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Statistical Seismology Seminars F
Updated on
29 October 2024 NEW! The
99th DateF@31 October 2024@@@TimeF@13:30 – 15:30 LocationF@4F Lounge, Institute of Statistical Mathematics
& Online, hybrid -1 SpeakerF@Dr.
Hsieh, Ming-Che iEarthquake
Disaster & Risk Evaluation and Management Center (E-DREaM),
National Central University, Taoyuan, Taiwan EAssociate
Research Fellow /
Visiting Researcher of ISMj TitleF@Toward Real-Time
Ground-Shaking-Intensity Forecasting Using ETAS and GMM: Insights from the
Analysis of Recent Large Earthquake Sequences in Taiwan, and Its Potential
Applications AbstractF@ Earthquake
forecasting, combined with precise ground-shaking estimations, plays a
pivotal role in safeguarding public safety, fortifying infrastructure, and
bolstering the preparedness of emergency services. This study introduces a
comprehensive workflow that integrates the epidemic-type aftershock sequence
(ETAS) model with a pre-selected ground-motion model (GMM), facilitating
accurate short-term forecasting of ground-shaking intensity, which is crucial
for effective earthquake warning. At first, an analysis was conducted on an
earthquake catalog spanning from 1994 to 2022 to optimize the ETAS
parameters. The dataset used in this analysis allowed for the further
calculation of total, background, and clustering seismicity rates, which are
crucial for understanding spatiotemporal earthquake occurrence. Subsequently,
short-term earthquake activity simulations were performed using these
update-to-date seismicity rates to generate synthetic catalogs. The
ground-shaking impact on the target sites from each synthetic catalog was
assessed by determining the maximum intensity using a selected GMM. This
simulation process was repeated to enhance the reliability of the forecasts.
Through this process, a probability distribution was created, serving as a
robust forecasting for ground-shaking intensity at sites. The performance of
the forecasting model was validated through two examples of the Taitung
earthquake sequence in September 2022, and the Hualien earthquake sequence in
April 2024, showing the workflowfs effectiveness in forecasting earthquake
occurrences and site-specific ground-shaking probability estimations. The
proposed forecasting model can quickly deliver short-term seismic hazard
curves and warning messages, facilitating timely decision-making. The possible
applications of the workflow will also be presented. Reference Ming]Che
Hsieh, Chung]Han Chan, Kuo]Fong Ma, Yin]Tung Yen, Chun]Te
Chen, Da]Yi Chen, Yi]Wun Mika Liao; Toward
Real]Time Ground]Shaking]Intensity Forecasting Using ETAS and GMM: Insights
from the Analysis of the 2022 Taitung Earthquake Sequence. Seismological
Research Letters 2024; doi:
https://doi.org/10.1785/0220240180 -2 SpeakerF@Petrillo, Giuseppe iNanyang
Technological University(NTU, Singapore) EVisiting
Researcher / Visiting Researcher of ISMj
TitleF@The Impact of Stress Redistribution on
the Spatial and Magnitude Patterns of Future Earthquakes AbstractF@ Predicting
the location and timing of the next major earthquake remains a critical
challenge in seismic forecasting. While it seems logical that future
earthquakes will occur in regions where stress has accumulated from previous
events, most forecasting models do not consider the relationship between
stress distribution and earthquake occurrence. In this study, we utilize a
physical earthquake simulator to investigate how stress redistribution
influences the likelihood of large earthquakes and aftershocks. Our results
show that major earthquakes are more likely to initiate near the edges of
previous ruptures, where stress has not yet been fully released.
Additionally, we explore how this redistribution of stress affects the
magnitude distribution of subsequent aftershocks. These findings provide
valuable insights for improving earthquake forecasting models by
incorporating stress evolution, potentially enhancing their predictive
accuracy. The
98th DateF@1 October 2024@@@TimeF@14:30 - 17:00 LocationF@Room D312B (Seminar Room), Institute of
Statistical Mathematics & Online, hybrid -1 SpeakerF@Dr.
Wu, Stephen iAssociate
Professor of ISMj TitleF@Potential of LLMs in seismology AbstractF@ The application
of Large Language Models (LLMs) in seismology holds significant promise, but
direct usage of LLMs as standalone tools often falls short in addressing the
complexity of seismic data and tasks. In this presentation, I will explore
LLM orchestration as a system-building challenge, demonstrating how
integrating multiple LLMs within a structured framework enhances the
potential for accurate and efficient problem-solving in seismology. This
approach allows for specialized task management and better adaptation to
domain-specific needs. To further refine these ideas, we organized a local
hackathon in Japan, inviting seismologists to provide feedback and insights
on the utility of orchestrated LLM systems for seismic analysis. The outcomes
of this collaborative effort will help shape future applications of LLMs in
the field. -2 SpeakerF@Zhan, Chengxiang iChina University of Geosciences
(Beijing) EGraduate
Student / Visiting Researcher of ISMj
TitleF@Neural Point Process: A Modulated
Renewal Model for Temporal Event Modeling AbstractF@ Recent
research has demonstrated that Neural Point Processes (NPPs) are effective in
modeling time series of discrete events. However, the underlying rationale
for this approach remains insufficiently explored. Two key questions arise:
First, how can NPPs successfully model event sequences using only a limited
amount of historical data? Second, does the amount of required historical
data vary depending on the type of point process being modeled? Here, we aim
to address both questions. We propose that NPPs can be interpreted as
modulated renewal models. Specifically, one neural network learns the renewal
process using the current waiting time as input, while another neural network
captures the modulation effect based on intervals between past events. Our findings
further reveal that the amount of historical data needed for accurate
modeling varies across different types of point processes. -3 SpeakerF@Prof.
Zhuang, Jiancang iProfessor of ISMj TitleF@Quantification of earthquake
predictability AbstractF@ In
earthquake forecasting, there is a significant gap between complete
randomness and complete deterministicity. This
presentation begins by discussing how to quantify predictability and
outlining the current state of earthquake predictability from an
information-theoretic perspective. -4 SpeakerF@Dr.
Clements, Timothy iU.S.
