Detection of Regional Infrasound Signals Using Array Data - Testing, Tuning, and Physical Interpretation
Friday, 18 December 2015
Poster Hall (Moscone South)
In order to understand the impact environmental conditions have on infrasound detection, an automated detector that accounts for both correlated and uncorrelated noise is run on data from a number of infrasonic arrays, all in a regional context. Data from six seismo-acoustic arrays in South Korea (BRDAR, CHNAR, KMPAR, KSGAR, TJIAR, and YPDAR), which are cooperatively operated by Korea Institute of Geoscience and Mineral Resources (KIGAM) and Southern Methodist University (SMU), were used. An adaptive F-detector (AFD) (Arrowsmith et al., 2009) is applied that utilizes the F-statistic (Blandford, 1974) with an adaptive procedure that assesses variations in coherent noise in order to reduce false alarms. The adaptive procedure is characterized by the time dependent C-value that is found to depend on the weather conditions and local site effects. Arrays located on islands or near the coast produce noise power densities that are higher, consistent with both higher wind speeds as well as ocean wave contributions that vary seasonally. These results suggest that optimal detection processing requires careful characterization of background noise level and its relationship to enviornmental measures at individual arrays. This study also documents significant seasonal variations in infrasound detections including daily time of occurrence, total number of detections, and phase velocity/azimuth estimates. These time-dependent effects in most part explained by atmospheric models across the Korean peninsula as described by Drob et al. (2003).