Progress Report on the ISM Project
2003-2007
Statistical Seismology Research Group
Prediction and Knowledge Discovery Research
Center
The
Institute of Statistical Mathematics
Research
Organization of Information and Systems
Table of Contents
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Motivations behind this project ₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯ |
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(1) Hypocenter data ₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯ |
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(2) Other geophysical
datasets ₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯ |
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(3) Point-process
models ₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯ |
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(4) Earthquake / Aftershock
forecasting ₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯ |
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(5) Exploration and modeling
of the interface between physical and stochastic processes ₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯ |
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(6) Space-time point-process
modeling ₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯ |
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References ₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯ |
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Objectives of the project ₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯ |
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Work Plan 2003-2007 ₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯ |
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Project
Members ₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯ |
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Research Accomplishments 2003-2005 ₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯ |
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Principal works during 2003 - 2005 ₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯ |
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(1)
Coseismic activation / quiescence triggered by a large earthquake and Coulomb
stress changes ₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯ |
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(2)
Relative quiescence in aftershock sequences and its mechanism ₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯ |
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(3) Seismicity
anomalies preceding large earthquakes and crustal stress changes ₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯ |
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(4)
Space-time ETAS modeling ₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯ |
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(5)
Modeling the interface between physical and stochastic process ₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯ |
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(6)
Simultaneous estimation of b-values
and detection rates of earthquakes for the application to aftershock probability
forecasting ₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯ |
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Published
papers 2003-2005 ₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯ |
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Refereed Journals ₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯ |
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Main Proceedings ₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯ |
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Future plans for the project ₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯ |
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(1) Examination of scenarios
for predicting asperity-slip based on the seismicity anomalies ₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯ |
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(2) Effective space-time
modeling of seismic activity and detection of seismicity anomalies ₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯ |
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(3) Predictive
space-time-magnitude characterization of foreshocks ₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯ |
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(4) Prediction and inversion
problem between seismicity changes and stress-changes ₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯ |
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(5) Bayesian Probability
assessments for Long-term prediction
₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯ |
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(6) Statistical modeling for
more effective use and quality improvements of datasets ₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯ |
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References ₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯₯ |
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Motivations behind this project
(1) Hypocenter
data
The
Hypocenter catalog of the Japan Meteorological Agency (JMA) is one of the most
valuable databases for earthquake prediction. This is because it contains
records of a large number of earthquakes dating back to 1925. The catalog
covers the whole of
(2) Other
geophysical datasets
There
are many precise geophysical records that are useful in discussing the
relationship with seismicity such as records of extensometers, tiltmeters,
volmetric strainmeters and the GPS. However, these records are usually affected
by various noises or ancillary geophysical signals caused by the earthtides,
and in particular, by meteorological factors such as barometric pressure,
precipitation, temperature and humidity. Therefore, it is important to model
the causal relationships and response functions of these effects in order to
calibrate the records for genuine quantities of interest. For example, the
computer program BAYTAP-G [Ishiguro et
al., 1984] used to implement the Bayesian deconvolution procedure for
removing tidal effects has been used with much frequency by many researchers in
seismology and geodesy in
(3) point-process
models
Point processes. A point-process is a
mathematical model of the stochastic occurrence of a series of events. The
modeling of point-processes became a powerful tool in the field of applied
statistics in the 1980's, for three reasons. Firstly, the concept of the
conditional intensity function provided us with an extensive free hand with
which to produce models describing the detailed interface between the physical
mechanism of occurrences and some stochastic factors. This is the predictive
occurrence rate function (roughly, the differential of the occurrence
conditional probability) of the present time, the occurrence times of the past
events and other relevant time series data such as magnitudes and other available
geophysical records. Use of this function also made available a general
effective simulation method using the thinning operation [Ogata, 1983]. Secondly, it became possible to write the likelihood
function directly in terms of the conditional intensity function. The third
reason was due to the availability of practical algorithms for optimizing
non-linear functions using a computer, enabling us to obtain the maximum
likelihood estimate (MLE), their error estimates, and the likelihood-ratio or
the AIC to examine the goodness-of-fit of models. Together with these
revolutionary bases, a diagnostic analysis of the model and data became
available with the time-transformation using the integral of the conditional
intensity function [Ogata, 1983,
1988; Ogata and Shimazaki, 1984; Ogata, 1999]. Benefiting from these, a
substantial number of applications became available, including the program
packages TIMSAC84 [Akaike et al.,
1985] and SASeis [Utsu and Ogata,
1997] in the IASPEI Software Library.
The ETAS model. The epidemic type aftershock
sequence (ETAS) model [Ogata, 1986,
1988, 1989] is one such model. It is generally accepted that each earthquake
changes the probability of successive earthquakes in a region, the size of
which scales with its magnitude, and by an amount that can be estimated using
the Gutenberg-Richter magnitude distribution and the Omori-Utsu law for the
rate of aftershocks, where aftershocks are allowed to be larger than the
mainshock. The ETAS model forms the basis of many current probabilistic
earthquake prediction schemes. Inherent in these models is the assumption that
the probability of a large earthquake is completely determined by the sum of
stresses transferred by prior earthquakes within a considered region. By a set
of parameter values the ETAS model is well adapted to various seismicity
patterns including the mainshock-aftershock type and swarm type.
Diagnostic analysis using the
ETAS model.
Since a sequence of aftershocks is triggered by complex mechanisms under
fractal random media, it is difficult to calculate the transferred stresses
within and near the rupture fault. That is, triggering mechanics within an
aftershock sequence are too complex for us to calculate the effect of stress
changes. Therefore, the statistical empirical laws of aftershocks are useful as
a practical representation of the outcome due to the complex interaction of the
self- or proximate triggering. On the other hand, the ETAS model is a
statistical model constructed based on the empirical laws of aftershocks.
Therefore, the model itself hardly describes the mechanism of affecting stress
changes behind the seismicity changes. Diagnostic analyses of the model can
reveal such new knowledge included in the data. That is to say, the activation
and quiescence relative to the model's prediction could suggest exogenous
stress-changes in the regions.
(4) Earthquake
/ Aftershock forecasting
Primary models for aftershock
forecasting. It has been about a decade
since aftershock probability forecasting [Reasenberg
and Jones, 1989] was implemented to inform the public in
Anomalous aftershock activity. Precursory seismic
quiescence as a predictor of large earthquakes has attracted much attention
amongst seismologists in the last several decades, ever since Inouye [1965] first proposed the
concept. This suggests that we need much more research into the relation
between the quiescence and subsequent earthquake activity in order to obtain an
effective prediction. We should also explain how quiescence can take place in a
much wider area than the rupture source [Inouye,
1965; Ogata, 1992]. Studying many
aftershock sequences should provide us with a better understanding of the
physical mechanism of the precursory utility. For predicting large aftershock, Matsu'ura [1986] noted the utility of
the quiescence in aftershock occurrences relative to the Omori-Utsu decaying
formula.
