Measurements and models of the urban roughness sublayer

Janet Barlow Department of MeteorologyUniversity 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

Urban boundary layer

mixed layer

~2-5h

~0.1zi

z

surface layer

zi~1km

windspeed potentialtemperature

Surface layer wind profile (Monin Obukhov similarity theory MOST)

z0 – roughness lengthd – displacement heightu* – friction velocity

L

z

z

dz

k

uzu m

0

ln)(

roughness sublayer

z/L – stability parameter

inertial sublayer

Street canyon, aspect ratio H/W=0.6

Spatially averaged wind profile

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

1.60

1.80

2.00

-0.2 -0.1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

<u>/Uref

z/H

Flat H/W=0.6

Urban roughness sublayer properties

Results from BUBBLE campaign, Christen (2005)

• 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 (?)

Planar area index

Frontal area index

Urban morphology

t

piP A

A

Square array

Staggered array

LES, Kanda (2006)

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

Part 1: momentum exchange and wind profiles

March 2008 at CSIRO, Canberra, working with John Finnigan and Ian Harman

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

2

( )exp

2

where (Inoue, 1968)

hc

h

z hU z U

L

u U

U

Thanks to Ian Harman for slide material

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 canopiesU

z/H

1

ΛX

ω~ U/(dU/dz)|H

ΛX = 8.1 ω• Generalise MOST to include canopy mixing

• 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

New roughness sublayer function

Test model using vegetation canopy data

• Wind tunnel data (Cheng and Castro, 2002)

Testing model with urban “canopy” data

• Staggered array of cubes• H=20mm, λF = 0.25• Laser Doppler Anemometry (LDA) at blue locations

• Direct numerical simulation (DNS) data (Coceal et al., 2007)

Testing model with urban data

• Staggered array of cubes• λF = 0.25• 16h x 12h x 8h domain• grid size h/32

Snapshot of (u,w) velocity plane

Compare LDA and DNS Reynolds stress

0

0.5

1

1.5

2

2.5

-1.8 -1.6 -1.4 -1.2 -1 -0.8 -0.6 -0.4 -0.2 0

u'w'/u*2

z/h

LDA DNS Derive β= u*/Uh from data

u* not easy to define!Large dU/dz at z = h

Compare LDA and DNS windspeed

0

1

2

3

4

5

6

7

8

9

-2 0 2 4 6 8 10 12 14 16

U/u*

z/h

LDA

DNS

Derive Lc/h from exponential fit to within-canopy winds

NB: Lc/h depends on β

Compare LDA and HF07 model

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

0 2 4 6 8 10

U/u*

z'/h

LDA (4pts)

beta=0.324,Lc/h=2.36

Coceal and Belcher (2004)Canopy drag lengthscale:

Compare DNS and HF07 model

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

-1 0 1 2 3 4 5 6 7 8

U/u*

z'/h

U/u* DNS

beta=0.399 Lc/h = 1.53

Reformulate model for pressure gradient driven flow?

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?

Thanks to Andreas Christen, UBC

A: maybe not!

BUBBLE campaign data

Profile in a street canyon, 1 year

Turbulence is strongly anisotropic

Next step: test model with BUBBLE data

Part 2: scalar exchange and temperature profiles

October 2007 in Japan, working with Manabu Kanda, Ken-Ichi Narita and Esben Almkvist

Street canyon modelFX

Ub

A

WT1

WT2

• 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 = 0.1HHarman, Barlow and Belcher (2004), Boundary-Layer Meteorol., 113, 387-409

0 STwF

Thermal internal boundary layers

Use law of the walle.g. CHENSI (Sini et al. 1996):

Validate against wind tunnel heated cube data

ATREUS projectK. Richards @ Hamburg exptS. Vardoulakis simulations

Thermal internal boundary layers

Q: What is the form of the TIBL for an urban surface at high Reynolds number?

Full scale thermal boundary layers- Louka et al. 2001- Balloons released near wall in Nantes ‘99 expt- very thin BL!

COSMO site, Japan

• Concrete cubes (c. 10cm shell), concrete base

• H = 1.5mScale 1:5

• λF = 0.25

• new sonic anemometer developed, head size 5cm (cf. 20cm)

Experimental set-up

• south east side of cube within array No direct sun• array of thermocouples: x: logarithmically spaced 0 to 25 cmz: 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

Temperature field

• s

• NB: x axis is x0.5

24th Nov 2007

Midday 12:34

Midnight 00:26

Flow around cubes

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

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 turbulenceaim 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