the forest–atmosphere interface. J Geophys Res Atmos 102(D12): 13409–13421
Katul GG, Mahrt L, Poggi D, Sanz C (2004) One- and two-equation models for canopy turbulence. Boundary-Layer Meteorol 113(1): 81–109
Katul GG, Porporato A, Nathan R, Siqueira M, Soons MB, Poggi D, Horn HS, Levin SA (2005) Mechanistic analytical models for long-distance seed dispersal by wind. Am Nat 166(3): 368–381
Katul G, Poggi D, Cava D, Finnigan J (2006) The relative importance of ejections and sweeps to momentum transfer in the atmospheric boundary layer. Boundary-Layer Meteorol 120(3): 367–375
Liepmann HW (1949) Die anwendung eines satzes uber die nullstellen stochastischer funktionen auf turbulenzmessungen. Helv Phys Acta 22(2): 119–126
Moeng CH, Sullivan PP (1994) A comparison of shear-driven and buoyancy-driven planetary boundary-layer flows. J Atmos Sci 51(7): 999–1022
Monin AS, Yaglom AM (1975) Statistical fluid mechanics. MIT Press, Cambridge, MA, p 782
Nakagawa H, Nezu I (1977) Prediction of contributions to Reynolds Stress from bursting events in open- channel flows. J Fluid Mech 80: 99–128
Nathan R, Katul GG, Horn HS, Thomas SM, Oren R, Avissar R, Pacala SW, Levin SA (2002) Mechanisms of long-distance dispersal of seeds by wind. Nature 418(6896): 409–413
Patton EG, Shaw RH, Judd MJ, Raupach MR (1998) Large-eddy simulation of windbreak flow. Boundary-Layer Meteorol 87(2): 275–306
Poggi D, Katul GG (2006) Two-dimensional scalar spectra in the deeper layers of a dense and uniform model canopy. Boundary-Layer Meteorol 121(2): 267–281
Poggi D, Katul G (2007) The ejection-sweep cycle over bare and forested gentle hills: a laboratory experiment. Boundary-Layer Meteorol 122(3): 493–515
Poggi D, Katul GG (2008a) The effect of canopy roughness density on the constitutive components of the dispersive stresses. Exp Fluids 45(1): 111–121
Poggi D, Katul GG (2008b) Micro- and macro-dispersive fluxes in canopy flows. Acta Geophys 56(3): 778–799
Poggi D, Katul G (2009) Flume experiments on intermittency and zero-crossing properties of canopy turbulence. Phys Fluids 21(6): 065103
Poggi D, Katul GG, Albertson JD (2004a) A note on the contribution of dispersive fluxes to momentum transfer within canopies—research note. Boundary-Layer Meteorol 111(3): 615–621
Poggi D, Katul GG, Albertson JD (2004b) Momentum transfer and turbulent kinetic energy budgets within a dense model canopy. Boundary-Layer Meteorol 111(3): 589–614
Poggi D, Porporato A, Ridolfi L, Albertson JD, Katul GG (2004c) The effect of vegetation density on canopy sub-layer turbulence. Boundary-Layer Meteorol 111(3): 565–587
Poggi D, Porporato A, Ridolfi L, Albertson JD, Katul GG (2004d) Interaction between large and small scales in the canopy sublayer. Geophys Res Lett 31(5): 4
Poggi D, Katul G, Albertson J (2006) Scalar dispersion within a model canopy: measurements and three-dimensional Lagrangian models. Adv Water Res 29(2): 326–335
Poggi D, Katul GG, Cassiani M (2008) On the anomalous behavior of the Lagrangian structure function similarity constant inside dense canopies. Atmos Environ 42(18): 4212–4231
Pope SB (2000) Turbulent flows. Cambidge University Press, UK, p 771
Raupach MR (1981) Conditional statistics of Reynolds stress in rough-wall and small-wall turbulent boundary layers. J Fluid Mech 108: 363–382
Raupach MR, Shaw RH (1982) Averaging procedures for flow within vegetation canopies. Boundary-Layer Meteorol 22(1): 79–90
Raupach MR, Thom AS (1981) Turbulence in and above plant canopies. Ann Rev Fluid Mech 13: 97–129
Raupach MR, Finnigan JJ, Brunet Y (1996) Coherent eddies and turbulence in vegetation canopies: the mixing-layer analogy. Boundary-Layer Meteorol 78(3–4): 351–382
Rice SO (1945) Mathematical analysis of random noise. Bell Syst Tech J 24(1): 46–156
Rodean H (1996) Stochastic Lagrangian models of turbulent diffusion. American Meteorological Society, Boston, MA, p 84
Sreenivasan KR, Bershadskii A (2006a) Clustering properties in turbulent signals. J Stat Phys 125(5–6): 1145–1157
Sreenivasan KR, Bershadskii A (2006b) Finite-Reynolds-number effects in turbulence using logarithmic expansions. J Fluid Mech 554: 477–498
Sreenivasan KR, Prabhu A, Narasimha R (1983) Zero-crossings in turbulent signals. J Fluid Mech 137(DEC): 251–272
Sullivan PP, McWilliams JC, Moeng CH (1994) A subgrid-scale model for large-eddy simulation of planetary boundary-layer flows. Boundary-Layer Meteorol 71(3): 247–276
Taylor GI (1938) The spectrum of turbulence. Proc R Soc Lond A Math Phys Sci 164(A919): 0476–0490
Tennekes H, Lumley JL (1972) A first course in turbulence. MIT Press, Cambridge, p 300
Wilson JD (2000) Trajectory models for heavy particles in atmospheric turbulence: comparison with observations. J Appl Meteorol 39(11): 1894–1912
Wyngaard JC, Clifford SF (1977) Taylor’s hypothesis and high frequency turbulence spectra. J Atmos Sci 34(6): 922–929
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Poggi, D., Katul, G.G. Evaluation of the Turbulent Kinetic Energy Dissipation Rate Inside Canopies by Zero- and Level-Crossing Density Methods. Boundary-Layer Meteorol 136, 219–233 (2010). https://doi.org/10.1007/s10546-010-9503-2
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10546-010-9503-2