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Real-Time Estimation of Earthquake Location and Magnitude for Seismic Early Warning in Campania Region, southern Italy A. Zollo and RISSC-Lab Research Group* with A.Lomax ( A.Lomax Scientific Software ) is a joint seismological research group between University of Naples - Dept of Physics and INGV – Osservatorio Vesuviano *

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Work Motivation Development and testing of a Seismic Early- Warning System for automated risk mitigation actions in Campania Region Need for robust and reliable real-time estimates of eqk location and magnitude to be obtained in an evolving, continually updated form. Need to provide with parameter uncertainty variation with time engineering structural control

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1980 Irpinia earthquake, Ms=6.9 Historical Earthquakes

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INGV catalogue ( ) M 2.5 INGV catalogue ( ) M 2.5 Early Warning Network 29 sites Osiris 24-bit Data Logger 6 channels: 3 accelerometers 3 seismometers (Short Period or Broad Band) Real time data analysis Early Warning Network 29 sites Osiris 24-bit Data Logger 6 channels: 3 accelerometers 3 seismometers (Short Period or Broad Band) Real time data analysis Recent Seismicity

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SEW System Peculiarities To time s eqk at 4-16 km depth TP first s s s TS target Latency & computation 3-5 s High spatial density : Station spacing < 15 km Characteristic times: Wide-Dynamics: Unsaturated signals up to 1 g 60 km 80 km 100 km

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Real-Time Earthquake Location Basic Ideas: Constraint from not-yet-triggered stations Tracing and crossing Equal Differential Time (EDT) surfaces Probabilistic estimation of eqk location vs time (Evolutionary Approach) Basic Ideas: Constraint from not-yet-triggered stations Tracing and crossing Equal Differential Time (EDT) surfaces Probabilistic estimation of eqk location vs time (Evolutionary Approach)

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When a first station S n triggers at t n = t now, we can already place limits on a pdf volume that is likely to contain the hypocenter (Voronoi cell). These limits are given by conditional EDT surfaces on which the P travel time to the first triggering station A is equal to the travel- time to each of the not-yet-triggered stations. As the current time t now progresses we gain the additional information that the not-yet-triggered stations can only trigger with t l > t now When the second and later stations trigger, we construct standard, true EDT surfaces between each pair of the triggered stations.These EDT surfaces are stacked with the volume defined by the not-yet-triggered stations to form the current hypocentral pdf volume. Real-time Evolutionary Location

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Earthquake location probability Seconds from first trigger Seconds from earthquake Origin Time Triggered stations Earthquake location probability Synthetic Examples

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Real-Time Magnitude Estimate Basic Ideas Use both early P- and S-wave information based on the high density / wide dynamics of the network Correlate low-pass filtered peak amplitudes with Magnitude in increasing time windows Regression analysis based on the European strong motion Data-Base (ESD, Ambraseys, 2004) Basic Ideas Use both early P- and S-wave information based on the high density / wide dynamics of the network Correlate low-pass filtered peak amplitudes with Magnitude in increasing time windows Regression analysis based on the European strong motion Data-Base (ESD, Ambraseys, 2004)

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European Strong Motion Data Base* * Ambraseys et al. (2004) 207 Events with 4M W 7.4 (Kokaeli,1999) 376 three-component records Epicentral distance 50 km Low-pass filter: 3 Hz Magnitude bin: Events with 4M W 7.4 (Kokaeli,1999) 376 three-component records Epicentral distance 50 km Low-pass filter: 3 Hz Magnitude bin: 0.3

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Vertical 3Hz low-pass filtered acceleration at station Bagnoli (1980, Irpinia Eqk, Ms=6.9) – Epicentral Distance: 20 Km 3Hz low-pass filtered acceleration at station Bagnoli (1980, Irpinia Eqk, Ms=6.9) – Epicentral Distance: 20 Km Horizontal H(t)= NS 2 (t)+EW 2 (t) Measurement of Peak Amplitude 1-sec 2-sec

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Log(PGD t ) vs Magnitude magnitude Log(displacement) P-wave S-wave Single data point Mean value 2-Weighted Standard Error

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A possible explanation The far-field approximation for displacement (f=3Hz, D> 5-6 km): moment rate Dynamic stress drop vs M Rise-time vs M Rupture dynamics Rupture kinematics The observed correlation between log(PGXt) and Magnitude would imply that dynamic stress release and/or rise-time scale with earthquake size in the very early stage of seismic ruptures Slip-rate vs M Active slip area vs M

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Summary A high-density, wide-dynamics seismic network is being installed in southern Italy for regional early-warning applications The system will implement a real-time eqk location method based on an evolutionary, probabilistic approach Early P- and S- signal amplitudes (less the 2 sec from first arrival) correlate with magnitude (4M w 7.4) as from the analysis of the European Strong Motion Data Base A combination of magnitude estimations obtained by early P/S peak amplitudes and predominant periods (Allen & Kanamori,2003) measured at different stations as a function of time may significantly improve the accuracy of the earthquake size estimation in real-time procedures.

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The End

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Multiple Events Each time a new pick is available, the algorithm: 1.Temporarily associates the pick to the current event 2.Relocates the event 3.Checks the travel-time RMS for the maximum likelihood hypocenter 4.If RMS < RMS thresh the pick is definitively associated, otherwise a new event is declared

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Vertical Modulus of horizontal components

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Strong Motion Data De Natale et al., BSSA,1987 Kanamori & Rivera, BSSA, 2004

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Log(PGX t ) vs Magnitude Early P-Wave Early S-Wave acceleration velocity displacement

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