Geological Surveyfs Earthquake Science Center in Moffett Field, CA, USAE Postdoctoral fellowj TitleF@A Ground Motion-based Approach to
Earthquake Early Warning and Earthquake Statistics AbstractF@ Real-time
earthquake early warning and forecasting systems have focused on using an
earthquake's location, origin time, and magnitude to forecast either ground
motion or the rate of earthquakes. Here, we suggest using continuous seismic
ground motion to forecast ground motion in the near (seconds) to intermediate
(days) future. I will introduce the GRAph
Prediction of Earthquake Shaking (GRAPES) algorithm (Clements et al. 2024,
GRL), a deep learning model trained to characterize and propagate earthquake
shaking across a seismic network, for use in earthquake early warning
(EEW). I will show that, when
applied to earthquake seismology, deep learning is not a black box; GRAPESf
internal activations, which I call gseismic vectorsh, correspond to the
arrival of distinct seismic phases.
While trained on earthquakes recorded in Japan, I will show that
GRAPES, without modification, outperforms the USGS ShakeAlert
earthquake early warning system on the 2019 M7.1 Ridgecrest, CA earthquake. I
will then apply earthquake forecasting techniques to extract the
Gutenberg-Richter b-value and Omori-Utsu parameters
from the distribution of recent ground motion recorded at a single nearby
seismometer during an aftershock sequence using a maximum likelihood
approach. We apply our ground motion-based approach to the two weeks
following the 2019 M7.1 Ridgecrest, CA earthquake sequence. The 97th
SpeakerF@Dr.
Guo, Yicun iUniverisity of Chinese Academy
of Sciences, China EAssisstant Professor
/ Visiting Researcher of ISMj
DateF@26 August 2024@@@TimeF@15:00-16:00 LocationF@4F Lounge,
Institute of Statistical Mathematics & Online, hybrid TitleF@Statistical modeling of 3D seismicity
and its correlation with fault slips along major faults in California AbstractF@ This
study applies a 3D Epidemic Type Aftershock Sequence (ETAS) model to the
earthquake catalog in California.
A new depth kernel function incorporating the scaling effect of mainshock
magnitudes is introduced into the model. The results demonstrate that the new
model improves data fitting, and we find a consistent decrease in aftershock
productivity with depth by stochastic reconstruction. We attribute this to
the decreasing fault coupling with depth or active seismic faulting in the
upper crust. Furthermore, we compare background seismicity rates derived from
the new model with the long-term slip rates on the faults in the study
region. We
reveal a linear increase in the seismicity rate with the slip rate on the
logarithmic scale, suggesting the accumulated strain on fault is partially
released by seismic activities. Additionally, a significant correlation
exists between the background seismicity rate and fault segments exhibiting
relatively high creep rates, especially in the transition zones for fault
coupling along the central San Andreas fault. This finding suggests that interseismic background earthquakes mostly occur in areas
with moderate coupling ratios. The 96th
SpeakerF@Dr.
Lei, Xinglin iSenior
Researcher of National Institute of Advanced Industrial Science and
Technology(AIST) DateF@5 August 2024@@@TimeF@15:00-16:00 LocationF@4F Lounge, Institute of Statistical Mathematics
& Online, hybrid TitleF@Can the extent of fluid involvement be
quantified by statistics for fluid-involved or fluid-driven seismicity? AbstractF@ The
complexity of seismic activity originates from the complexity of the fault
system itself and the interactions between faults during earthquakes. When overpressured fluids are involved underground, the
interaction between fluid diffusion and faulting makes seismicity even more
complex. Whether there is a specific correlation between the extent of fluid
involvement and the statistical characteristics of seismicity is an
interesting and worth exploring topic. This report presents systematic
analysis results of several seismic sequences with significantly different
levels of fluid involvement (including long-term low-pressure water injection
and short-term multiple high-pressure water injection-induced seismicity, as
well as natural earthquake swarms involving fluids of different extents). It
summarizes some basic understandings and highlights several future research
directions. The 95th
SpeakerF@Dr.
Gerstenberger, Matt iGNS Science, New Zealand ESeismologist/NSHM Leadj DateF@10 June 2024@@@TimeF@16:00-17:00 LocationF@4F Lounge, Institute of Statistical Mathematics
& Online, hybrid TitleF@The New Zealand National Seismic
Hazard Model: modelling uncertainty and implications for its use AbstractF@ In
2022 a significant revision of the New Zealand National Seismic Hazard Model
(NSHM) was released. The revision was a significant change to all components
of the model and resulted in a large increase in hazard across New Zealand.
An important focus of the revision was on the understanding and modelling of
uncertainties that impact that resultant hazard forecasts. Following a traditional probabilistic
seismic hazard analysis approach, all uncertainties are split into two
categories: 1) aleatory, which is defined as inherent randomness in
earthquake processes; and 2) epistemic, which is defined as uncertainty in
our knowledge. The distinction between the two is not always clear cut, yet
the choice in how any parameter is modelled has clear implications for
decisions based on the NSHM. In
NZ the NSHM has significant uptake across government and private sectors. It
underpins, for example, the NZ building code, large
engineering projects, long-term planning and the insurance industry. In this
talk I will discuss how we model the uncertainty, what some of the key
uncertainties are (e.g., non-Poisson occurrence rates, and ground shaking),
and how these uncertainties are passed on and used, or not used, in decision
making. Importantly, I will discuss how the choice in how the uncertainty is
modelled, can lead to the uncertainty being ignored or, potentially, over-emphasised. The 94th
SpeakerF@Dr.
Koh, Jonathan iOeschger
Centre for Climate Change Research(OCCR), University of Bern, Switzerland EPost-doctoral researcher DateF@16 April 2024@@@TimeF@16:00-17:00 LocationF@4F Lounge, Institute of Statistical Mathematics
& Online, hybrid TitleF@Estimating shared random effects
between model components in Bayesian hierarchical frameworks AbstractF@ Estimating
shared random effects between model components can help reveal and interpret
common unseen drivers of different facets of the response. This can increase
parsimony and reduce estimation uncertainty, or tackle observation biases due
to heterogeneity in sampling effort that would otherwise lead to biased
statistical inferences. In this talk I will cover two main applications of
this methodology, on modelling wildfire activity (Koh et al., 2023) and the
first arrival date of migratory birds (Koh and Opitz, 2023). References:
Koh, J. and T. Opitz
(2023). Extreme-value modelling of migratory bird arrival dates: Insights
from citizen science data. Preprint on ArXiv:2312.01870. Koh, J., F. Pimont, J.-L. Dupuy, and T. Opitz (2023). Spatiotemporal
wildfire modelling through point processes with moderate and extreme marks. The Annals of
Applied Statistics 17 (1), 560–582. The 93rd SpeakerF@Dr.
