In-Canopy Turbulence—State of the Art and Potential Improvements

  • M. Theobald
  • B. Loubet
  • C. Ammann
  • L. Branislava
  • B. Chojnicki
  • L. Ganzeveld
  • B. Grosz
  • M. Kaasik
  • S. Noe
  • J. Olejnik
  • J. Rinne
  • M. Shapkalijevski
  • D. Simpson
  • O. Tchepel
  • J.-P. Tuovinen
  • T. Weidinger
  • R. Wichink Kruit
Chapter

Abstract

The turbulence within and immediately above a vegetation canopy is the driver of the exchange processes of heat, trace gases and particles between the soil, the plants and the atmosphere above.

References

  1. Acevedo OC, Fitzjarrald DR (2001) The early evening surface-layer transition: temporal and spatial variability. J Atmos Sci 58:2650–2667Google Scholar
  2. Acevedo OC, Fitzjarrald DR (2003) In the core of the night-effects of intermittent mixing on a horizontally heterogeneous surface. Bound-Layer Meteorol 106:1–33Google Scholar
  3. Acevedo OC, Moraes OLL, Fitzjarrald DR, Sakai RK, Mahrt L (2007) Turbulent carbon exchange in very stable conditions. Bound-Layer Meteorol 125:49–61Google Scholar
  4. Acevedo OC, da Silva R, Fitzjarrald DR, Moraes OLL, Sakai RK, Czikowsky MJ (2008) Nocturnal vertical CO2 accumulation in two Amazonian ecosystems. J Geophys Res 113, paper no. G00B04Google Scholar
  5. Byun D, Schere KL (2006) Review of the governing equations, computational algorithms, and other components of the Models-3 Community Multiscale Air Quality (CMAQ) modeling system. Appl Mech Rev 59:51Google Scholar
  6. Denmead OT, Bradley EF (1985) Flux-gradient relationships in a forest canopy. In: Hutchison BA, Hicks BB (eds) Forest-atmosphere interactions. D. Reidel, Dordrecht (NLD), pp 421–442Google Scholar
  7. Dupont S, Patton EG (2012) Influence of stability and seasonal canopy changes on micrometeorology within and above an orchard canopy: the CHATS experiment. Agric For Meteorol 157:11–29Google Scholar
  8. Dupont S, Otte TL, Ching JK (2004) Simulation of meteorological fields within and above urban and rural canopies with a mesoscale model. Bound-Layer Meteorol 113:111–158Google Scholar
  9. Edburg SL, Stock D, Lamb BK, Patton EG (2012) The effect of the vertical source distribution on scalar statistics within and above a forest canopy. Bound-Layer Meteorol 142:365–382Google Scholar
  10. Fitzjarrald DR, Moore KE (1995) Physical mechanisms of heat and mass exchange between forests and the atmosphere. In: Lowman M, Nadkarni N (eds) Forest canopies—a review of research on a biological frontier. Academic Press, San Diego, 624 pGoogle Scholar
  11. Foudhil H, Brunet Y, Caltagirone JP (2005) A fine-scale k − ε model for atmospheric flow over heterogeneous landscapes. Environ Fluid Mech 5:247–265Google Scholar
  12. Ganzeveld L, Lelieveld J, Dentener FJ, Krol MC, Bouwman AF, Roelofs GJ (2002a) The influence of soil-biogenic NOx emissions on the global distribution of reactive trace gases: the role of canopy processes. J Geophys Res 107Google Scholar
  13. Ganzeveld L, Lelieveld J, Dentener FJ, Krol MC, Roelofs GJ (2002b) Atmosphere-biosphere trace gas exchanges simulated with a single-column model. J Geophys Res 107(D16) Google Scholar
  14. Grell GA, Dudhia J, Stauffer DR (1994) A description of the fifth-generation Penn State/NCAR mesoscale model (MM5). NCAR technical note NCAR/TN-398+STR. doi:10.5065/D60Z716B
  15. Hanna SR, Tehranian S, Carissimo B, Macdonald RW, Lohner R (2002) Comparisons of model simulations with observations of mean flow and turbulence within simple obstacle arrays. Atmos Environ 36:5067–5079Google Scholar
  16. Jacobs AFG, vanBoxel JH, Nieveen J (1996) Nighttime exchange processes near the soil surface of a maize canopy. Agric For Meteorol 82:155–169Google Scholar
  17. Kaimal JC, Finnigan JJ (1994) Atmospheric boundary layer flows, their structure and measurement. Oxford University Press, New YorkGoogle Scholar
  18. Kruijt B, Malhi Y, Lloyd J, Norbre AD, Miranda AC, Pereira MGP, Culf A, Grace J (2000) Turbulence statistics above and within two Amazon rain forest canopies. Bound-Layer Meteorol 94:297–331Google Scholar
  19. Lalic B, Mihailovic DT (2004) An empirical relation describing leaf area density inside the forest for environmental modelling. J Appl Meteorol 43:641–645Google Scholar
  20. Lalic B, Mihailovic DT (2008) Turbulence and wind above and within the forest canopy. In: Gualtieri C, Mihailovic DT (eds) Fluid mechanics of environmental interfaces. Taylor & Francis (GBR), pp 221–240Google Scholar
  21. Lalic B, Mihailovic DT, Rajkovic B, Arsenic ID, Radlovic D (2003a) Wind profile within the forest canopy and in the transition layer above it. Environ Model Softw 18:943–950Google Scholar
