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宁波非气象雷达回波的人工智能识别及滤波
引用本文:何彩芬,黄旋旋,丁烨毅,朱龙彪.宁波非气象雷达回波的人工智能识别及滤波[J].应用气象学报,2007,18(6):856-864.
作者姓名:何彩芬  黄旋旋  丁烨毅  朱龙彪
作者单位:宁波市气象局 , 宁波 315012
摘    要:统计分析2003—2006年宁波雷达的非气象杂波, 影响杂波主要为地物杂波, 包括普通地物杂波 (NP杂波) 和异常地物杂波 (AP杂波) ; 并分析这些杂波在反射率因子、径向速度、谱宽产品上不连续的离散状分布等特征。基于以上特征及传统杂波识别的经验而设计出一种近似模拟人眼模糊识别的稳定安全的多维线性近似的杂波识别及其过滤算法, 在 190 个个例测试中大都效果较好, 尤其在 150 km 以内, 能够在确保降水数据完整、准确的基础上有效过滤非气象杂波。

关 键 词:人工智能    NP杂波    AP杂波    滤波    多普勒天气雷达
收稿时间:2007-01-23
修稿时间:2007-07-11

The Artificial Intelligence Identification and Filtering Methods for Non-meteorological Radar Echo in Ningbo
He Caifen,Huang Xuanxuan,Ding Yeyi,Zhu Longbiao.The Artificial Intelligence Identification and Filtering Methods for Non-meteorological Radar Echo in Ningbo[J].Quarterly Journal of Applied Meteorology,2007,18(6):856-864.
Authors:He Caifen  Huang Xuanxuan  Ding Yeyi  Zhu Longbiao
Affiliation:Ningbo Meteorological Bureau , Ningbo 315012
Abstract:The products of Doppler weather Surveillance Radar are occasionally contaminated by non-meteorological echo. For example, the accuracy and reliability of the precipitation-estimating products are reduced significantly by the clutter contamination. For the purpose of improving the accuracy of the products, the clutter removalwork should be firstly done before further developing new radar products. Statistical analysis of non-meteorological radar echo in Ningbo from 2003 to 2006 shows that these clutters mainly are normal propagation ground clutters (NPGC) and abnormal propagation ground clutters (APGC) . The radar-derived products are contaminated by the two types mostly. The following characteristics are shown: they are mostly common in low elevations, discrete distribution of reflectivity products, radial velocity values and spectrum widths values in clutter around zero occasionally mixing with high values and significant horizontal and vertical gradient. Based on echo characteristics and the traditional experience on clutter identification, a stationary safe multidimensional linear approximation algorithm simulating manual eyes' fuzzy logic is designed, which takes full account of the relationship between computation efficiency and data quality. The following three rules should be obeyed by clutter removal. The first is conservation, which is to avoid removing precipitation echoes improperly. The second is independency, that is different clutter is identified and filtered respectively. The third is diversity, that is to utilize three moments of R, V, W of more than two elevations (now use 0.5°and 1.5°) as many as possible and other real time data. The flow chart of clutter removal quality control is given and key points are as below: to build echo background to classify the echoes such as clear or light rain, moderate rain, heavy rain, the edge of strong echoes, strong echoes and strong clutters and so on, identification of isolated clutters, clutter filtering based on the horizontal and vertical reflectivity gradient, identification of small region where the reflectivity values have a sharp change. 190 cases have been tested with the techniques under weather conditions including clear sky, showers and deep convections. Results show that it works well, and has good performance to remove the nonmeteorological radar echoes completely and accurately within the range of 150 km. But out of the range, it doesn't operate well while the radial velocity is fussy. Because of the great horizontal and vertical gradient in small scale deep convective systems, for the sake of conservation, not only a very strict threshold is set but also the removal work is given up to protect the real precipitation echo where fussy radial velocity exists. The cases in the article prove that it doesn't cause wrong removal in small-scale deep convections. If satellite data, real time surface and sounding data can be combined together with radar base data, and time continuity of radar data is taken into account as well, the technique may probably be applied up to a valid range of 200 km even further away in the future.
Keywords:artificial intelligence  APGC  NPGC  clutter filtering  Doppler weather radar
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