Ueda,
Taku iJSPS
Research Fellowship for Young Scientists of Disaster Prevention Research
Institute, Kyoto University /Visiting
Researcher of ISMj DateF@30 January 2024@@@TimeF@16:00 -17:00 Online TitleF@Spatial correlation of the shear
strain energy change and the number of declustered
crustal earthquakes in Japan AbstractF@ The
spatial correlation of geodetically estimated strain rate and the background
seismicity has been discussed in several areas worldwide. In Japan, however,
there are azimuthal differences between the geodetically estimated maximum
contraction strain rate and the seismologically estimated maximum compression
stress. Thus, the increase in strain may not necessarily represent stress
accumulation. In this study, we compare the number of background events for
the crustal seismicity in Japan with the shear strain energy change which
considers the background stress field and the current crustal deformation. We
estimated the strain rate field using geodetically-estimated secular
velocities according to the method using the basis function expansion. We
calculated the stress change using the estimated strain tensor assuming the
state of plane stress and evaluated the shear strain energy change
considering the background stress field estimated by Uchide
et al. (2022) at  intervals. We used  shallow ( km depth) crustal
earthquakes and applied the nearest neighbor distance approach to decluster the catalog during 2002—2010. The
shear strain energy change is weakly positively correlated with the number of
background earthquakes, and especially in SW Japan, this correlation is
significantly better compared with the correlation between the strain rate
and seismicity. In some areas, the seismicity rate is remarkably high
compared with that expected from linear regression with shear strain energy
change. These regions may be affected by crustal fluids that possibly weaken
the fault strength. The
92nd Statistical Seismology Seminars
& DateF@7 November 2023@@@TimeF@10:00 - 12:00 E
14:00 - 16:30 LocationF@4F Lounge, Institute of Statistical Mathematics
& Online, hybrid 10:00 - 12:00 Presentations
by graduate students -1 SpeakerF@Li,
Yongbo iInstitute
of Geophysics, China Earthquake Administration, China EGraduate Student /Visiting
Researcher of ISMj TitleF@A Three-Dimensional Spherical
Epidemic-Type Aftershock Sequence (3D-SETAS) Model and Its Application in the
Alaska Region
(Li, Y.*, Zhuang, J. and Chen, S.) -2 SpeakerF@Wang, Zhifeng iChina University of Geosciences
(Wuhan) EGraduate
Student /Visiting Researcher of ISMj
TitleF@Bayesian inversion for finite fault
earthquake source models and uncertainty analysis
(Wang, Z.*, Zhuang, J. and Wang, D.) -3 SpeakerF@Si, Zhengya iInstitute of Geophysics, China
Earthquake Administration, China EGraduate
Student /Visiting Researcher of ISMj TitleF@Bayesian merging of earthquake
magnitudes determined by multiple seismic networks
(Si, Z.*, Zhuang, J., Gentili, S., Jiang, C. and Wang, W.) -4 SpeakerF@Piao, Jian iPeking
University, China EGraduate
Student /Visiting Researcher of ISMj TitleF@On the spatial response kernel in the
ETAS model
(Piao, J.*, Zhuang, J. and Zhou, S.) -5 SpeakerF@Mao, Ning iInstitute
of Geophysics, China Earthquake Administration, China EGraduate Student /Visiting
Researcher of ISMj TitleF@Extraction of secular variation
signals and estimation of transfer function from geomagnetic stations
(Mao, N.* and Chen, S.) 14:00 -
16:30 -6 SpeakerF@Dr.
Peng, Hong iProject
Researcher of ISMj TitleF@Constructing an empirical envelope
function of seismic waveforms -7 SpeakerF@Dr.
Petrillo, Giuseppe iProject Assistant Professor of ISMj TitleF@Decoding the Puzzle of Earthquake
Magnitude Dependency -8 SpeakerF@Dr.
Guo, Yicun
iUniversity
of Chinese Academy of Sciences, China EAssistant
Professorj TitleF@Detection and Characterization of
Earthquake Swarms in Nankai and Its Association With Slow Slip Events -9 SpeakerF@Dr. Gentili, Stefania
iNational
Institute of Oceanography and Experimental Geophysics, Italy EResearcher TitleF@Aftershock forecasting by the NESTORE
machine learning algorithm: applications to Italy, Slovenia, California,
Greece and some preliminary results on Japan
(Gentili, S.*, Chiappetta, G., Petrillo, G., Brondi,
P., Zhuang, J. and Di Giovambattista, R.) -10 SpeakerF@Niu, Yuanyuan iC Ph.D.
Student of The Graduate University for Advanced Studies (SOKEN-DAI)j TitleF@Nonparametric Bayesian inference for
ETAS model
(Niu, Y.* and Zhuang, J.) The 91st SpeakerF@Prof.
Guan, Yongtao iDepartment
of Management Science, School of Business Administration, University of
Miami, USA EProfessorj DateF@3 October 2023@@@TimeF@16:00-17:00 Online TitleF@Group Network Hawkes Process AbstractF@ In this
work, we study the event occurrences of individuals interacting in a network.
To characterize the dynamic interactions among the individuals, we propose a
group network Hawkes process (GNHP) model whose network structure is observed
and fixed. In particular, we introduce a latent group structure among
individuals to account for the heterogeneous user-specific characteristics. A
maximum likelihood approach is proposed to simultaneously cluster individuals
in the network and estimate model parameters. A fast EM algorithm is
subsequently developed by utilizing the branching representation of the
proposed GNHP model. Theoretical properties of the resulting estimators of
group memberships and model parameters are investigated under both settings
when the number of latent groups G is over-specified or correctly specified.
A data-driven criterion that can consistently identify the true G under mild
conditions is derived. Extensive simulation studies and an application to a
data set collected from Sina Weibo are used to illustrate the effectiveness
of the proposed methodology. The 90th
SpeakerF@Dr.
