Boundary-Layer Meteorology

, Volume 168, Issue 1, pp 127–153 | Cite as

Large-Eddy-Simulation Study of the Effects of Building-Height Variability on Turbulent Flows over an Actual Urban Area

  • Toshiya YoshidaEmail author
  • Tetsuya Takemi
  • Mitsuaki Horiguchi
Research Article


Large-eddy simulation (LES) is used to investigate the effects of building-height variability on turbulent flows over an actual urban area, the city of Kyoto, which is reproduced using a 2-m resolution digital surface dataset. Comparison of the morphological characteristics of Kyoto with those of European, North American, and other Japanese cities indicates a similarity to European cities but with more variable building heights. The performance of the LES model is validated and found to be consistent with turbulence observations obtained from a meteorological tower and from Doppler lidar. We conducted the following two numerical experiments: a control experiment using Kyoto buildings, and a sensitivity experiment in which all the building heights are set to the average height over the computational region \(h_{all}\). The difference of Reynolds stress at height \(z=2.5h_{all}\) between the control and sensitivity experiments is found to increase with the increase in the plan-area index (\(\lambda _p\)) for \(\lambda _p > 0.32\). Thus, values of \(\lambda _p\approx 0.3\) can be regarded as a threshold for distinguishing the effects of building-height variability. The quadrant analysis reveals that sweeps contribute to the increase in the Reynolds stress in the control experiment at a height \(z= 2.5h_{all}\). The exuberance in the control experiment at height \(z=0.5h_{all}\) is found to decrease with increase in the building-height variability. Although the extreme momentum flux at height \(z=2.5h_{all}\) in the control experiment appears around buildings, it contributes little to the total Reynolds stress and is not associated with coherent motions.


Actual urban building Large-eddy simulation Atmospheric turbulence Roughness parameter Reynolds stress Quadrant analysis 



We thank three anonymous reviewers for their helpful comments and suggestions. We would like to express our deepest gratitude to Dr. Wim Vanderbauwhede at the University of Glasgow, who helped to create an MPI version of the code. We thank Dr. Hiromasa Nakayama at the Japan Atomic Energy Agency for his guidance on the LES modelling. We also thank Prof. Hajime Nakagawa of Kyoto University for conducting the field measurements at the Ujigawa Open Laboratory. This research partly used computational resources under the Collaborative Research Program for Young Scientists provided by the Academic Centre for Computing and Media Studies, Kyoto University. This study was supported by JSPS Kakenhi grant numbers 26282107 and 16H01846, and DPRI Collaborative Research 28H-04 and 29S-01.

Supplementary material

10546_2018_344_MOESM1_ESM.pdf (401 kb)
Supplementary material 1 (pdf 400 KB)


