A Velocity–Dissipation Lagrangian Stochastic Model for Turbulent Dispersion in Atmospheric Boundary-Layer and Canopy Flows

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• 作者：Tomer Duman (1)
  Gabriel G. Katul (2)
  Mario B. Siqueira (3)
  Massimo Cassiani (4)
  
• 关键词：Canopy ; Dispersion ; Dissipation ; Lagrangian stochastic model
• 刊名：Boundary-Layer Meteorology
• 出版年：2014
• 出版时间：July 2014
• 年：2014
• 卷：152
• 期：1
• 页码：1-18
• 全文大小：
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• 作者单位：Tomer Duman (1)
  Gabriel G. Katul (2)
  Mario B. Siqueira (3)
  Massimo Cassiani (4)
  
  1. Nicholas School of the Environment, Duke University, Durham, NC, USA
  2. Department of Civil and Environmental Engineering, Nicholas School of the Environment, Duke University, Durham, NC, USA
  3. Department of Mechanical Engineering, Universidade de Brasília, Brasília, Brazil
  4. The Norwegian Institute for Air Research (NILU), Oslo, Norway
  
• ISSN：1573-1472

文摘

An extended Lagrangian stochastic dispersion model that includes time variations of the turbulent kinetic energy dissipation rate is proposed. The instantaneous dissipation rate is described by a log-normal distribution to account for rare and intense bursts of dissipation occurring over short durations. This behaviour of the instantaneous dissipation rate is consistent with field measurements inside a pine forest and with published dissipation rate measurements in the atmospheric surface layer. The extended model is also shown to satisfy the well-mixed condition even for the highly inhomogeneous case of canopy flow. Application of this model to atmospheric boundary-layer and canopy flows reveals two types of motion that cannot be predicted by conventional dispersion models: a strong sweeping motion of particles towards the ground, and strong intermittent ejections of particles from the surface or canopy layer, which allows these particles to escape low-velocity regions to a high-velocity zone in the free air above. This ejective phenomenon increases the probability of marked fluid particles to reach far regions, creating a heavy tail in the mean concentration far from the scalar source.