Hsieh, Ming-Che iEarthquake
Disaster & Risk Evaluation and Management Center (E-DREaM),
National Central University, Taiwan EAssociate
Research Fellowj DateF@29 August 2023@@@TimeF@16:30-17:30 Online TitleF@Seismic Hazard Assessment for
Metropolises and Sciences Parks in Taiwan: Analyzing Ground Motions Using
Deterministic and Probabilistic Methods AbstractF@ Seismic
hazard assessment (SHA) is essential for engineering constructions, hazard
mitigation strategies, and earthquake-early warnings. The fundamental of SHA
is based on analyzing empirical ground motion datasets and constructing
ground motion models (GMMs) through parametrization and regression
techniques. However, significant challenges arise due to the absence of (1)
empirical ground motions from local large-magnitude earthquakes and (2) the
incorporation of physical effects, such as source-rupture processes and
complex wave propagation media, into a generalized functional form of GMM. To
conquer these challenges in estimating ground motion, physics-based ground
motion simulation is a powerful tool for deterministic seismic hazard
assessment. In recent years, we have conducted ground motion simulations,
taking great care to consider the characteristics of fault rupture, various
scales of subsurface structures, basin geometry, high-resolution topographic
relief, and more for earthquake scenarios in metropolitan areas and science
parks in Taiwan. These results have been integrated into loss estimation and
practical mitigation strategies. Furthermore, we have developed a short-term
seismic intensity forecasting procedure for earthquake warnings based on the
epidemic-type aftershock sequence (ETAS) and the ground motion model. Unlike
traditional probabilistic seismic hazard analysis (PSHA), which provides the
probability of ground motion exceeding certain levels over 30 or 50 years for
engineering concerns, our forecasting model can deliver warning messages
within a short period to facilitate timely decision-making. An example of the
Taitung earthquake sequence in September 2022 demonstrates the good
performance of forecasting seismic intensity. Keywords:
seismic hazard assessment, ground motion model, physics-based ground motion
simulation, epidemic-type aftershock sequence The 89th
SpeakerF@Prof.
Peng, Zhigang iSchool of Earth
and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, USA EProfessorj DateF@16 June 2023@@@TimeF@16:00 - Online TitleF@What can emissingf events tell us about
earthquake statistics and physical mechanism of earthquake triggering? AbstractF@ Large
earthquakes are generally followed by many smaller events known as
aftershocks. Sometimes they are preceded by foreshocks. While the general
statistical behaviors of earthquake sequences are well known, the physical
mechanisms for foreshock and aftershock generation are still in debate.
Several studies have shown that immediately before or after large
earthquakes, many smaller events are missing in the standard earthquake
catalog, which may hamper our understanding of the physical processes during
this important time period. Here I review recent advances in building more
complete earthquake catalogs using waveform-based techniques such as template
matching or machine learning. I will present several case studies to show how
these improved earthquake catalogs reveal new patterns in the space-time
evolutions of these earthquake sequences. I will end the talk with some open
questions/suggestions that can potentially further improve earthquake
detection immediately before or after large earthquakes. The 88th -1 SpeakerF@Dr.
Hainzl, Sebastian iGFZ German Research Centre for
Geosciences, Germany ESenior
Researcher DateF@17 March 2023@@@TimeF@15:00 -16:00 LocationF@Room D313/314 (Seminar Room), Institute of
Statistical Mathematics & Online TitleF@Stress-based seismicity modeling AbstractF@ While
the ETAS model successfully describes the first-order characteristics of
short-term earthquake clustering due to earthquake interactions, it can only
model earthquake activation, not unloading effects. To be more realistic,
seismicity models based on estimated stress can be applied. Two widely-used
physics-based seismicity models are the Coulomb Failure and Dieteriches Rate-State models, which assume pre-existing
populations of faults that respond to changes in Coulomb stress. I will
discuss a modified Coulomb-Failure model in which instantaneous triggering is
replaced by a mean time-to-failure that depends exponentially on the absolute
stress value. For critical initial stresses, we show that the model leads to
identical forecasts as the Rate-State model and reproduces the Omori-Utsu relation for aftershock decays and stress-shadowing
effects. Thus, both previous stress-based seismicity models can be seen as
special cases of the new model. However, the new stress response model can
also account for subcritical initial stress conditions, which is particularly
relevant for induced seismicity in intraplate regions. Furthermore, I will
present the results of a recent systematic analysis of the dependence of
seismicity parameters (b-value and Omori-parameters) on the calculated stress
changes and discuss the possible use of these relationships in seismicity
modeling. -2 SpeakerF@Stockman,
Sam iComputational
Statistics and Data Science, University of Bristol, UK EPh.D. Studentj DateF@17 March 2023@@@TimeF@16:00 -17:00 LocationF@Room D313/314 (Seminar Room), Institute of
Statistical Mathematics & Online TitleF@Forecasting the 2016-2017 Central
Apennines Earthquake Sequence with a Neural Point Process AbstractF@ While
the ETAS model successfully describes the first-order characteristics of
short-term earthquake clustering due to earthquake interactions, it can only
model earthquake activation, not unloading effects. To be more realistic,
seismicity models based on estimated stress can be applied. Two widely-used
physics-based seismicity models are the Coulomb Failure and Dieteriches Rate-State models, which assume pre-existing
populations of faults that respond to changes in Coulomb stress. I will
discuss a modified Coulomb-Failure model in which instantaneous triggering is
replaced by a mean time-to-failure that depends exponentially on the absolute
stress value. For critical initial stresses, we show that the model leads to
identical forecasts as the Rate-State model and reproduces the Omori-Utsu relation for aftershock decays and stress-shadowing
effects. Thus, both previous stress-based seismicity models can be seen as
special cases of the new model. However, the new stress response model can
also account for subcritical initial stress conditions, which is particularly
relevant for induced seismicity in intraplate regions. Furthermore, I will
present the results of a recent systematic analysis of the dependence of
seismicity parameters (b-value and Omori-parameters) on the calculated stress
changes and discuss the possible use of these relationships in seismicity
modeling. The 87th SpeakerF@Dr.
Sato,
Daisuke iJSPS
Research Fellowship for Young Scientists of Disaster Prevention Research
Institute, Kyoto Universityj DateF@26 December 2022@@@TimeF@16:00 -17:00 Online TitleF@Inventing appropriate solving methods
of hierarchical Bayesian inversions when using regularization priors AbstractF@ Regularization
(e.g. damping, smoothing, and sparsity) is a robust technique to resolve ill
conditions in inverting model parameters more than data. However, it leaves
questions in tuning the hyperparameters that weight data misfits and
regularization losses, namely, the likelihood and prior. Therefore,
hierarchical Bayes naturally follow to evaluate the model parameters and
hyperparameters probabilistically. In this talk, I introduce our study on an
appropriate solving method for hierarchical Bayesian problems. In linear
inverse problems, surprisingly, we find a significant part of standard
approaches fail to invert many model parameters, including orthodox Monte
Carlos and the posterior maximum, despite the use of regularization (Sato Fukahata and Nozue, 2022).
