Xing CHEN, Zhen LI, Zi-bo ZHUANG, et al. A small scale wind shear detection algorithm of modified F-factor for wind-profiling lidar[J]. Optics and precision engineering, 2018, 26(4): 927-935.
DOI:
Xing CHEN, Zhen LI, Zi-bo ZHUANG, et al. A small scale wind shear detection algorithm of modified F-factor for wind-profiling lidar[J]. Optics and precision engineering, 2018, 26(4): 927-935. DOI: 10.3788/OPE.20182604.0927.
A small scale wind shear detection algorithm of modified F-factor for wind-profiling lidar
Aiming at the problem that a small but strong clear sky wind shear induced by the complex terrain or geographical environment and other factors cannot be detected by the existing wind shear detection algorithm
a small scale wind shear detection algorithm of lidar's modified F factor was put forward. The vertical wind speed component that could not be directly measured by lidar in traditional F-factor was converted into radial wind speed gradient by theoretical model
thus the key point for solving the F-factor fell on the way to obtaining the radial wind speed gradient. Firstly
the wind speed profile of lidar glide-path scanning was extracted from the clear sky field data. Then
by using the least squares method
radial gradient of the wind speed profile was calculated
and the modified F-factor was solved thereby
and the wind shear was determined according to its empirical threshold. Finally
the actual lidar wind field data provided by the Hong Kong International Airport were used for experimental verification. The experimental results show that when the wind shear in the range of 400m to 800m
the algorithm can detect the small scale wind shear which fail to be detected by the existing ramps algorithm
and enlarge the detection range for 2NM. The method proposed uses the ground lidar data to measure the change of the airborne index and has obvious effect in detecting the small scale wind shear of several hundred meters
which makes sense for reducing the missing report rate of the wind shear and improving the wind shear rate.
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references
张杰.中小尺度天气学[M].北京:气象出版社, 2006:2-4.
ZHANG J. Small and Medium Scale Synoptic[M]. Beijing:China Meteorological Press, 2006:2-4. (in Chinese)
JIANG L H, ZHAO L Y, XIONG X L. The gradient search alerting algorithm of low-level wind shear based on adaptive scale[J]. Science Technology and Engineering, 2015, 15(31):1-6. (in Chinese)
XU Q Y, NING H SH, CHEN W SH, et al.. Applications of meteorological radar for the civil aviation safety[J]. Acta Electronica Sinica, 2010, 38(9):2147-2151. (in Chinese)
ZHANG Y Y, GONG K, HE SH F, et al.. Progress in laser Doppler velocity measurement techniques[J]. Laser & Infrared, 2010, 40(11):1157-1162. (in Chinese)
LI Y ZH, XUE B, ZHAO Y Y. Development of wide field of view technology of synthetic aperture lidar[J]. Opt. Precision Eng., 2016, 24(10):300-308. (in Chinese)
ABARI C F, PEDERSEN A T, MANN J. An all-fiber image-reject homodyne coherent Doppler wind lidar[J]. Optics Express, 2014, 22(21):25880-25894.
JIA X D. Development of 1. 55 μm coherent lidar for wind sensing [D]. Hefei: University of Science and Technology of China, 2015. (in Chinese)
CHAN P W, HON K K. Observation and numerical simulation of terrain-induced Windshear at the Hong Kong international airport in a planetary boundary layer without temperature inversions[J]. Advances in Meteorology, 2016, 2016:1454513.
JIANG L H, YAN Y, XIONG X L, et al.. Doppler lidar alerting algorithm of low-level wind shear based on ramps detection[J]. Infrared and Laser Engineering, 2016, 45(1):0106001. (in Chinese)
PROCTOR F H, HINTON D A, BOWLES R L. A Windshear Hazard Index[M]. Washington D.C:NASA Langley Technical Report Server, 2000.
BYRD G P, PROCTOR F H, BOWLES R L. Evaluation of a technique to quantify microburst Windshear hazard potential to aircraft[C]. Proceedings of the 29 th IEEE Conference on Decision and Control , IEEE , 1990: 689-694.
金长江.美国低空风切变危险性评估的研究概况[J].飞行力学, 1993, 11(1):1-7.
JIN CH J. Research status of Harzard estimation criterion of low-level Windshear in America[J]. Flight Dynamics, 1993, 11(1):1-7. (in Chinese)
CHAN P W, HON K K, SHIN D K. Combined use of headwind ramps and gradients based on LIDAR data in the alerting of low-level Windshear/turbulence[J]. Meteorologische Zeitschrift, 2011, 20(6):661-670.
CHAN P W. Application of LIDAR-based F-factor in Windshear alerting[J]. Meteorologische Zeitschrift, 2012, 21(2):193-204.
LEE Y F, CHAN P W. LIDAR-based F-factor for wind shear alerting:different smoothing algorithms and application to departing flights[J]. Meteorological Applications, 2014, 21(1):86-93.
SHUN C M, CHAN P W. Applications of an infrared Doppler lidar in detection of wind shear[J]. Journal of Atmospheric and Oceanic Technology, 2010, 25(5):637-655.
HU Q, LI Y X, SONG J Z, et al.. Application of Doppler lidar data in wind forecasting[J]. Laser & Infrared, 2012, 42(3):268-273. (in Chinese)
BOWLES R L. Windshear detection and avoidance: airborne systems survey[C]. Proceedings of the 29 th IEEE Conference on Decision and Control , IEEE , 1990: 708-736.
FROST W. Flight in low-level wind shear[R]. NASA-CR-3678. Washington: NASA, 1983.
JIN CH J, ZHANG H, ZHU R B, et al.. A study on low level Windshear risk estimation criterion[J]. Acta Aeronautica et Astronautica Sinica, 1992, 13(10):481-486. (in Chinese)
韩雁飞. 强杂波背景下的低空风切变检测技术研究[D]. 天津: 中国民航大学, 2013.
HAN Y F. Detection of low-altitude wind shear in strong clutter [D]. Tianjin: Civil Aviation University of China, 2013. (in Chinese)
VICROY D D. Microburst vertical wind estimation from horizontal wind measurements[R]. N95-10567. Washington: NASA, 1995: 143-176.