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本文中采用的激光雷达是由西南技术物理研究所研制的一部全光纤、相干、多普勒脉冲体制雷达。该雷达具有体积小、重量轻、移植性好等特点。雷达通过发射激光脉冲,以大气中直径为100nm~1000nm大小的气溶胶粒子作为探测目标,根据大气中气溶胶颗粒随风运动对激光信号产生的多普勒偏移来探测大气风场信息[11]。雷达发射激光波长为1.55μm,整机平均电功率为200W,探测距离超过3km,空间和时间分辨率分别为30m和2s。探测模式包括不同仰角全方位扫描的平面位置指示(plane position indicator, PPI)模式、固定方位上下俯仰扫描的量程高度指示(range height indicator, RHI)模式、仰角90°的风廓线模式和一定方位范围内扫描的下滑道模式。雷达探测资料包括大气风场的水平风速和风向、垂直风向和风速以及信噪比等。雷达主要性能参量如表 1所示。
Table 1. Main technical parameters of wind lidar
items technical specifications average power ≤200W wavelength 1.55μm elevation angle range 1°~180° azimuth range 0°~360° maximum detection range ≥3km minimum detection range ≤0.045km range resolution ≤30m time resolution ≤2s elevation resolution ≤0.1° velocity resolution ≤0.5m/s -
温度平流是指冷暖空气水平运动引起的某些地区温度降低或者升高的现象,是大规模天气变化的重要原因[12-13]。根据热成风定理,当某一层中风向随高度顺转有暖平流,风向随高度逆转有冷平流。本文中通过激光雷达风廓线模式下探测的水平风速和风向,考虑标准大气的特性以及大气压和温度关系,反演得到了温度平流,公式如下:
$ - \bar v\Delta T \approx \frac{{ - \bar pf{v_1}{v_2}{\rm{sin}}({\theta _1} - {\theta _2})}}{{R\Delta p}} $
(1) 式中, p=(p1+p2)/2,Δp=p1-p2,p1和p2为不同时刻测到的大气压,v1和v2为不同时刻测到的风速,v为平均风速, ΔT为温度变化量,θ1和θ2为风向,R=8.314为气体常数,f为科氏常数。图 5为急流发生发展期间对应的温度平流随时间的高度变化图。可见,在第一阶段,19:00~23:00之间,1.3km以上温度平流非常弱,较强的冷暖平流出现在该高度以下,与低空急流的位置相一致; 0.6km以下为冷平流,0.6km~1.3km为暖平流,强度在0K/s~1.5×10-4K/s,下冷上暖的结构表明此时刻大气层结稳定。入夜后,机场地面降温比大气快,2017-11-30T23:00~2017-12-01T01:30时,低层均为暖平流,且下部弱,上部略强,此时低空急流高度升高,强度减弱。第二阶段,随着冷空气的入侵,低层平流逐渐减小,温度平流高度随急流高度升高而升高。
湍流是指流体运动杂乱无章、不同层次的流体质点发生激烈的混合现象。流体质点的运动轨迹杂乱无章,其对应的物理量也随空间激烈变化。飞机遭遇湍流时会产生颠簸,飞机的飞行高度和角度都会发生变化,这时飞机通常会脱离飞行员的控制。湍流耗散率是指在分子粘性作用下由湍流动能转化为分子热运动的速率,湍流速度在空间上随机涨落,从而形成显著的速度梯度,在分子粘性力作用下通过内摩擦不断地将湍流动能转化为分子动能[14-19]。湍流耗散率值越大,代表湍流强度越大。
本文中利用激光雷达测量的谱宽值以及风速来计算湍流耗散率ε,公式如下[20-21]:
$ \varepsilon = 2{\rm{ \mathit{ π} }}{\left( {\frac{2}{{3a}}} \right)^{3/2}}{\sigma _{\bar v}}^3{({L^{2/3}} - {L_1}^{2/3})^{ - 3/2}} $