Their problematic behaviors are all analytically explained by the entropic
effect of the model-parameter space, which is cared in the empirical Bayes,
as suggested in an early work of Robbins (1956). The same issue remains in
nonlinear problems, and I will also talk about numerical methods under
development to fix this "bug" of ordinary Monte Carlos. The 86th -1 SpeakerF@Dr.
Zhuang, Jiancang iAssociate Prof. of ISMj DateF@14 November 2022@@@TimeF@16:00 -16:45 Online TitleF@Evaluating earthquake forecasts with
likelihood based marginal and conditional scores AbstractF@ Earthquake
forecasting consists of the forecasts of the numbers,occurrence times, locations, and magnitudes
of seismic events, and even the correlations among them. In order to evaluate
each component in the forecasting, CSEP provides varieties of testing
criterions but still far from enough. In this study, starting from the essential
meanings of the full likelihood of a point process, I will explain how to
evaluate the marginal likelihoods for each component in the forecasts and the
conditional likelihoods for some components under the condition that some
other components are given. These marginal and conditional likelihoods are
the bases for
the marginal and conditional scores in performance evaluation when multiple
models are used in forecasting. -2 SpeakerF@Sofiane
Rahmani iCenter of
Research in Astronomy, Astrophysics and Geophysics(CRAAG), Algeria EPh.D. Studentj DateF@14 November 2022@@@TimeF@16:45 -17:30 Online TitleF@Time-dependent and spatiotemporal
statistical analysis of Algerian seismicity AbstractF@ Northeastern
Algeria is known by its high seismic activity as reflected by several
hundreds of events occurring every year. Recently, this area has been the
seat of several seismic sequences such as the 2010 Beni-Ilmane
earthquake sequence and the 2012–2013 Bejaia earthquake sequences. On the
other hand, it is also observed that the seismic activity of this part of
Algeria is dominated by swarms, with high concentrations in time and space,
from a few days to several months, ranging from a few kilometers to ten
kilometers, and sometimes showing a migration of several kilometers in
several weeks. Our
main objective is to understand the global behavior of this seismic zone, it
is of crucial importance to understand what are the soliciting forces and how
they interact. These rupture processes are still under debate, but can be
deduced from the analysis of seismic swarms or aftershock sequences, as both
share similarities. Using a model corresponding to accurate detection and
relocation, we will study seismic clusters in detail by analyzing it from the
inside by identifying the different families that compose it. In doing so, we
will isolate the aftershocks, induced by the coseismic
stress transfer, from the swarm-like events, and we will analyze separately
their spatio-temporal behavior by a fine
statistical analysis. Because the stochastic models, which include an
increasing part of physical reasoning, have been slowly accepted during the
last three decades. The subject of statistical seismology aims at bridging
the gap between physics-based models without statistics, and statistics-based
models without physics. Our objectives are also to understand what mechanisms
are at work in the case of sequences and in the case of swarms, to see to
what extent it is possible to link the observations and analyses that will be
carried out to the regional seismotectonic context, and to understand what
influence this may have for the calculation of seismic hazard. The 85th SpeakerF@Dr.
Nishikawa,
Tomoaki iAssistant
Professor of Disaster Prevention Research Institute, Kyoto University/ Visiting
Researcher of ISMj DateF@3 October 2022@@@TimeF@16:15 -18:15 Online TitleF@Application of the ETAS model to slow
earthquake research AbstractF@ The
epidemic-type aftershock-sequence (ETAS) model is a standard statistical
model of fast earthquake activity. We are attempting to apply the ETAS model
to slow earthquake research. The attempts are focused on the following three
topics: (1) detection of slow earthquakes, (2) improvement of the ETAS model
by considering slow earthquake activity, and (3) construction of a
statistical model to describe slow earthquake activity. In this presentation,
we will present the results of (1) regarding the elucidation of the slow
earthquake distribution in the Japan Trench and preliminary results regarding
(2) and (3). The 84th SpeakerF@Peng,
Hong iResearch
Center for Earthquake Prediction, Disaster Prevention Research Institute,
Kyoto UniversityE Ph.D.
Studentj DateF@7 July 2022@@@TimeF@16:00 -18:00 Online TitleF@Characteristics of foreshocks
preceding the mainshocks in Japan AbstractF@ Studying
the foreshocks is an important way to understand the physical mechanism of
earthquakes. In this research, I will use the Japan Meteorological Agency
(JMA) earthquake catalogue from 2001 to 2021 to investigate the
spatiotemporal characteristics of foreshocks for mainshocks. I have three
important conclusions about the earthquakes in Japan: 1) No dependence of the
mainshock magnitude on the foreshock magnitude; 2) No obvious trend between
the foreshock-mainshock distance and the mainshock magnitude; 3) A decrease
in the foreshock-mainshock time difference with the increased foreshock
magnitude. These results of the foreshock-mainshock sequence seem to be more
consistent with the triggering mechanism rather than the
nucleation-controlled process. Thus, I suggest that the ecascade modelf or
rupture-controlled model is more reasonable for explaining the physical
mechanism of earthquakes in Japan. The 83rd SpeakerF@Dr.
Petrillo, Giuseppe iVisiting
Researcher of ISM / DateF@26 April 2022@@@TimeF@16:00 -18:00 Online TitleF@Statistical mechanics models for
seismic occurrence AbstractF@ Earthquake
occurrence is characterized by quite universal scaling relationships, in
particular regarding the events after a big shock: the aftershocks. Here I
discuss a fault model of two elastic interfaces with different rheology. This
model contains a mechanism for the aftershock occurrence and I will show that
our data recover the experimental scaling relationships at an excellent
qualitative level. We also find that large earthquakes are often anticipated
by a preparatory phase characterized by the occurrence of foreshocks.
Finally, I will mention that thanks to these models, it is possible to carry
out extensive simulations to verify the predictability of seismic phenomena. The 82nd SpeakerF@Dr.
Yano, Keisuke iAssociate
Professor of ISMj DateF@1 February 2022@@@TimeF@16:30 -18:00 Online TitleF@l1 trend filtering based detection of
slow slip events AbstractF@ Slow
slip events characterized by a slower fault rapture compared to regular
earthquakes have been discovered in tectonic zones worldwide and have helped
us understand the surrounding stress environment including megathrust zone.
In this talk, I will present a new detection method of slow slip events using
l1 trend filtering, a sparse estimation technique together with combined
p-value techniques. The proposed method provides not only candidates of the
events but also confidence values for detections. The synthetic tests showed
that our method successfully detect almost all events with few misdetections.
