| 长沙机场阵列天气雷达风场验证 |
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| 引用本文： | 李渝, 马舒庆, 杨玲, 等. 长沙机场阵列天气雷达风场验证. 应用气象学报, 2020, 31(6): 681-693. DOI: 10.11898/1001-7313.20200604. |
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| 作者姓名： | 李渝 马舒庆 杨玲 甄小琼 乔丹 |
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| 作者单位： | 1.成都信息工程大学电子工程学院, 成都 610225;2.中国气象局大气探测重点开放实验室, 成都 610225;3.中国气象局气象探测中心, 北京 100081;4.中国科学院大气物理研究所, 北京 100029;5.雷象科技(北京)有限公司, 北京 100089 |
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| 摘 要： | 利用2019年4—9月高时空分辨率的长沙机场阵列天气雷达资料开展三维变分（three-dimensional variational data assimilation，3DVAR）风场反演研究。为验证该算法的反演效果，选取外场试验中10次降水过程，在阵列天气雷达的三维精细探测区内，采用阵列天气雷达合成风场和1部L波段边界层风廓线雷达产品作为参考值对阵列反演风场进行验证评估。结果表明：在稳定性降水条件下，阵列反演风场与阵列合成风场、风廓线雷达产品的结果较为一致；在对流性降水条件下，由于不均匀性会造成风廓线测风精度下降，风廓线雷达产品与阵列反演风场和阵列合成风场差异较大。阵列反演风场与阵列合成风场在稳定性、对流性降水条件下水平风速相对偏差分别低于19%，29%，水平风向差分别低于14.92°，26.35°，稳定性降水条件下阵列反演风场更优，误差在可接受范围内。两种算法得到的风场结构符合各类天气系统的基本特征，水平风场空间分布和风速、风向非常接近。
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| 关 键 词： | 阵列天气雷达 3DVAR 反演风场 合成风场 验证评估 |
| 收稿时间： | 2020-06-15 |
| 修稿时间： | 2020-08-31 |
Wind Field Verification for Array Weather Radar at Changsha Airport |
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| Li Yu, Ma Shuqing, Yang Ling, et al. Wind field verification for array weather radar at Changsha Airport. J Appl Meteor Sci, 2020, 31(6): 681-693. DOI: 10.11898/1001-7313.20200604. |
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| Authors: | Li Yu Ma Shuqing Yang Ling Zhen Xiaoqiong Qiao Dan |
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| Affiliation: | 1. College of Electronic Engineering, Chengdu University of Information Technology, Chengdu 610225;2. CMA Key Laboratory of Atmospheric Sounding, Chengdu 610225;3. Meteorological Observation Center of CMA, Beijing 100081;4. Institute of Atmospheric Physics, China Academy of Sciences, Beijing 100029;5. Rayshon Technology Co. Ltd., Beijing 100089 |
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| Abstract: | Synthesizing or retrieving the radial velocity of weather radar can obtain a three-dimensional wind field, which is an important research direction in radar meteorology. A fine three-dimensional wind field helps to study the structure and motion characteristics of small-scale and meso-scale weather systems. Array weather radar (AWR) consists of three-phased array transmit-receive subarrays (referred as transceiver subarrays), which is used for synchronous detection. AWR data are of high temporal and spatial resolution, thus ensuring the correctness of wind field synthesis and retrieval.According to domestic and aboard research, three-dimensional variational data assimilation (3DVAR) wind field retrieval algorithm is quite mature. Using AWR data of 10 rainfall cases at Changsha airport from April to September in 2019, the wind field is retrieved and evaluated. In the three-dimensional fine detection area of the AWR, detection data of a L-band boundary layer wind profile radar and the AWR synthetic wind field are used as reference value to evaluate the retrieved wind field.Results show that the retrieved wind field, the synthetic wind field, and wind profile radar product are more consistent and reasonable in stable precipitation process. In addition, the result error is larger in convective precipitation. The unevenness of the environmental wind field in convective precipitation can reduce the accuracy of wind measurement, and therefore it is not enough to explain the rationality of the AWR retrieved wind field. The wind profile radar is quite different from the AWR retrieved and the synthetic wind field. For different precipitation types, the wind field structure retrieved by AWR and the wind field obtained by AWR synthetic wind field are consistent with the basic characteristics of various weather systems. The spatial distribution and size direction of the horizontal wind field of two algorithms are very close. Error results show that the relative deviation of horizontal wind speed in the stable and convective precipitation is less than 19% and 29%, and the difference of horizontal wind direction is lower than 14.92° and 26.35°, respectively. The error is within the acceptable range. Compared with the AWR synthetic wind field, the retrieved wind field result during stable precipitation process is better than that during convective precipitation process. |
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| Keywords: | array weather radar (AWR) 3DVAR retrieved wind field synthetic wind field verification and evaluation |
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