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A Direct Comparison Between Established Infrasonic Data Processing Pipelines from the DNE18 Virtual Experiment

The Dynamic Network Experiment 2018 (DNE18) was a virtual experiment designed to quantitatively assess current capabilities of multi-modal data processing for local and regional nuclear explosion monitoring. The experiment was a collaborative effort between Los Alamos National Laboratory (LANL), Sandia National Laboratories (SNL), Lawrence Livermore National Laboratory and Pacific Northwest National Laboratory. One component of the experiment was the establishment of a baseline for infrasonic signal detection and event identification. This baseline was established using proprietary infrasonic data processing packages at both LANL (InfraPy) and SNL (Bloodhound). The DNE18 data set spanned December, 2010 through February, 2011 and included data collected on the University of Utah seismic network. The analysis of this data set using a consistent set of processing parameters allows for a direct comparison of the algorithms utilized in each processing pipeline. For each processing toolkit, automated detection and event catalogs were created. The detection catalogs have been compared against both each other and an analyst-produced catalog to quantify detector performance in terms of precision and recall. Subsequent event association and location results in the event catalogs have been compared in terms of completeness and measures of error. This comparison expands upon previously published studies quantifying the performance of automatic infrasonic signal detectors and also presents a comparison of infrasonic detection, association and localization analyses in a functioning pipeline.

Presenting Author: Fransiska K. Dannemann Dugick

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