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| 基于小波技术的地面大气电场数据处理 | |
| 引用本文： | 李艳,王振会,陈红兵,徐文.基于小波技术的地面大气电场数据处理[J].气象科学,2012,32(2):177-181. |
| 作者姓名： | 李艳 王振会 陈红兵 徐文 |
| 作者单位： | 1. 南京信息工程大学气象灾害省部共建教育部重点实验室,南京210044;南京信息工程大学大气物理学院,南京210044 2. 江苏省气象局,南京,210008 3. 江苏省气候中心,南京,210008 |
| 基金项目： | 科技部公益性行业(气象)科研专项(GYHY200806014) |
| 摘 要： | 使用安装在南京信息工程大学实验场的法国电场仪AMEO340于2009年观测试验期间的观测资料,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了小波函数为sym5的7层分解,大大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了地面大气电场值的主要变化趋势,而且能清晰的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。 |
| 关 键 词： | 闪电 小波分析 电场 时频特性 |
| 收稿时间： | 2010/11/27 0:00:00 |
| 修稿时间： | 1/9/2011 12:00:00 AM |
Using wavelet analysis to process the data of ground atmospheric electric field |
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| LI Yan,WANG Zhenhui,CHEN Hongbing and XU Wen.Using wavelet analysis to process the data of ground atmospheric electric field[J].Scientia Meteorologica Sinica,2012,32(2):177-181. | |
| Authors: | LI Yan WANG Zhenhui CHEN Hongbing and XU Wen |
| Institution: | ###############################################################################################################################################################################################################################################################;###############################################################################################################################################################################################################################################################;Jiangsu Meteorological Bureau, Nanjing 210008, China;Jiangsu Climate Center, Nanjing 210008, China |
| Abstract: | Using ground atmospheric field data during 2009 for a year which is recorded by the AMEO340 installed in Nanjing University of Information Science & Technology, we calculated the ground atmospheric electric field sampling squence data by fast Fourier transform in order to get the power spectrum of ground atmospheric electric field sequence. The ground atmospheric electric field data from sunny and lightning days were analyzed with wavelet function for the sym5's seven-layer decomposition in this paper. The overlap between the waveform of ground atmospheric electric field signals was greatly reduced by this method. The lightning data of ground atmospheric electric field signals were decomposed by seven-layer. It was found that the low-frequency component of the ground atmospheric electric field signals during lightning clearly identified the number of strong positive and negative ground flashes. So it can supply more effective information for both its gradual upward trend and the lightning nowcasting by using the characteristics of the ground atmospheric electric field singnals. |
| Keywords: | Lightning Wavelet analysis Field Noise |
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