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

Abstract

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.