1. Brazilian “Strong-Motion” Data Stéphane Drouet, ON, Rio de Janeiro Marlon Pirchiner, IAG/USP, São Paulo Marcelo Assumpção, IAG/USP, São Paulo Luis Carlos Ribotta, IPT, São Paulo GEM-SARA Topic 6 Workshop November 2014

2. Primary source of the records
Initial selection criteria Mmin~3 (whatever M scale)
Period
Records collected by Marcelo Assumpção (IAG-USP) from the largest recorded events (11 earthquakes)
Additional records from Luis Carlos Ribotta (ITP), 11 events (from which 9 are recorded at a single station)
From 2011
Records from the Rede Sismografica Brasileira ( 17 events

3. Map
Map of the events (red stars) and stations (blue triangles)

4. Data type and pre-processing
Only velocimetric digital records
Most of the recordings are sample at 100 sps (some of the oldest have lower sampling rate)
For all the records noise, P-wave and S-wave windows have been selected by hand

5. Processing
Taper 5%
Padding with 0.0 up to next power of 2 of record length
Integration and derivation to get displacement and acceleration
Records are cut between tp-10 sec and ts+duration (duration defined by hand but based on 95% of energy after S and 10% of maximum amplitude)
Mean removed using pre-event if tp>5 sec or using the mean of the whole record
fmin and fmax are selected based on the theoretical shape of the Fourier acceleration spectra
Zero-phase bandpass Butterworth filter between fmin and fmax
Data files written including pads

6. Example of time series (original)

7. Example of time series (processed)

8. Magnitude-distance scatter
mw from 2.0 to 5.2
Repi from 4 to 1800 km
No “strong-motion” data

9. Ground-Motion amplitude

10. Metadata Very little information Event information
Localization, mR from the IAG/USP catalogue, Mw from spectral analysis
3 focal mechanisms for the largest events from specific studies (to be updated)
Site information
Kappa and H/V analysis

11. Spectral analysis
Far-field S-waves Fourier spectra = Source x Path X Site
𝐴 𝑖𝑗𝑘 = 2R 𝜃𝜑 4 𝜋𝜌𝑣 𝑆 3 𝑀 0 𝑖 × 2 𝜋𝑓 𝑘 𝑓 𝑘 𝑓 𝑐 𝑖 𝑅 𝑖𝑗 𝛾 exp − 𝜋𝑅 𝑖𝑗 𝑓 𝑘 𝑄 0 𝑓 𝛼 𝑣 𝑆 𝑆 𝑗𝑘

12. Magnitudes

13. High-frequency attenuation
Get station information K (hard-rock/rock)
Get anelastic attenuation Q-values (regionalization)
Fig. 4 – Example of high-frequency fit to estimate K.
S-waves
noise
Fig. 5 – Computed K values against distance. The resulting Q factor is indicated on top.
Fig. 5 – Computed K values against distance. The resulting Q factor is indicated on top.

14. H/V ratios from S-waves
Flat site response, with amplitude close to one => good rock sites, consistent with the very low kappa values

15. To be done Check geology of the sites
Search for additional focal mechanisms and eventually fault information
Produce a stochastic GMPE using the results of the spectral analysis (stress drop, Q)
Include other data:
from RSBR (data available)
Search additional data from collaborators in Brazil