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研究生:廖育恩
研究生(外文):Yu-EnLiao
論文名稱:台灣桃園國際機場小尺度近即時風場模擬之探析
論文名稱(外文):Research of Simulation of Microscale Near Real-Time Wind Field at Taiwan Taoyuan International Airport
指導教授:袁曉峰袁曉峰引用關係
指導教授(外文):Tony Yuan
學位類別:碩士
校院名稱:國立成功大學
系所名稱:民航研究所
學門:運輸服務學門
學類:航空學類
論文種類:學術論文
論文出版年:2015
畢業學年度:103
語文別:中文
論文頁數:189
中文關鍵詞:低空風切微爆氣流CALMET
外文關鍵詞:low level wind shearmicroburstCALMET
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本研究藉由台灣桃園國際機場建置之低空風切警報系統之警報資料,配合自動氣象觀測系統與中央氣象局探空測站資料,作為CALMET氣象模式之邊界條件,模擬桃園國際機場低空風場,以解決低空風切警報系統無法建立垂直風場結構,顯示局部區域氣流的上升與下沉現象,而不能根本面上解決飛行在低空域的航機避開尚未觸及地面之微爆氣流風險的問題。
本研究包含三個主要流程:第一個流程蒐集桃園國際機場自2011年7月至2012年7月間,低空風切警報系統所發布的低空風切警報。對警報範圍內各區域的警報類型、發生風切的強烈程度做分類與統計。由氣象歷史資料,對發生較強烈的風切警報作當日中尺度氣象背景原因歸納,顯示發布嚴重風切警報及微爆氣流警報的天氣現象多為颱風或鋒面系統通過;統計資料中,機場南面發生微爆氣流警報比例較高,東北面較常發生嚴重風切警報(風增情形),而西北面則較平均。
第二個流程以2012年2月25日LLWAS發布微爆氣流警報時段為例,使用CALMET氣象模式進行數值計算,模擬機場周遭區域之風場。經由輸入資料的處理與模式敏感度分析,使該模式適合於本研究中,短時間、小尺度的時間/空間解析度的要求下使用。本流程顯示LLWAS中央測站所量測的風速/風向數據受到周圍建物影響而有較大的模擬誤差。由於探空資料的缺乏,模式對於低空風場的模擬,尤其在行星邊界層內,約100至1000公尺高度的空域較難準確演示真實風場。本流程亦經由模式敏感度分析,對探空站分布密度提出建議。
第三個流程藉由模式演示下沉氣流發生及消散週期的案例觀察,建立低空風切現象的生命週期、位置與強度之計算與分析方法,並以此為基礎,提出如何應用外延法建立預測風場的構想,對將有可能發生微爆氣流的區域做出報告,進而提升飛航安全。

SUMMERY

This thesis research used the near surface data from Low Level Wind Shear Alert System (LLWAS) and Automated Weather Observing System (AWOS), as well as the upper air data from CWB as boundary conditions for CALMET meteorological model to simulate low level (〈1000 meters) wind field above Taiwan Taoyuan International Airport. For CALMET, a model commonly used on meso-scale wind field modeling, the research focuses on modification and compliance of CALMAT for 3-dimensional wind field simulation in micro-scale region. The results show that the predicted wind field below 100 meters height has reliable accuracy, however, restricted by the amount of upper air station data, the model cannot adequately predict higher level (100meters -1000meters) wind field. Nevertheless, by sensitivity analysis with dummy higher level wind field data, the CALMET model shows good low level wind field prediction. The thesis research demonstrates that the model is able to predict updrafts and downdrafts in local area as well as wind shear occurrence, which may be used to alert aircrafts to avoid microbursts and wind shear at the phase of approach and landing.

