Determination of the Thermal Roughness Length for a Built - - PowerPoint PPT Presentation

Determination of the Thermal Roughness Length for a Built Environment using High Resolution Weather Stations

Daniel Nadeau

• E. Bou-Zeid, M. B. Parlange, G. Barrenetxea, M. Vetterli

Stockholm, 11 June 2008

Motivations

Urban population is increasing

now: 3.3 billion 2030 prediction: 5 billion (UN, 2008) Larger stress of built-up areas on the atmosphere

Need to model land-atmosphere interactions in urban areas

surface roughness z0 thermal roughness length z0h Two methods to do so: morphometric or micrometeorological

2

Motivations

Morphometric approaches

• b ildi

t t l l t h t use building geometry to calculate roughness parameters different models often lead to widely varying estimates of roughness characteristics

Micrometeorological approaches

Stockholm area as seen by Modis

surface temperature typically inferred from satellite measurements MODIS:1-km spatial resolution for Tsfc

Source: NASA, 2008

Resolution too low to account for spatial heterogeneities

3

Motivations

• b ildi

t t l l t h t

Morphometric approaches

different models often lead to widely varying estimates of roughness characteristics use building geometry to calculate roughness parameters

Micrometeorological approaches

Stockholm area as seen by Modis

surface temperature typically inferred from satellite measurements MODIS:1-km spatial resolution for Tsfc Resolution too low to account for spatial heterogeneities

Source: NASA, 2008

Need for high resolution measurements of urban surfaces

4

Research Objectives

• better understand the impacts of spatial heterogeneities on

l d t h i t ti l b t i land-atmosphere interactions over complex urban terrain

• calculate roughness lengths for momentum (z0) and for heat

(z0h) using in situ measurements

Source: S. Mortier, 2007

5

Background

Thermal roughness length z0h

z z0 + d0 z0h + d0 z = 0

Source:Voogt and Grimmond, JAM, 2000

• also referred to as radiometric roughness length or scalar roughness for heat
• intercept of the logarithmic profile for potential temperature in the inertial

sublayer

6

Background

Thermal roughness length z0h over heterogeneous surfaces

Sugita and Brutsaert (WRR, 1990)

vegetated small hills flat grassland with low hedges

Hignett (BLM, 1994) Voogt and Grimmond (JAM, 2000)

sparsely vegetated surfaces light industrial area

Mahli (QJRMS, 1996)

10-17 10-16 10-15 10-14 10-13 10-12 10-11 10-10 10-9 10-8 10-7 10-6 10-5 10-4 10-3 10-2

g

10-1 100

z0h (m)

7

Background

Monin-Obukhov Similarity Theory in the ABL

* ln z

d z d z u u ⎡ ⎤ ⎛ ⎞ − − ⎛ ⎞ ⎛ ⎞ = Ψ + Ψ ⎢ ⎥ ⎜ ⎟ ⎜ ⎟ ⎜ ⎟

WIND SPEED

ln

m m

u k z L L = − Ψ + Ψ ⎢ ⎥ ⎜ ⎟ ⎜ ⎟ ⎜ ⎟ ⎝ ⎠ ⎝ ⎠ ⎢ ⎥ ⎝ ⎠ ⎣ ⎦

z : surface roughness (m)

⎡ ⎤ ⎛ ⎞

AIR TEMPERATURE

z0: surface roughness (m)

*

ln

h s h h p h

z d z d z H ku c z L L θ θ ρ ⎡ ⎤ ⎛ ⎞ − − ⎛ ⎞ ⎛ ⎞ − = − Ψ + Ψ ⎢ ⎥ ⎜ ⎟ ⎜ ⎟ ⎜ ⎟ ⎝ ⎠ ⎝ ⎠ ⎢ ⎥ ⎝ ⎠ ⎣ ⎦

z0h: thermal roughness length (m)

8

The EPFL Campus

a 750 x 500 m campus essentially consisting of buildings, vegetation, roads, and parking lots

S EPFL 2008

9

Source: EPFL, 2008

10

The Experimental Setup

Sensorscope stations

• 92 wireless weather stations
• operating from Nov. 06 to May 07
• perating from Nov. 06 to May 07
• sampling time of 2 min, but we use 30

min averages

• parameters measured: skin

t t i t t i d temperature, air temperature, wind speed, relative humidity, etc.

11

The Experimental Setup

SODAR SODAR

N

12

The Experimental Setup

SODAR / RASS system

• operating from Jul. 06 to May 07

i d d fil

• wind and temperature profiles

measured from 40 to 400 m

• averaging time of 30 min

13

Finding Neutral Profiles

• Buildings range from 5 to 30 m

Range of interest

g g

• Assume blending height ≈ 2 x h0
• zmax/zmin > 2 (Bottema, AE, 1997)

[ 40 100] m z z z ⇒

Adapted from Britter and Hanna, ARFM, 2003

min max

[ 40, 100] m z z z ⇒ = = = 20 m d ⇒ =

(estimated)

1) consistent wind direction with height 2) > 5 /

Criteria for near-neutral conditions

2) u > 5 m/s 3) Least-square fitting between u and ln(z - d0) yields R² ≥ 0.5 4) |Ri | ≤ 0 1

