论文

基于激光雷达和航空器报告识别低空风切变及其演变过程研究

  • 丁婕 ,
  • 张镭 ,
  • 胡泽勇 ,
  • 王介民 ,
  • 张开俊 ,
  • 梁捷宁 ,
  • 王元 ,
  • 张志达 ,
  • 徐丽丽 ,
  • 王瑾 ,
  • 蔡涛
展开
  • 1. 半干旱气候变化教育部重点实验室,兰州大学大气科学学院,甘肃 兰州 730000
    2. 中国科学院西北生态环境资源研究院寒旱区陆面过程与气候变化重点实验室,甘肃 兰州 730000
    3. 中国民用航空西北地区空中交通管理局甘肃分局,甘肃 兰州 730087
    4. 中国科学院大学,北京 100049
    5. 兰州大学西部生态安全省部共建协同创新中心,甘肃 兰州 730000
    6. 兰州中心气象台,甘肃 兰州 730020

丁婕(1992 -), 女, 甘肃兰州人, 博士研究生, 主要从事航空气象学及其应用的研究. E-mail:

收稿日期: 2022-08-22

  修回日期: 2022-10-21

  网络出版日期: 2023-09-26

基金资助

第二次青藏高原综合科学考察研究项目(2019QZKK0103); 国家自然科学基金项目(91837208); 中国科学院战略性先导科技专项(XDA20060101)

Study of Low-Level Wind Shear and Its Evolution Based on LIDAR and Aircraft Reports Identification

  • Jie DING ,
  • Lei ZHANG ,
  • Zeyong HU ,
  • Jiemin WANG ,
  • Kaijun ZHANG ,
  • Jiening LIANG ,
  • Yuan WANG ,
  • Zhida ZHANG ,
  • Lili XU ,
  • Jin WANG ,
  • Tao CAI
Expand
  • 1. Key Laboratory for Semi-Arid Climate Change of the Ministry of Education,College of Atmospheric Sciences,Lanzhou University,Lanzhou 730000,Gansu,China
    2. Key Laboratory of Land Surface Processes and Climate Change in Cold and Arid Regions,Northwest Institute of Eco-Environment Resources,Lanzhou 730000,Gansu,China
    3. Gansu Sub -Bureau of Northwest Air Traffic Management Bureau of Civil Aviation of China,Lanzhou 730087
    4. University of Chinese Academy of Sciences,Beijing 100049,China
    5. Collaborative Innovation Center for Western Ecological Safety,Lanzhou University,Lanzhou 730000,Gansu,China
    6. Lanzhou Central Meteorological Observatory,Lanzhou 730020,Gansu,China

Received date: 2022-08-22

  Revised date: 2022-10-21

  Online published: 2023-09-26

摘要

低空风切变是影响航空安全和高效运行的重要因素。中川机场作为山地型内陆机场, 受复杂地形和天气系统影响, 风切变发生频率高且多发于夏季。本文根据航空器报告统计分析2009 -2018年中川机场低空风切变事件的时空分布特征, 采用基于测风激光雷达(Windcube 400s-at)资料的风切变识别方法对比了固定窗口法和自适应窗口法的识别效果, 并探究了该地区风切变三维结构的连续演变和空间分布特征。研究表明, 近十年中川机场低空风切变事件发生频次的增长率大于航班量的增长率; 受天气影响, 低空风切变事件峰值出现于4 -7月和8 -10月; 67.2%低空风切变事件伴随对流天气, 多发生于午后200 m高度以下, 危险性高、 风切变强度受对流天气强度影响。相比于固定窗口法, 自适应窗口法识别范围更大, 更适用于风切变三维结构连续演变的研究。该区域风切变垂直空间分布低, 水平尺度多为1000~1500 m和2000~2600 m, 过程持续时间多在20 min内, 移动方向主要受背景风影响。本文研究结果有助于进一步了解该区域风切变的特征, 为低空风切变识别、 演变机理和预报预警等提供参考。

