the empirical m odel
DESCRIPTION
The Empirical M odel. Karen Felzer USGS Pasadena. A low modern/historical seismicity rate has long been recognized in the San Francisco Bay Area . Stein 1999. The Bay Area rate changes was carefully studied by WGCEP 2002 ( Reasenberg et al. , 2003). They found:. - PowerPoint PPT PresentationTRANSCRIPT
The Empirical Model
Karen FelzerUSGS Pasadena
A low modern/historical seismicity rate has long been recognized in the San Francisco Bay Area
Stein 1999
The Bay Area rate changes was carefully studied by WGCEP 2002 (Reasenberg et al., 2003). They found:
• Average seismicity rates from 1850-1906 were 2.2 x above long term rates.
• Rates from 1951-1998 were lower than 1850-1906 rates.
• The rate change amplitude varied by fault.• No current physical model adequately explains the rate
changes.• The rate changes have been fairly stable since 1951.• Final recommendation: Set all rates to 0.58 x long term
rates for 2001-2031.
1850-1905 vs. 1951-1998 rates, by fault, as compared to the long term average
Figure 8, Reasenberg et al. (2003)
Note: Variability of rate change on different faults
Seismicity rate plots as a function of time with various smoothing kernels
Figure 5, Reasenberg et al. (2003)Ra
te
YearNote: Rate >1951 fairly stable and deemed unlikely to
change without a large earthquake
Important take-away points
• Over ≥50 year periods seismicity rates can be relatively but significantly different from the long term average.
• The change in rates throughout the San Francisco Bay Area is spatially variable
0.79
0.46
0.64
0.66
0.64 Statewide:0.82
*Average short term = average of 1906-2006, 1942-2006, and 1984-2006
Results from WGCEP 2007, Appendix M
WGCEP 2008 found that the rate change actually extends over most of the state of California
Is this real? A low current seismicity rate statewide also agrees with geodetic/deformation studies
“The western U.S. has been 37% below its long-term-average seismicity during 1977-2008” (Bird, 2009)
“73-86% of the geodetic moment rate in California appears in the existing earthquake catalogue” (Ward, 1998)
However: The statewide seismicity rate decrease is spatially variable, with some areas above their long-
term average
1932-2010 M≥4 seismicity divided by long term seismicity rate forecast of Bird
(2009)
Will a spatially variable empirical model forecast better?
Log(Smoothed Seismicity/Strain)2
0
-2
A spatially variable, completely empirical model = smoothed seismicity
This is the Helmstetter et al. approach, which is the winning the 5 year RELM forecasting test
Normalized log of rate
Smoothed seismicity performs better than long term rates over the last 1, 5, 10, and 50 years
Correlation coefficient between forecast and realized seismicity rates
We look at the performance of the 5 year smoothed seismicity forecast in detail
Correlation coefficient between forecast and realized seismicity rates
2006-10 smoothed seismicity /forecast for last 5 years
Performance of 1932-2005 smoothed seismicity forecast for 2006-2010
Decay of Landers/Hector
Mine aftershocks could be
corrected for
Baja aftershocks
could be added
Aftershocks could be placed
preferentially on high slip faults
We might be able to improve performance with aftershock and fault modeling
2006-2010 smoothed seismicity /forecast for last 5 years
Can the spatially variable empirical model be applied to the largest
earthquakes?
Most of the statewide rate decrease comes from the San Andreas fault
1932-2010 M≥4 seismicity vs. long
term seismicity rate forecast of Bird
(2009)
Overall the San Andreas should host at least ~40% of California’s M≥7 earthquakes
Name Year Month Magnitude On SAF?
Lompoc 1927 11 7.1 No
1934 12 7.0 No
Kern County 1952 7 7.5 No
Landers 1992 6 7.3 No
Hector Mine 1999 10 7.1 No
El Mayor-Cucapah
2010 4 7.2 No
M≥7 earthquake record south of the triple junction >1906
The absence of M≥7 earthquakes from the San Andreas is significant at 95% confidence
Proposal for changeOld Method
• Start with long term slip rate, known-faults based model + smoothed seismicity.
• Move all rates up or down to empirically fit modern catalog.
New Method• Start with smoothed
seismicity rates.• Simulate where aftershocks
might occur over the forecast period, and add aftershocks in real time.
• Adjust azimuth of smoothing kernel for spontaneous events and aftershocks to produce more events where long term rates are high (on faults!)
Goal: Forecast where seismicity will occur in the short term, match the long term model over the long term
Conclusions
• We observe that regional seismicity rates vary significantly from their long term rates over periods at least as long as 50 years. Propagating empirically observed rate changes has historically produced a better forecast.
• The rate changes appear to apply to M≥7 earthquakes.• Simple smoothed seismicity maps may provide the
best forecasts for ≤50 year periods provided that the map is updated as aftershocks occur with input from the long term slip model.
Statewide, rate of M≥6.0 1857-1927 is ~65% of
1927-2006
The statewide rate decrease can also be seen if we just look at larger earthquakes
Smoothed seismicity performs better than long term rates over the last 1, 5, 10, and 50 years
Fraction of bins in which forecast and realized rates agree by >50%: