8:30 AM - 8:45 AM
[S01-3-01] The Global Seismographic Network (GSN): New VBB Borehole Sensors, Sensor Emplacement Techniques and Data Quality Assessment using MUSTANG
The Global Seismographic Network (GSN) is a 152 station, globally-distributed, permanent network of high quality seismological and geophysical sensors. The central design goal of the GSN is “to record with full fidelity and bandwidth all seismic signals above the Earth noise, accompanied by some efforts to reduce Earth noise by deployment strategies". After over 20 years of operation, most of the network's technical design goals have been met. The challenge is to continue to modernize the network and maintain high data quality in an era of flat or declining budgets.
We will present a number of approaches to maintain GSN data quality and improve overall network noise performance. These include: 1) Standardizing equipment across the network, e.g. deploying new Quanterra Q330HR dataloggers; 2) Developing next-generation very broadband borehole sensors to replace the failing KS-54000 sensors (one third of the network); 3) Using the results of noise analyses to determine where new sensor emplacement techniques, e.g. shallow boreholes, might achieve lower noise performance for the existing site conditions. We also show how shallow borehole installations may be adapted to vaults (which make up two thirds of the network), as a means of reducing tilt-induced signals on the horizontal components.
The GSN is creating a prioritized list of proposed infrastructure and equipment upgrades at selected stations with the ultimate goal of optimizing overall network data availability and noise performance. For this effort, we are utilizing data quality metrics and Probability Density Functions (PDFs)) generated by the IRIS Data Management Centers' (DMC) MUSTANG (Modular Utility for Statistical Knowledge Gathering) tool. We will present our MUSTANG metric analysis and show GSN sites which could benefit the most from instrumentation and infrastructure upgrades.
We will present a number of approaches to maintain GSN data quality and improve overall network noise performance. These include: 1) Standardizing equipment across the network, e.g. deploying new Quanterra Q330HR dataloggers; 2) Developing next-generation very broadband borehole sensors to replace the failing KS-54000 sensors (one third of the network); 3) Using the results of noise analyses to determine where new sensor emplacement techniques, e.g. shallow boreholes, might achieve lower noise performance for the existing site conditions. We also show how shallow borehole installations may be adapted to vaults (which make up two thirds of the network), as a means of reducing tilt-induced signals on the horizontal components.
The GSN is creating a prioritized list of proposed infrastructure and equipment upgrades at selected stations with the ultimate goal of optimizing overall network data availability and noise performance. For this effort, we are utilizing data quality metrics and Probability Density Functions (PDFs)) generated by the IRIS Data Management Centers' (DMC) MUSTANG (Modular Utility for Statistical Knowledge Gathering) tool. We will present our MUSTANG metric analysis and show GSN sites which could benefit the most from instrumentation and infrastructure upgrades.