1. Task 3: Irpinia Fault System WP3.1 Seismic noise analysis and Green Functions Project – DPC S5 High-resolution multi-disciplinary monitoring of active fault test-site areas in Italy Vassallo Maurizio, Gaetano Festa, Antonella Bobbio, Piero Brondi 24 March 2010 –INGV Rome

2. Broad-band ISNet stations and Ambient seismic Noise RSF3 RDM3 PGN3 COL3 TEO3 Ambient seismic noise acquired for 18 months at 5 stations of ISNet equipped with broad-band velocimeters (Trillium 40) ISNet dense seismic network: A field laboratory to study the seismic source at small scales An advanced infrastructure to test early warning procedures Broad-band stations: RSF3 Rocca S. Felice (AV) TEO3 Teora (AV) RDM3 Ruvo del Monte(PZ) COL3 Colliano (SA) PGN3 Pignola (PZ)

3. Green functions from ambient seismic noise and Ф A and Ф B are the seismic fields received by two sensors in A and B When the propagation medium satisfies the equipartition principle for a complete diffuse wavefield we can compute the Green function G AB (t) between two recording points A and B by the cross-correlation functions of the respectively seismic fields: G AB (t) can be reitrieved by the causal part (t > 0) and anticausal part (t<0) of the cross correlation function C AB (t) Lobkis and Weaver (2001) Where

4. Data collecting and processing Phase 2: cross-correlation and stack Continuous seismic data acquired for 18 months at 5 broad band stations of ISNet Remove mean; remove trend; band pass filter and cut to length 6 hours time domain normalization (1-bit normalization) Spectral Normalization (spectral whitening) Compute cross- correlation Compute the stack of correlations Phase 1: single station data preparation

5. Cross-correlations and stacks Common low frequency signal Higher stability of signal during the spring and summer symmetric stack energetic signal between -30 e 30 s asymmetric stack energetic signal between -70 e 70 s Distance between stations 27 km |One year of data (2009) | Distance between stations 40 km

6. small variations in the processed stacks  processing not effective Processing to increase signal quality Spectral whitening Recoursive Butterworth filter between 0.1 Hz and 1 Hz Stack of traces with high S/N Whitening Recoursive filter

7. Dispersion analysis [0.1Hz-1Hz] frequency (Hz) Group velocity (m/s) Period (s) Group velocity (km/s) PGN-RSF PGN-TEO Group velocity (km/s) Period (s) Surface wave analysis of stacks Velocity analysis for identification of phases Picking for dispersion curves reconstruction Velocity models Comparison between picked dispersion curves and dispersion curves computed using the 1D velocity models of the area

8. Dispersion analysis [0.1Hz-1Hz] Dispersion computed only for far stations pairs, for near stations pairs low S/N in stack traces  problems for velocity analysis

9. Dispersion analysis [10s-50s] All stacks filtered in 0.05Hz-0.08 Hz PGN-RSF 0.01 Hz 0.02 Hz 0.03 Hz 0.04 Hz 0.05 Hz 0.06 Hz 0.07 Hz 0.08 Hz 0.09 Hz 0.10 Hz Time-dispersion analysis Surface wave propagation Frequency Distance Period (s) Group velocity (km/s) RDM-RSF Period (s) Group velocity (km/s) RDM-PGN Velocity analysis Preliminary results

10. Dispersion analysis [10s-50s] Preliminary results Clear surface waves identified on stack traces for all broad band stations

11. Conclusions Data collections and processing 100% completed Computed cross-Correlations and Green functions for all pairs of broad band stations 100% completed Velocity and dispersion analysis 80-90% completed Inversion dispersion curves for reconstruction of velocity models 30-40% completed WP 3.1 activities 24 months 18 months 12 months 6 months Data collection and processing Green functions Dispersion analysis Velocity models Time Schedule