| 降水时风廓线雷达风场反演效果评估 |
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| 引用本文： | 林晓萌, 尉英华, 陈宏, 等. 降水时风廓线雷达风场反演效果评估. 应用气象学报, 2020, 31(3): 361-372. DOI: 10.11898/1001-7313.20200310. |
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| 作者姓名： | 林晓萌 尉英华 陈宏 王艳春 |
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| 作者单位： | 天津市气象台, 天津 300074 |
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| 摘 要： | 风廓线雷达（wind profile radar，WPR）因具有高时空分辨率特点，成为当前短时临近预报的重要参考工具。降水时WPR同时接收大气湍流回波和降水粒子散射回波，现有技术不能有效分离叠加在一起的湍流信号和降水信号，导致降水期间风廓线雷达反演的风场数据严重缺失或失真。根据风廓线雷达探测技术原理及降水天气的功率谱特点，提出了降水天气时风廓线雷达湍流信号提取方法（WPR-HW），并选取2015—2018年天津10次降水过程对WPR-HW方法进行模式检验及个例效果评估。结果表明：WPR-HW方法对改善降水期间风廓线雷达风场数据缺失问题效果明显，在选取的10次降水过程中，目前通用的风廓线雷达风场反演方法（WIND）风场数据平均缺失率为25.4%，WPR-HW方法未出现风场数据缺失现象；WPR-HW方法较WIND方法反演风场数据可信度有显著提高，反演数据与再分析数据的风速均方根误差由WIND方法的2.3 m·s-1降至WPR-HW方法的1.6 m·s-1，风向均方根误差由WIND方法的45°降至WPR-HW方法的22°，从而验证WPR-HW方法在降水期间适用。
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| 关 键 词： | 风廓线雷达 功率谱 风场 |
| 收稿时间： | 2019-12-10 |
| 修稿时间： | 2020-02-20 |
The Effect Assessment of Wind Field Inversion Based on WPR in Precipitation |
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| Lin Xiaomeng, Wei Yinghua, Chen Hong, et al. The effect assessment of wind field inversion based on WPR in precipitation. J Appl Meteor Sci, 2020, 31(3): 361-372. DOI: 10.11898/1001-7313.20200310. |
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| Authors: | Lin Xiaomeng Wei Yinghua Chen Hong Wang Yanchun |
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| Affiliation: | Tianjin Meteorological Observatory, Tianjin 300074 |
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| Abstract: | Wind profile radar(WPR), taking atmospheric turbulence of clear air as main detecting object, is the main reference tool currently for short-time forecast because of its high spatial and temporal resolution. In the past few decades, WPR spectral data processing mainly focuses on the wind spectrum estimation. In recent years, with the use of WPR data expansion, there are increasingly high demand for WPR data accuracy, but because of ground clutter and external noise, flying objects, the presence of disturbances such as precipitation and limitations of Fourier Transform method itself, there are often multiple overlapped peaks, which makes it difficult to judge the spectral meaning, resulting in large error detection products. WPR has a large dynamic reception range, so it can receive the echo of scattering of atmosphere turbulence and precipitation particles simultaneously. However, the superimposed spectrum of atmosphere and precipitation cannot be separated effectively. In the meantime, the wind field calculation is based on the hypothesis of local uniform and isotropy, which cannot be met during precipitation with great spatial variability and leads to data of WPR serious deficiency or distortion. It's of great importance to establish an effective spectral extraction programs under different weather conditions to improve the accuracy of spectral estimation for wind field data after the inversion, thereby enhancing the wind profile accuracy of radar detection.A method of WPR-HW is developed for the case of precipitation according to the principle of WPR detection and the feature of spectrum, and then the effectiveness of the method is tested using ECMWF ERA Interim data. 10 precipitation cases in Tianjin are investigated to verify the significance of wind field data processed by WPR-HW in severe convection prediction. Results show that the WPR-HW has significant advantage compared with the recent WIND method (the universal method of wind field inversion from WPR) in integrity and reliability. For the wind field data in 10 precipitation cases, the leakage rate of WIND is 25.4% while that of WPR-HW is 0. The root mean square error in wind speed of WPR-HW is 1.6 m·s-1 while that of WIND is 2.3 m·s-1. The RMSE in wind direction of WPR-HW is 22° while that of WIND is 45°. The wind field processed by WPR-HW is able to make up for the deficiency and distortion of WPR data effectively in precipitation, which thus benefit to improve the timeliness and accuracy in strong convective weather forecasting. |
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| Keywords: | WPR power spectrum wind field |
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