The application to real data in the Nankai subduction zone in western
Shikoku, southwest Japan, revealed our method detected new potential events
in addition to all known events. The 81st SpeakerF@Dr.
Takeo, Akiko iEarthquake
Research Institute, University of Tokyo EAssistant
Professorj DateF@16 November 2021@@@TimeF@16:00 -18:00 Online TitleF@Observation, detection, evaluation and
interpretation of slow earthquakes: is it episodic or chaotic? AbstractF@ I
introduce observation of slow earthquakes by broadband seismometers in the
Nankai subduction zone. This includes (i) how to
detect deep very low frequency earthquakes (VLFEs) with moment magnitudes of
~3 at the period range of 20-50 s related to tectonic tremors at a frequency
range of 2-8 Hz, (ii) how to evaluate the reliabilities of individual and
total VLFE detections, and (iii) how to interpret the VLFE activities. I
currently focus on the temporal change in the activity mode from episodic to
potential chaotic during a high-stress loading period, which might be
mathematically and physically interesting. The 80th
SpeakerF@Shen,
Xun iPh.D.
Student of The Graduate University for Advanced Studies (SOKEN-DAI)j DateF@19 October 2021@@@TimeF@16:00 - 18:00 Online TitleF@Residual Analysis for State Space
Models AbstractF@ This
presentation introduces a novel residual analysis-based algorithm for model
learning and hidden state inference in State-Space Models (SSMs) with a
nonlinear response. An SSM with nonlinear response has linear state equation
while the observation equation includes a linear part and a nonlinear part,
where the information of the nonlinear part is not available. In this study,
a neural network model is used to approximate the unknown nonlinear part in
the observation equation, and an Expectation-Maximization (EM) algorithm is
proposed to infer the hidden state and learn the parameters in both the
linear part and the neural network model, from the given sequences of input
data and observation data. In the E-Step, the posterior mean and covariance
for the system hidden state given the sequences of the system input and
observations is inferred via a Kalman filter-based forward recursion and
Rauch-Tung-Streibel smoother backward recursion. In
the M-Step, the model parameters are optimized according to the inferred
hidden state, input data, and observation data. The M-Step consists of two
components: a reconstruction procedure, in which uses the residuals of the
linear model to fit the neural network model, and a parametrization
procedure, which identifies the parameters in the linear part of the state
space model. We apply this newly proposed method to a numerical example and
in a case study of battery capacity estimation. The results show that the
proposed method can achieve better performance on the model learning and
hidden state inference than previously developed tools. The 79th
SpeakerF@Dr.
Wang, Ting iOtago Univeristy (Department of Mathematics and Statistics),
New ZealandEAssociate
Professorj DateF@21 September 2021@@@TimeF@13:00 -14F00 Online TitleF@A time series model for forecasting
earthquake energy release AbstractF@ Large
earthquakes often occur repeatedly. Modelling the history of earthquakes can
help forecast future hazardous events. In this talk, I will present a time
series model that we have developed to study recurrence patterns of
earthquakes. This model captures both the intensity of earthquake occurrence
and patterns of earthquake energy release in time. I will discuss the
forecasts of earthquake energy release using this model. The 78th
SpeakerF@Dr.
Xiong, Ziyao iProject
Assistant Professor of ISMj DateF@27 July 2021@@@TimeF@16:00 - 18:00 Online TitleF@The Research of Long-Term Earthquake
Hazard Estimated from a Modern Catalog AbstractF@ In
this study, to obtain optimal estimates of the earthquake hazard in North
China based on the modern earthquake catalog, we used two variable kernel
function estimation methods, proposed by Stock and Smith, and Zhuang, the
Bayesian Delaunay tessellation smoothing method by Ogata (ODTB), and a newly
proposed incomplete centroidal Voronoi tessellation (ICVT) method, to
calculate the total and background seismic spatial occurrence rates for the
study area. The sophisticated ODTB method is more stable than the others, but
is relatively expensive, in terms of computation demands, whereas Zhuang et
al.fs kernel estimate and the new ICVT method are able to provide reasonable
estimates and easier to implement. We also calculated the spatial variations
of the b-value, using the Bayesian method with smoothness prior proposed by
Ogata. Using comparative analyses and simulation experiments, we show that
all the methods give similar spatial patterns of seismic occurrences. The 77th SpeakerF@Dr.
Yamada, Masumi iDisaster
Prevention Research Institute, Kyoto University EAssistant Professorj DateF@24 June 2021@@@TimeF@16:00 -18:00 Online TitleF@IPFx: a new
source determination algorithm for earthquake early warning AbstractF@ An
earthquake early warning (EEW) system rapidly analyzes seismic data to report
the occurrence of an earthquake before strong shaking is felt at a site. In
Japan, the integrated particle filter (IPF) method, a new source estimation
algorithm, was recently incorporated into the EEW system to improve the
source estimation accuracy during active seismicity. The problem of the
current IPF method is that it uses the trigger information computed at each
station in a specific format as the input and is therefore applicable to only
limited seismic networks. This study proposes the extended IPF (IPFx) method to deal with continuous waveforms and merge
all Japanese real-time seismic networks into a single framework. The new
source determination algorithm processes seismic waveforms in two stages. The
first stage (single-station processing) extracts trigger and amplitude
information from continuous waveforms. The second stage (network processing)
accumulates information from multiple stations and estimates the location and
magnitude of ongoing earthquakes based on Bayesian inference. In 10 months of
continuous online experiments, the IPFx method
showed good performance in detecting earthquakes with maximum seismic
intensity >=3 in the Japan Meteorological Agency (JMA) catalog. By merging
multiple seismic networks into a single EEW system, the warning time of the
current EEW system can be improved further. The IPFx
method provides accurate shaking estimation even at the beginning of event
detection and achieves seismic intensity error <0.2 5 s after detecting an
event. This method correctly avoided two major false alarms on January 5,
2018, and July 30, 2020. The IPFx method offers the
potential of expanding the JMA IPF method to global seismic networks. The 76th
SpeakerF@Dr.