本文引用格式

丁婕 , 张镭 , 胡泽勇 , 王介民 , 张开俊 , 梁捷宁 , 王元 , 张志达 , 徐丽丽 , 王瑾 , 蔡涛 . 基于激光雷达和航空器报告识别低空风切变及其演变过程研究[J]. 高原气象, 2023 , 42(5) : 1338 -1350 . DOI: 10.7522/j.issn.1000-0534.2022.00094

Abstract

Low-level wind shear significantly impacts aviation safety and operational efficiency.Zhongchuan Airport, located in a mountainous inland region, experiences the influence of complex terrain and weather systems.Wind shear is frequently observed during the summer season.This study analyzes the spatial and temporal characteristics of low-level wind shear events at Zhongchuan Airport using aircraft reports spanning from 2009 to 2018.During the observation period from May 2016 to November 2017, a total of 18 low-level wind shear events were confirmed through aircraft verification.Two methods, namely the fixed and adaptive window methods, were compared to identify wind shear events using LIDAR data from the Windcube 400s-at instrument.The study also explored the continuous evolution and spatial characteristics of the three-dimensional wind shear structure.The results indicate that the frequency of low-level wind shear events has increased at a faster rate compared to the flight volume at Zhongchuan Airport over the past ten years.The peak months for low-level wind shear events at Zhongchuan Airport are April-July and August-October, influenced by local weather patterns.The peak months for low-level wind shear events at Zhongchuan Airport are April-July and August-October, influenced by local weather patterns.Wind shear induced by convective weather occurs in the weak or non-echo region surrounding the convective cloud, resulting from the convergence of updrafts and downdrafts outside the cloud, or the formation of a gust front following the downdraft's contact with the ground.The wind shear factor is correlated with the intensity of radar echoes.Compared to the fixed window method, the adaptive window method had a larger recognition range due to the different data sets included in the recognition window.Therefore, the adaptive window method was found to be more suitable for studying the three-dimensional evolution of wind shear structures.Therefore, the adaptive window method is better suited for studying the evolution of the three-dimensional wind shear structure.The wind shear in the vicinity of Zhongchuan Airport is characterized by a low spatial distribution, small horizontal scale, and short duration, primarily concentrated in the small-scale and γ mesoscale.In other words, the wind shear events occurred at relatively low altitudes, with horizontal scales mostly ranging between 1000~1500 m and 2000~2600 m, lasting less than 20 minutes.Furthermore, 40.5% of the wind shear events were attributed to the movement of the wind, primarily influenced by the background wind.The findings of this study contribute to a better understanding of the characteristics of wind shear, offering valuable insights for the identification, mechanisms, forecasting, and early warning of low-level wind shear events at Zhongchuan Airport.