2 2 v v g

g z Ri U V θ θ ∂ ∂ = ⎡ ⎤ ⎛ ⎞ ⎛ ⎞ ∂ ∂ ⎢ ⎥ + ⎜ ⎟ ⎜ ⎟

4) |Rig| ≤ 0.1

z z ⎢ ⎥ + ⎜ ⎟ ⎜ ⎟ ∂ ∂ ⎢ ⎥ ⎝ ⎠ ⎝ ⎠ ⎣ ⎦

14

Wind Sectors

0° 300° 330° 60° 30° 270° 90° 60 240° 120° 90 210° 180° 150° 120 180

15

Finding Neutral Profiles

300 330 60 30

60° 30° 0° 330° 300°

240 270 300 90 60

100 200

270° 90°

240 210 180 150 120

300 400

240° 210° 180° 150° 120°

Number of cases of wind speed exceeding 5 m/s Number of cases of wind speed exceeding 5 m/s. Measurements at 50 m from July 06 to May 07.

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Momentum Surface Roughness

60° 30° 0° 330° 300°

300 330 60 30

no data

100 200

270° 90°

240 270 300 90 60

300 400

240° 210° 180° 150° 120°

240 210 180 150 120

2 00

Number of cases of wind speed exceeding 5 m/s

Center of large towns and cities (Stull 1988)

1.25 1.50 1.75 2.00

m)

Number of cases of wind speed exceeding 5 m/s. Measurements at 50 m from July 06 to May 07.

Center of large towns and cities (Stull, 1988)

0.25 0.50 0.75 1.00

z0 (m

Total number of profiles: 16 128

Median of surface roughness distribution for wind sectors with sufficient data.

270° 300° 330° 0° 30° 60°

wind sector

Near-neutral profiles: 108 (0.7 %)

17

Thermal Roughness Length

Regression for near-neutral potential temperature profiles

3 Nov. 2006 at 7:30 pm

5 5.5 4 4.5

d0) (m)

2 5 3 3.5

ln(z-d

1.5 2 2.5

ln(z0h)

18

• 3.5
• 3
• 2.5
• 2
• 1.5
• 1
• 0.5

1

θs - θ (K)

Thermal Roughness Length

Preliminary results for z0h

( )(

)

0.247 *

exp 4.31Re 5

h

z z k ⎡ ⎤ = − − ⎣ ⎦

For bluff-rough surfaces

10

(Cahill et al., WRR, 1997)

* 0

Re u z

10

• 5

*

Re ν =

10

• 10

z0h (m)

bluff rough sfcs

15

bluff-rough sfcs using θsfc median for θsfc cases using θair median for θair cases

5 10 15 x 10

4

10

• 15

Re*

19

Thermal Roughness Length

Considering surface type

SKIN TEMPERATURE

30 Stations over VEGETATION Stations over GRAVEL

AIR TEMPERATURE

30

Stations over VEGETATION Stations over GRAVEL 15 20 25

perature [°C]

Stations over GRAVEL Stations over CONCRETE

15 20 25

rature [°C]

Stations over GRAVEL Stations over CONCRETE 5 10 15

Skin Tem

5 10 15

Air Tempe

00:00 06:00 12:00 18:00 00:00

00:00 06:00 12:00 18:00 00:00

14 Mar 2007 14 Mar 2007

20

Thermal Roughness Length

,vegetation ,urban s s s

a b θ θ θ = +

Using a weighted average:

a: estimated fractional cover of vegetation For a 10 km fetch

10

b: estimated fractional cover of built-up areas

10

• 5

10

• 10

z0h (m)

bluff-rough sfcs g using θsfc median for θsfc cases using θair median for θair cases using weighted θsfc i i ht d θ

5 10 15 x 10

4

10

• 15

Re*

using weighted θsfc cases

21

Conclusions and Future Work

Conclusions

• momentum surface roughness obtained by regressing near neutral profiles
• momentum surface roughness obtained by regressing near-neutral profiles
• large values of z0h found (compared to literature): from 10-6 to 1 m
• z0h very far from approximation for bluff-rough surfaces
• study convective cases for z0h

Future work

study convective cases for z0h

• footprint analysis
• compare with morphometric models
• perform LES simulations

p

Source: E. Ouyang, E. Bou-Zeid, 2007

22

Future Work

Modeling shaded areas

• shaded areas can greatly

shaded areas can greatly influence skin temperature and in turn the spatially averaged heat flux (Sun and Mahrt, BLM, 1995)

• dependance of z0h on the sun

angle (Kustas et al., AFM, 1989)

• heat flux dominated by sunlit

areas (Voogt and Grimmond, JAM, 2000)

23

Thank you !

24

Thermal Roughness Length

Dependance of z0/z0h on the flow

Source: Brutsaert, Evaporation into the Atmosphere, 1982

25

Instruments

SODAR/RASS accuracy

u horizontal: 0 1 - 0 3 m/s u horizontal: 0.1 0.3 m/s u vertical: 0.03 - 0.1 m/s wind direction: 2 - 3° thickness of vertical layers: 5 – 100 m y range: 200 – 500 m temperature: 0.2 °C

Scintec Flat Array SFAS

Sensorscope accuracy

surface temperature: 0.6°C air temperature: 0.3°C p

Sensorscope station