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Wind Lidar Applicability in Low Visibility Weather in Qingdao
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摘要: 利用2021年4月—2022年12月青岛国家基本气象站多普勒测风激光雷达和L波段探空系统低空风场观测数据, 对比非降水时低能见度天气下测风激光雷达的探测高度和精度。结果表明:测风激光雷达在青岛地区具有良好的适用性, 在能见度大于10000 m的非降水天气, 其平均最大探测高度稳定在约1200 m, 水平风速均方根误差约为1.2 m·s-1, 水平风向均方根误差约为25°。在能见度小于10000 m的低能见度天气下, 测风激光雷达在不同能见度和相对湿度范围内的探测高度和精度受干扰程度存在差异。在能见度为1000~10000 m、相对湿度小于90%的霾天, 此时大气能见度降低主要是气溶胶粒子含量增加所致, 测风激光雷达的探测能力与高能见度天气下相当。当相对湿度高于95%时, 此时大气能见度降低是空气中水汽含量的增加所致, 严重干扰了激光在大气中的传输, 测风激光雷达的探测高度和精度均有所降低, 尤其在能见度小于1000 m的雾天, 需谨慎使用其风速和风向数据。Abstract: Utilizing data of Doppler wind lidar and L-band radiosonde system installed at Qingdao National Basic Meteorological Observing Station from April 2021 to December 2022, their detection capability and accuracy under low visibility weather conditions are compared and evaluated, specifically in terms of detection height, horizontal wind speed and wind direction, using data obtained from L-band radiosonde system as the reference standard. During non-precipitation weather, when visibility exceeds 10000 m, the wind lidar demonstrates a stable average maximum detection height of approximately 1200 m. The root mean square errors of the wind speed and direction fluctuate around 1.2 m·s-1 and 25°, respectively. However, when the visibility drops below 10000 m, the detection height and accuracy of the wind lidar are influenced by the level of interference, particularly in different visibility and relative humidity ranges. In situations where visibility is below 1000 m, the decrease in atmospheric visibility is attributed to increased water vapor content in the air, with relative humidity consistently exceeding 95%. This high humidity significantly interferes with laser transmission in the atmosphere, resulting in an average maximum detection height of less than 400 m. The correlation between horizontal wind speed and direction decreases to 0.91 and 0.94, and the root mean square error increases to 1.4 m·s-1and 42.7°, respectively. When the visibility ranges between 1000 m and 10000 m, the wind lidar's detection capability varies with the water vapor content in the atmosphere. In cases where relative humidity is below 90%, meeting the criteria for hazy days, the decrease in atmospheric visibility is primarily due to increased aerosol particle content. Under these conditions, the average maximum detection height remains stable above 1200 m. The correlation coefficients for horizontal wind speed and direction are as high as 0.97 and 0.98, with root mean square errors of about 1.1 m·s-1 and 22.3°, respectively. These results are comparable to the detection capability demonstrated under high visibility weather conditions. As relative humidity increases, the impact of water vapor attenuation on laser transmission starts to affect the detection height and accuracy of the wind lidar to varying degrees. When the relative humidity exceeds 95%, the average maximum detection height influenced by water vapor decreases to below 400 m. The correlation coefficient of wind speed decreases to 0.94, with a corresponding increase in the root mean square error to 1.5 m·s-1, and the accuracy of wind direction remains relatively stable under these conditions.