Using the ETAS model and on the basis
of the proposed procedure, 259 aftershock sequences of various threshold
magnitudes are investigated for the 76 main shocks of M6 class or over that
occurred in and around
Seismicity rate change and
Coulomb's failure stress change. We are concerned with the precise
prediction of time- and history-dependent occurrence rates of an earthquake
sequence, particularly, aftershock sequences, in order to test the hypothesis
that abrupt stress-change due to a seismic or an aseismic slip triggers a
seismicity-rate-change in the surrounding area. This is because stress changes
in a region are very frequently affected by nearby events, which trigger
further aftershock clusters. In principle, seismic activity should be enhanced
in the zones where an increment of Coulomb's failure stress (CFS) is positive,
and also activity should be reduced (seismic quiescence) in the stress-shadow
zones. For example, some retrospective case studies have shown the stress
shadow [e.g., Harris, 1998; Toda and Stein, 2002] due to large
earthquakes to coseismically inhibit the activity in some neighboring seismic
regions in
(5) Exploration
and modeling of the interface between physical and stochastic processes
External stress changes and
swarms. It is well known that
volcanic swarms and other swarms are affected by magma intrusion [Dieterich et al., 2000; Toda et al., 2002] and water migration [Matsu'ura and Karakama, 2005]. According
to the Coulomb failure criterion, the variation of both, stress and pore pressure,
can result in earthquake rupture. Aftershock sequences characterized by the
Omori-Utsu law are often assumed to be the consequence of varying stress,
whereas earthquake swarms are supposed to be triggered by fluid intrusions.
Statistical models for describing the relationship are desired. Also, there are
some papers reporting that occurrence rates of some swarms and aftershocks are
correlated to certain components of earth-tide's time series [e.g., Iwata, 2002]. It is desirable to
have models examining the causal relationship between mechanisms of earthquakes
and stress tensors of stresses due to earth-tide.
Inversion. On the other hand, it will
be informative to produce an image of the geophysical quantities in time and
space, by making an inversion of the parameters of the statistical models of
earthquake occurrences. Such examples include b-values of the G-R magnitude
frequency [Ogata et al. 1991 and
1993], and p-values of the Omori-Utsu model for the aftershock decay [Mogi, 1967]. More examples should also
be considered, making use of models such as the extended space-time ETAS model,
making use of a Bayesian framework. The geophysical quantities could include
the stress distribution and temperatures of the crust, and the friction
coefficients of the fault interface (asperities) etc.
Quiescence and activation
relative to the ETAS prediction and crustal stress changes. Seismic quiescence and
activation have attracted much attention amongst seismologists as the
precursors to a large earthquake. Of particular interest is that the
stress-changes transferred from a far-field rupture or silent slip can cause
seismic changes in a region. On the other hand, since a sequence of aftershocks
is triggered by complex mechanisms under heterogeneous fractal media, it is
difficult to precisely describe the transfer of stresses both within and near
to the field. In other words, triggering mechanics within an aftershock
sequence are too complex to calculate the effect of stress changes.
Nevertheless, we can use statistical empirical laws as a practical solution to
aftershock triggering. That is to say, fitting and extrapolating a suitable
statistical model for normal seismic activity in a situation without exogenous
stress changes provides us with an alternative method through which to see the
seismicity changes explicitly. Thus, our motivation is to show the possibility
that the diagnostic analysis based on fitting the ETAS model, and its
space-time extension, fitting to regional seismicity can be helpful in
detecting small exogenous stress changes. Indeed, these changes are so slight
that the geodetic records from the GPS network can barely recognize systematic
anomalies in the time series of displacement records.
(6) Space-time
point-process modeling
The
relative quiescence before great earthquakes is discussed in wide seismic
regions in Ogata [1992] for high
threshold magnitudes of more than M5. However, these are too high to discuss
intermediate strong earthquakes. The locations of earthquakes from hypocenter
catalogs are now accurate enough to discuss the spatial aspect of seismicity,
such as the clustering of aftershocks and seismicity gaps. Ogata [1998] considers several possible extensions of the ETAS
model to space-time data, based on classical empirical studies of aftershocks,
and also on a number of contrasting speculative hypotheses about the physical
nature of the space-time clustering. Their goodness-of-fit is compared by the
aid of the AIC for two data sets from tectonically distinctive areas in and
around
However, as the data size
increases, spatial heterogeneity of the seismic activity becomes conspicuous.
For example, shape of the anistropic clustering becomes more complex, differing
from place to place. Even cluster sizes are significantly different from one
another, especially between those in offshore and inland area [Utsu, 1969; Ogata, 2001].
Furthermore, according to the restricted trigger model [Ogata, 2001], secondary aftershocks of
large cluster sizes are located around the boundary of the main rupture zone of
the 1995
References
Akaike, H.,
Ozaki, T., Ishiguro, M., Ogata, Y., Kitagawa, G., Tamura, Y., Arahata, E.,
Katsura, K. and Tamura, R. (1985) Time Series and Control Program Package,
TIMSAC-84 (, Computer Science Monograph, No. 22/23, The Institute of
Statistical Mathematics,
Aki, K. (1965)
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Objectives of the project were as
follows:
(1) To
develop practical space-time models that are sufficiently close to the real
seismic activity. Specifically, the model must elaborate enough to spatially
adapt to various different clustering patterns. In order to represent various
seismicity patterns, we will adopt a hierarchical space-time point-process
model, in which the parameter values are dependent on the location of the
earthquakes.
(2) To
detect and evaluate anomalous features of general seismicity and aftershock
activity relative to the modeled rate by the ETAS model, to explore its
space-time features using statistical diagnostic methods and to make modeling
of seismicity anomalies.
(3) To
explore the relation between the seismicity-rate-change in a region and the
stress-change in the crust, which varies due to the fault mechanisms of
earthquakes.
(4) To
statistically model the relationship between the occurrence time series of
focal earthquakes in a region and the time series records of anomaly events, in
order to enhance the performance of probability forecasting.
(5) To
model the heterogeneity of various datasets which are affected by some
instrumental and geophysical factors, such as various noises, missing events or
values, and detection rate changes of earthquakes in time and space.
Work Plan 2003 – 2007
We
will undertake as many of the followings as early as possible:
(1) We
will apply the ETAS model to a number of sequences of earthquakes from various
regions over a recent period to examine any significant deviation of the
activity from the rate predicted by the model. We will explore matching such an
anomaly and a crustal stress-change due to a co-seismic and a pre-seismic slip
somewhere in order to examine whether such a seismic anomaly can be a sensitive
sensor of stress change.
(2) We
will particularly be concerned with the anomalously quiet aftershock activity
preceding a large aftershock.
(3) We will make use of fault mechanism data of
earthquakes to calculate the Coulomb-stress-change estimation transferred from a
pre-slip or a slow slip in order to discuss the significance of the causal
relation between stress change and seismicity anomalies.
(4) We will try to make a statistical point process
model to explain the causality between geodetic anomalies and seismicity anomalies
in the same field.
(5) We
will publish a software package to make programs available such as the
estimation and diagnostic procedure of the ETAS model for the seismologists,
after testing the stability of such programs.
(6) We will make a practical model
to enable real-time probability forecasting of aftershocks immediately after a
large earthquake (say, within 24hours), when the detection rate of aftershocks
is extremely low, due to contamination of arriving seismic waves. This is
urgent since the majority of large aftershocks are most likely to occur during
this period, and hence forecasting during this time is most critical for public
in the affected area.