Chang, Ying iDepartment
of Earth and Space Sciences, DateF@14 January 2020@@@TimeF@13:30 -14:30 LocationF@Room D313/314 (Seminar Room),
Institute of Statistical Mathematics TitleF@Differences between mantle wedge
earthquakes and intraslab intermediate-depth
earthquakes from spatial b-value image AbstractF@ Intermediate-depth
earthquakes follow the power law distribution, the Gutenberg-Richter law logN=a-bM. The b-value shows
the proportion of small magnitude earthquakes relative to the large ones. A
large proportion of small earthquakes usually appears in high thermal anomaly
region and low ambient stress status field. High b-value anomalies in
subduction zones have been associated with dehydration of subducting oceanic
crust, which is a plausible mechanism of intermediate-depth earthquakes, or
low velocities indicating magmatic activities. The analysis of b-value may be
a useful tool to investigate the mechanisms of earthquakes and an indicator
of structural difference in subduction zones, and especially beneficial to
subduction zones which have intensive small magnitude earthquakes. In
southwestern Colombian subduction zone, a high rate of intermediate-depth
earthquakes appears in the Cauca cluster from the earthquake catalog of Servicio Geológico Colombiano. Previous study of the intermediate-depth
earthquakes in the cluster show a continuous 20-km
thick seismic zone dipping to southeast with 33–43 dip angle increasing to
the south, and two mantle wedge earthquake columns extending 30–40 km normal
to and above the top surface of the subducting slab. The focal mechanisms of
earthquakes in the cluster have various types and variable orientations of
nodal planes. The intermediate-depth earthquakes in southwestern Colombian
subduction zone occur in a spatial variant tectonic stress field and have
complex mechanisms. Intraslab earthquakes generally
have smaller b-value than mantle wedge earthquakes. In the slab, high b-value
anomalies appear in the top layer of the subducting slab and the mantle
wedge. The facts of focal mechanisms, the stress fields, and b-value
anomalies indicate dehydrated fluid involved structures and magmatic
activities. The 75th -1 SpeakerF@Prof.
Li, Honglei iInstitute
of Geophysics, China Earthquake Administration, China E Assistant Professorj DateF@28 August 2019@@@TimeF@13:00 -13:45 LocationF@Room D313/314 (Seminar Room),
Institute of Statistical Mathematics TitleF@Bayesian assimilation inversion of
gravity anomalies and parameters optimization AbstractF@ It is
well known that the gravity inversion is a classical ill-posed problem. The
parameters of regularization must be introduced for inversion. In this study,
we design a Bayesian assimilation inversion strategy, according to the
subjective blindness problems in the gravity anomaly inversion, which can
optimize balance multi-source gravimetric data, various model constraints and
multiple hyperparameters which related to the accuracies of the observation
data. We employed the Akaikefs Bayesian Information Criterion (ABIC) for the
estimated these trade-off parameters. Based on this novel strategy, we
designed some cases to test gravity inversion using gravity datasets from the
difference measurements with varying accuracy levels. This inversion strategy
can achieve different type gravimetric observations integration primely,
evaluate the observations and prior model constraints weight objectively and
it will have a very bright application prospect in the future. -2 SpeakerF@Prof.
Chen, Shi iInstitute
of Geophysics, China Earthquake Administration, China EProfessorj DateF@28 August 2019@@@TimeF@13:45 -15:00 LocationF@Room D313/314 (Seminar Room),
Institute of Statistical Mathematics TitleF@A Bayesian approach of network
adjustment for campaigned gravity survey: methodology and model test AbstractF@ The
drift rate of the relative gravimeter differs from time to time and from
meter to meter, and it is inefficient to estimate the drift rate by returning
to the base station or stations with known gravity value frequently in a
campaigned gravity survey for the large-scale region. Unlike the conventional
gravity adjustment procedure which employed a linear drift model, we assumed
the variation of drift rate is a smooth function of the time-lapse, and
proposed a new gravity data adjustment method by means of objective Bayesian
statistical interference. Some hyper-parameters were used to as trade-off to
balance the fitted residuals of gravity differences between station pairs and
the smoothness of the temporal variation of the drift rate. We employed the
Akaikefs Bayesian Information Criterion (ABIC) to estimate these
hyper-parameters. A comparison between results from applying the classical
and the Bayesian adjustment methods to some simulated datasets shows that the
new method is more robust and adaptive for solving the problems that are
caused by the irregular non-linear meter drift. The new adjustment method is
capable to recover the time-varying drift rate function of each gravimeter,
and also to optimize the weight constraints for each gravimeter that is used
in the gravity survey. We also carried out an error analysis for the inverted
gravity value at each station on based the marginal distribution. Finally, we
used this approach to process the real campaigned gravity data from an
observation network in North China. In this study, we rewrite the network
adjustment equations by introducing new trade-off parameters that balance the
residual of campaigned gravity data and the drift rate of the relative
gravimeter. This new method is tested with some synthetic datasets that are
been simulated with different drift models based on a real gravity
observation network. A comprehensive analysis on the fitting residuals and
the accuracy of adjustment is carried out. -3
SpeakerF@Dr.
Bayona, Jose Antonio iGFZ German
Research Center for Geosciences E
Post-doctoral fellowj DateF@28 August 2019@@@TimeF@1530 -16:15 LocationF@Room D313/314 (Seminar Room),
Institute of Statistical Mathematics TitleF@An updated global hybrid earthquake
model obtained from the optimal combination of interseismic
strain rates and smoothed-seismicity data AbstractF@ The
construction of global seismicity forecasts gives promise of definitive
prospective test results to be obtained in only a decade. Hence, there have
been several efforts to generate global earthquake-rate
models based on interseismic strain rates and
earthquake-catalog data, which currently provide high-resolution global
coverage. The Global Earthquake Activity Rate (GEAR1) seismicity model, for
instance, optimally combines crustal deformation rates with
smoothed-seismicity information to forecast long-term rates of earthquake
production worldwide. The
total earthquake number, spatial, and magnitude distributions forecasted by
GEAR1 are all consistent with observed seismicity, according to 2-yr
prospective test results. Nonetheless, inconsistencies in spatial seismicity
between the Seismic Hazard Inferred From Tectonics
(SHIFT_GSRM2f) earthquake forecast, the tectonic parent component of GEAR1,
and the observations are also found during the evaluation period. These
discrepancies primarily stem from SHIFT_GSRM2f underestimations of
subduction-zone earthquake activity. The
Subduction Megathrust Earthquake Rate Forecast (SMERF) earthquake model was
accordingly designed to improve SHIFT_GSRM2f estimates of shallow interface
seismicity. SMERF is based on the use of regional seismicity parameters and
the conservation of moment principle. Therefore, the physics-based and
data-driven approach of SMERF is desired to upgrade the tectonic parent
component of GEAR1. In
this study, we integrate SMERF earthquake rates in subduction zones with
SHIFT_GSRM2f estimates everywhere else on Earth to generate a new global
geodetic-based earthquake model, referred to as the Tectonic Earthquake
Activity Model (TEAM) seismicity forecast. We detect significant spatial
variations of earthquake activity between SHIFT_GSRM2f and TEAM in all
subduction zones. Particularly, we identify the major differences
within subduction interfaces like Bougainville, Southern Kuril and Western
Alaska. We
moreover combine TEAM with the Kagan–Jackson smoothed seismicity (KJSS)
model, the earthquake parent component of GEAR1, to create an updated hybrid
seismicity model named GEAR2. We currently explore the optimal combination of
geodetic strain rates and earthquake- catalog data needed to better
characterize spatial earthquake patterns worldwide. Finally, we will submit
the earthquake-rate forecasts to the Collaboratory for the Study of
Earthquake Predictability (CSEP) testing center for independent retrospective,
pseudo-prospective and prospective evaluation. The 74th
SpeakerF@Dr.
