Measurements and models of the urban roughness sublayer

1. Measurements and models of the urban roughness sublayer Janet Barlow Department of Meteorology University of Reading, UK Co-workers: Omduth Coceal (Reading) John Finnigan, Ian Harman (CSIRO, Australia) Esben Almkvist (Sweden), Manabu Kanda, Ken-Ichi Narita (Japan) Funds from The Met Office, CSIRO, Tokyo Institute of Technology

2. Urban boundary layer windspeed potential temperature z zi~1km mixed layer ~0.1zi surface layer inertial sublayer ~2-5h roughness sublayer z/L – stability parameter z0 – roughness length d – displacement height u* – friction velocity Surface layer wind profile (Monin Obukhov similarity theory MOST)

3. Street canyon, aspect ratio H/W=0.6

4. Spatially averaged wind profile

5. Urban roughness sublayer properties • Wind profile deviates from surface layer form MOST does not apply • Inflection point in wind profile • shear instability causes eddies • Flow is highly turbulent • effective dispersion of pollution • Turbulence is efficent, and intermittent • coherent eddies generated at top of buildings (?) Results from BUBBLE campaign, Christen (2005)

7. Urban morphology Planar area index Frontal area index Square array Staggered array LES, Kanda (2006)

8. Summary • Flow in urban roughness sublayer deviates from MOST • Turbulence transfers momentum efficiently • Large coherent turbulent structures generated within canopy • Barlow, J.F. and Coceal, O. (2008) A review of urban roughness sublayer turbulence, report for Met Office Today Part 1: momentum exchange and wind profiles Testing a vegetation canopy model Part 2: scalar exchange and temperature profiles Experiments to determine temperature near walls

9. Part 1: momentum exchange and wind profiles March 2008 at CSIRO, Canberra, working with John Finnigan and Ian Harman

10. U Simple canopy RSL model (Harman and Finnigan 2007) • Homogeneous, dense canopy • Drag force Fd= U2/Lc with Lc = 1/(Cda) • Lc: canopy drag lengthscale a: leaf area index • Use mixing length model for stress term • At steady state Thanks to Ian Harman for slide material

11. z/H 1 U Single lengthscale to represent canopy mixing • Assume that MOST holds above canopy • BUT need additional lengthscale to represent canopy mixing • Raupach et al. 1996: Mixing layer analogy for vegetation canopies ΛX ω~ U/(dU/dz)|H ΛX = 8.1 ω • Generalise MOST to include canopy mixing

12. New roughness sublayer function • Assume that changes in scale on δω • c1 = f (β, k, lm) • c2: relates z to δω • Influence of RSL decays over depth • Calculate entire wind profile • from β and LC

13. Test model using vegetation canopy data

14. Testing model with urban “canopy” data • Wind tunnel data (Cheng and Castro, 2002) • Staggered array of cubes • H=20mm, λF = 0.25 • Laser Doppler Anemometry (LDA) at blue locations

15. Testing model with urban data • Direct numerical simulation (DNS) data (Coceal et al., 2007) • Staggered array of cubes • λF = 0.25 • 16h x 12h x 8h domain • grid size h/32 Snapshot of (u,w) velocity plane

16. Compare LDA and DNS Reynolds stress Derive β= u*/Uh from data u* not easy to define! Large dU/dz at z = h

17. Compare LDA and DNS windspeed Derive Lc/h from exponential fit to within-canopy winds NB: Lc/h depends on β

18. Compare LDA and HF07 model Coceal and Belcher (2004) Canopy drag lengthscale:

19. Compare DNS and HF07 model Reformulate model for pressure gradient driven flow?

20. Verdict: • Significant differences between data and model – magnitude and form of windspeed profile BUT broad features captured • Q: Is urban canopy turbulence proportional to a single lengthscale? • A: maybe not! • BUBBLE campaign data • Profile in a street canyon, 1 year • Turbulence is strongly anisotropic • Next step: test model with BUBBLE data Thanks to Andreas Christen, UBC

21. Part 2: scalar exchange and temperature profiles October 2007 in Japan, working with Manabu Kanda, Ken-Ichi Narita and Esben Almkvist

22. Ub FX WT2 A WT1 Street canyon model • In-street flow = recirculation + ventilated region • Bulk aerodynamic form for fluxes • Flow and surface roughness determine wT1 for flux from the surface to A across thermal internal boundary layer (TIBL) • Transfer velocity wT2 across shear layer from A • Parameterise depth of TIBL = 0.1H Harman, Barlow and Belcher (2004), Boundary-Layer Meteorol., 113, 387-409

23. Thermal internal boundary layers Use law of the wall e.g. CHENSI (Sini et al. 1996): Validate against wind tunnel heated cube data ATREUS project K. Richards @ Hamburg expt S. Vardoulakis simulations

24. Thermal internal boundary layers • Full scale thermal boundary layers • - Louka et al. 2001 • Balloons released near wall in Nantes ‘99 expt • very thin BL! Q: What is the form of the TIBL for an urban surface at high Reynolds number?

25. COSMO site, Japan • Concrete cubes (c. 10cm shell), concrete base • H = 1.5m • Scale 1:5 • λF = 0.25 • new sonic anemometer developed, head size 5cm (cf. 20cm)

26. Experimental set-up • south east side of cube within array • No direct sun • array of thermocouples: • x: logarithmically spaced 0 to 25 cm • z: 0.1, 0.3, 0.5, 0.8, 1.0H • Sampling rate: 0.5Hz for 2 months (!) • Also: sonic anemometers, surface energy balance Thanks to Esben Almkvist, Ken-Ichi Narita, Manabu Kanda

27. Temperature field • NB: x axis is x0.5 • 24th Nov 2007 • Midday 12:34 • Midnight 00:26 • Flow around cubes • s

28. Verdict (so far): • Thermal boundary layer thin (<1.5cm mostly) by day, thicker at night. • cf. HBB04, estimate depth = 0.1H = 15cm… • Next step: • check windspeed and direction; derive transfer coefficients

29. Conclusions • Urban roughness sublayer resembles vegetation RSL in SOME respects • Vegetation RSL model captures SOME of flow characteristics • Research needed to formulate general model of turbulence • aim for similar, SIMPLE urban RSL model • Scalar exchange with urban surfaces hard to observe and simulate • Next step: test HF scalar RSL model against data j.f.barlow@reading.ac.uk