The Hong Kong University of Science and Technology

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The Hong Kong University of Science and Technology
Department of Mathematics
Presented by
HUI Kin Yip Ronald
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Low Level Wind Field Analysis Around an
International Airport
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Contents

• Introduction and Background
• Methodology
• LLWAS model
• Ideal Cases
• Gust Front model
• Microburst model
• Real Cases
• Conclusions

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What is Windshear?

• Any change of wind speed and/or direction
• Can appear suddenly in thunderstorms
• Associated with gust fronts and microbursts

Why is windshear so dangerous?

• Dangerous when an aircraft near the ground
• Unbalanced forces appeared suddenly
• Difficult to predict
• Hard for a pilot to make corrections

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CRASH!!!
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Objectives

• Study the model of a windshear alerting system
  and test in real time situation by studying the
  wind field model
• Design a windshear warning system
• Detect the occurrence of strong windshear
• Real case test of system on the Bai-yun
  International Airport in Guangzhou, China

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Methodology

• Use Automatic Weather Station (AWS)

• It is low-cost, easy to maintain and easy to
  install at any places

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Introduction and History of LLWAS

• LLWAS Low Level Windshear Alerting System
• Developed in 1970s by the US Government
• Developed under the Joint Airport Weather Studies
  (JAWS)
• Started at Denver, Colorado in 1982
• Most commonly used method for detecting windshear
  in US nowadays
• It is not well-tested in Asia-Pacific region

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Methodology on Ideal Case

• Only two phenomena will be focused
• Gust Front
• Microburst

• Calculation of Global Wind Difference (GWD)

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Gust Front

• A leading edge of a mesoscale pressure dome
  followed by a surge of gusty winds on or near the
  ground (Wakimoto, 1982)
• Typical length 12 km (along front) and 0.5 km
  (across front)
• Propagation speed 5 to 20 m/s (Uyeda and Zrnic,
  1985)

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Gust Front Model

• Assumptions
• Wind speed at head 0 m/s
• Wind speed in the front 10 m/s
• Wind speed is increasing linearly for 400 m
• The front is propagating in a constant direction

• Background wind speed is added

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Comparisons

• Skew angle of a gust front is the angle between
  the runway and the path of the gust
• Different skew angles of the gust fronts are
  applied
• GWD values of different gust locations are
  calculated in both cases

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Gust Front with 0 skew angle
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Gust Front with 30 skew angle
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Gust Front with 90 skew angle
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Results

• Facts
• Errors apeared near the ends of the runway when
  the skew angle is small
• Errors near the centre of the runway increases
  with the skew angle
• Maximum error ? 3 m/s
• Conclusion
• Reasonable estimate for the gust passing through
  the runway nearly from one end to another

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Microburst

• An outward-moving airflow induced by the
  evaporatively cooled downdraft from a
  thunderstorm or heavy rain.

• Typical duration 10 min
• Typical radius 2 to 3 km

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Microburst Model

• A simplified mathematical microburst model from
  Wilson and Flueck (1986) is used
• Assumptions
• it satisfies the mass continuity equation
• it exhibits realistic radial outflow at ground
  level
• it is symmetric about its centre
• it is radially symmetric about the origin

• Background wind speed is added

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Microburst Model
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Comparisons

• 8 different locations
• Locations of the microbursts are lying on a line
  perpendicular to the runway
• 10 different size of the microbursts
• Radius of microburst 1.8 to 3.8 km

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Results

• Facts
• Both 16-AWS and 18-AWS networks give reasonable
  descirptions to the ideal situation
• However, 16-AWS gives a relatively better result

• Conclusion
• Resonable estimate for idealized microbursts

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Availability of the Real Data

• Operation Period
• 27th June 1998 to 26th October 1998
• a total of 122 days
• Daily Data Monitoring is applied
• Data is collected in different time intervals
• BY1,3,5,6,7,8 every ONE second
• BY2,4 every FIVE seconds
• Time averaging is used to remove high frequency
  fluctuations with periods shorter than 1 minute
  (e.g. jet wash)

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ONE minute
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Case Selection

• All data was averaged by every minute
• GWD is found in each minute
• Criteria for case study
• Failure Periods
• Testing Periods
• Thunderstorm and rainy Days
• High wind speed Periods
• METAR information is used

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Case Selection
Case Date METAR info GWD No. of AWS I 0701
TS, RA, 11 8.10 5 II 0712 TS, RA, 7
9.22 8 III 0714 TS, RA, 4 7.74 8 IV 0722
N/A 7.41 6 V 0911 TS, RA, 5
7.21 7 VI 0913 NIL, 5 7.20 7 VII 1007
NIL, 5 11.39 7 VIII 1013 NIL, 1
9.68 7
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Methodology

• Divergence (DIV) along the runway is used

• Windshear is associated with a pair of
  convergence and divergence zones
• If the pair is moving, it is gust-front like
• If the pair is nearly stationary, it is more
  likely a microburst

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Case I 980701
1440
1520
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Results

• There is a pair of moving divergence and
  convergence zones from 1452 to 1500
• It had gust-front features
• Figures about this case
• GWD ? 8.10 m/s
• Length of Gust ? 195.65 m
• Duration ? 10 minutes
• Skew angle ? 10.49

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Case VII 981007
0230
0300
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Results

• There is a pair of nearly stationary divergence
  and convergence zones
• It had microburst features
• Figures about this case
• GWD ? 11.39 m/s
• Radius of Microburst ? 1.5 km
• Duration ? 8 minutes

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Conclusions

• Our mathematical model can describe and detect
  the occurrence of windshear in both idealized and
  real cases
• It registers a few cases of interesting
  meteorological phenomena which had similar (but
  weaker) characteristics
• Its setup price is relatively cheap, but it is
  reliable and easy to install
• A denser AWS network (with more AWS) can improve
  the skill of the system
• It is suitable detecting windshear for airports
  in the Asia-Pacific Region

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Acknowledgements

• Department of Mathematics, HKUST
• Civil Aviation Administration of China (CAAC)
• Center for Coastal and Atmospheric Research
  (CCAR), HKUST
• 'Operational Windshear Warning System (OWWS)'
  consultancy project
• Your participation

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Thank You