EARLYWARNING TESTSITE NAPLES Giovanni Iannaccone INGV AMRA scarl

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EARLY-WARNING TEST-SITE NAPLESGiovanni
IannacconeINGV AMRA scarl
With the main contribution of RISSC-Lab team A.
Bobbio, L. Cantore, V. Convertito, M. Corciulo,
M. DiCrosta, L. Elia, A. Emolo, G. Festa, I.
Iervolino, M. Lancieri, C. Martino, C. Satriano,
T. Stabile, M. Vassallo, A. Zollo and P. Gasparini
Final Project Meeting Potsdam June, 3-5,2009
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The Irpinia Seismic Network (ISNet) of AMRA
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Current seismicity
INGV catalogue (1981-2002), Mgt2.5
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Current seismicity Local eq detected by ISNet (
400 events since January 2008, 1 lt M lt 3.0)
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The Irpinia Seismic Network (ISNet)
Seismic Stations and Local Control Centers
50 Km
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The Irpinia Seismic Network (ISNet)
Local Control Centers Virtual Sub-Networks
50 Km
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The Irpinia Seismic Network (ISNet)
Current Communication System HDSL Internet
Radio-Links
50 Km
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Example of Local Control Center
Property of AMRA
Hosted by Astronomical Observatory
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Data Information Flow
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Real-Time Data Management EarthWorm
Earthworm (USGS, 1993 - )

• Modular
• System Independent
• Scalable
• Connectable
• Robust

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Ground shaking maps
A simulated M 6.6 earthquake located at center
of ISNet

• Using ShakeMap
• Testing an alternative technique (GRSmap)
• (Visit the poster by Convertito et al)

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QVTM classification and site amplification
coefficients

• QVTM classification map for Campania Lucania
  region
• Estimation of corrective coefficients from the
  spectral ratio technique

Spectral ratio for station CLT3
M Q V T
Blue Mesozoic Green Quaternary Red
Tertiary-Quaternary (Volcanic) Yellow Tertiary.
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Near-Real-Time Damage Assessment at Naples
WP3 AMRA NORSAR
Structural Survey of RC buildings in the test
area (AMRA)
Arenella District 5.25 km2 72,000 inhabitants
gt 1,400 buildings gt 85 Reinforced Concrete
pre-code residential buildings
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Near-Real-Time Damage Assessment at Naples
WP3 AMRA NORSAR
Vulnerability analysis of the building stock
(AMRA)
Loss assessment based on shakemaps (NORSAR)
Irpinia 1980 scenario
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ISNet Bulletin (http//lxserver.ov.ingv.it)
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PRESTo - Probabilistic evolutionaRy Early
warning SysTem
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PRESTo a new stand-alone software tool for
earthquake early warning
Block diagram of the PRESTo software package
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EEW Development at AMRA
The effort to build an EEW System is both
technological and scientific
PRESTo - Probabilistic evolutionaRy Early
warning SysTem
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OK, NOW THE ISNet RELATED EWS IS RUNNING
ARE WE REALLY SURE ?

• WHAT WE NEED TO DO
• Improvement of ISNet
• Quantitative evaluation of the early-warning
• system performances
• Target applications

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Improvement of ISNet
50 Km

• - Communication system with fully proprietary
  radio-links
• LCC strengthening (i.e. solid state disks)
• Add low cost innovative seismic sensors to
  increase ISNet stations and
• for urban (structural) monitoring

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EW System performance(How can it be verified
whether an EEWS is WORKING correctly? )

• The main test would be to wait until a
  significant number of earthquakes have been
  recorded, also of medium to large energy, and to
  verify the number of alarms that have correctly
  been sent, along with the number of false alarms
  and alarms missed.
• To verify the significance of each alarm,
  including the useful time before the arrival of
  the destructive seismic wave (lead time), and the
  predicted amplitude at a site with respect to
  that which is actually recorded.
• (For instance, the EEWS operating in Japan by JMA
  was tested for 29 months, starting in February
  2004. During this period, the JMA sent out 855
  earthquake early warnings, with only 26
  recognized as false alarms due technical problems
  or human error)