Key words: low level wind shear, microburst, CALMET

INTRODUCTION

Low level wind shear is a micro-scale meteorological phenomenon occurring over a short time and small distance. It is commonly observed near microbursts and downbursts caused by thunderstorms and whether fronts. Wind shear has a significant effect during take-off and landing of aircraft due to its effects on control of the aircraft, and it has been a sole or contributing cause of many aircraft safety events. Low level wind shear alert system (LLWAS) measures surface wind direction and wind speed using a network of remote sensor stations which situated near runways and along approach or departure paths of airport. The purpose of LLWAS is to detect low level wind shear and provide alarm information to air traffic control. LLWAS information is expected to reduce the hazard that aircraft encounters low level wind shear and improve aeronautical safety. However, LLWAS has several limitations: (1) winds above the sensors are not detected; (2) winds beyond the peripheral sensors are not detected; (3) updrafts and downdrafts are not detected; and (4) if a shear boundary happens to pass a particular peripheral sensor and the centerfield sensor simultaneously, an alarm will not occur.[1] The above stated limitations leads to some meteorological phenomena such as microbursts which may be smaller than the spacing between the sensors and thus may not be detected. Delta Air Lines Flight 191, a widely known aircraft crash event was resulted from a fatal wind shear caused by a microburst. The microburst occurred in the air and had yet to touch the ground and detected by LLWAS sensors.
This research intends to use numerical modeling to resolve the limitations of LLWAS. By using LLWAS and AWOS measured data as boundary conditions for CALMET, this meteorological model simulated 3-dimensional wind field above Taiwan Taoyuan International Airport. The parameters and setting in CALMET is trimmed to suit for high temporal and spatial resolution requirement of micro-scale and highly dynamic wind field simulation. Further analyze downdraft events, this research also establishes methods to characterize and describe the life cycle, location, and strength of downburst near the surface.


MATERIALS AND METHODS

This research collects the LLWAS data of Taoyuan International Airport in time period from 01/07/2011 to 31/07/2012. Based on the strength of wind gain, wind loss, alert area, and mesoscale meteorological information during the time interval, the data are statistical analyzed to find the possible causes of low level wind shear in the area. By choosing the time period sensitive to wind shear occurrence, detailed information of LLWAS, AWOS and sounding balloon are collected as the boundary conditions that CALMET meteorological modeling is required to simulate low level wind field. Simulation predicted wind field at altitudes 10m, 30m, 50m, 100m, 150m, 200m, 300m and 500m at a time step of 10 seconds are analyzed. The accuracy of positional CALMET modeling is justified by the time period sum of errors of the predicted and true measure wind speeds and wind directions individually. In order to identify the strength and the cover area of downdraft, a set of characterizing parameters and a procedure have been developed. In addition, a method base on image processing has been developed to calculate wind shear strength along and cross the runways.


RESULTS AND DISCUSSION

The statistical analysis of LLWAS alert data is listed in table 2.3-3(mesoscale meteorological events) and appendix I(alert areas). The data shows that the southern west part of the airport is more frequent to have microburst (serious wind loss) occurrence in the time period, while in the north of the northern east part of the airport, wind shear (serious wind gain) occurs more frequent. For modeling, the geological parameters setting in CALMET are listed in table 4.1.1-1 and the parameter settings for simulation are listed in appendix III. The error analysis of CALMET modeling is discussed in chapter 5.1 and the related data are given in appendix I. The results show that a relatively large deviation of wind direction and wind speed data at LLWAS-CF station of Taoyuan International Airport in cope with other stations’ measurements. In the wind shear field diagram, CF station area constantly presented turbulence which should be caused by the obstruction of the closely neighbored buildings, that is, North-east monsoon flows through terminal 1 changes direction and speed to form a turbulence on the leeward of the building.
For case analysis, the wind field and parameter-time diagram are shown in appendix V and listed in table 5.2-3, respectively. The parameters designed to describe downdraft (downdraft area ratio, maximum value of downdraft, mean-value of downdraft, and standard deviation in specific area) show good sensitivity to downdraft events. By comparing the alert information and the simulated wind shear field shown in appendix VI, the accuracy and reliability of the model can be justified.


CONCLUSION

The results show that the predicted wind field below 100 meters height has reliable accuracy, however, restricted by the amount of upper air station data, the model cannot adequately predict higher level (100meters -1000meters) wind field. Although the present air data is not enough for CALMET to model the higher level wind field, however, it displayed temporal and spatial occurrence process of downdrafts using higher level wind field dummy data. In future study, more upper air data such as from weather Doppler radar and from downlink of aircraft sensors are recommended for more precise modeling.

