Characteristics of Ground Motion Generated by Wind Interaction With Trees, Structures, and Other Surface Obstacles
Characteristics of Ground Motion Generated by Wind Interaction With Trees, Structures, and Other Surface Obstacles
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DOI：
10.1029/2018jb017151
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发表时间：
2019-08-01
影响因子：
3.9
通讯作者：
Ben-Zion, Yehuda
中科院分区：
文献类型：
--
作者：
Johnson, Christopher W.;Meng, Haoran;Ben-Zion, Yehuda
对圣哈辛托断层上Sage Brush Flats临时部署的连续地震波形的分析揭示了风与地表上方障碍物相互作用产生的地震和震颤信号。在风速超过2 m/s时，现场出现类似震颤的波形，这发生在部署持续时间的70%。对风的响应具有显著的空间变异性，在大型地表物体附近具有最高的地面运动。与风有关的信号显示，地面速度超过M1.0-1.5地震的平均地面运动的6-31%的一天。波形频谱表明与风速和距当地结构的距离相关的振幅调制。类似地震的信号被发现来自当地的结构和植被，并在几十米的长度尺度上进行修改。还观察到源自研究区域以外的瞬态信号，其振幅大于一些微震事件。与风有关的地面运动有助于当地的高频地震噪声。这些信号中的一些可能与地下材料的小故障相关联。在风力增强的情况下，148米深处的钻孔地震仪显示出通常用于地震和震颤检测的1-8 Hz频带中的能量增加。风相关的地震和震颤样信号，由于在时域和频域的相似功能，应占地震检测算法。正确识别与风有关的地面运动有助于理解连续地震波形的组成和表征浅层地壳的力学性质。简明扼要地震记录包含有关大气和人为现象的信息，这些现象可能发生在比构造事件大得多的日常记录中。我们的特征信号与地震和震颤的波形，产生的阵风与表面上的物体相互作用，并调制周围的环境噪声。风的相互作用可能会在地壳浅层产生微观故障，产生高频能量，有助于当地的地震噪音。非构造信号的分类变得越来越重要，因为地震检测算法采用机器学习技术，利用数据来建立检测模型。随着算法的不断改进，正确识别不同类别的信号将提供更好的检测模型。
Analysis of continuous seismic waveforms from a temporary deployment at Sage Brush Flats on the San Jacinto fault reveals earthquake- and tremor-like signals generated by the interaction of wind with obstacles above the surface. Tremor-like waveforms are present at the site during wind velocities above 2 m/s, which occur for 70% of the deployment duration. The response to the wind has significant spatial variability with highest ground motions near large surface objects. The wind-related signals show ground velocities that exceed the average ground motions of M1.0-1.5 earthquakes for 6-31% of the day. Waveform spectra indicate a modulation of amplitude that correlates with wind velocity and distance from local structures. Earthquake-like signals are found to originate from local structures and vegetation, and are modified on length scales of tens of meters. Transient signals originating beyond the study area are also observed with amplitudes greater than some microseismic events. The wind-related ground motions contribute to local high-frequency seismic noise. Some of these signals may be associated with small failures of the subsurface material. During elevated wind conditions a borehole seismometer at a depth of 148 m shows increased energy in the 1-8-Hz band that is commonly used for earthquake and tremor detection. The wind-related earthquake- and tremor-like signals should be accounted for in earthquake detection algorithms due to the similar features in both time and frequency domains. Proper recognition of wind-related ground motions can contribute to understanding the composition of continuous seismic waveforms and characterize mechanical properties of the shallow crust.Plain Language Summary Seismic recordings contain information on atmospheric and anthropogenic phenomena which can occur over much larger portions of the daily records than tectonic events. We characterize signals with earthquake- and tremor-like waveforms that are generated as wind gusts interact with objects on the surface and modulate the ambient environmental noise. The wind interaction may produce microfailures in the shallow crust generating high-frequency energy that contributes to the local seismic noise. The classification of nontectonic signals is becoming increasingly important as earthquake detection algorithms employ machine learning techniques that utilize the data to build a detection model. Properly identifying different classes of signals will provide better detection models as the algorithms continue to improve.