  22. Lalic B, Mihailovic DT, Rajkovic B, Arsenic ID, Radlovic D (2003b) Wind profile within the forest canopy and in the transition layer above it. Environ Model Softw 18:943–950Google Scholar
  23. Lalic B, Mihailovic DT, Rajkovic B, Kapor D (2010) An approach to forest-atmosphere interaction modelling: Implications of momentum turbulent transport within the forest. In: Mihailovic DT, Lalic B (eds) Advances in environmental modeling and measurements. Nova Science Publishers, New York, pp 67–76Google Scholar
  24. Lee X, Huang J, Patton EG (2012) A large-eddy simulation study of water vapour and carbon dioxide isotopes in the atmospheric boundary layer. Bound-Layer Meteorol 145:229–248Google Scholar
  25. Loubet B, Cellier P, Milford C, Sutton MA (2006) A coupled dispersion and exchange model for short-range dry deposition of atmospheric ammonia. Q J R Meteorol Soc 132:1733–1763Google Scholar
  26. Martens CS, Shay TJ, Mendlovitz HP, Matross DM, Saleska SR, Wofsy SC et al (2004) Radon fluxes in tropical forest ecosystems of Brazilian Amazonia: night-time CO2 net ecosystem exchange derived from radon and eddy covariance methods. Glob Change Biol 10:618–629Google Scholar
  27. Ogée J, Peylin P, Cuntz M, Bariac T, Brunet Y, Berbigier P, Richard P, Ciais P (2004) Partitioning net ecosystem carbon exchange into net assimilation and respiration with canopy-scale isotopic measurements: an error propagation analysis with 13CO2 and CO18O data. Global Biogeochemical Cycles 18:GB2019Google Scholar
  28. Patton EG, Shaw RH, Judd MJ, Raupach MR (1998) Large-eddy simulation of windbreak flow. Bound-Layer Meteorol 87:276–306Google Scholar
  29. Personne E, Loubet B, Herrmann B, Mattsson M, Schjoerring JK, Nemitz E, Sutton MA, Cellier P (2009) SURFATM-NH3: a model combining the surface energy balance and bi-directional exchanges of ammonia applied at the field scale. Biogeosciences 6:1371–1388Google Scholar
  30. Raupach MR (1988) Canopy transport processes. In: Steffen WL, Denmead OT (eds) Flow and transport in the natural environment: advances and applications. Springer, Berlin, pp 95–129Google Scholar
  31. Raupach MR, Finnigan JJ, Brunet Y (1996) Coherent eddies and turbulence in vegetation canopies: the mixing-layer analogy. Bound-Layer Meteorol 78:351–382Google Scholar
  32. Ryall DB, Maryon RH, Derwent RG, Simmonds PG (1998) Modelling long-range transport of CFCs to mace head Ireland. Q J R Meteorol Soc 124:417–446Google Scholar
  33. Simpson D, Benedictow A, Berge H, Bergström R, Emberson LD, Fagerli H, Flechard CR, Hayman GD, Gauss M, Jonson JE, Jenkin ME, Nyri A, Richter C, Semeena VS, Tsyro S, Tuovinen J-P, Valdebenito A, Wind P (2012) The EMEP MSC-W chemical transport model—technical description. Atmos Chem Phys 12:7825–7865Google Scholar
  34. Skamarock WC, Klemp JB, Dudhia J, Gill DO, Barker DM, Wang W, Powers JG (2005) A description of the advanced research WRF Version 2 (No. NCAR/TN-468+STR). National Center for Atmospheric Research, Boulder, CO, Mesoscale and Microscale Meteorology DivisionGoogle Scholar
  35. Sofiev M, Genikhovich E, Keronen P, Vesala T (2010) Diagnosing the surface layer parameters for dispersion models within the meteorological-to-dispersion modeling interface. J Appl Meteorol Climatol 49:221–233Google Scholar
  36. Staebler RM, Fitzjarrald DR (2004) Observing subcanopy CO2 advection. Agric For Meteorol 122:139–156Google Scholar
  37. Staebler RM, Fitzjarrald DR (2005) Measuring canopy structure and the kinematics of subcanopy flows in two forests. J Appl Meteorol 44:1161–1179Google Scholar
  38. Thom AS (1971) Momentum absorption by vegetation. Q J R Meteorol Soc 97:429–439Google Scholar
  39. Tóta J, Fitzjarrald DR, Staebler RM, Sakai RK, Moraes OMM, Acevedo OC, Wofsy SC, Manzi O (2009) Amazon rain forest subcanopy flow and the carbon budget: Santarém LBA-ECO site. J Geophys Res G: Biogeosci 114Google Scholar
  40. van Gorsel E, Harman IN, Finnigan JJ, Leuning R (2011) Decoupling of air flow above and in plant canopies and gravity waves affect micrometeorological estimates of net scalar exchange. Agric For Meteorol 151:927–933Google Scholar
  41. Walton S, Gallagher MW, Duyzer JH (1997) Use of a detailed model to study the exchange of NOx and O3 above and below a deciduous canopy. Atmos Environ 31:2915–2931Google Scholar
  42. Wilson C, Stover E, Boman B (2004) Minimizing direct deposition of pesticides into waterways associated with Indian River citrus production. HortTechnol 14:545–550Google Scholar
  43. Wu Y, Brashers B, Finkelstein PL, Pleim JE (2003) A multilayer biochemical dry deposition model. 1. Model formulation. J Geophys Res 108, paper no. 4013Google Scholar