(7) We
will develop methods of diagnostic analysis for space-time seismicity data by
introducing a space-time seismicity-ratio of real seismicity to the predicted
by the space-time ETAS model, and modeling it in Bayesian framework.
(8) We
will prepare a software package to publish the MLE and Bayesian procedure of
the space-time ETAS model, and test the stability of such programs with many
datasets.
Project Members:
Statistical
Seismology Research Group, Prediction and
Yosihiko
OGATA, Prof. of the Institute of Statistical Mathematics (ISM)
Shinji TODA, Visiting Prof. of the ISM and Geological Survey of Japan, AIST,
2005 -
Yasuaki MURATA, Geological Survey of Japan, AIST , Visiting Assoc. Prof. of the
ISM 2003 - 2004
Jiancang ZHUANG, Research Fellow upon JSPS program, 2001 - 2005
Kazuyoshi NANJO, Research Fellow upon JSPS program, 2003 -
Takaki IWATA, Research Fellow of ISM,
2005 -
Masatsugu WAKAURA, Graduate Student, The
Ushio TANAKA, Graduate Student, The
Akiko KUTSUNA, part-time assistant
Research Accomplishments 2003 – 2005
Principal works during 2003 - 2005
(1) Coseismic
activation / quiescence triggered by a large earthquake and Coulomb stress
changes
It
is clearly seen that after a large earthquake, many off-fault activities with
positive Coulomb stress increments are enhanced, while negative ones (stress
shadow) are inhibited, in regions that include many earthquakes of similar
fault-mechanisms detected down to small magnitudes. Such various examples are
shown in western
Seismicity changes in western
Significant
changes in seismicity (both quiescence and activation) took place during the
period of 1944-1946 in some regions in western
Seismicity-changes and
stress-changes triggered by the 2003 Tokachi earthquake [A21, A33]. Coseismic
activation and quiescence are conspicuous in the eastern inland region of
Hokkaido after the 2003 great earthquake of M8.0 in the space-time occurrence
of microearthquakes detected from 2001 through 2003 (depth
25km).
The ’CFF
for the receiver faults with N75oE right lateral strike-slip at the depth
of 10km and the Tokachi-Oki event's slip model takes positive and negative
values in the western and eastern part, respectively, which is corresponds well
to the regions of activation and quiescence in microseismicity. The exception
is that the very active spot in the western region suddenly stopped the
activity after the great event, but this is also well explained by the
different alignment of the receiver fault from the rest of the western part of
the microseismicity. We found
another triggered activation and quiescence in a complicated manner within the
3D volume down to 100km depth beneath the southern inland region of
Coseismic activation and
quiescence relative to the ETAS model [22, A19]. Fitting and extrapolating the
ETAS model for normal seismic activity in a situation without exogenous stress
changes provides us with an alternative method through which we can detect the
relative changes of seismicity sensitively. Thus, the diagnostic analysis based
on fitting the ETAS model is helpful in detecting small exogenous stress
changes. For example, shallow earthquakes (M >=1.5) in the Tohoku inland
region of largest ’CFF values (ranging +5~+50 millibars) due to the 2003 May 26
Miyagi-Ken-Oki earthquake of M7.1 is seen to be activated relative to the
predicted occurrence rate by the ETAS model. The foreshock activity during the
first event of M5.5 and the mainshock of M6.2 (the both occurred at 26 July
2003) was more active than the predicted rate by the ETAS fitted in the
preceding interval. But the aftershock activity the mainshock of M6.2 seems
similar to the predicted rate.
(2) Relative
quiescence in aftershock sequences and its mechanism
In
order to extract regional stress-changes transferred from the slip of a
far-field fault, we have to remove the effect of the complex, proximate
triggering mechanics occurring within aftershock clusters. As a practical
solution, the ETAS model is fitted to the sequence of events from the region in
order to precisely mimic the normal activity there. We are primarily concerned
with seismicity-rate-changes (enhancement and reduction) relative to the rate
predicted by the ETAS model, and explore matching them to the pattern of
Coulomb's stress-changes that occur due to a rupture or a suspected silent
slip. We have shown a number of such examples from recent seismic activities in
Aftershock activity of large
earthquakes in Southern California [2]. The Hector Mine aftershock activity
has been normal, relative to the decay predicted by the ETAS model during the
14 months of available data and no further large event has taken place in the
vicinity up until now. In contrast, although the aftershock sequence of the
1992 Landers earthquake (M=7.3), including the 1992 Big Bear earthquake (M=6.4)
and its aftershocks, fits very well to the ETAS up until about 6 months after
the mainshock, the activity showed clear lowering relative to the modeled rate
(relative quiescence) and the anomaly lasted nearly 7 years, leading up to the
Hector Mine earthquake (M=7.1) in 1999. Specifically, the relative quiescence
occurred only in the shallow aftershock activity, down to depths of 5 - 6 km. The
sequence of deeper events showed clear, normal aftershock activity that fitted
well to the ETAS throughout the whole period. We argue several physical
explanations for these results. Among them, we strongly suspect aseismic slips
within the Hector Mine rupture source that could inhibit the crustal relaxation
process within "shadow zones" of the Coulomb's failure stress
change. Furthermore, the aftershock
activity of the 1992 Joshua Tree earthquake (M=6.1) sharply lowered in the same
day of the mainshock, which can be explained by a similar scenario due to
aseismic slip.
Consecutive earthquakes in
Miyagi Prefecture and its offshore [22, A19]. Anomalous seismicity such as
quiescence and activation is defined by a systematic deviation of seismic
activity from the predicted rate by the ETAS model that represents the normal
occurrence-rate of earthquakes in a region indicating the empirical triggering
effect by the previous events. The model is fitted to a dataset of origin-times
and magnitudes of earthquakes or aftershocks during May-August 2003 in and
around northern
Anomalous aftershock activity
of the 2004 Niigata-Ken-Chuetsu earthquake of M6.8 [A30]. We are concerned with
the drastic shift of the depth distribution of aftershocks against time, around
0.5 days after the mainshock when we have no major aftershock. The cross-section
of ’CFF
diagram for the aftershocks of similar mechanisms to the mainshock's on the
plane of fault's strike direction of the mainshock (reverse faulting) against
depth shows positive and negative values in shallow and deep parts of the
aftershock volume, respectively, by the assumed precursory slip of the large
M6.1 event that occurred 3.7 days after the mainshock. The precursory slip can
be triggered by the mainshock rupture with a large positive ’CFF.
