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In the Pursuit of 99% Data Return - Case Study of the Italian National Accelerometric Network

Description: 

99% of data return over an entire year - no timing issues - no micro gaps. These performance indicators tell the story of sound engineering, outstanding dataloggers, enterprise-class software, and rigorous maintenance. Data return is the primary benchmark of the success of any real-time monitoring network. Without data, operators, data users, and, ultimately, information consumers gain no value from the investment in the system. Moreover, monitoring systems related to the observational sciences, like seismology, rely even more so on high data returns because an earthquake cannot be repeated. If the system has data gaps, generates error-laced returns, or experiences downtime, critical information for real-time and future post-processing can be missed.

The mission-critical Italian National Accelerometric Network, RAN (Rete Accelerometrica Nazionale), informs the Italian Civil Protection Department, DPC (Dipartimento della Protezione Civile) about destructive and felt earthquakes. It consists of more than 700 stations, of which about 440 are closely monitored. Real-time data availability in 2024 was over 98.5%, with station availability beyond 99.5% since 2017. Typically, the network locates about 1800 events per year. Earthquakes with an M4 or larger magnitude trigger a temporary 10-station array deployment around the epicenter. These stations telemeter acceleration measurements in real-time to the data center, and the data streams are immediately included in the automatic processing flow, providing valuable information on the aftershock sequence. DPC shares the data with other government agencies and academic institutions in real-time and on request. The automatic processing results include, in between others, PGA, PGV, PGD, PSAs, Housner and Arias intensity, and response spectra.

Session: Network Seismology: Recent Developments, Challenges and Lessons Learned - I

Type: Oral

Date: 4/15/2025

Presentation Time: 09:00 AM (local time)

Presenting Author: Mathias

Student Presenter: No

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