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Key words:
- wind lidar;
- low-level wind;
- visibility;
- fog;
- haze
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图 1 0~30000 m(a)和0~2000 m(b)能见度条件下测风激光雷达最大探测高度分布概率(填色)和平均最大探测高度变化曲线(黑色实线)
Fig. 1 Probability of maximum detection height distribution(the shaded) and average maximum detection height(the black line)of wind lidar under visibility conditions of 0-30000 m(a) and 0-2000 m(b)
图 2 不同能见度条件下测风激光雷达水平风速和风向均方根误差变化
Fig. 2 Root mean square errors of horizontal wind speed and wind direction of wind lidar under different visibilities
图 3 低能见度天气下测风激光雷达最大探测高度分布概率(填色)和平均最大探测高度(黑色实线)随相对湿度变化
Fig. 3 Probability of maximum detection height distribution(the shaded) and average maximum detection height(the black line) of wind lidar varing with relative humidity under low-visibility conditions
图 4 低能见度天气下测风激光雷达水平风速和风向均方根误差随相对湿度变化
Fig. 4 Root mean square errors of horizontal wind speed and wind direction of wind lidar varing with relative humidity under low-visibility conditions
图 5 不同情形下水平风速散点及线性拟合分布
Fig. 5 Scatter plots and linear fitting of horizontal wind speed under different conditions
图 6 不同情形下水平风向散点及线性拟合分布
Fig. 6 Scatter plots and linear fitting of horizontal wind direction under different conditions
图 7 不同情形下测风激光雷达水平风速和风向误差的概率密度分布
Fig. 7 Probability density distribution of horizontal wind speed and wind direction error of wind lidar under different conditions
图 8 雾、霾天气下各高度层水平风速比例分布
Fig. 8 Ratio of wind speed at each level under the fog and haze conditions
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[1] 陈雯超, 宋丽莉, 王志春, 等. 不同天气条件下脉冲激光风廓线仪测风性能. 应用气象学报, 2017, 28(3):327-339. doi: 10.11898/1001-7313.20170307Chen W C, Song L L, Wang Z C, et al. The wind measuring performance of WINDCUBE V2 pulse laser wind profiler under different weather conditions. J Appl Meteor Sci, 2017, 28(3): 327-339. doi: 10.11898/1001-7313.20170307 [2] 张容焱, 张秀芝, 杨校生, 等. 台风莫拉克(0908)影响期间近地层风特性. 应用气象学报, 2012, 23(2): 184-194. http://qikan.camscma.cn/article/id/20120207Zhang R Y, Zhang X Z, Yang X S, et al. Wind characteristics study in surface layer of Typhoon Morakot(0908). J Appl Meteor Sci, 2012, 23(2): 184-194. http://qikan.camscma.cn/article/id/20120207 [3] 陈申鹏, 端义宏, 李青青. 基于高塔观测的登陆台风边界层风切变指数拟合. 应用气象学报, 2022, 33(2): 155-166. doi: 10.11898/1001-7313.20220203Chen S P, Duan Y H, Li Q Q. Fitting of wind shear index in the boundary layer of landfalling typhoons based on high tower observation. J Appl Meteor Sci, 2022, 33(2): 155-166. doi: 10.11898/1001-7313.20220203 [4] 林晓萌, 尉英华, 张楠, 等. 基于地基遥感设备构建遥感探空廓线. 应用气象学报, 2022, 33(5): 568-580. doi: 10.11898/1001-7313.20220505Lin X M, Wei Y H, Zhang N, et al. Construction of air-sounding-profile system based on foundation-remote-sensing equipment. J Appl Meteor Sci, 2022, 33(5): 568-580. doi: 10.11898/1001-7313.20220505 [5] 李明华, 范绍佳, 王宝民, 等. 珠江三角洲秋季大气边界层温度和风廓线观测研究, 应用气象学报, 2008, 19(1): 53-60. http://qikan.camscma.cn/article/id/20080110Li M H, Fan S J, Wang B M, et al. Observation study on the temperature and wind profiles over the Pearl River Delta in autumn. J Appl Meteor Sci, 2008, 19(1): 53-60. http://qikan.camscma.cn/article/id/20080110 [6] 范琪. 低空风切变识别分析中激光测风雷达的应用研究. 成都: 成都信息工程大学, 2017.Fan Q. Lidar for Low-Level Wind Shear Identification and It's Application in Aviation Meteorology. Chengdu: Chengdu University of Information Technology, 2017. [7] Wu S H, Liu B Y, Liu J T, et al. Wind turbine wake visualization and characteristics analysis by Doppler lidar. Optics Express, Optical Society of America, 2016, 24(10): A762-A780. [8] 刘芳霞, 唐智亿, 刘嘉锡, 等. 