Relative quiescence reported
before the occurrence of the largest aftershock (M5.8) with likely scenarios of
precursory slips considered for the stress-shadow covering the aftershock area [30, A27, A35]. Monitoring of
aftershock sequences to detect lowering activity, relative to the modeled rate
(the relative quiescence), becomes realistic and practical in predicting the
enhancement of the likelihood of having a substantially large aftershock, or
even another earthquake of similar size to the mainshock or larger. A
significant relative quiescence in the aftershock sequence of the 2005 March
earthquake of M7.0 off the western coast of
(3) Seismicity
anomalies preceding large earthquakes and crustal stress changes
An
earthquake prediction scenario from the implication of the relative quiescence
can be based on the asperity hypothesis in the sense that precursory slip
around asperities applies more shear stress to the asperities which promotes
the rupture of the main fault. On the other hand, aseismic slips in a
particular region are not necessarily a precursor to the large event but may be
aseismic slips that are repeated in the same region with no subsequent large
events. Therefore, identification of an aseismic slip leading to the rupture of
an asperity remains a further difficult research theme in earthquake
prediction. At present, this issue should be considered in terms of
probabilistic prediction proactively making likely scenarios of precursory
slips.
Intermediate-term seismicity
anomalies preceding the rupture around the focal region of the 2004
Niigata-Ken-Chuetsu earthquake of M6.8 [A27, 29]. The ETAS model is applied to
four sequences of earthquakes (M>=2), which occurred from 1997 through to
October 2004 in four respective regions divided around the source of the 2004
Niigata-Ken Chuetsu earthquake. The four regions are divided North, East, South
and East around the source by the boundaries of positive and negative CFS
increments (i.e., the counters of neutral CFS increment) for the receiver
faults (10km depth) of dominating angles in this region. The actual cumulative
number of events deviates upward in region North and South, but downward in
East and West, from the predicted cumulative curve after the change-point,
consistently with the regions of the Coulomb increments. These show that
precursory slip may have taken place in the Chuetsu mainshock fault plane.
Synchronous seismicity changes
in and around the northern
Features of seismic activities
in and around Tohoku District, northern Japan, prior to the large interplate
earthquakes off the coast of Miyagi Prefecture [29, A20]. This paper is concerned with
the intermediate-term prediction of the forthcoming M7.4 ~ 8.2 earthquake on
the plate boundary, off the east coast of Miyagi Prefecture, northern Japan,
which has the highest occurrence probability among the long-term forecasted
events announced to the public. Seismicity and aftershocks in the regions of
stress-shadow show significantly lower activity than the rate predicted by the
ETAS model (the relative quiescence) during some years preceding each of the
previous ruptures in 1936 and 1978, whereas the seismicity is normal or even
activated in the regions of neutral or increasing Coulomb failure stress (CFS),
which leads to the scenario based on the likely precursory slip within or near
to the source.
Assuming such a scenario, a number
of sequences of earthquakes or aftershocks during 1979-2004 from various
regions in northern
Anomalies in the aftershock
sequences of the 2003 Tokachi-Oki earthquake of M8.0 and the 2004 Kushiro-Oki
earthquake of M7.1, and seismicity changes in the eastern 
2.5)
of the 2003 Tokachi-Oki earthquake of M8.0 become quiet relative to the ETAS
five months after the mainshock. Latitude coordinates of the aftershock
epicenters against the transformed time by the ETAS model show that the
quiescence took place in the southern part of the aftershock area whereas the
northern part was normal. This is explained by the shadowing of the DCFS assuming slips in or near the source
of the 2004 Kushiro-Oki earthquake of M7.1. At the same time, this slip should
affect contrasting DCFS pattern in eastern
Seismicity in and around the
Kyushu District, preceding the 2005 earthquake of M7.0 at the western offshore
region of Fukuoka Prefecture [A34]. The ETAS model is applied to the sequences of events
with M1.5
during the 10 year period from1995 to March 23, 2005 in the 10 regions in which
DCFS values are calculated for the most
frequent angles of receiver faults for the respective depths, assuming stress
transfer by the rupture on the fault model of the M7.0 earthquake. The activity
is normal or activated relative to the ETAS prediction in the regions where DCFS values are positive, and the relative
quiescence in the stress-shadow regions. This may support the hypothesis of
precursory slips within the fault of the M7.0 earthquake.
On distributions of focal
mechanisms
[12, A11, A22, A25, A29]. We see a change of the normalized frequency
distribution of DCFS values before and after
1995, calculated at the hypocenter of all earthquakes listed in the JMA earthquake
mechanisms catalog in a wide area of northern
Next, we discussed the likelihood
of three rupture models of the 2005 earthquake of M7.4 off the coast of the
(4) Space-time
ETAS modeling
Stochastc
clustering / declustering by the space-time ETAS model
[13, 25, 33, A17, A18, A27]. On the basis of the
space-time ETAS model and the thinning procedure, this paper gives the method
of how to classify the earthquakes in a given catalogue into different clusters
stochastically. The key points of this method are the probabilities of one
event being triggered by another previous event and of it being a background
event. Making use of these probabilities, we can reconstruct the functions
associated with the characteristics of earthquake clusters to test a number of
important hypotheses about the earthquake clustering phenomena.
We applied this reconstruction method to the shallow seismic data in
Hierarchical
Space-Time Model for Regional Seismicity [1, A2,
A5, A6, A9]. A space-time point-process model is specified in which earthquake
intensity is modelled as a function of previous earthquakes' occurrence times,
locations, and magnitudes. Specific forms of the function of locations and times
are based on the established empirical laws, such as the modified Omori formula
and the Utsu-Seki scaling law of aftershock area against magnitude, but their
parameter values are known to be different from place to place. Thus the
parameters are further considered to be functions of spatial locations (but not
time) represented by linear interpolation over a tessellation based on observed
locations of earthquakes. Using the smooth representation for each parameter
function in the model, a penalized log-likelihood method is used for the
fitting, where the optimal weights of the penalties are objectively tuned by an
empirical Bayesian method. Having done that, our final goal is to detect the
temporal deviation of the actual seismicity rate from that of the modeled
occurrence rate. For this procedure we estimate the space-time residual
function represented by linear interpolation over a 3-dimensional tessellation
based on observed times and locations of earthquakes, carrying out the similar
penalized log-likelihood method. According to the estimated residual function,
there are a number of zones where temporal deviation from the fitted model,
with quiet periods, occurred before large earthquakes.
Hierarchical
Space-Time Model for characterizing regional seismicity and anomaly detection
[11, A2, A5, A6, A9]. The regional earthquake occurrence rate is modeled as a
function of previous activity for which the specific form is based on empirical
laws, such as the modified Omori formula and the Utsu-Seki scaling law of
aftershock area against magnitude. Its parameters, including the p-value of the
aftershock decay rate, can vary from place to place, showing some geophysical
feature appearing correlated with the crustal temperature. This model is used
to visualize features of the regional seismic activities in and around
Furthermore, this space-time model enables us to magnify anomalous
periods and regions where the actual occurrence rates deviate systematically
from the modeled one. Thus, the activation and quiescence relative to the
model's prediction could provide sensitive detection of stress-changes in the
regions. We are concerned with relative activation and lowering of the seismicity
to explore the regions matching the pattern of Coulomb's stress changes due to
a rupture or silent slip elsewhere. For example, such anomalies as those seen
in the seismic activity in most central
rupture and the interplate aseismic slip during
2001 beneath the western Tokai region, respectively.
