We explore the application of GPS data to earthquake early warning and investigate whether the coseismic ground deformation can be used to provide fast and reliable magnitude estimations and ground shaking predictions. We use an algorithm to extract the permanent static offset from GPS displacement time series and invert for the slip distribution on the fault plane, which is discretized into a small number of rectangular patches. We developed a completely “self‐adapting” strategy in which the initial fault plane model is built based on a quick, approximate magnitude estimation and is then allowed to increase in size based on the evolutionary magnitude estimation resulting from the slip inversion. Two main early warning outputs are delivered in real‐time: magnitude and the along‐strike extent of the rupture area. These are finally used to predict the expected ground shaking due to the finite source. We tested the proposed strategy by simulating real‐time environments for three earthquakes. For theM_w9.0, 2011 Tohoku‐Oki earthquake, our algorithm provides the first magnitude estimate of 8.2 at 39 s after the origin time and then gradually increases to 8.9 at 120 s. The estimated rupture length remains constant from the outset at ~360 km. For theM_w8.3, 2003 Tokachi‐Oki earthquake, the initial magnitude estimate is 8.5 at 24 s and drops to 8.2 at 40 s with a rupture length of 290 km. Finally, for theM_w7.2, 2010 El Mayor‐Cucapah earthquake, the magnitude estimate is 7.0 from the outset with a rupture length of 140 km. The accuracy of the ground shaking prediction using the GPS‐based magnitude and finite extent is significantly better than existing seismology‐based point source approaches. This approach would also facilitate more rapid tsunami warnings.

A new strategy for a P wave‐based, on‐site earthquake early warning system has been developed and tested on Japanese strong motion data. The key elements are the real‐time, continuous measurement of three peak amplitude parameters and their empirical combination to predict the ensuing peak ground velocity. The observed parameters are compared to threshold values and converted into a single, dimensionless variable. A local alert level is issued as soon as the empirical combination exceeds a given threshold. The performance of the method has been evaluated by applying the approach to the catalog of Japanese earthquake records and counting the relative percentage of successful, missed, and false alarms. We show that the joint use of three peak amplitude parameters improves the performance of the system as compared to the use of a single parameter, with a relative increase of successful alarms of about 35%. The proposed methodology provides a more reliable prediction of the expected ground shaking and improves the robustness of a single‐station, threshold‐based earthquake early warning system.

A fundamental feature of any earthquake early warning system is the ability of rapidly broadcast earthquake information to reach a wide audience of potential end users and stakeholders, in an intuitive, customizable way. Smartphones and other mobile devices are nowadays continuously connected to the Internet and represent the ideal tools for earthquake alerts dissemination to inform a large number of users about the potential damaging shaking of an impending earthquake. Here we present a mobile app (named ISNet EWApp or simply EWApp) for Android devices which can receive the alerts generated by a network-based Early Warning system. Specifically, the app receives the earthquake alerts generated by the PRESTo EEWS, which is currently running on the accelerometric stations of the Irpinia Seismic Network (ISNet) in southern Italy. In the absence of alerts, EWApp displays the standard bulletin of seismic events that have occurred within the network. In the event of a relevant earthquake, the app has a dedicated module to predict the expected ground-shaking intensity and the available lead time at the user's position and to provide customized messages to inform the user about the proper reaction to adopt during the alert. We first present the architecture of both the network-based system and EWApp and then describe its essential operational modes. The app is designed in a way that is easily exportable to any other network-based early warning system.

When a seismic rupture starts, the process may evolve into multiple ways, generating different size earthquakes. Contrasting models have been proposed to describe the evolution of the rupture process while limited observations at the scale of real earthquake data are available, so that a unifying theory is still missing. Here we show that small and large earthquake ruptures are different before the arrest and they do not exhibit a common, size-independent, universal behaviour. For earthquakes with magnitude 4 < M < 9 occurred in Japan, we measure the initial rate of the P-wave peak amplitude and show that this quantity is correlated to the final event magnitude and not affected by distance attenuation, thus being a proxy for the initiation time of the rupture process. While opening new views on the rupture preparation process, our findings can have significant implications on the effective development of fast and reliable methods for source characterization and ground shaking prediction.

Seismic sequences are a powerful tool to locally infer geometrical and mechanical properties of faults and fault systems. In this study, we provided detailed location and characterization of events of the 3–7 July 2020 Irpinia sequence (southern Italy) that occurred at the northern tip of the main segment that ruptured during the 1980 Irpinia earthquake. Using an autocorrelation technique, we detected more than 340 events within the sequence, with local magnitude ranging between −0.5 and 3.0. We thus provided double difference locations, source parameter estimation, and focal mechanisms determination for the largest quality events. We found that the sequence ruptured an asperity with a size of about 800 m, along a fault structure having a strike compatible with the one of the main segments of the 1980 Irpinia earthquake, and a dip of 50–55° at depth of 10.5–12 km and 60–65° at shallower depths (7.5–9 km). Low stress drop release (average of 0.64 MPa) indicates a fluid-driven initiation mechanism of the sequence. We also evaluated the performance of the earthquake early warning systems running in real-time during the sequence, retrieving a minimum size for the blind zone in the area of about 15 km.

This work is aimed at the automatic and fast characterization of the extended earthquake source, through the progressive measurement of the P-wave displacement amplitude along the recorded seismograms. We propose a straightforward methodology to quickly characterize the earthquake magnitude and the expected length of the rupture, and to provide an approximate estimate of the average stress drop to be used for Earthquake Early Warning and rapid response purposes. We test the methodology over a wide distance and magnitude range using a massive Japan earthquake, accelerogram data set. Our estimates of moment magnitude, source duration/length and stress drop are consistent with the ones obtained by using other techniques and analysing the whole seismic waveform. In particular, the retrieved source parameters follow a self-similar, constant stress-drop scaling (median value of stress drop = 0.71 MPa). For the M 9.0, 2011 Tohoku-Oki event, both magnitude and length are underestimated, due to limited, available P-wave time window (PTWs) and to the low-frequency cut-off of analysed data. We show that, in a simulated real-time mode, about 1–2 seconds would be required for the source parameter determination of M 4–5 events, 3–10 seconds for M 6–7 and 30–40 s for M 8–8.5. The proposed method can also provide a rapid evaluation of the average slip on the fault plane, which can be used as an additional discriminant for tsunami potential, associated to large magnitude earthquakes occurring offshore.