40 Characteristics of Wind Shear in Recent Three Years at Incheon International Airport

Monday, 13 January 2020
Hall B (Boston Convention and Exhibition Center)
Jae Won Lee, KMA, Incheon, Korea, Republic of (South); and S. K. KIM, K. Y. BYEN, and J. KIM
Manuscript (202.0 kB)

1. Introduction
Wind shear is a microscale meteorological phenomenon which refers to changes in wind direction and/or speed over a short distance. It can normally occur due to strong temperature inversion or atmospheric density gradients. (FAA, 2008). In particular, low-level wind shear has contributed to a significant number of aviation accidents and has given rise to more than 400 deaths in the United States and 1,400 deaths worldwide from 1973 to 1985 (NCAR, 2017).
Incheon International Airport (N37 27’ 45’’, E126 26’ 21’’, elevation 7m) is a maritime airport constructed on a man-made island in 2001. It operates 24-hour unlike the other inland international airports in South Korea. There is no domestic flight except for transfer in Incheon International Airport, but it can be used for emergency landings at curfew time of other international airports. The paper studied the characteristics of occurrence of hourly wind shear from December, 2015 to November, 2018. We focused on the Terminal Doppler Weather Radar (TDWR) radial velocity to classify the types of wind shear and tried to contribute to the safety of Incheon International Airport by suggesting a risk-matrix to minimize the damage in the occurrence of severe wind shear.
2. Dataset and method of research
In Incheon International Airport, Aeronautical Meteorological Personnel (AMP) is using mostly two ways to observe wind shear. One is TDWR and the other is Low Level Wind shear Alert System (LLWAS). If air-traffic controllers or pilots report regarding wind shear to AMP, AMP makes a database about the reports.
TDWR has been operating since 2001 to detect and forecast weather conditions on and around airports. The radar device is product of Mitsubishi Electric Co., Ltd. The video process and radar control process, which are radar signal processing devices, and IRIS software are products of Vaisala (US SIGMET at the time of introduction). All of the equipment except the antenna and the server controller have two independent channels of software and hardware, so that the system automatically switches in the event of one system failure. The frequency band is C-Band (5.637GHz), the transmitter output is Klystron (maximum output 250kW), and the detection range is 150m - 120km in Doppler mode. It has a performance of 300m - 428km in intensity mode.
LLWAS was installed in Incheon International Airport for the first time in 2001, and currently utilized equipment is the product of Selex ES GmbH (now) Leonard LEONARDO Germany GmbH in Germany installed in 2010. The top of the aircraft uses twelve sensors located around the runway to detect wind shear and microbursts near the airport at altitudes around 30 meters.

3. Analysis
3-1. Accuracy analysis of observation equipment
The data quality of wind shear alarm near Incheon International Airport can check the precision of the two wind shear instruments. Unfortunately, the accuracy of the alarm cannot be evaluated because of absence of true alarm data. Precision was assessed by calculating the Critical Success Index (CSI) monthly for three years.

3-2. Monthly and Seasonal characteristics (Climate data perspective)
At the Incheon International Airport during December 2015 - November 2018, the frequency of wind shear occured once in every 22-29 hour-interval in winter, while an average of 50-100 hour-interval in summer.
The incidence of wind shear alarm at Incheon International Airport occurred relatively in the afternoon. The effect of convection on the solar activity and the phase change of the sea breeze due to the location of the airport on the coast should also be considered. In the autumn of 2016, the period of particularly showing different characteristics showed a high incidence from evening to dawning.

3.3. Classification according to radial velocity type (radar image characteristic point of view)
Classification by radial velocity can be divided into 4 types:
(1) Low-level jet shape: When the low level jet-stream analyses about 850hPa, the low-level jet shape observed in summer season. Also, this shape signifies the strong wind so in the radial velocity image, we could see the velocity folding. The frequency of velocity folding increased just before wind shear occurred. The strongest 10-minute average wind speed recoded mostly higher 20KT. As the wind direction changes from SE to SW, the probability of microburst increases.
(2) The convergence-divergence pattern: It is a form where both convergence and divergence appear around the TDWR. There was no clear and visible shape in this pattern, so the observer should have monitored in real time.
(3) S-shape: The S-shape does not appear frequently, but when it does, wind shears was observed with a high probability. If the shape makes a clear ‘S’, then wind shear and microburst can appear together. The clearer the S-shape is, the higher possibility the microburst occur. S-shape is more likely to occur at atmospheric veering.
(4) The horizontal-shear shape: This type is similar to the low-lever jet shape, but the microburst does not occur. Not like the low-lever jet shape, the strongest wind speed line makes convergence and divergence.
Usually, the S-shape can be observed in spring, the low-level jet shape in summer, and the convergence-divergence shape in autumn.
4. Application to operational now-casting for aviation
As shown in the figure (A), a risk-matrix which is composed of frequency of occurrence (i.e., small to large) and leading-time (i.e., 30-120 min) deducted in the pattern study. Verification for the risk matrix was accomplished using dataset during January-May 2018. In order to improve operational aviation weather monitoring for decision making and visualization, an enhanced risk-matrix was reconstructed using June-September 2018 dataset (B in the figure), and verified. The one concern is, TDWR cannot process the radial velocity clearly when it rains, so forecasters have difficulties to use the risk-matrix.

When the forecasters decide to warn wind shear and microburst, it is very important to notice even before several minutes these phenomena occur. In this reason, this study to upgrade the risk-matrix should be continued.

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