| 基于小波分析的地面大气电场观测数据处理技术研究 |
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| 引用本文： | 陈红兵,徐文,王振会,李艳.基于小波分析的地面大气电场观测数据处理技术研究[J].南京气象学院学报,2012(6):762-767. |
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| 作者姓名： | 陈红兵 徐文 王振会 李艳 |
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| 作者单位： | [1]江苏省气象局,江苏南京210008 [2]江苏省气象信息中心,江苏南京210008 [3]南京信息工程大学气象灾害省部共建教育部重点实验室,江苏南京210044 [4]南京信息工程大学大气物理学院,江苏南京210044 [5]贵州省大气探测技术与保障中心,贵州贵阳550002 |
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| 基金项目： | 科技部公益性行业（气象）科研专项（GYHY200806014） |
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| 摘 要： | 使用南京信息工程大学实验场的AMEO340电场仪一年观测试验资料，将大气电场仪采样序列数据经快速傅里叶变换，得到序列的功率谱，对晴天和伴有闪电天气的地面大气电场数据进行小波函数为sym5的7层分解，某种程度上降低了地面大气电场数据波形的重叠度。通过对伴有闪电天气的地面大气电场数据进行小波7层分解，地面大气电场信号的低频部分不仅突出显示出地面大气电场值的主要变化趋势，而且能清晰地分辨出闪电过程中较强的正负地闪次数，为利用地面大气电场强度值的变化特征进行闪电预警提供了更有效的信息。
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| 关 键 词： | 电场数据 小波分析 时频特性 |
Processing technology of surface atmospheric electric field observations based on wavelet analysis |
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| CHEN Hong-bing,XU Wen,WANG Zhen-hui,LI Yan.Processing technology of surface atmospheric electric field observations based on wavelet analysis[J].Journal of Nanjing Institute of Meteorology,2012(6):762-767. |
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| Authors: | CHEN Hong-bing XU Wen WANG Zhen-hui LI Yan |
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| Institution: | Jiangsu Meteorological Bureau, Nanjing 210008, China ;2. Jiangsu Meteorological Information Center, Nanjing 210008, China; 3. Key Laboratory of Meteorological Disaster of Ministry of Education,NUIST,Nanjing 210044, China; 4. School of Atmospheric Physics,NUIST,Nanjing 210044 ,China; 5. Guizhou Technical Support Center for Atmospheric Sounding, Guiyang 550002, China) |
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| Abstract: | Using one year ground atmospheric electric filed data by the AMEO340 installed in Nanjing University of Information Science and Technology, this paper calculates the ground atmospheric electric field sampling series by the fast Fourier transform in order to get power spectrum of the ground atmos pheric electric field series. The ground atmospheric electric field data of sunny and lightning days are analyzed with sevenlayer decomposition of the sym5 wavelet function, which decreases the overlapping degree of ground atmosphere electric field data waveform to some extent. The ground atmospheric elec tric field signals of lightning days are decomposed by the sevenlayer decomposition. The lowfrequency component of the ground atmospheric electric field signals not only can highlight its main change trend, but also can clearly identify the number of strong positive and negative ground flashes. So it can supply more effective information for the lightning nowcasting by using the characteristics of the ground atmos pheric electric field singnals. |
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| Keywords: | electric field data wavelet analysis time-frequency features |
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