(5) Modeling
the interface between physical and stochastic process
Detecting
fluid signals in seismicity data through statistical earthquake modeling
[14]. According to the Coulomb failure criterion, the variation of both stress
and pore pressure can result in earthquake rupture. Aftershock sequences
characterized by the Omori-Utsu law are often assumed to be the consequence of
varying stress, whereas earthquake swarms are supposed to be triggered by fluid
intrusions. The role of stress triggering can be analyzed by modeling the 3D
elastic stress changes in the crust. However, fluid flows initiating seismicity
cannot be identified without dealing with both pore pressure variations and
earthquake connected stress field changes resulting in complex seismicity
patterns.
We show that the ETAS model is an appropriate tool to extract the
primary fluid signal from such complex seismicity patterns. We analyze a large
earthquake swarm that occurred in the year 2000 in Vogtland/NW-
Model simulations are performed in which earthquakes are triggered by
fluid intrusion as well as coseismic and postseismic stress changes on a fault
plane embedded in a 3D elastic half-space. They reproduce the observed swarm
characteristics including the temporal power-law increase of the seismic moment
release. Analyzing these simulations, we find that the proposed deconvolution
procedure is able to reveal the underlying pore pressure variations. This model
may be applied to the swarm owing to magma intrusion [e.g., A7].
Analysis
of observations on the ultra-low frequency electric field in the Beijing Region
[24]. This paper presents a preliminary analysis of observations on ultra-low
frequency ground electric signals from stations operated by the China
Seismological Bureau over the last 20 years. The data analyzed consists of
estimates of the total strengths (cumulated amplitudes) of the electric signals
during 24-hour periods. The thresholds are set low enough so that on most days
a zero observation is returned. Non-zero observations are related to electric
and magnetic storms, occasional man-made electrical effects, and, apparently,
some pre-, co-, or postseismic signals.
To investigate the extent that the electric signals can be considered as
preseismic in character, the electric signals from each of five stations are
jointly analyzed with the catalogue of local earthquakes within circular
regions around the selected stations. A version of Ogata's Lin-Lin algorithm is
used to estimate and test the existence of a pre-seismic signal. This model
allows the effect of the electric signals to be tested, even after allowing for
the effects of earthquake clustering. It is found that, although the largest
single effect influencing earthquake occurrence is the clustering tendency,
there remains a significant preseismic component from the electrical signals.
Additional tests show that the apparent effect is not postseismic in character,
and persists even under variations of the model and the time periods used in
the analysis. Samples of the data are presented and the full data sets have
been made available on local websites.
Microseismicity
and Earthtide [15, A1]. This paper analyzes the
microseismicity in the Tanba region during the two year period following the
1995
(6) Simultaneous
estimation of b-values and detection rates of earthquakes for the application
to aftershock probability forecasting [A31, A32].
It
is known that the detection rate of aftershocks is extremely low during the
period immediately following a large earthquake due to the contamination of
arriving seismic waves. This has resulted in considerable difficulty in
obtaining an estimate of the empirical laws of aftershock decay and the
magnitude frequency immediately after the main shock. This paper presents an
estimation method for predicting the underlying occurrence rate of aftershocks
of any magnitude range, based on the magnitude frequency model that combines
Gutenberg-Richter's law with the detection rate function. This procedure
enables us to announce real-time probability forecasting of aftershocks
immediately after the mainshock, when the majority of large aftershocks is
likely to occur.
Published papers 2003 - 2005
Refereed Journals:
2003:
[1] Ogata, Y.,
Katsura, K. and Tanemura, M. (2003) Modelling of heterogeneous space-time occurrences
of earthquakes and its residual analysis, Applied
Statistics (J. Roy. Stat. Soc. Ser. C.),
Vol. 52, Part 4, pp. 499-509 (2003).
[2] Ogata, Y., Jones, L. and Toda, S. (2003) When and
where the aftershock activity was depressed: Contrasting decay patterns of the
proximate large earthquakes in southern
[3] Ogata, Y. (2003) Examples of statistical models and
methods applied to seismology and related earth physics, International
Handbook of Earthquake and Engineering Seismology, International
Association of Seismology and Physics of Earth's Interior, Vol. 81B,
HandbookCD#2, Chapter 82.
[4] Toda, S. and Stein, R.S. (2003) Toggling
of seismicity by the 1997
[5] Vere-Jones, D. and Ogata, Y. (2003) Statistical
principles for seismologists, International Handbook of Earthquake and Engineering
Seismology, International Association of Seismology and Physics of Earth's
Interior, Vol. 81B, pp. 1573-1586.
2004:
[6] Cho,
[7] Iwata, T., and Nakanishi, I. (2004) Hastening of occurrences of
earthquakes due to dynamic triggering: The observation at Matsushiro, central
[8] Nanjo, K., Nagahama, H. and Yodogawa, E.. (2004) Symmetry in the
Self-organized Criticality, The Journal of the International Society for the
Interdisciplinary Study of Symmetry (ISIS-Symmetry) Symmetry: Art and Science
2004 (Editors D. Nagy and G. Lugosi) ISIS-Symmetry,
[9] Nanjo, K. and Nagahama H. (2004) Fractal Properties of Spatial
Distributions of Aftershocks and Active Faults, Chaos, Solitons and Fractals,
19, pp. 387-397, doi: 10.1016/S0960-0779(03)00051-1.
[10] Nanjo,
K. and
Nagahama, H. (2004) Discussions on Fractals, Aftershocks and Active Faults: Diffusion
and Seismo-electromagnetism, The Arabian Journal for Science and Engineering,
2004, 29, 2C, pp. 147-167.
[11] Ogata, Y. (2004) Space-time model for regional seismicity and detection of crustal stress changes, J. Geophys. Res., Vol. 109, No. B3, B03308, doi:10.1029/2003JB002621.
[12] Ogata, Y. (2004) Seismicity quiescence and activation in
western
[13] Zhuang, J., Ogata, Y. and Vere-Jones, D. (2004) Analyzing earthquake clustering features by using stochastic reconstruction Journal of Geophysical Research, 109, B5, B05301, doi:10.1029/2003JB002879.
2005:
[14] Hainzl, S. and Ogata, Y.
(2005) Detecting fluid signals in seismicity data through statistical earthquake
modeling, J. Geophys. Res., Vol.110,
No.B5, B05S07, doi:10.1029/2004JB003247 (2005).
[15] Iwata, T. and Young, P. (2005) Tidal stress/strain and the
b-value of acoustic emissions at the
Underground Research Laboratory, Canada, Pure and Applied Geophysics, 162, pp. 1291-1308.
[16] Iwata,
T., M. Imoto, and S. Horiuchi (2005) Probabilistic
estimation of earthquake growth to a catastorophic one, Geophys. Res. Let., 32.
L19307, 10.1029/2005GL023928.
[17] Nanjo,
K.Z., Nagahama, H. and
Yodogawa, E. (2005) Symmetropy of fault patterns: Quantitative measurement of
anisotropy and entropic heterogeneity, Mathematical
Geology, 37, 3, pp. 277-293,
doi: 10.1007/s11004-005-1559-z.