  1. Bou-Zeid E, Overney J, Rogers BD, Parlange MB (2009) The effects of building representation and clustering in large-eddy simulations of flows in urban canopies. Boundary-Layer Meteorol 132(3):415–436CrossRefGoogle Scholar
  2. Cañadillas B, Westerhellweg A, Neumann T (2011) Testing the performance of a ground-based wind LiDAR system: one year intercomparison at the offshore platform FINO1. Dewi Mag 38:58–64Google Scholar
  3. Cheng H, Castro IP (2002) Near wall flow over urban-like roughness. Boundary-Layer Meteorol 104(2):229–259CrossRefGoogle Scholar
  4. Chorin AJ (1967) A numerical method for solving incompressible viscous flow problems. J Comput Phys 2(1):12–26CrossRefGoogle Scholar
  5. Christen A, van Gorsel E, Vogt R (2007) Coherent structures in urban roughness sublayer turbulence. Int J Climatol 27(14):1955–1968CrossRefGoogle Scholar
  6. Coceal O, Thomas T, Castro I, Belcher S (2006) Mean flow and turbulence statistics over groups of urban-like cubical obstacles. Boundary-Layer Meteorol 121(3):491–519CrossRefGoogle Scholar
  7. Coceal O, Dobre A, Thomas T, Belcher S (2007a) Structure of turbulent flow over regular arrays of cubical roughness. J Fluid Mech 589:375–409CrossRefGoogle Scholar
  8. Coceal O, Dobre A, Thomas TG (2007b) Unsteady dynamics and organized structures from dns over an idealized building canopy. Int J Climatol 27(14):1943–1953CrossRefGoogle Scholar
  9. Counihan J (1975) Adiabatic atmospheric boundary layers: a review and analysis of data from the period 1880–1972. Atmos Environ 9(10):871–905CrossRefGoogle Scholar
  10. ESDU (1985) Characteristics of atmospheric turbulence near the ground. Part II: single point data for strong winds (neutral atmosphere). ESDU International, LondonGoogle Scholar
  11. Giometto M, Christen A, Meneveau C, Fang J, Krafczyk M, Parlange M (2016) Spatial characteristics of roughness sublayer mean flow and turbulence over a realistic urban surface. Boundary-Layer Meteorol 160(3):425–452CrossRefGoogle Scholar
  12. Goldstein D, Handler R, Sirovich L (1993) Modeling a no-slip flow boundary with an external force field. J Comput Phys 105(2):354–366CrossRefGoogle Scholar
  13. Inagaki A, Castillo MCL, Yamashita Y, Kanda M, Takimoto H (2012) Large-eddy simulation of coherent flow structures within a cubical canopy. Boundary-Layer Meteorol 142(2):207–222CrossRefGoogle Scholar
  14. Kaimal J, Wyngaard J, Izumi Y, Coté O (1972) Spectral characteristics of surface-layer turbulence. Q J R Meteorol Soc 98(417):563–589CrossRefGoogle Scholar
  15. Kanda M (2006) Large-eddy simulations on the effects of surface geometry of building arrays on turbulent organized structures. Boundary-Layer Meteorol 118(1):151–168CrossRefGoogle Scholar
  16. Kanda M, Moriwaki R, Kasamatsu F (2004) Large-eddy simulation of turbulent organized structures within and above explicitly resolved cube arrays. Boundary-Layer Meteorol 112(2):343–368CrossRefGoogle Scholar
  17. Kanda M, Inagaki A, Miyamoto T, Gryschka M, Raasch S (2013) A new aerodynamic parametrization for real urban surfaces. Boundary-Layer Meteorol 148(2):357–377CrossRefGoogle Scholar
  18. Macdonald R, Griffiths R, Hall D (1998) An improved method for the estimation of surface roughness of obstacle arrays. Atmos Environ 32(11):1857–1864CrossRefGoogle Scholar
  19. Nakajima C, Mitsuta Y, Tanaka M (1979) Ujigawa meteorological tower for boundary layer monitoring. Ann Disaster Prev Res Inst 22B(2):127–141Google Scholar
  20. Nakayama H, Takemi T, Nagai H (2011) Les analysis of the aerodynamic surface properties for turbulent flows over building arrays with various geometries. J Appl Meteorol Clim 50(8):1692–1712CrossRefGoogle Scholar
  21. Nakayama H, Takemi T, Nagai H (2012) Large-eddy simulation of urban boundary-layer flows by generating turbulent inflows from mesoscale meteorological simulations. Atmos Sci Lett 13(3):180–186CrossRefGoogle Scholar
  22. Nakayama H, Leitl B, Harms F, Nagai H (2014) Development of local-scale high-resolution atmospheric dispersion model using large-eddy simulation. Part 4: turbulent flows and plume dispersion in an actual urban area. J Nucl Sci Technol 51(5):626–638CrossRefGoogle Scholar
  23. Nakayama H, Takemi T, Nagai H (2015) Large-eddy simulation of turbulent winds during the fukushima daiichi nuclear power plant accident by coupling with a meso-scale meteorological simulation model. Adv Sci Res 12(1):127–133CrossRefGoogle Scholar
  24. Nakayama H, Takemi T, Nagai H (2016) Development of LO cal-scale H igh-resolution atmospheric DI spersion M odel using L arge-E ddy S imulation. Part 5: detailed simulation of turbulent flows and plume dispersion in an actual urban area under real meteorological conditions. J Nucl Sci Technol 53(6):887–908CrossRefGoogle Scholar
  25. Oikawa S, Meng Y (1995) Turbulence characteristics and organized motion in a suburban roughness sublayer. Boundary-Layer Meteorol 74(3):289–312CrossRefGoogle Scholar
  26. Oke TR (1988) Street design and urban canopy layer climate. Energy Build 11(1):103–113CrossRefGoogle Scholar
  27. Park SB, Baik JJ, Han BS (2015) Large-eddy simulation of turbulent flow in a densely built-up urban area. Environ Fluid Mech 15(2):235–250CrossRefGoogle Scholar
  28. Ratti C, Di Sabatino S, Britter R, Brown M, Caton F, Burian S (2002) Analysis of 3-d urban databases with respect to pollution dispersion for a number of European and American cities. Water Air Soil Pollut Focus 2(5–6):459–469CrossRefGoogle Scholar
  29. Raupach M (1981) Conditional statistics of Reynolds stress in rough-wall and smooth-wall turbulent boundary layers. J Fluid Mech 108:363–382CrossRefGoogle Scholar
  30. Roth M (2000) Review of atmospheric turbulence over cities. Q J R Meteorol Soc 126(564):941–990CrossRefGoogle Scholar
  31. 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
  32. Smagorinsky J (1963) General circulation experiments with the primitive equations: I. The basic experiment. Mon Weather Rev 91(3):99–164CrossRefGoogle Scholar
  33. Stoll R, Porté-Agel F (2006) Effect of roughness on surface boundary conditions for large-eddy simulation. Boundary-Layer Meteorol 118(1):169–187CrossRefGoogle Scholar
  34. Wallace JM (2016) Quadrant analysis in turbulence research: history and evolution. Annu Rev Fluid Mech 48:131–158CrossRefGoogle Scholar
  35. Xie ZT (2011) Modelling street-scale flow and dispersion in realistic winds towards coupling with mesoscale meteorological models. Boundary-Layer Meteorol 141(1):53–75CrossRefGoogle Scholar
  36. Xie ZT, Castro IP (2009) Large-eddy simulation for flow and dispersion in urban streets. Atmos Environ 43(13):2174–2185CrossRefGoogle Scholar
  37. Xie ZT, Coceal O, Castro IP (2008) Large-eddy simulation of flows over random urban-like obstacles. Boundary-Layer Meteorol 129(1):1–23CrossRefGoogle Scholar
  38. Zaki SA, Hagishima A, Tanimoto J, Ikegaya N (2011) Aerodynamic parameters of urban building arrays with random geometries. Boundary-Layer Meteorol 138(1):99–120CrossRefGoogle Scholar
  39. Zhu X, Iungo GV, Leonardi S, Anderson W (2017) Parametric study of urban-like topographic statistical moments relevant to a priori modelling of bulk aerodynamic parameters. Boundary-Layer Meteorol 162:231–253CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Disaster Prevention Research InstituteKyoto UniversityKyotoJapan

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