wind speed profiles over greater london, ukbl_met/actual/non_protect... · wind speed profile...
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© University of Reading 2008 www.reading.ac.uk 18 December 2012
Wind speed profiles over Greater London, UK Daniel Drew, Janet Barlow and Siân Lane
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Introduction
• Vertical wind speed profiles are required to address a
number of wind engineering problems:
• Dispersion of pollution
• Designing tall buildings
• Several theoretical and empirical models:
• Power law
• Log law
• Deaves and Harris model
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Wind speed profile models
3
• Log law (Eurocode)
𝑈 𝑧 =𝑢∗
𝜅ln
𝑧
𝑧0 z0=0.8 m for an urban surface (Cook, 1985).
• Deaves and Harris Model (UK, Australia)
𝑈 𝑧 =𝑢∗𝑘
𝑙𝑛𝑧
𝑧0+ 5.75
𝑧
ℎ− 1.88
𝑧
ℎ
2
− 1.33𝑧
ℎ
3
+ 0.25𝑧
ℎ
4
h, the height of the boundary layer is assumed to equal 3250 m.
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4
Introduction
• Vertical wind speed profiles are required to address a
number of wind engineering problems:
• Dispersion of pollution
• Designing tall buildings
• Several theoretical and empirical models:
• Power law
• Log law
• Deaves and Harris model
• Little validation of models, particularly in urban areas.
• Assessed wind speed profile over Greater London.
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The surrounding surface is very heterogeneous (parks, urban, river)
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Gill instruments R3-50 ultrasonic anemometer
•Measures horizontal and vertical components of wind.
•Sampling frequency = 20 Hz
Instruments at BT Tower (190 m)
Observations analysed to estimate:
𝑈∗2 = 𝑢′𝑤′2 + 𝑣′𝑤′2
𝐿 =−𝑢∗
3𝑇
𝜅𝑔 𝑤′𝑇′
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Halo Photonics Streamline pulsed Doppler lidar
•Fully programmable scanner
•Doppler Beam Swinging Method
•Gate length = 30 m
•80 measurement gates
•Instrument location = 20 m above ground level
•Min. measurement height = 90 m above lidar (110 m above ground)
•Profile every 2 minutes
•21st May 2011 – 6th Jan 2012
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Doppler beam swinging method
• Three-beam wind-profiling method
• Derives wind speeds from one vertical and two tilted beams
• 2 s of data taken consecutively in each direction (40,000 pulses)
• Short scan time means flow will not change much over scan period.
• Interval between scans = 120 s
• See Pearson et al. (2009) for comparison with other methods in a rural setting.
θ = 15°
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Halo Photonics Streamline pulsed Doppler lidar
•Fully programmable scanner
•Doppler Beam Swinging Method
•Gate length = 30 m
•80 measurement gates
•Instrument location = 20 m above ground level
•Min. measurement height = 90 m above lidar (110 m above ground)
•Profile every 2 minutes
•21st May 2011 – 6th Jan 2012
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30th September 2011
11
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Mean wind speed profile
• Derived from 5500 hours of observations
• Compared with the 3 models
12
Surface dependent
parameters (Cook, 1997)
z0=0.8 m
h=3250 m
α=0.32
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Stability
• Data filtered by stability derived from BT tower observations.
13 UQ25 UQ50 UQ75
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High wind speeds
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LOW:
U<UQ25
MEDIUM:
UQ25<U<UQ50
HIGH:
UQ50<U<UQ75
VERY HIGH:
U>UQ75
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Terrain dependent parameters
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Roughness length, z0
• Derived from log law using
u* observed at BT tower.
16
• Morphological values determined in Wood et al. (2010).
z0mean= 0.6 m
z0mean= 0.9 m
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Power law exponent, α
• Derived from wind profile
observations.
• Good agreement for
westerly winds.
17
𝛼 =1
ln(𝑧1𝑧2)
0.5
𝑧0
αmean= 0.23
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Boundary layer height, h
18
ℎ =𝑈∗
6𝑓
hmean= 1050 m
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Model comparison
19
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Conclusions
20
Future Work
• Presented wind speed profiles derived from lidar observations.
• High wind speeds occur during neutral conditions. • High wind speed profile shows reasonable fit with
model profiles (log law and Deaves and Harris).
• Lack of Doppler lidar observations below 90 m restricts potential to assess wind loading models- potential for Sodar.
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Extra slides
21
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Doppler beam swinging method
• Three-beam wind-profiling method
• Derives wind speeds from one vertical and two tilted beams
• 2 s of data taken consecutively in each direction (40,000 pulses)
• Short scan time means flow will not change much over scan period.
• Interval between scans = 120 s
• See Pearson et al. (2009) for comparison with other methods in a rural setting.
θ = 15°
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No
. of d
ata
po
ints
Lid
ar w
ind
sp
eed
(m
s-1)
Wind speed (60 minute average)
•60 minute average used to include sufficient data from lidar.
•Some of RMSE can be explained by standard error (average SE = 0.4 ms-1).
•Some difference likely due to large separation between instruments.
Y=0.98x+0.56
RMSE=1.4
Weighted best fit