[18] Nanjo, K.Z., Turcotte, D.L. and
Shcherbakov, R. (2005) A model of damage mechanics for the deformation of the
continental crust, J. Geophys. Res., 110, B7, B07403, DOI:
10.1029/2004JB003438.
[19] Nanjo, K.Z. and Turcotte, D.L. (2005) Damage
and rheology in a fiber-bundle model, Geophys.
J. Int., 2005, 162, pp. 859-866, doi:10.1111/j.1365-246X.2005.02683.x.
[20] Holliday, J.R., Nanjo, K.Z., Tiampo, K.F., Rundle, J.B.
and Turcotte, D.L. (2005) Earthquake forecasting and its verification, Nonlinear Processes in Geophysics, 12, pp. 965-977, doi:
1607-7946/npg/2005-12-965.
[21] Ogata, Y. (2005)
Synchronous seismicity changes in and around the
northern
[22] Ogata, Y. (2005) Detection of
anomalous seismicity as a stress change sensor, J. Geophys. Res., Vol.110, No.B5, B05S06, doi:10.1029/2004JB003245.
[23] Toda, S., Stein, R.S., Richards-Dinger, K. and Bozkurt,
S. (2005) Forecasting the evolution of seismicity in
southern
[24] Zhuang, J., Vere-Jones, D.,
Guan, H., Ogata, Y. and Ma, Li (2005) Preliminary analysis of
observations on the ultra-low frequency electric field in the Beijing region, Pure
and Applied Geophysics, 162, pp.
1367-1396.
[25] Zhuang, J. Chang, C., Ogata, Y. Chen, Y. (2005) A study on the
background and clustering seismicity in the Taiwan region by using point
process models, J. Geophys. Res., 110, B5, B05S18, doi:10.1029/ 2004JB003157.
In press or accepted:
[26] Nanjo, K.Z., Nagahama, H. and Yodogawa, E., Symmetropy of earthquake patterns:
asymmetry and rotation in a disordered seismic source, Acta Geophysica Polonica, in press, Volume 54.
[27] Nanjo, K.Z., Rundle, J.B., Holliday, J.R. and Turcotte, D.L., Pattern informatics and its
application for optimal forecasting of large earthquakes in
[28] Chen, C.C., Rundle, J.B., Holliday, J.R., Nanjo, K.Z., Turcotte, D.L., Li, S.C. and
Tiampo, K.F., The 1999 Chi-Chi, Taiwan, earthquake as a typical example of
seismic activation and quiescence, Geophys.
Res. Let., 2005 accepted.
[29] Ogata, Y., Seismicity anomaly scenario prior to the major recurrent earthquakes off the east coast of Miyagi Prefecture, northern Japan, and its implication for the intermediate-term prediction, Special Issue on Dynamics of Seismicity Patterns and Earthquake Triggering, eds. S. Hainzl, G. Zoler and I. Main, Tectonophysics, in press.
[30] Ogata, Y., Anomaly monitoring
of aftershock sequence by a reference model: A case study of the 2005
earthquake of M7.0 at the western
[31] Ogata, Y. and Zhuang, J., Space-time ETAS models and an improved extension, Special Issue on Critical Point Theory and Space-Time Pattern Formation in Precursory Seismicity, eds. K. Tiampo and M. Anghel, Tectonophysics, in press.
[32] Toda, S. and Matsumura, S., Spatio-temporal stress states estimated from seismicity rate changes in the Tokai region, central Japan, Tectonophysics, in press.
[33] Zhuang J., Ogata Y. and Vere-Jones D., Diagnostic analysis of space-time branching processes for earthquakes. Chapter 15 of Case Studies in Spatial Point Process Models, Eds. Baddeley A., Gregori P., Mateu J., Stoica R. and Stoyan D. Springer-Verlag, New York, in press.
Main
Proceedings:
2003:
[A1] Iwata,
T. and Katao, H.
(2003) Analysis of
a correlation between the phase of the moon and the occurrences of
microearthquakes in the Tanba plateau through the point-process modeling, Programme and Abstracts of the 2003, Fall
Meeting of the Seismol. Soc.
[A2] Ogata,
Y. (2003) A practival space-time model for regional seismicity (invited), EGS-AGU-EUG Joint Assembly,Nice,
France, Geophysical Research
Abstract , Volume 5, 2003, CD-ROM,
ISSN: 1029-7006
[A3] Ogata,
Y. (2003) Sesimicity-change-analysis by a space-time point-process model
(invited) The 3rd Statistical Seismology Workshop,
[A4] Ogata,
Y. (2003) Seismicity quiescence and activation in western
[A5] Ogata,
Y. (2003) Seismicity changes in western
[A6] Ogata, Y. (2003) A
space-time model for regional seismicity
and detection of seismicity changes (in Japanese), Chikyu Monthly, 25, 10, pp. 783-787.
[A7] Toda, S. and Stein, R.S. (2003) Earthquake triggering by volcano-tectonic events: An example
from the 2000 Izu Islands swarm (invited talk), XXIII Ceneral Assembly of the
International Union of Geodesy and Geophysics, 2003.
[A8] Toda, S.
(2003) A Fresh Look at the Triggering of Earthquake Pairs, Such
as the Landers-Big Bear, Landers-Hector Mine, Izmit-Duzce, and Nenana-Denali,
and March-May 1997 Kagoshima Events (invited talk), American Geophysical Union 2004 fall meeting.
2004:
[A9] Ogata, Y. (2004) The 6th World Congress of the Bernoulli Society for Mathematical Statistics and Probability, and 67th Annual Meeting of the Institute of Mathematical Statistics, gSpace-time model for regional seismicity and detection of crustal stress changesh, July 25-29, 2004, Barcelona, Spain, (invited lecture)
[A10] Ogata,
Y. (2004) Statistical models of point processes and prediction and
discovery in seismic activity (in Japanese), Spring Meeting of the Mathematical
Society of Japan,
[A11] Ogata,
Y. (2004) Static triggering and statistical modeling (in
Japanese), The 156-th Meeting of
Coordinating Committee for Earthquake Prediction , Geographical Survey
Institute, Kudan, Tokyo, February 16, 2004, Japan (topics invited lecture)
[A12] Ogata,
Y. (2004) Synchronous seismicity changes in and around the
northern
[A13] Ogata,
Y. (2004) Stress changes, seismicity changes and statistical models,
Workshop on Seismic Activity and Probabilities of Major Earthquakes in the
Kanto and Tokai Area , Central Japan, Wadati Memorial Hall, Institute for Earth
Science and Disaster Prevention, Tsukuba, Japan (invited presentation), http://kt-jisin.bosai.go.jp/WS/Program/index.html,
(invited talk)
[A14] Nanjo, K.Z., Rundle, J.B. and Holliday, J.R.. (2004) Pattern Informatics and Its Application to Forecasting Large Earthquakes in Japan, Abstract for AGU 2004 Fall Meeting, Eos Trans. AGU, 85(47), Fall Meet. Suppl., Abstract NG22A-07 (invited talk).
[A15] Toda, S. (2004) Recent progress in earthquake triggering study and possible applications to earthquake prediction (in Japanese), The 156-th Meeting of Coordinating Committee for Earthquake Prediction , Geographical Survey Institute, Kudan, Tokyo, February 16, 2004, Japan (topics invited lecture).
