Comparing the performance of regional earthquake early warning algorithms in Europe

Abstract

Several earthquake early warning (EEW) algorithms have been developed worldwide for rapidly estimating real-time information (i.e., location, magnitude, ground shaking, and/or potential consequences) about ongoing seismic events. We quantitatively compare the performance of popular regional EEW algorithms for European conditions of seismicity and network density, to identify the best context-specific algorithms for location and moment magnitude prediction. We specifically test PRobabilistic and Evolutionary early warning SysTem (PRESTo), Earthquake Alarms Systems (ElarmS), Virtual Seismologist (original version), and an implementation of the Virtual Seismologist magnitude component within SeisComP, VS(SC), which we use jointly with the module for locating events. We first investigate the operational performance of the PRESTo and SeisComP (using and VS(SC)) platforms, to evaluate the timeliness and accuracy of the provided estimates in real-time simulation mode, accounting for the continuous streaming of data and effective processing times. Then, we conduct a conceptual study focusing particularly on algorithm accuracy, in which we separately examine the location and magnitude components of PRESTo, ElarmS and Virtual Seismologist, along with the module for location, accounting for both bias and uncertainty in the resulting predictions. We finally illustrate the performance improvement that the best algorithmic combinations for location and magnitude estimation (i.e, + PRESTo magnitude component and + ElarmS magnitude component) can offer at the ground-motion prediction (decision-making) stage of EEW, relative to the original (complete) versions of the algorithms. The findings of this study can be used to inform current and future implementations of EEW systems in Europe.