基于激光测风雷达的西安重污染天气过程特征指标. 灾害学, 2021, 36(4): 88-95. doi: 10.3969/j.issn.1000-811X.2021.04.015Liu F X, Tang Z Y, Liu J X, et al. Evolvement characteristics of heavy pollution process in Xi'an based on wind lidar observation. J Catastrophology, 2021, 36(4): 88-95. doi: 10.3969/j.issn.1000-811X.2021.04.015 [9] 代冰冰, 何敏, 杨靖新, 等. 利用激光雷达判别机场晴空风切变事件成因. 气象科技, 2021, 49(4): 589-596.Dai B B, He M, Yang J X, et al. Causal analysis of a clear sky wind shear event at a plateau airport in southwest China using lidar data. Meteor Sci Technol, 2021, 49(4): 589-596. [10] 刘佳鑫, 云龙, 邵士勇, 等. 深圳地区多普勒测风激光雷达的湍流观测. 大气与环境光学学报, 2021, 16(5): 383-391.Liu J X, Yun L, Shao S Y, et al. Observation of turbulence using Doppler wind lidar in Shenzhen. J Atmos Environ Opt, 2021, 16(5): 383-391. [11] 夏俊荣, 王普才, 闵敏. 新型多普勒测风激光雷达Windcube的风参数观测与验证. 气候与环境研究, 2011, 16(6): 733-741.Xia J R, Wang P C, Min M. Observation and validation of wind parameters measured by Doppler wind lidar Windcube. Clim Environ Res, 2011, 16(6): 733-741. [12] Hu Q, Rodrigo P J, Pedersen C. Remote wind sensing with a CW diode laser lidar beyond the coherence regime. Opt Lett, 2014, 39(16): 4875-4878. doi: 10.1364/OL.39.004875 [13] Choukulkar A, Brewer W A, Sandberg S P, et al. Evaluation of single and multiple Doppler lidar techniques to measure complex flow during the XPIA field campaign. Atmos Meas Tech, 2017, 10(1): 247-264. doi: 10.5194/amt-10-247-2017 [14] 李林, 张治国, 杜传耀, 等. 多普勒测风激光雷达与L波段探空对比分析. 大气与环境光学学报, 2022, 17(5): 494-505.Li L, Zhang Z G, Du C Y, et al. Inter-comparison of wind measurements between Doppler wind lidar and L-band radiosonde. J Atmos Environ Opt, 2022, 17(5): 494-505. [15] 范琪, 朱克云, 郑佳锋, 等. 不同天气类型下全光纤相干激光测风雷达探测性能分析. 中国激光, 2017, 44(2): 326-335.Fan Q, Zhu K Y, Zheng J F, et al. Detection performance analysis of all-fiber coherent wind lidar under different weather types. Chinese J Lasers, 2017, 44(2): 326-335. [16] 陈泉, 史文浩, 汤杰, 等. 降雨强度对激光雷达测风精度的影响研究. 气象科技, 2022, 50(3): 324-333.Chen Q, Shi W H, Tang J, et al. Research on influence of rainfall intensity on accuracy of wind observation based on Doppler lidar. Meteor Sci Technol, 2022, 50(3): 324-333. [17] 张志坚, 张静, 伍光胜, 等. 超大城市综合气象观测试验之测风激光雷达数据评估. 热带气象学报, 2022, 38(2): 253-264.Zhang Z J, Zhang J, Wu G S, et al. Evaluation of wind lidar data inmegacities experiment on integrated meteorological observation. J Trop Meteor, 2022, 38(2): 253-264. [18] 史文浩, 汤杰, 陈勇航. 等. 多普勒激光雷达探测台风"利奇马"边界层风场精度分析. 热带气象学报, 2020, 36(5): 577-589.Shi W H, Tang J, Chen Y H, et al. Study on the accuracy of Doppler wind lidar in measuring the boundary layer wind field of Typhoon Lekima. J Trop Meteor, 2020, 36(5): 577-589. [19] 赵文凯, 赵世军, 单雨龙, 等. 激光测风雷达风场探测性能评估. 中国测试, 2022, 48(1): 147-153.Zhao W K, Zhao S J, Shan Y L, et al. Evaluation of wind detection performance based on wind lidar. China Meas Test, 2022, 48(1): 147-153. [20] 刘冬韡, 穆海振, 贺千山, 等. 一种基于实景图像的低能见度识别算法. 应用气象学报, 2022, 33(4): 501-512. doi: 10.11898/1001-7313.20220410Liu D W, Mu H Z, He Q S, et al. A low visibility recognition algorithm based on surveillance video. J Appl Meteor Sci, 2022, 33(4): 501-512. doi: 10.11898/1001-7313.20220410 [21] 王羽飞, 齐彦斌, 李倩, 等. 一次长白山夏季雾的宏微观特征. 