[A16] Toda, S., and Matsumura, S. (2004) Spato-temporal stress
states estimated from seismicity rate changes in the Tokai region, central
Japan (invited talk), American Geophysical Union 2004 fall meeting.
[A17] Zhuang, J., Ogata, Y. and Vere-Jones, D. (2004) Diagnostic analyses of space-time branching
processes for earthquakes, Spatial Point Process Modeling and its Applications,
Benicassim, Castellon, Spain, Spatial Point Process Modelling and Its
Applications, Col-Lecco Treballis D'Infomatica/Tecnologia, Num. 20, ISBN
84-8021-475-9 Publication de la Universitat Jaume-I, Castello de la Plana,
Spain, pp. 273-292.
[A18] Zhuang, J., Ogata, Y. and Vere-Jones, D. (2004) Visualizing goodness-of-fit of point-process
models for earthquake clusters., Analysis of Natural and Social
Phenomena: Data Science and System Reduction; an international workshop of the
21st Century COE program at Keio University, http://coe.math.keio.ac.jp/english/event/cherry_bud/index.html, (invited talk).
[A19] Ogata, Y. (2004) Quiescence of the 2003 foreshock/aftershock activities in and
off the coast of Miyagi Prefecture, northern Japan, and their correlation to
the triggered stress-changes (in Japanese), Report of the Coordinating
Committee for Earthquake Prediction, 71,
pp. 260-267, Geographical Survey Institute of Japan.
[A20] Ogata, Y. (2004) Statistical analysis of seismic activities in and around
Tohoku District, northern Japan, prior to the large interplate earthquakes off
the coast of
[A21] Ogata, Y. (2004) Seismicity changes and stress
changes in and around the northern
[A22] Ogata, Y. (2004) Static triggering and statistical modeling (in Japanese),
Report of the Coordinating Committee for
Earthquake Prediction, Vol. 72, pp. 631-637, Geographical Survey Institute
of Japan.
[A23] Toda, S. (2004) Recent progress in
earthquake triggering study and possible applications to earthquake prediction
(in Japanese), Report of the Coordinating Committee for Earthquake
Prediction, 72, pp.
624-626, Geographical Survey Institute of Japan.
[A24] Toda, S. (2004) Seismicity changes
in inland activity before and after the 2003 Miyagi-Ken-Oki earthquake and its
implications (in Japanese), Chikyu Monthly, 27, 1, 56-61.
[A25] Ogata, Y. (2004) On changes of statistical distribution of focal
mechanisms of events prior to the main ruptures, Programme
and Abstracts of the 2005 Fall Meeting of
the Seismol. Soc.
2005:
[A26] Murata, Y. and Ogata, Y. (2005) Surficial density
estimation from gravity data using Delaunay triangular network, Joint meeting for
Earth and Planetary Science, J031-004, Makuhari, Chiba Prefecture, Japan, May
2005.
[A27] Ogata, Y.(2005) Seismicity anomalies
measured by the ETAS model and stress changes (solicited), The General Assembly
2005 of the European Geosciences Union (EGU), , April 24-29, 2005, the Austria
Center Vienna (ACV), Vienna, Austria (invited lecture).
[A28] Ogata, Y. (2005) Seismicity changes in western
[A29] Ogata, Y. (2005) On the aftershock activity of the 2004 earthquake of M7.4
at the southeast off the coast of the Kii Peninsula, and constraints on the
fault rupture models by the mechanisms and space-time pattern of the
aftershocks (in Japanese), Report of the Coordinating Committee for Earthquake
Prediction, 73, pp. 495-498
Geographical Survey Institute of Japan.
[A30] Ogata, Y. (2005) On an
anomalous aftershock activity of the
2004 Niigata-Ken-Chuetsu earthquake of M6.8, and intermediate-term seismicity
anomalies preceding the rupture around the focal region (in Japanese), Report
of the Coordinating Committee for Earthquake Prediction, 73, pp. 327-331, Geographical Survey Institute
of Japan.
[A31] Ogata, Y. (2005) Simultaneous estimation of b-values and detection rates of
earthquakes for the application to aftershock probability forecasting (in
Japanese), Report of the Coordinating Committee for Earthquake Prediction,
Vol. 73, pp. 666-669, Geographical Survey Institute of Japan.
[A32] Ogata, Y. (2005) Toward urgent forecasting of aftershock hazard: Simultaneous estimation of b-value of the Gutenberg-Richterfs law of the magnitude frequency and changing detection rates of aftershocks immediately after the mainshock, preprint.
[A33] Ogata, Y. (2005)
Anomalies in the aftershock sequences of the 2003 Tokachi-Oki earthquake of
M8.0 and the 2004 Kushiro-Oki earthquake of M7.1 and seismicity changes in the
eastern Hokkaido inland (in Japanese), Report of the Coordinating Committee
for Earthquake Prediction, 74,
pp. 83-88, Geographical Survey Institute of Japan.
[A34] Ogata, Y. (2005)
Seismicity changes in and around Kyushu District before the 2005 earthquake of
M7.0 in the western offshore of Fukuoka Prefecture (in Japanese), Report of
the Coordinating Committee for Earthquake Prediction, 74, pp. 523-528, Geographical Survey Institute of Japan.
[A35] Ogata, Y. (2005)
Relative quiescence reported before the occurrence of the largest aftershock
(M5.8) in the aftershocks of the 2005 earthquake of M7.0 at the western
Fukuoka, Kyushu, and possible scenarios of precursory slips considered for the
stress-shadow covering the aftershock area (in Japanese), Report of the
Coordinating Committee for Earthquake Prediction, 74, pp. 529-535, Geographical Survey Institute of Japan.
[A36] Ogata, Y. (2005) Anomalies in the aftershock sequences of the 2003 Tokachi-Oki earthquake of M8.0
and the 2004 Kushiro-Oki earthquake of M7.1 and seismicity changes in the
eastern Hokkaido inland, Programme and
Abstracts of the 2005 Fall Meeting of
the Seismol. Soc.
[A37] Toda, S.
(2005) Style of stress accumulation and release in northern Honshu
Future plan for the project
(1) Examination
of scenarios for predicting asperity-slip based on the seismicity anomalies
Anomaly
monitoring of aftershock sequences to detect lowering activity, relative to the
modelled rate (the relative quiescence), is now becoming realistic and
practical in predicting the enhancement of the likelihood of having a
significantly large aftershock, or even another earthquake of similar size or
larger occurring. In order to predict the location of a large aftershock or
another proximate large earthquake, we have to assume that a significant slip
may have occurred within and near to the source of the suspected earthquake due
to the acceleration of quasi-static (slow) slips on the fault as the time of
rupture of the major asperity approached. This is indicated, for example, by
the analysis of small repeating earthquake data. Thus, we should look carefully
at the activity in the stress-shadow, transferred from the slip. Such scenarios
for the prediction should be useful for examining and explaining any such
anomalous features.