Copyright information

© Éditions Quæ 2015

Authors and Affiliations

  • M. Theobald
    • 1
  • B. Loubet
    • 2
  • C. Ammann
    • 3
  • L. Branislava
    • 4
  • B. Chojnicki
    • 5
  • L. Ganzeveld
    • 6
  • B. Grosz
    • 7
  • M. Kaasik
    • 8
  • S. Noe
    • 9
  • J. Olejnik
    • 5
    • 10
  • J. Rinne
    • 11
  • M. Shapkalijevski
    • 6
  • D. Simpson
    • 12
    • 13
  • O. Tchepel
    • 14
  • J.-P. Tuovinen
    • 15
  • T. Weidinger
    • 7
  • R. Wichink Kruit
    • 16
  1. 1.Higher Technical School of Agricultural EngineeringTechnical University of Madrid (UPM)MadridSpain
  2. 2.INRAAgroParisTech, UMR 1402 ECOSYSThiverval-GrignonFrance
  3. 3.Air Pollution and Climate GroupResearch Station AgroscopeZurichSwitzerland
  4. 4.Faculty of AgricultureUniversity of Novi SadNovi SadSerbia
  5. 5.Meterology DepartmentPoznan University of Life SciencesPoznanPoland
  6. 6.Max Planck Institute for ChemistryMainzGermany
  7. 7.Department of MeteorologyEotvos Lorand UniversityBudapestHungary
  8. 8.University of TartuTartuEstonia
  9. 9.Department of Plant Physiology, Institute of Agricultural and Environmental SciencesEstonian University of Life SciencesTartuEstonia
  10. 10.Department of Matter and Energy Fluxes, Global Change Research CenterAS CRBrnoCzech Republic
  11. 11.Department of PhysicsUniversity of HelsinkiHelsinkiFinland
  12. 12.Norwegian Meteorological InstituteOsloNorway
  13. 13.Department Earth and Space SciencesChalmers University TechnologyGothenburgSweden
  14. 14.CESAM and Department of Environment and PlanningUniversity of AveiroAveiroPortugal
  15. 15.Finnish Meteorological InstituteHelsinkiFinland
  16. 16.TNOClimate, Air and SustainabilityUtrechtThe Netherlands

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