应用气象学报, 2022, 33(4): 442-453. doi: 10.11898/1001-7313.20220405Wang Y F, Qi Y B, Li Q, et al. Macro and micro characteristics of a fog process in Changbai Mountain in summer. J Appl Meteor Sci, 2022, 33(4): 442-453. doi: 10.11898/1001-7313.20220405 [22] 潘玮, 左志燕, 肖栋, 等. 近50年中国霾年代际特征及气象成因. 应用气象学报, 2017, 28(3): 257-269. doi: 10.11898/1001-7313.20170301Pan W, Zuo Z Y, Xiao D, et al. Interdecadal variation of haze days over China with atmospheric causes in recent 50 years. J Appl Meteor Sci, 2017, 28(3): 257-269. doi: 10.11898/1001-7313.20170301 [23] 陆雪, 高山红, 饶莉娟, 等. 春季黄海海雾WRF参数化方案敏感性研究. 应用气象学报, 2014, 25(3): 312-320. http://qikan.camscma.cn/article/id/20140307Lu X, Gao S H, Rao L J, et al. Sensitivity study of WRF parameterization schemes for the spring sea fog in the Yellow Sea. J Appl Meteor Sci, 2014, 25(3): 312-320. http://qikan.camscma.cn/article/id/20140307 [24] 周雪松, 郭启云, 夏元彩, 等. 基于往返式平漂探空的FY-3D卫星反演温度检验. 应用气象学报, 2023, 34(1): 52-64. doi: 10.11898/1001-7313.20230105Zhou X S, Guo Q Y, Xia Y C, et al. Inspection of FY-3D satellite temperature data based on horizontal drift round-trip sounding data. J Appl Meteor Sci, 2023, 34(1): 52-64. doi: 10.11898/1001-7313.20230105 [25] 罗雄光, 梁国锋, 杨超. L波段雷达系统不同测风方法计算结果分析. 气象科技, 2015, 43(6): 1025-1029.Luo X G, Liang G F, Yang C. Result analysis of L-band radar wind mesurement system in different methods. Meteor Sci Technol, 2015, 43(6): 1025-1029. [26] 雷勇, 郭启云, 钱媛, 等. L波段雷达探空高度评估及其质量标识. 应用气象学报, 2018, 29(6): 710-723. doi: 10.11898/1001-7313.20180607Lei Y, Guo Q Y, Qian Y, et al. Evaluation and quality mark of radiosonde geopotential height of L-band radar. J Appl Meteor Sci, 2018, 29(6): 710-723. doi: 10.11898/1001-7313.20180607 [27] 李林蔚, 陈亚军, 弓宇恒. 激光测风雷达反演风场产品在冬运会的适用性分析. 现代电子技术, 2022, 45(13): 93-98.Li L W, Chen Y J, Gong Y H. Applicability of wind field products retrieved from wind lidar in the Winter Games. Mod Electron Technol, 2022, 45(13): 93-98. [28] 王栋成, 邱粲, 董旭光, 等. 济南边界层风廓线雷达与L波段雷达大风探空测风对比. 气象, 2019, 45(8): 1169-1180.Wang D C, Qiu C, Dong X G, et al. Comparing strong wind data observed by boundary layer wind profiling radar and L-band radar in Jinan. Meteor Mon, 2019, 45(8): 1169-1180. [29] 吴兑. 霾与雾的区别和灰霾天气预警建议. 广东气象, 2004, 26(4): 1-4.Wu D. A discuss on the difference between haze and fog and the warning of brownish haze weather. Guangdong Meteor, 2004, 26(4): 1-4. [30] 黄健, 吴兑, 黄敏辉, 等. 1954-2004年珠江三角洲大气能见度变化趋势. 应用气象学报, 2008, 19(1): 61-70. http://qikan.camscma.cn/article/id/20080111Huang J, Wu D, Huang M H, et al. Visibility variations in the Pearl River Delta of China during the period of 1954-2004. J Appl Meteor Sci, 2008, 19(1): 61-70. http://qikan.camscma.cn/article/id/20080111 [31] 吕文丽, 时晓曚, 张凯. 青岛地区一次雾-霾过程能见度特征及影响因素分析. 气象与环境学报, 2023, 39(3): 47-55.Lü W L, Shi X M, Zhang K. Visibility characteristics and influencing factors of a fog-haze process in Qingdao. J Meteor Environ, 2023, 39(3): 47-55. [32] 王亚民, 高国强. 雾天环境下激光传输的衰减特性研究. 红外, 2013, 34(12): 14-19.Wang Y M, Gao G Q. Study of attenuation characteristics of laser propagation in fog. Infrared, 2013, 34(12): 14-19. [33] 韩雪, 周晨. 大气探测激光雷达的分类和特征. 南京大学学报(自然科学), 2023, 59(5): 900-913.Han X, Zhou C. Classification and features of atmospheric lidars: A review. J Nanjing Univ(Nat Sci), 2023, 59(5): 900-913. [34] 吴兑. 再论都市霾与雾的区别. 气象, 2006, 32(4): 9-15.Wu D. More discussions on the differences between haze and fog in city. Meteor Mon, 2006, 32(4): 9-15. -
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