多普勒雷达退速度模糊及风切变的仿真与识别

发布时间：2018-07-09 21:16

本文选题：多普勒雷达 + 退速度模糊　；参考：《南京信息工程大学》2016年硕士论文

【摘要】：风切变是气象界公认的对飞机航行危害最大的灾害性天气之一,尤其是下击暴流,是典型的风切变。减少风切变对飞行的危害是航空气象关注的问题。为了降低下击暴流对飞机航行带来危害,对下击暴流的结构和回波特征有一定了解也是非常重要的。同时,利用多普勒雷达资料识别风切变,也是对风切变预警的一个重要方法。我国的新一代多普勒天气雷达是灾害性天气预警的重要工具,但是雷达资料的基数据中,常出现数据质量问题,例如速度模糊,它是影响速度资料正确应用的主要因素之一,尤其是C波段雷达,波长比S波段的波长短,更容易发生速度模糊现象。因此,在对数据处理前应该退除速度模糊现象。只有确保数据资料正确,才能保证对速度资料的有效应用,降低风切变带来的损失。新一代天气雷达发展的趋势是双偏振多普勒雷达,其偏振量主要用于粒子的相态识别、以及对降水的估计改进等。位于南京信息工程大学的C波段双偏振雷达(简称NUIST-CDP) 2014年开始投入科研和教学使用,结合偏振参量对风切变进行研究,可以有效的识别强对流、暴雨等灾害性天气回波中存在的风切变区域,并由此改进灾害性天气短临预报的方法。本文的研究内容主要针对多普勒径向速度资料的应用而展开,对速度模糊的退除、下击暴流的仿真和风切变的识别进行研究,具体如下：(1)对南京信息工程大学C波段双偏振雷达的速度资料进行退速度模糊处理,通过人机交互的方法,圈出速度模糊并进行退除。将同时刻位于龙王山的S波段雷达(CINRAD-SA)探测到的数据与之对比,验证人机交互退模糊可行性。(2)利用MATLAB软件,仿真下击暴流的三维结构、特别是垂直剖面结构,并结合雷达探测是极坐标扫描的特点,将仿真的风场结构投影到雷达径向上,通过个例分析,总结下击暴流的结构特征。(3)利用最小二乘法识别风切变,通过改变拟合窗口的大小,并结合区域生长法的识别效果,对比识别算法。将最小二乘法分段拟合法应用到退除速度模糊后的NUIST-CDP雷达资料中,结合偏振参量分析NUIST-CDP资料识别风切变以及切变中的降水区。
[Abstract]:Wind shear is recognized as one of the most harmful weather hazards to aircraft navigation, especially the downburst current, which is a typical wind shear. Reducing the harm of wind shear to flight is a problem concerned by aeronautical meteorology. In order to reduce the damage to aircraft navigation caused by downburst flow, it is also very important to have a certain understanding of the structure and echo characteristics of downburst flow. At the same time, using Doppler radar data to identify wind shear is also an important method for wind shear warning. The new generation of Doppler weather radar in China is an important tool for early warning of disastrous weather. However, in the basic data of radar data, data quality problems, such as velocity ambiguity, are often found, which is one of the main factors affecting the correct application of velocity data. Especially for C band radar, the wavelength is shorter than that of S band, so it is easy to produce velocity ambiguity. Therefore, speed ambiguity should be removed before data processing. Only by ensuring that the data are correct, the effective application of velocity data can be ensured and the loss caused by wind shear can be reduced. The development trend of the new generation weather radar is dual polarization Doppler radar, which is mainly used for particle phase identification and precipitation estimation. The C-band dual-polarization radar (NUIST-CDP), located at Nanjing University of Information Engineering, has been used in scientific research and teaching since 2014. Combining polarization parameters to study wind shear, it can effectively identify strong convection. The windshear region existing in the echo of heavy rain and other disastrous weather, and the method of short-term and imminent forecast of disastrous weather is improved. This paper mainly focuses on the application of Doppler radial velocity data. The details are as follows: (1) the velocity data of the C-band dual-polarization radar of Nanjing University of Information Engineering are processed by de-velocity fuzzy processing, and the velocity blur is circumscribed and removed by the method of human-computer interaction. The data detected by S-band radar (CINRAD-SA) in Longwangshan are compared to verify the feasibility of human-computer interaction deblurring. (2) the 3D structure, especially the vertical section structure, of the downburst flow is simulated by using MATLAB software. Combined with the characteristic that radar detection is polar coordinate scanning, the simulated wind field structure is projected onto the radar radial direction, and the structural characteristics of the downburst flow are summarized through an analysis of an example. (3) the wind shear is identified by using the least square method. By changing the size of the fitting window and combining the recognition effect of the region growth method, the recognition algorithm is compared. The least square method is applied to the NUIST-CDP radar data after the de-velocity is blurred, and the polarization parameters are used to identify the wind shear and the water drop region in the shearing process of the NUIST-CDP data.
【学位授予单位】：南京信息工程大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：P412.25;V321.2

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