IMPACT OF TYPHOON PRECIPITATION INTENSITY ON THE APPLICABILITY OF WIND PROFILER RADAR
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摘要: 以2019年8月在浙江舟山对1909号超强台风“利奇马”的移动观测试验为基础,利用同一地点释放的9次GPS探空气球,对比了风廓线雷达和多普勒激光测风雷达与GPS探空的吻合程度,并利用车载雨滴谱仪对风廓线雷达在不同台风降水强度下的适用性进行了研究。结果表明,在100~300 m高度范围内激光测风雷达观测风速比风廓线雷达更准确。由水平风速对比结果可知,风廓线雷达在3~4 km高度范围内偏差最小(3.59 m/s),相关性最高(0.86),而在1 km高度下偏差最大(6.39 m/s),相关性最低(0.54);在中雨及大雨条件下适用性最差,最大风速偏差约为18 m/s。由水平风向对比结果可知,风廓线雷达与GPS探空总体上吻合较好,相关系数均大于0.85,均方根偏差均小于11 °。另外,降水强度对风廓线雷达的风向观测影响较小,风向偏差随降水强度的变化总体趋于平稳,基本分布在-20 °~20 °之间。Abstract: Based on the field experiment on Super Typhoon Lekima (2019), which was conducted in Zhoushan, Zhejiang Province in August 2019, the wind profiler radar (WPR) and doppler wind lidar (DWL) measurements are compared with those from nine balloon-borne GPS radiosondes launched at the same location. Besides, the impact of typhoon precipitation intensity recorded by the vehicle-mounted raindrop spectrometer on the applicability of WPR is investigated. The results show that the DWL data is more accurate than the WPR data within the height of 100~300 m. As indicated by the comparison of horizontal wind speed measured by the WPR and GPS radiosonde, the best agreement can be achieved at the height of 3~4 km with correlation coefficient of 0.86 and root mean square (RMS) of 3.59 m/s and the worst agreement appears when the height is lower than 1 km with correlation coefficient of 0.54 and RMS of 6.39 m/s. The WPR shows bad applicability in moderate and heavy rainfall with the maximum RMS of wind speed being up to approximately 18 m/s. The comparison of horizontal wind direction shows that the WPR and GPS radiosonde are generally in good agreement with correlation coefficient greater than 0.85 and RMS less than 11 °. The precipitation intensity has little influence on the WPR-measured wind direction, which tends to remain steady with the bias distributed between -20 ° and 20 °.
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Key words:
- wind profiler radar /
- Doppler wind lidar /
- radiosonde /
- Lekima /
- precipitation
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表 1 风廓线雷达、GPS探空仪和激光测风雷达参数设置
参数 风廓线雷达(Airda 3000M) GPS探空仪(Vaisala RS41-SG) 激光测风雷达(Windcube V2) 测量范围/m 50~5 000 0~40 000 40~290 测量高度层数 59 - 12 采样频率 5 min 0.5 Hz 1 Hz 风速精度/(m/s) 0.1 0.1 0.1 m/s 风速偏差/(m/s) ±1 (< 30), ±2 (30~60) ±0.15 - 风速测量范围/(m/s) 0~60 0~160 0~80 风向精度/° 1 1 1 风向偏差/° ±15 ±2 - 工作温度范围/℃ -30~+50 -90~60 -35~+45 工作湿度范围 ~90% ~100% 0~100% -