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EW System performance(How can it be verified
whether an EEWS is WORKING correctly? )
Currently in southern Apennines only low M eqs
Export the developed methodology
Test with low magnitude earthquakes
Off line test using seismograms (files) recorded
by other seismic networks
Test with synthetic seismograms computed at ISNet
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Tests with low magnitude earthquakes

Application of PRESTo to an Irpinia microeq ML
2.5
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Off line test using seismograms recorded by other
seismic networks
Application of PRESTo to the June 14, 2008, 0843
(JT), Mw 6.9 Iwate eq (Japan)
Screenshot of PRESTo, processing the SAC files of
the Iwate earthquake
Evolution with time of the magnitude estimate and
of its uncertainty. The vertical red bar marks
the estimated origin time (T0) of the
earthquake. The interval (6 sec) elapsed from the
origin time to the first magnitude estimate with
a low uncertainty is highlighted by a yellow
dashed pattern
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Application of PRESTo to the June 14, 2008, 0843
(JT), Mw 6.9 Iwate eq (Japan)
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Tests with synthetic seismograms computed at ISNet
Application of PRESTo to synthetic seismograms of
1980, Ms 6.9 Irpinia eq
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Tests with synthetic seismograms computed at ISNet

• Computation of synthetic seismograms for a large
  number earthquake scenarios
• We introduce two main parameters
• Prediction error definition
• PE Log10(PGVobs/PGVpred)
• Where PGVobs are measured on synthetics and
  PGVpred are predicted by the early warning
  procedure (PE is computed as a function of time
  for the whole number of simulated eqk scenarios)
• Effective Lead Time
• Time interval between the S-arrival at the
  target and the time at which the prediction error
  distribution is stable (no significant variation
  of magnitude, location after this time).

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Tests with synthetic seismograms computed at ISNet

• Computation of synthetic seismograms for a large
  number of M6 and M7 earthquake scenarios
• Off-line, but sequentially application of the EW
  chain of methodologies to investigate the areal
  distribution of lead-time and prediction error on
  PGV

• 300 rupture scenarios for a M 6.9 earthquake
• 90 rupture scenarios for a M 6.0 inside the
  network
• 90 rupture scenarios for a M 6.0 at the border of
  the network

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Synthetic seismograms
Tests with synthetic seismograms computed at ISNet

• Hybrid source model based on k-square slip
  distribution (Gallovic and Brokesova, 2008)
• Complete wavefield Green function in a1-D
  velocity model
• Waveforms have been noise contaminated and
  convolved by the site transfer function to
  account for site effects

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Effects of source complexity on the prediction
error
Tests with synthetic seismograms computed at ISNet
Strong directivity
Strong directivity
Weak directivity
Directivity, radiation pattern and point-source
attenuation law determine the azimuthal variation
of the prediction error distribution
TRCEW
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EW System performance (M 7) Effective Lead-Time
Tests with synthetic seismograms computed at ISNet
Time interval between the S-arrival at the target
and the time at which the prediction error
distribution is stable (no significant variation
of magnitude, location after this time).
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EW System performance (M 7) Prediction error
Tests with synthetic seismograms computed at ISNet
Probability of Prediction Error
The probability that the prediction error
(PElog(PGVtrue) log(PGVesti)) is within
1-sigma interval of the standard error on the
Ground Motion Prediction Equation. High values of
PPE means high performance of the system in terms
of prediction of ground shaking level at the
target.
Small errors
Large errors
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Conclusions

• Need for a quantitative evaluation of the
  Early-Warning system performances in terms of
  expected lead times, predicted ground motion
  intensity along with their uncertainties, for the
  main regional targets (export our procedures on
  other seismic networks)
• Need to identify target applications (i.e.
  shut-down of equipments, saufguards of
  life-lines, alert for hospitals, schools,
  transportation networks,) and to design and
  develop ad hoc control systems and mechanisms
  for real-time damage reduction