(2) 式中, a=0.55, 为Kolmogorov常数,σv为激光雷达平均速度的标准差,L为抽样时间内不同时间不同高度平均风速和抽样时间的乘积,L1为激光雷达每个波束测得平均风速与脉冲重复时间的乘积。图 6为湍流耗散率随时间高度变化图。当天湍流耗散率量级在10-5m2·s-3~10-3.8m2·s-3之间。在第一阶段,由于低空急流风向不变,风速变化小,因此在低空急流高度上湍流耗散率量级在10-5m2·s-3~10-4.7m2·s-3之间,而急流核的湍流耗散率最弱; 而低空急流上方风向随高度顺转,风速变化较大,导致湍流耗散率达到10-3.8m2·s-3,湍流增强,这个现象与CONANGLA等人[9]得出的低空急流高度湍流最小,低空急流上方存在持续较大湍流结论一致。2017-11-30T23:00~2017-12-01T01:30,随着低空急流的减弱,风速变化增大,湍流迅速增强。在第二阶段,在01:00, 低空急流消失,近地层由于随着冷空气主体侵入,风速小,风向变化大; 在02:00, 近地层和1.9km出现了湍流耗散率最大值,冷空气慢慢过境,湍流强度由强变弱。
基于激光测风雷达的低空急流结构特征研究
Structural characteristics of low-level jet based on wind lidar
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摘要: 低空急流对航空安全保障以及灾害性天气预警预报等具有重要意义。为了研究低空急流的结构特征,基于激光测风雷达收集的数据,对西宁机场2017-11-30~2017-12-01的气象资料进行了分析。结果表明, 低空急流风速随高度先增大后减小,强度和厚度随时间减弱,急流轴高度随时间升高,在急流中心出现了强的冷暖平流,并随急流减弱而减弱,急流顶风向随高度顺转,湍流较强,01:30时急流结构受到破坏,湍流强度达到最大; 21:00以后低空急流中出现湍流团,风速波动较明显,湍流团尺度先增大后减小。这一结果说明高激光测风雷达对低空急流的结构特征以及低空急流内部强度和脉动有很好的探测效果。Abstract: Low-level jet is of great significance to aviation security and severe weather warning and forecast. In ordar to study the structual features of low-level jet, the wind lidar data from xining airport from 2017-11-30 to 2017-12-01 were analyzed in detail. Results show that the low-level jet velocity decreased after the first increased with height, the strength and thickness decreased with time, and the jet axis height increased with time. There appeared a cold advection in the center of the jet, and its intensity drops with the jetdecreases. The rushing wind turn along with height at the top of the jet, and the turbulence is strong. The jet structure was damaged at 01:30, and the turbulent intensity reached the maximum. After 21:00, the turbulence cluster appeared in the low-level jet, and the wind speed fluctuation was obvious. The turbulence cluster scale first increased and then decreased. The results showed that the wind lidar has a very good detection effect on the structural characteristics of low-level jet as well as the internal intensity and pulsation of low-level jet.
