Small-scale spatial variability of turbulence statistics, (co)spectra and turbulent kinetic energy measured over a regular array of cube roughness

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• 作者：Matthias Roth ; Atsushi Inagaki ; Hirofumi Sugawara…
• 关键词：Urban scale model ; Roughness sublayer ; Spatial variability ; Turbulence statistics ; (Co)spectra ; Turbulent kinetic energy
• 刊名：Environmental Fluid Mechanics
• 出版年：2015
• 出版时间：April 2015
• 年：2015
• 卷：15
• 期：2
• 页码：329-348
• 全文大小：1,428 KB
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• 刊物类别：Earth and Environmental Science
• 刊物主题：Environment
  Environmental Physics
  Mechanics
  Hydrogeology
  Meteorology and Climatology
  Oceanography
  
• 出版者：Springer Netherlands
• ISSN：1573-1510

文摘

The spatial variability of flow and turbulence properties above an outdoor scale model of regular cube roughness under neutral stability is investigated using eight simultaneously employed sonic anemometers which are characterized by an extra short transducer span (0.05?m) and high sampling rate (50?Hz). Measurements are conducted in a layer between the top of the cubes with a plan area density of 0.25 and two times the height of the roughness, \(H\) . Large spatial variability (horizontal and vertical) is observed at the two lowest measurement levels ( \(z=H\) and \(1.25H\) ) for all variables considered which include mean wind, Reynolds stress, integral statistics, (co)spectra, budget of turbulent kinetic energy and a spatial quadrant analysis of the momentum transfer. The spatial inhomogeneity almost disappears at \(z = 1.5H\) where normalized variables attain homogeneous surface layer values for neutral stratification. The present results support a new conceptual framework to explain the turbulence behavior just above the canopy consisting of two sublayers which develop in response to the strongly varying surface. Although an individual measurement location below \(z = 1.5H\) is unable to produce representative turbulence statistics above the present bluff body roughness, averaging across a sufficient number of measurement locations to achieve complete spatial sampling of all surface characteristics (canyon spaces, rooftops, etc.), produces representative statistics even at heights which are probably still within the roughness sublayer with values close to the respective inertial subrange predictions.