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基于小波变换的地震前后GNSS ZTD异常变化分析
引用本文:王勇,娄泽生,刘严萍,王轩.基于小波变换的地震前后GNSS ZTD异常变化分析[J].全球定位系统,2019,44(3):62-68.
作者姓名:王勇  娄泽生  刘严萍  王轩
作者单位:1.天津城建大学 地质与测绘学院,天津 300384
基金项目:天津市自然科学基金(17JCYBJC21600);河北省自然科学基金(D2015209024)
摘    要:地震前后的水汽变化特征分析可为震前地震预测和灾后次生灾害预警提供参考.该文借助小波变换方法开展地震前后全球卫星导航系统(GNSS)天顶对流层延迟(ZTD)(水汽)的异常变化研究.通过对ZTD结合地震与降水数据来分析地震前后水汽变化特征,利用小波变换的方法分解重构ZTD数据,分析GNSSZTD在地震前后的异常变化.研究发现:地震前后存在水汽突变情况,小波变换后的ZTD能更清楚显示震后水汽变化特征与地震关系及水汽周期变化.

关 键 词:地震  水汽  天顶对流层延迟  降水  小波变换

Abnormal change of GNSS ZTD before and after earthquake based on wavelet transform
WANG Yong,LOU Zesheng,LIU Yanping,WANG Xuan.Abnormal change of GNSS ZTD before and after earthquake based on wavelet transform[J].Gnss World of China,2019,44(3):62-68.
Authors:WANG Yong  LOU Zesheng  LIU Yanping  WANG Xuan
Institution:1.School of Geology and Geomatics, Tianjin Chengjian University, Tianjin 300384, China2.School of Economics and Management, Tianjin Chengjian University, Tianjin 300384, China3.School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454000, China
Abstract:The characteristics analysis of precipitable water vapor (PWV) change before and after earthquakes can provide reference for earthquake prediction and early warning of secondary disasters after earthquakes. In this paper, the abnormal changes of GNSS ZTD (PWV) before and after earthquakes are studied with the method of wavelet transform. By combining ZTD, seismic and precipitation data, the characteristics of water vapor change before and after earthquakes are analyzed. The ZTD data is decomposed and reconstructed by wavelet transform, and the abnormal changes of GNSS ZTD before and after earthquakes is analyzed. It is found that there is a sudden change of water vapor before and after earthquakes, and the ZTD after wavelet transform can clearly show the relationship between the characteristics of water vapor change and earthquakes and the change of water vapor cycle after earthquakes. 
Keywords:earthquake  precipitable water vapor  zenith tropospheric delay  precipitation  wavelet transform
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