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Key words:
- laser technique /
- low-level jet /
- turbulent dissipation rate /
- temperature advection
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Table 1. Main technical parameters of wind lidar
items technical specifications average power ≤200W wavelength 1.55μm elevation angle range 1°~180° azimuth range 0°~360° maximum detection range ≥3km minimum detection range ≤0.045km range resolution ≤30m time resolution ≤2s elevation resolution ≤0.1° velocity resolution ≤0.5m/s -
[1] ZHU Q G. Principes and methods of weather[M].4th ed. Beijing:Metrorological Press, 2000:10(in Chinese). [2] ZHOU X Y, LIAO F, SUN G F. Study on the relationship between mesoscale wind field changes and rainstorm using windprofiler data[J].Plateau Meteorology, 2015, 34(2):526-533(in Chinese). [3] ZHOU J, ZHENG J J, MIAO Ch Sh, et al. The characteristics and numerical simulation of diurnal variations of low-level jet and meiyu front heavy rainfall[J].Journal of Tropical Meteorology, 2017, 3(5):750-761(in Chinese). [4] YANG Sh N, LU Q X, YU Ch. Analysis on mesoscale convective system and impact of low-level wind in a meiyu heavy rainfall event [J].Meteorological Monthly, 2017, 43(1):21-33(in Chinese). [5] LIU H Y. Characteristics of low level jet over the taklimakan desert and its impact on dust[D].Lanzhou: Lanzhou University, 2015: 37-54(in Chinese). [6] LIAO X N, SUN Zh B, HE N, et al. A case study on the rapid cleaned away of PM2.5 pollution in beijing related with bl jet and its mechanism[J].Environmental Science, 2016, 37(1):51-59(in Chinese). [7] BANTA R M, NEWSOM R K, LUNDQUIST J K, et al. Nocturnal low-level jet characteristics over kansas during cases-99[J].Boundary-Layer Meteorology, 2002, 105(2):221-252. doi: 10.1023/A:1019992330866 [8] CONANGLA L, CUXART J. On the turbulence in the upper part of the low-level jet:An experimental and numerical study[J].Boundary-Layer Meteorology, 2006, 118(2):379-400. doi: 10.1007/s10546-005-0608-y [9] LI J, SHU W J. Observation and analysis of nocturnal low-level jet characteristics over beijing in summer[J].Chinese Journal of Geophysics, 2008, 51(2):360-368 (in Chinese). [10] WANG Sh J. Effect of high temperature weather on flight at caojiapu airport in xining[J].Air Traffic Management, 2010(6):25-27(in Chinese). [11] LI C, ZHAO P E, PENG T, et al. Technical research of 3-D wind lidar[J].Laser Technology, 2017, 41(5):703-707(in Chinese). [12] ZHAI L. Wind profile data characteristics of a heavy rain process during beijing olympic games[J].Meteorological Monthly, 2008, 34(s1):26-31(in Chinese). [13] YANG B, WEI D. Second development of wind profile data and its application in weather forecasing[J].Meteorological Science, 2010, 38(4):413-417(in Chinese). [14] KALAPUREDDY M C R, KUMAR K K, SIVAKUMAR V, et al. Diurnal and seasonal variability of tke dissipation rate in the abl over a tropical station using uhf wind profiler[J].Journal of Atmospheric and Solar-Terrestrial Physics, 2007, 69(4/5):419-430. [15] XIE H L. Research on flow field structure of boundary layer under typical weather based on lidar data[D].Chengdu: Chengdu University of Information Technology, 2018: 21-27(in Chinese). [16] TU A Q, DONG D B, WENG N Q. Retrieval of clear-air turbulent dissipation rate using spectral width measured by wind profiler[J].High Power Laser and Particle Beams, 2008, 20(10):1608-1613(in Chinese). [17] XIAO F W. Research of turbulent dissipation rate features in shenzhen using LAP-3000 wind profiler dataset[J].Journal of the Meteo-rological Sciences, 2011, 31(s1):1-6(in Chinese). [18] JIANG D H, WANG Ch G, WU D, et al. Analysis and research on the diurnal variation characteristics of the boundary layer in guangzhou area using wind profile radar data[J].Journal of Tropical Meteorological, 2013, 29(1):129-135(in Chinese). [19] WANG X F, WANG Ch G, BU L B, et al. Study on characteristics of turbulent disspation rate in Shenzhen using LAP-3000 wind profiler radar data[J].Meteorological Science, 2011, 31(s1):4-9(in Chin-ese). [20] ZHANG C Y, WENG N Q. Research on the characteristics of clear-day dynamic turbulence in troposphere based on wind profile radar[J].Chinese Journal of Lasers, 2013, 40(12):1213003(in Chin-ese). doi: 10.3788/CJL201340.1213003 [21] ZHANG C Y, JIANG D B, WENG N Q. Analysis of spectral width and turbulence disspation rate of wind profile radar[J].Journal of Atmospheric and Environmental Optics, 2009, 4(6):406-413(in Chinese).