参考文献

null
Bateman C D.Reactive Windshear Warning Instrument: EP88903098.7[P].1992-07-08[2022-08-22].
null
Boilley A Mahfouf J F2013.Wind shear over the Nice C?te d'Azur airport: case studies[J].Natural Hazards and Earth System Sciences13(9): 2223-2238.DOI: 10.5194/nhess-13-2223-2013 .
null
Chan P W2010.LIDAR-based turbulence intensity calculation using glide-path scans of the Doppler Light Detection And Ranging (LIDAR) systems at the Hong Kong International Airport and comparison with flight data and a turbulence alerting system[J].Meteorologische Zeitschrift19(6): 549-563(15).DOI: 10.1127/0941-2948/2010/0471 .
null
Chan P W Lee Y F2011.Application of a ground-based, multi-channel microwave radiometer to the alerting of low-level windshear at an airport[J].Meteorologische Zeitschrift20(4): 423-429.DOI: 10.1127/0941-2948/2011/0275 .
null
Chan P W Hon K K2015.Performance of super high resolution numerical weather prediction model in forecasting terrain-disrupted airflow at the Hong Kong International Airport: case studies[J].Meteorological Applications23(1): 101-114.DOI: 10.1002/met.1534 .
null
Eloubaidy A F Plate E J1972.Wind shear-turbulence and reaeration coefficient[J].American Society of Civil Engineers98(1): 153-170.DOI: 10.1061/JYCEAJ.0003193 .
null
Gerz T Forster C Tafferner A2012.Mitigating the impact of adverse weather on aviation[M].Springer, Berlin, Heidelberg.DOI: 10.1007/978-3-642-30183-4_39 .
null
Gultepe I Sharman R Williams P D, et al, 2019.A review of high impact weather for aviation meteorology[J].Pure and Applied Geophysics176(5): 1869-1921.DOI: 10.1007/s00024-019-02168-6 .
null
Harris F I Glover K M Smythe G R1985.Gust front detection and prediction[C].Preprints 14th conference on Severe Local Storms, Bulletin of the American Meteorological Society, Boston, 342-345.
null
Huang J Ng M K P Chan P W2021.Wind shear prediction from light detection and ranging data using machine learning methods[J].Atmosphere12(5): 644.DOI: 10.3390/atmos12050644 .
null
International Civil Aviation Organization, 2005.Manual on low-level wind shear and turbulence, 1st ed[M].Montréal, Canada: International Civil Aviation Organization.222..
null
International Civil Aviation Organization, 2016.ICAO Safety Report, 2016 ed[R/OL].(2016-07-13)[2022-08-20].
null
International Civil Aviation Organization, 2019.ICAO Safety Report, 2019ed[R/OL].(2019-10-08)[2022-08-20].
null
Ito J Niino H Yoshino K2020.Large Eddy simulation on horizontal convective rolls that caused an aircraft accident during its landing at Narita Airport[J].Geophysical Research Letters47(6), e2020GL086999.DOI: 10.1029/2020GL086999 .
null
Kessler, Edwin, 1985.Wind shear and aviation safety[J].Nature315(6016): 179-180.DOI: 10.1038/315179a0 .
null
Li L Q Shao A M Zhang K J, et al, 2020a.Low-level wind shear characteristics and lidar-based alerting at Lanzhou Zhongchuan International Airport, China[J].Journal of Meteorological Research34(3): 633-645.DOI: 10.1007/s13351-020-9134-6 .
null
Li L Q Xie N J Fu L Y, et al, 2020b.Impact of Lidar data assimilation on low-level wind shear simulation at Lanzhou Zhongchuan International Airport, China: a case study[J].Atmosphere11(12): 1342.DOI: 10.3390/atmos11121342 .
null
Lin C Y Zhang K J Chen X T, et al, 2021.Overview of low-level wind shear characteristics over Chinese mainland[J].Atmosphere12(5): 628.DOI: 10.3390/atmos12050628 .
null
