Boundary Layer Meteorology The wind that shakes the buildings

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1 Boundary Layer Meteorology The wind that shakes the buildings Prof. Janet F. Barlow Department of Meteorology Director Technologies for Sustainable Built Environments (TSBE) Centre University of Reading

2 Today s talk A brief history of turbulence and wind engineering A framework for urban boundary layers Recent research findings in London

3 A history of BL turbulence and wind engineering 1904 Prandtl: Fluid flow in very little friction 1935 Pagon: 8 papers on aerodynamics in civil engineering 1941 Kolmogorov: -5/3 power law for spectrum 1946 Obukhov: length defined for surface layer 1950 von Karman: applications of aerodynamics in engineering 1954 Monin Obukhov similarity theory published 1961 AmSocCivEng: 6 papers on wind actions on structures 1961 Davenport: model of wind-excited behaviour of structures st Int Symp on Wind Effects on Buildings and Structures (Teddington, UK) 1968 Kansas experiment: established surface layer theory predictions 1970 BLM journal started 1971 Businger et al: flux profile results 1972 Kaimal et al: spectral results for varying stabilities 1973 Minnesota experiment: mixed layer scaling demonstrated for BLayer 1974 Willis and Deardorff: mixed layer scaling deduced from lab experiments 1980 JWEIA started

4

5 The Kansas Experiment, 1968

6 z obs z eff X Shellard, 1963 conf paper

7 Davenport 1963 conf discussion To do

8 Wind profile over different surfaces Davenport conf paper

9 Wind profiles over inhomogeneous surfaces Framework for the urban boundary layer: Scale Heterogeneity Roughness sublayer Canopy-like turbulence (?) Urban units Packing density and roughness

10 Effect of urban area on wind profile Plate and Kiefer (2001)

11 Different scales of the Urban Boundary Layer Urban Boundary Layer, z i Internal Boundary Layer, z IBL Street canyon, H/W Building, H Street m Neighbourhood m City 1-10km

12 Urban roughness sublayer Kastner-Klein and Rotach 2004

13 Wind profiles in RSL z 3H H U(z)

14

15 Mixing layer hypothesis (Raupach et al 1996) Inflection point in mean wind profile unstable, leads to growth of coherent structures Responsible for mixing throughout vegetation canopy depth Turbulence highly efficient (e.g. R uw > surface layer values)

16 Coherent structures: urban field study evidence Feigenwinter et al. (2005) in Basel Ensemble averaged coherent structure Ejection-sweep cycle Temperature microfront Quadrant analysis and skewness profiles: sweeps dominate within canopy, ejections above

17 Coherent structures: deductions from DNS Coceal et al. 2007c: cartoon Consensus not yet reached about coherent structures over urban surfaces form, generation

18

19 Street canyon flow H/W = 0.6 Isolated roughness H/W < 0.3 Wake interference 0.3 < H/W < 0.65 Skimming flow H/W > 0.65 H/W = 1.0 Oke, 1988

20 Defining packing density Frontal area index f : Frontal area/lot area Plan area index p : Plan area/lot area

21 Roughness parameters depend on packing density

22 Padhra 2010, PhD thesis London s packing density

23 London-based research projects DAPPLE ( ) street level dispersion REPARTEE ( ) vertical pollutant distribution ACTUAL ( ) building design interactions with urban climate at a range of scales ClearfLo ( ) air quality at city scale

24 Regent s Park 1.6 km Westminster City Council rooftop 1.6 km BT Tower Hyde Park River Thames

25 Barlow et al JWEIA

26 Cities are collections of relatively short streets between intersections - the classical street canyon is a rarity. Westminster City Council rooftop DAPPLE Arnold et al. 2004, STOTEN

27 2004 campaign BT Tower NE wind direction Barlow et al BLM Led by A. Robins

28 Wood et al. 2009, BAMS

29 Funded under the Challenging Engineering programme ( )

30 ACTUAL: observing flow at range of scales Bradley and Barlow, ISARS conf 2012 NEW urban sodar <200m Doppler lidar Barlow et al ACP 90m < z < 2000m BT Tower at 190 m Wood et al BLM Helfter et al ACP Barlow et al JWEIA Barlow et al BLM Roof top at ~20m KCL: Scintillometers (various heights) Grimmond et al. Wood et al STOTEN

31 Regent s Park 1.6 km Westminster City Council rooftop Hyde Park 1.6 km BT Tower KCL rooftop River Thames

32 How do urban winds and temperatures drive building infiltration? Room next to busy road (~3600 veh hr -1 ) Use ambient pollution (NOx) as a tracer to monitor ventilation rate Aidan Brocklehurst, PhD with Stuart Upton (BRE)

33 Lag of indoor concentrations ~ 4 hours Infiltration rate driven strongly by wind direction

34 What is the evolution of winds along an urban river throughout a day? 4 11 New horizontal scanning lidar technique Comparison with sonic anemometry, scintillometer Wood et al. 2012, STOTEN C cloudy, S sunny Feb to May 2011 Curtis Wood, post-doc (now FMI) Collaboration with Sue Grimmond et al. at KCL

35 How well do Doppler lidar measured wind-speeds compare with mast-based measurements? LiDAR gate resolution Doppler lidar observed windspeed using Doppler beam swinging (DBS) Comparison with BT winds: U lidar =0.98 U BT Sampling error ~ 0.4 ms -1 L Lane S.E. et al., JWEIA Dan Drew, post-doc

36 How do measured UBL wind profiles compare with ESDU non-equilibrium model? (a) 1km square roughness length map for London MacDonald (1998) applied to LUCID building (a) morphology (b) (b) Roughness length along transect WCC to London Heathrow Black: morphology Red: land use proxy (Cook 1997) Drew et al., subm. JWEIA

37 Lidar wind-speed profile, U > U 75 (1052 hours): red Urban morphology roughness: black circles Land use proxy: black stars

38 How do measured BL wind profiles compare with meteorological models? Unified Model (UM), 1.5km resolution, M. Best heat flux scheme Forecast model (blue), lidar (red) 22:00 UHI, strong jet present Sian Lane, PhD CASE award Met Office

39 Conclusions Homogeneous boundary layers (reasonably!) well understood Inhomogeneous BL s much focus on urban Combination of methods yields best insight New remote sensing techniques well suited to UBL investigations

40 Where do the research challenges lie? Low wind conditions Stability effects Low carbon building design Green infrastructure Cities as laboratories

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