目錄
第一章 緒論 1
1.1 前言 1
1.2 案例回顧:Delta 191航班事件 2
1.3 研究動機與目的 6
1.4 論文架構 7
第二章 低空風切與低空風切警報系統(LLWAS) 8
2.1 低空風切與微爆氣流 8
2.2 桃園國際機場之低空風切警報系統 11
2.3 低空風切警報統計與氣象背景探析 18
第三章 CALMET氣象模式 26
3.1 模式緣起 26
3.2 模式計算原理 28
3.2.1 網格系統 28
3.2.2 風場模擬程序 30
3.3 模式輸入資料 41
3.4 模式特色 43
第四章 研究方法 44
4.1 CALMET模式操作流程 44
4.1.1 地理資料前處理 44
4.1.2 氣象資料前處理 49
4.1.3 CALMET控制檔參數設定 57
4.1.4 模擬輸出檔後處理 59
4.2 地面風場驗證 62
4.3 垂直風場與下沉氣流之量化分析 64
4.4 延跑道/垂直跑道方向風切圖 67
第五章 研究結果與案例分析 71
5.1 模擬結果與測站剔除 71
5.1.1 未剔除任何測站之結果 71
5.1.2 LLWAS-3號站之剔除 85
5.1.3 LLWAS-CF站之剔除 87
5.2 案例分析 89
5.3 模式靈敏度分析 98
第六章 結論、建議與未來工作 113
6.1 研究總結 113
6.2 建議 115
6.2.1 對於CALMET模式的建議 115
6.2.2 對氣象偵測系統的建議 116
6.3 未來工作 117
6.3.1 分析個案數累積 117
6.3.2 外延法與風場預測 117
參考文獻 120


1.Aircraft Accident Report: Delta Air Lines, Inc., Lockheed L-101 1-385-1, N726DA,Dakkas/Fort Worth- International Airport, Texas, National Transportation Safety Board, United States Government, 1985.
2.Delta Air Lines Flight 191, Wikipedia, http://en.wikipedia.org/wiki/Delta_Air_Lines_Flight_191
3.Manual on Low-Level Wind Shear, International Civil Aviation Organization, Doc 9817, 2005.
4.余曉鵬,台灣桃園及松山機場低空風切警報系統(LLWAS)介紹
5.童茂祥,淺談低空風切警示系統,2009年飛航安全冬季刊
6.CALPUFF Modeling System Version6 User Instructions, 2011
7.The CGIAR Consortium for Spatial Information (CGIAR-CSI),
SRTM 90m Digital Elevation Data from http://srtm.csi.cgiar.org/
8.Advanced Spaceborne Thermal Emission and Reflection Radiometer, Wikipedia, http://en.wikipedia.org/wiki/Advanced_Spaceborne_Thermal_Emission_and_Reflection_Radiometer
9.許榮桀,以CALMET模式模擬台灣地區混和層高度,國立台灣大學環境工程研究所碩士論文,2005
10. 黃隆明、張台聖,混和層高度簡易估算法之探討,水土保持學報 44(3):231 – 250 (2012)
11. 中央研究院計算中心GIS小組─開發,范成棟─程式撰寫,http://www.ascc.sinica.edu.tw/gis/ISTIS/tools.html(WGS84_TM2)
12. 中央研究院計算中心GIS小組─開發,范成棟─程式撰寫,http://www.ascc.sinica.edu.tw/gis/ISTIS/tools.html(Transform座標轉換軟體)
13. 陳世芳,混和層高度診斷方法之研究,國立台灣大學環境工程研究所碩士論文,2004
14. Sikuli Script, http://www.sikuli.org/
15. 莊清堯,航電人員不可不知的低空風切角報系統(LLWAS),飛航服務總台
16. Weiguo Wang, William J. Shaw, Timothy RE. Seiple, Jeremy P. Rishel, and Yulong Xie, “An Evaluation of a Diagnostic Wind Model (CALMET), Pacific Northwest National Laboratory, Richland, Washington, 2008
17. Francis L. Ludwig, Douglas K. Miller, Shawn G. Gallaher, “Evaluating a Hybrid Prognostic-Diagnostic Model That Improves Wind Forecast Resolution in Complex Complex Coastal Topography, Journal of Applied Meteorology and Climatology, 2006
18. WRF Users Page, http://www2.mmm.ucar.edu/wrf/users/

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