Nechaj P Gaál L Bartok J, et al, 2019.Monitoring of low-level wind shear by ground-based 3D lidar for increased flight safety, protection of human lives and health[J].International Journal of Environmental Research and Public Health16(22): 4584.DOI: 10.3390/ijerph16224584 .
null
Oude Nijhuis A C P Thobois L P Barbaresco F, et al, 2018.Wind hazard and turbulence monitoring at airports with Lidar, Radar, and Mode-S downlinks: The UFO Project[J].Bulletin of the American Meteorological Society99(11): 2275-2293.DOI: 10.1175/bams-d-15-00295.1 .
null
Shun C M Lau S Y2002.Implementation of a Doppler light detection and ranging (LIDAR) system for the Hong Kong International Airport[C].10th conference on Aviation, Range, and Aerospace Meteorology, American Meteorological Society, Portland, USA, 8.3.
null
Shun C M Chan P W2008.Applications of an infrared Doppler lidar in detection of wind shear[J].Journal of Atmospheric and Oceanic Technology25(5): 637-655.DOI: 10.1175/2007JTECHA1057.1 .
null
Stoll S A2012.Microburst detection by the low-level wind shear alert system[J].Weather46(11): 334-347.DOI: 10.1002/j.1477-8696.1991.tb07074.x .
null
Thobois L Cariou J P Gultepe I2019.Review of Lidar-based applications for aviation weather[J].Pure and Applied Geophysics, 176(4/5).DOI: 10.1007/s00024-018-2058-8 .
null
Wildmann N Bodini N Lundquist J K, et al, 2019.Estimation of turbulence dissipation rate from Doppler wind lidars and in situ instrumentation for the Perdig?o 2017 campaign[J].Atmospheric Measurement Techniques12(12): 6401-6423.DOI: 10.5194/amt-12-6401-2019 .
null
Wilson J W Roberts R D Kessinger C, et al, 1984.Microburst wind structure and evaluation of Doppler Radar for airport wind shear detection[J].Journal of Climate & Applied Meteorology23(6): 898-915.DOI: 10.1175/1520-0450(1984)023<0898: MWSAEO>2.0.CO; 2 .
null
范琪, 郑佳锋, 周鼎富, 等, 2020.基于激光测风雷达的机场低空风切变识别算法[J].红外与毫米波学报13(4): 462-472.DOI: 10.11972/j.issn.1001-9012.2020.04.011 .
null
蒋立辉, 闫妍, 熊兴隆, 等, 2016.基于斜坡检测的多普勒激光雷达低空风切变预警算法[J].红外与激光工程45(1): 27-33.DOI: 10.3788/IRLA201645.0106001 .
null
蒋立辉, 刘晓宇, 李贞, 等, 2018.兰州中川机场周围地形和建筑物对风场的影响研究[J].计算机与数字工程46(3): 561-565, 626.DOI: 10.3969/j.issn.1672-9722.2018.03.030 .
null
李典南, 许东蓓, 2021.双流机场雷暴天气特征及天气形势分类研究[J].高原气象40(5): 1164-1176.DOI: 10.7522/j.issn. 1000-0534.2020.00110 .
null
刘新伟, 黄武斌, 蒋盈沙, 等, 2021.基于 LightGBM 算法的强对流天气分类识别研究[J].高原气象40(4): 909-918.DOI: 10. 7522/j.issn.1000-0534.2020.00075 .
null
胡明宝, 谈曙青, 汤达章, 等, 2000.单部多卜勒天气雷达探测低空风切变方法[J].南京气象学院学报23(1): 113-118.DOI: 10.13878/j.cnki.dqkxxb.2000.01.018 .
null
梁海河, 张沛源, 葛润生, 2002.多普勒天气雷达风场退模糊方法的研究[J].应用气象学报13(5): 591-599.DOI: 10.3969/j.issn.1001-7313.2002.05.008 .
null
刘晓英, 吴松华, 张洪玮, 等, 2020.基于相干多普勒测风激光雷达的不同成因类型的低空风切变观测[J].红外与毫米波学报39(4): 491-504.DOI: 10.11972/j.issn.1001-9014.2020.04.014 .
null
王楠, 刘黎平, 徐宝祥, 等, 2007.利用多普勒雷达资料识别低空风切变和辐合线方法研究[J].应用气象学报18(3): 314-320.DOI: 10.11898/1001-7313.20070307 .
null
王珊珊, 2007.多普勒天气雷达合成切变模块设计[J].科技信息0(18): 82-83.
null
闫文辉, 黄兴友, 李盈盈, 等, 2019.基于多普勒天气雷达的低空多普勒速度的切变识别算法研究[J].热带气象学报35(2): 253-261.DOI: 10.16032/j.issn.1004-4965.2019.022 .
null
张洪玮, 王琪超, 吴松华, 2018a.基于相干多普勒激光雷达的北京机场春季低空风切变观测研究[J].大气与环境光学学报13(1): 34-41.DOI: 10.3969/j.issn.1673-6141.2018.01.004 .
null
张洪玮, 吴松华, 尹嘉萍, 等, 2018b.基于短距相干测风激光雷达的机场低空风切变观测[J].红外与毫米波学报37(4): 468-476.DOI: 10.11972/j.issn.1001-9014.2018.04.015 .
null
张蔚然, 吴翀, 刘黎平, 等, 2021.双偏振相控阵雷达与业务雷达的定量对比及观测精度研究[J].高原气象40(2): 424-435.DOI: 10.7522/j.issn.1000-0534.2020.00056 .
文章导航

/