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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). - PowerPoint PPT Presentation
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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