In fact, given an anomaly of seismicity
rate change, the difficulty lies in identifying the slip location and its
imminence to a major rupture; most of them are unknown so far as no other data
or constraints are available. For probable predictions, Ogata [2005c] explored and reported several scenarios of stress
transfers from some thinkable slips, such as that they could have been
triggered by the M7.0 rupture at 20th March 2005 off western Fukuoka city and
moreover that the stress-shadows due to the slips should, in turn, have covered
the majority of the aftershock region. These include a conjugate fault of the
main fault rupture and several known active faults near the rupture fault.
However, the largest aftershock that occurred two weeks later was not included
in the suspected scenarios. The only exception was the predicted unlikely slip
within the Kego Fault that runs through the urban area in the city of
(2) Effective
space-time modeling of seismic activity and the detection of seismicity
anomalies
In
any application of the (hierarchical) space-time ETAS model, the data has to be
homogeneous in space and time. The threshold magnitude of completely detected
earthquakes throughout a long period and wide region is high, and the number of
earthquakes above such a threshold magnitude is very limited compared to the
number of listed earthquakes in a catalog. This is because the detection rate
of earthquakes for each magnitude is dependent on time and location.
Especially, the detection rate of aftershocks is extremely low during the
period immediately following the main shock, due to contamination of arriving
seismic waves.
For an estimation of the detection
rate in time and space, we propose utilizing the statistical model introduced
by Ogata and Katsura [1993] for the
simultaneous estimation of the b-values
of Gutenberg-Richter law together with the detection-rate (probability) of
earthquakes of each magnitude-band from the provided data of all detected
events, where both parameters are allowed to change in time. Thus, by using all
the detected earthquakes in a given period and area, we can estimate the
underlying ETAS rate of both the detected and undetected events and their
b-value changes, taking the time-varying missing rates of events into account.
It is our hope that it will become possible to give details of seismicity
patterns such as aftershock productivity parameters to delineate asperities [Ogata, 2005a] over the period and region
of the relative quiescence as given in Ogata
et al. [2003].
As a primary step toward achieving
this objective, Ogata [2005b]
presents an estimation method for predicting underlying occurrence rate of
aftershocks of any magnitude range. This procedure enables real-time
probability forecasting of aftershocks immediately after the mainshock, when
the majority of large aftershocks is likely to occur and when the forecasting
is most critical for public in the affected area.
(3) Predictive
space-time-magnitude characterization of foreshocks
Descrimination of foreshocks
and clustering / declustering algorithms as a short-term prediction. Discrimination of foreshock
sequences from other clustering activity is an important problem in short term
earthquake prediction. When sequential earthquake activity starts somewhere, it
can be a swarm, a foreshock sequence, or simply a mainshock-aftershock
sequence. Therefore, it is very desirable to know whether the activity is a
precursor to a forthcoming significantly larger earthquake or not. Ogata et al. [1995, 1996 and 1999] and [Ogata, 1999b] investigated data sets of
earthquake clusters to discriminate features of foreshocks from earthquakes of
other cluster types in a statistical senseCand found several features of some
predictive value, including the fact that foreshocks were more closely-spaced
in time than either swarms or aftershocks, the fact that foreshocks were closer
together in space than other types of events, and that foreshocks' sizes were
more likely to increase chronologically than the other types. By modeling such
discriminating features they developed probability forecasts of an earthquake
cluster being of foreshock type.
However the primary difficulty of
this procedure is to find a suitable declustering algorithm for real-time
forecasting of probability. There are two contrasting typical clustering
algorithms, that is, the magnitude-based clustering (MBC) and the
single-link-clustering (SLC) ones. The MBC based forecast performs very well,
but a MBC cluster cannot formed until the occurrence of the main shock. The SLC
algorithm is better for the real-time recognition of a cluster, but does not
perform objectively. Recently, based on the space-time ETAS model, Zhuang et al. [2002, 2005] proposed a
stochastic clustering algorithm, which appears quite useful in such a
forecasting. Because of its stochastic nature, a Baysian predictive procedure
will be useful.
(4) Prediction
and inversion problem between seismicity changes and stress-changes
It
is becoming important to study how to make predictions and how to solve inverse
problems based on the quantitative relationships between seismicity rate changes (due to the ETAS) and stress-changes. In
particular, we are concerned with the theory of rate/state-dependent friction
and its application to the seismicity-rate-change equation of Dieterich [Dieterich, 1994; Dieterich et al., 2000; Toda
and Stein, 2003].
(5) Bayesian
Probability assessments for Long-term prediction
Inference of hazard of a fault
rupture and its uncertainty from data of a small number of events, possibly
with uncertain occurrence times. Conventionally, a probability of the
next rupture during a future period is calculated by the predictive hazard
function into which we plug the MLE values of BPT model [Matthews et al., 2002] estimated by the historical data of
occurrence times. However, when the number of events in the data is small, the
predictive hazard function based on the MLE usually causes a serious bias of
hazard rates. Therefore, in order to see the uncertainty of estimated hazard
functions, we use the Bayesian inference introducing a set of appropriate prior
distributions. Furthermore, if a record of the slip-sizes of the events is
available, Ogata [2001, 2002]
proposes an extended renewal process for a stochastic version of the
time-predictable model of Shimazaki and
Nakata [1980] by assuming the same distribution of the ratio of the time
interval of the successive pair of events to the slip size of the first event
of the pair. Thus, we can estimate more effectively not only the hazard
function of the next event but also its uncertainty based on the occurrence
time data of the events associated with the records of corresponding slip
sizes.
When paleoearthquake data is
analyzed, our further concern is the raw data in which occurrence times of
events themselves are uncertain and given by confidence intervals or some
chronological likelihood function [e.g., Sieh
et al., 1989] inferred from geological evidences based on trench studies.
For such records, we consider another Bayesian inference in which each
uncertainty of occurrence time is interpreted as a prior distribution
associated with the likelihood of a renewal process model [Ogata, 1999]. Integration of the posterior function with respect to
the uncertain occurrence times and also the parameters of the renewal process
model is implemented in order to compare the goodness-of-fit of competing renewal
processes (e.g., log-Normal, Weibull and BPT models). Thus, the corresponding
marginal posteriors of the model provide both estimates of distributions of the
uncertain occurrence times and also the predictive hazard rates associated with
the selected renewal process model. Particularly, in the case where occurrence
time of the last event is uncertain, a natural assessment of current and future
hazard of the forthcoming rupture can be provided.
(6) Statistical
modeling for more effective use and quality improvements of datasets
There
are many precise measurements such as geodetic extensometers, tiltmeters,
volmetric strainmeters, GPS and so on. However, these records are always
affected by some noises and other signals of various kinds caused by the motions
of the sun, moon, and particularly meteorological factors such as balometric
pressure, precipitation, temperature and humidity. Therefore, it is important
to model the causality and response functions of these effects in order to know
the genuine records of interest. Special care should be put to the GPS time
series data to detect geodetic anomalies sensitively, since this dataset is now
playing an important role similar to the earthquake catalog in the sense that
the stations are very densely located throughout
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Earthquake Prediction, 73, pp.
666-669.
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