台北松山機場10號跑道儀器進場區域之低空風切監測與模擬研究

The Observation and Model Simulation of Low-Level Wind Shear at the Runway #10 Instrument Approach Region of Songshang Airport, Taipei

劉沛滕(Pei-Teng Liu)；林博雄(Po-Hsiung Lin)

低空風切 ； 台北盆地 ； 低空風切警示系統 ； 氣象觀測網 ； 數值模擬 ； low-level wind shear ； taipei basin ； low level windshear alert system ； meteorological observatory network ； numerical simulation

航空安全及管理季刊

1卷3期（2014 / 07 / 01）

244 - 269

繁體中文

低空風切是影響飛行起降安全因子之一，其定義為600公尺以下的高度，出現水平方向15 kts/km的風切，並且持續存在10秒鐘以上。台北松山機場自2001年啟用低空風切警示系統（Low Level Windshear Alert System, LLWAS）來監測跑道上空低空風切。然而，台北盆地受到東亞冬夏季風和颱風天氣與氣候系統壟罩和碗型盆地地形影響，低空風切可能不只在松山機場LLWAS監測範圍內，尤其在強盛東北季風和地形交互作用之下，低空風切應會發生在台北盆地西側（林口臺地東側坡地）和西北側（大屯山南坡）區域。為了探討以上情境，本研究在松山機場10號跑道儀器進場區域LLWAS西側新增四個氣象觀測站和一套雲冪儀，透過這一臨時性氣象觀測網進行高時間解析觀測。密集觀測資料經過資料處理和高度推算後，使用「三角形遞迴運算法」所得到的輻合與輻散場，達到低空風切閾值部份來代表250公尺高度低空風切強度。經過2012年冬季2個月資料分析結果顯示，這一臨時觀測網確實能觀測到低空風切現象，並且其發生時間和松山機場LLWAS警報紀錄時間相近。此外，為了解數值天氣模式對低空風切的模擬效果，本研究也使用WRF（Weather Research Forecasting）中尺度氣象模式進行較高時間（10分鐘）與空間（1公里網格）解析度模擬，模擬結果顯示WRF模式對於台北盆地低空風切能合理掌握時空分佈特性。

Low-level wind shear is one of the important factors of flight safety factors. Low-level wind shear is defined as 15 kts/km wind vector difference which persists more than 10 seconds between surface and 2,000 feet (600 m) height. Low-level wind shear could be detected by Low Level Windshear Alert System (LLWAS) and it was installed at Song-Sang Airport ((ICAO airport code RCSS) since 2001. However, under the interaction of monsoon and typhoon synoptic weather flow and the bow topography of Taipei Basin, the low-level wind shear phenomena may occur outside the LLWAS detecting range. Low-level wind shear might occur at western (eastern slope of Linkou highland) and north-western (southern slope of Datnu Mountain) regions of Taipei Basin, especially through the influences of northeast monsoon. In order to prove the above spatial scenario of terrain induced wind shear, study low-level wind shear over, a temporal observation network with four mobile weather stations and one ceilometer LiDAR (Light Detection and Ranging) was conducted at the instrument approach region of RCSS runway #10. After data quality control and wind field estimation at 250 m height, the divergence/convergence values were estimated by ＂triangle recursion calculation method＂, and the area which was over the threshold of low level shear was marked. During 2-month field campaign period in the winter of 2012, the observatory network detected several cases of low-level wind shear which also corresponded with RCSS LLWAS warning record well. Meanwhile, this study checked the performance of numerical weather model simulation on low-level wind shear, The Weather Research Forecasting (WRF) model was used to simulate these observed low-level wind shear cases. The result shows that 10-min and 1-km grid resolution of WRF wind simulation could give reasonable time and spatial distribution of low-level wind shear at Taipei Basin.

1. UCAR, 2013: Low Level Wind-shear Alert System (LLWAS). http://www.rap.ucar.edu/projects/llwas/
2. UCAR, 1992: Network Expansion LLWAS (Phase III), Algorithm Specification. University Corporation for Atmospheric Research, Appendix A&B, pp. 51..
3. ICAO(2005).Manual on Low-Level Wind Shear.International Civil Aviation Organization.
4. Lester, P. F.(2004).Aviation Weather.Jeppesen Sanderson Inc..
5. Lin, C.Y.,Chen, F.,Huang, J.C.,Chen, W.C.,Liou, Y.A.,Chen, W.N.,Liu, S.C.(2008).Urban heat island effect and its impact on boundary layer development and land-sea circulation over northern Taiwan.Atmospheric Environment,42,5635-5649.
6. Meyer, D.R.,Isaminger, M.A.,Proseus, E.A.(1999).Study of the Network Expansion LLWAS (LLWAS-NE) fault identification and system warning optimization through joint use of LLWAS-NE and TDWR Data.Conference on Aviation, Range, and Aerospace Meteorology
7. Münkel, C.(2006).Boundary layer and air quality monitoring with a commercial LiDAR ceilometer.Proc. SPIE 6367., LiDAR Technologies, Techniques, and Measurements for Atmospheric Remote Sensing II
8. Peterson, E.W.,Hennessey, J.P., Jr.(1978).On the use of power laws for estimates of wind power potential.J. Appl. Meteorology,17,390-394.
9. Schäfer, K.,Emeis, S.,Jahn, C.,Münkel, C.,Schrader, S.,Höß, M.(2008).New results from continuous mixing layer height monitoring in urban atmosphere.Proc. SPIE 7107., Remote Sensing of Clouds and the Atmosphere XIII
10. 王嘉瑋(2011)。國立臺灣大學大氣科學研究所。
11. 何台華、涂明聖、蒲金標、魏志憲(2005)。2002 年梅雨季中正與松山機場低空風切之個案研究。大氣科學，33，119-142。
12. 余曉鵬、童茂祥(2011)。臺灣桃園及松山機場低空風切警告系統（LLWAS）介紹。2011 年飛行安全秋季刊，64-73。
13. 梅可忠(2012)。國立臺灣大學大氣科學研究所。
14. 郭忠暉、吳拱辰(2006)。新型低空風切警告系統LLWAS-RS 簡介。飛航天氣，5，28-37。
15. 彭啟明、林松錦(1995)。台灣北部地區混合層高度的觀測與模擬。大氣科學，23，311-336。
16. 蒲金標(2004)。中正國際機場低空風切之分析研究。第八屆全國大氣科學學術研討會，82-92。
17. 蒲金標(2003)。臺灣松山機場低空風切警告系統與低空風切診斷分析。大氣科學，31，181-198。
18. 劉沛滕(2013)。國立臺灣大學大氣科學研究所。