Application of SeisComP at the Central Weather Administration (CWA) for Earthquake Monitoring and Early Warning: A Case Study of the 2024 ML 7.2 Hualien, Taiwan, Earthquake Sequence

    SeisComP (Seismological Communication Processor) is an open-source, free seismic monitoring software that features an automated seismic data processing workflow, flexible database integration, and data interface capabilities. This study integrates SeisComP with the scanloc module, ETHZ-SED SeisComP Earthquake Early Warning (EEW) system algorithms, and SeisBench to develop three distinct seismic monitoring systems, optimizing three key tasks for the Central Weather Administration (CWA): earthquake early warning, seismic activity analysis, and global earthquake data acquisition. During the M_L 7.2 Hualien earthquake on April 3, 2024, at 7:58 AM (UTC+8) CWA, in collaboration with ETHZ-SED, applied the EEW algorithms, including the Virtual Seismologist (VS) and Finite-Fault Rupture Detector (FinDer). Both algorithms, tested in parallel at the time, successfully generated complete results within 26 seconds of the earthquake’s origin. Based on these results, Public Warning System (PWS) alerts would have been issued for 17 out of 19 counties in Taiwan, thereby supporting CWA’s existing system. For the seismic activity analysis system, which integrates SeisComP, SeisBench, and the scanloc module, 3,789 automatic location results were produced within three days of the event. Compared to 604 official earthquake reports from CWA, the horizontal location error was approximately 4 km, the depth error 5 km, and the magnitude error 0.17. These results demonstrate the system’s ability to quickly assess seismic activity and estimate subsequent disaster risks. It also has the potential to automate earthquake catalog creation and reduce manual workload. In the global earthquake monitoring system, data is received from IRIS and GEOFON, currently generating results for earthquakes with magnitudes of 6.0 or larger and depths of 30 km or less in the Pacific region. In addition to providing valuable data for tsunami simulations, the system utilizes the global network to calculate Moment Magnitude Mw, which is derived from broadband P-wave amplitudes. For example, the system calculated a M_w of 7.4 for the 2024 Hualien event, which closely matched the magnitude result reported by the USGS. This helps avoid saturation issues with CWA’s M_L estimation, particularly for larger earthquakes, and provides a more accurate measurement of earthquake size and dynamics, ultimately enhancing the system’s ability to monitor and assess earthquake risk. This study successfully tested the use of SeisComP in the aforementioned tasks. Although discrepancies remain between automatic results and the official catalog, ongoing testing and parameter optimization are expected to significantly enhance Taiwan’s earthquake monitoring capabilities and integrate more seismic data, ultimately improving the quality of earthquake monitoring services.

Keywords: SeisComP, earthquake early warning, earthquake monitoring