[1] 张霭琛. 现代气象观测[M]. 北京: 北京大学出版社, 2000: 289-298. [2] 胡明宝. 风廓线雷达探测与应用[M]. 北京: 气象出版社, 2015: 1-194. [3] ISHIHARA M, KATO Y, ABO T, et al. Characteristics and performance of the operational wind profiler network of the Japan Meteorological Agency[J]. J Meteor Soc Japan, 2006, 84(6): 1 085-1 096. [4] 李培荣, 肖天贵, 王超. 基于风廓线雷达对成都重污染天气过程的研究[C]//环境工程2019年全国学术年会, 北京, 2019: 542-550. [5] 李祥龙, 白洁. 空军装备研究所气象所. 风廓线雷达探测风切变条件的应用研究[C]//第27届中国气象学会年会, 北京, 2012. [6] 邓闯, 阮征, 魏鸣, 等. 风廓线雷达测风精度评估[J]. 应用气象学报, 2012, 23(5): 523-533. [7] RALPH F M, NEIMAN P J, VAN DE KAMP D W, et al. Using spectral moment data from NOAA's 404-MHz radar wind profilers to observe precipitation[J]. Bull Amer Meteor Soc, 1995, 76(10): 1 717-1 740. [8] LAMBERT W C, TAYLOR G E. Data quality assessment methods for the eastern range 915 MHz wind profiler network[R]. NASA Contract or Report NASA, CR-1998-207906, 1998. [9] 王欣, 卞林根, 彭浩, 等. 风廓线仪系统探测试验与应用[J]. 应用气象学报, 2005, 16(5): 693-698. [10] 裴丽丝, 邱崇践. 多普勒雷达VAD风廓线资料的质量评估[J]. 热带气象学报, 2013, 29(4): 597-606. [11] 齐佳慧, 郝巨飞, 耿飞. CFL-06型风廓线雷达与L波段探空雷达测风对比分析[J]. 气象与环境科学, 2019, 42(2): 135-143. [12] 廖菲, 邓华, 侯灵. 降水条件下风廓线雷达数据质量分析及处理[J]. 热带气象学报, 2016, 32(5): 588-596. [13] 万蓉, 周志敏, 崔春光, 等. 风廓线雷达资料与探空资料的对比分析[J]. 暴雨灾害, 2011, 30(2): 130-136. [14] 贺文煌, 周登, 马超, 等. 对流层风廓线雷达资料质量分析[J]. 解放军理工大学学报(自然科学版), 2016, 17(6): 552-557. [15] 姜丽黎, 余晖. 基于动力相似方法的台风极端降水概率预报研究[J]. 热带气象学报, 2019, 35(3): 353-364. [16] 赵坤, 王明筠, 朱科锋, 等. 登陆台风边界层风廓线特征的地基雷达观测[J]. 气象学报, 2015, 73 (5): 837-852. [17] 王叶红, 赵玉春, 罗昌荣, 等. 双雷达风场反演拼图在登陆台风"莫兰蒂"(1614)强降水精细预报中的同化应用试验[J]. 气象学报, 2019, 77(4): 617-644. [18] MAY PETER T. Comparison of wind-profiler and radiosonde measurements in the tropics[J]. Jatmosoceanic Technol, 1993, 10(1): 122- 127. [19] YING M, ZHANG W, YU H, et al. An overview of the China Meteorological Administration tropical cyclone database[J]. Journal of Atmospheric & Oceanic Technology, 2014, 31(2): 287-301. [20] 李晨光, 刘淑媛, 陶祖钰. 华南暴雨试验期间香港风廓线雷达资料的评估[J]. 热带气象学报, 2003, 19(3): 269-276. [21] ZHANG J A, ATLAS R, EMMITT G D, et al. Airborne Doppler wind lidar observations of the tropical cyclone boundary layer[J]. Remote Sensing, 2018, 10(6): 825. [22] 中国气象服务协会. T/CMSA 0013-2019. 短时气象服务降雨量等级[S]. 2019. [23] WOLFE D E, FAIRALL C W, INTRIERI J M, et al. Shipboard multisensor wind profiles from NEAQS 2004: radar wind profiler, high resolution Doppler lidar, GPS rawinsonde[C]//13th Symposium onMeteorological Observations and Instrumentation, Joint Poster Session JP2.27, 2005. [24] 王志春, 植石群, 丁凌云, 等. 华南沿海地区车载风廓线雷达资料的分析与应用[J]. 气候与环境研究, 2013, 18(2): 195-202 [25] 董德保, 张统明, 芮斌. 风廓线雷达大气风场观测误差分析[J]. 气象科技, 2014, 42(1): 48-53. [26] 陈玉宝, 高玉春, 刘秉义, 等. 基于切比雪夫方法的多普勒激光雷达高空风场垂直探测精度的评估分析[J]. 热带气象学报, 2014, 30 (2): 327-344.