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Seasonal variations of infrasound detections and their characteristics in the western US

机译:美国西部次声探测的季节性变化及其特征

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Automatic infrasound detection is analyzed with infrasonic data from the western US for the time period of November 2010 to October 2012. Data from nine University of Utah Seismograph Stations (UUSS) infrasonic arrays are supplemented by three additional arrays in Nevada, operated by Southern Methodist University (SMU). In this study, the detection procedure is based on an adaptive F-detector (AFD) that accounts for both correlated and uncorrelated noise by capturing the time-varying background noise conditions. The adaptation of the detector, characterized by time varying linear remapping of the F-distribution (C-value), depends on the background noise level at the arrays including weather conditions with seasonal variations and local site effects. The infrasound detection catalog consists of 580,177 signals, depending on time and space as well as data availability at individual stations. Based on the Ground-to-Space (G2S) specifications, the number of detections is shown to be correlated with seasonal variations in the stratospheric winds, illustrating the time varying nature of infrasound propagation. These seasonal variations of infrasound detections include the number of detections, correlation value, occurrences in time, phase velocity, and azimuth. The majority of events occur during working hours, Monday through Friday, suggesting a human cause. Based on the automatic detection results, we reviewed the waveforms generated from the known repeated sources such as Dugway Testing Ground (DTG) and Utah Test and Training Range (UTTR) in Utah, and New Bomb (NB) in Nevada. In order to validate the automatic infrasound detection catalog, we document the celerities of automatic infrasound arrivals during the summer and winter using the seismic origin times of NB explosions. Infrasound propagation is dependent on the seasonal variation of wind conditions as well as source location and array distribution.
机译:使用美国西部从2010年11月到2012年10月这段时间的次声数据对自动次声检测进行分析。来自犹他大学的9个地震台站(UUSS)的次声阵列的数据由内华达州南部卫理公会大学运营的三个额外阵列进行补充(SMU)。在这项研究中,检测过程基于自适应F检测器(AFD),该F检测器通过捕获时变的背景噪声条件来解决相关噪声和不相关噪声。检测器的适应性以F分布(C值)的时变线性重映射为特征,取决于阵列的背景噪声水平,包括具有季节性变化和局部站点效应的天气条件。次声检测目录包括580,177个信号,具体取决于时间和空间以及各个站点​​的数据可用性。根据地对空(G2S)规范,探测次数显示与平流层风的季节变化相关,说明了次声传播的时变性质。次声检测的这些季节性变化包括检测次数,相关值,时间出现,相速度和方位角。大多数事件发生在周一至周五的工作时间内,表明是人为原因。基于自动检测结果,我们回顾了从已知重复源(例如,犹他州的Dugway测试场(DTG)和犹他州测试与训练场(UTTR)以及内华达州的新炸弹(NB))生成的波形。为了验证自动次声检测目录,我们使用NB爆炸的地震起源时间记录了夏季和冬季自动次声波到达的速度。次声传播取决于风况的季节性变化以及源位置和阵列分布。

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