Chen, Feng iSchool of
Mathematics and Statistics, University of New South Wales, AustraliaESenior Lecturerj DateF@21 May 2019@@@TimeF@15:00-16:00 LocationF@Room D312B (Seminar Room), Institute
of Statistical Mathematics TitleF@Direct Likelihood Evaluation for the
Renewal Hawkes Process AbstractF@ An
interesting extension of the widely applied Hawkes self-exiting point
process, the renewal Hawkes (RHawkes) process, was
recently proposed by Wheatley et al. (2016 CSDA), which has the potential to
significantly widen the application domains of the self-exciting point
processes. However, the authors claimed that computation of the likelihood of
the RHawkes process requires exponential time and
therefore is practically impossible. They proposed two
Expectation-Maximization (EM) type algorithms to compute the maximum
likelihood estimator (MLE) of the model parameters. Because of the
fundamental role of likelihood in statistical inference, a practically
feasible method for likelihood evaluation is highly desirable. In this talk
we present an algorithm that evaluates the likelihood of the RHawkes process in quadratic time, a drastic improvement
from the exponential time claimed by Wheatley et al. We demonstrate the
superior performance of the resulting MLEs of the model relative to the EM
estimators through simulations. We also present a computationally efficient
procedure to calculate the Rosenblatt residuals of the process for
goodness-of-fit assessment, and a simple yet efficient procedure for future
event prediction. The proposed methodologies were applied on real data from
seismology and finance. This talk is based on joint work with Tom Stindl. The R package implementing the proposed
methodology is available on the CRAN:
https://cran.r-project.org/web/packages/RHawkes/. The 73rd
SpeakerF@Prof.
Wang, Baoshan iEarthquake
and Volcano Research Center Graduate School of Environmental Studies, Nagoya
University EVisiting
Professor (University of Science
and Technology of China E
Professor)j DateF@23 April 2019@@@TimeF@15:00-16:00 LocationF@Room D312B (Seminar Room), Institute
of Statistical Mathematics TitleF@Migration of micro-earthquakes during
cyclic operation of Underground Gas Storage and the Changdao
earthquake swarm AbstractF@ The
distribution of earthquakes is controlled by the stress state and material
properties. And the migration of earthquakes can be used to infer the changes
in subsurface stress or medium properties. In this presentation, we will
introduce two case studies of seismicity migrations related respectively to
the Hutubi Underground Gas Storage (UGS) in Junggar
Basin and the Changdao earthquake swarm occurred in
the Bohai Sea. We first use the matched and filter technique to detect more
events than the local catalog. And then we relocate the detected events using
double difference method with waveform cross-correlation-based differential
travel-times. Micro-earthquakes clearly migrate outward from the UGS during
the cyclic operation, the migration may result from the stress transfer
during multiple injection and extraction. The seismicity during Changdao earthquake swarm unilaterally migrated
south-west accompanied by some bursts along several conjugate faults. We
suggest that fluid diffusions are responsible for the earthquake migration in
Changdao. The 72nd -1 SpeakerF@Prof.
Chen, Xiaofei iDepartment
of Earth and Space Sciences, Southern University of Science and Technology,
China E Professorj DateF@22 January 2019@@@TimeF@13:30 -14:30 LocationF@Room A504 (Seminar Room), Institute of
Statistical Mathematics TitleF@Phase diagram of earthquakes and
implications -2 SpeakerF@Dr.
Nanjo, Kazuyoshi iGlobal
Center for Asian and Regional Research, University of Shizuoka E Project Associate Professorj DateF@22 January 2019@@@TimeF@14:30 -15:30 LocationF@Room A504 (Seminar Room), Institute of
Statistical Mathematics TitleF@An investigation into the relation
between the occurrence of large earthquakes and time-dependent decrease in b
value AbstractF@ The
Gutenberg-Richter frequency-magnitude distribution of earthquakes is well
established in seismology. The b value, the slope of the relation between
frequency and magnitude is typically 1, but it often shows variations around
1. The b value has shown a pronounced decrease over several years prior to
large earthquakes around their hypocenters. Specific examples include the
M9-class 2011 Tohoku and 2004 Sumatra earthquakes (e.g., Nanjo et al., 2012).
However, it has remained uncertain whether there is the existence of tendency
that large earthquakes occur, following the appearance of b-value decrease.
To prove this existence, we are now trying to create a method to make and
evaluate trial retrospective forecasts of large earthquakes (e.g., M8+
earthquakes from 1980 to 2017 on the worldwide basis, using the ANSS
catalog), based on decreasing trend in b values. This is still ongoing
research, so that, in this talk, we present the preliminary result. Based on it, we then discuss the
possibility that a decrease in b values can be considered as a precursor to
large earthquakes and an important indicator that has potential in terms of
forecasting large earthquakes. -3
SpeakerF@Dr.
Wang, Yuchen iEarthquake
Research Institute, University of Tokyo E
Post-doctoral fellowj DateF@22 January 2019@@@TimeF@1530 -16:30 LocationF@Room A504 (Seminar Room), Institute of
Statistical Mathematics TitleF@Tsunami Data Assimilation in Disaster
Mitigation AbstractF@ Tsunami
data assimilation has been proposed for tsunami early warning. It estimates
the tsunami waveform by assimilating offshore observed data into a numerical
simulation, without calculating initial sea surface height at the source. The
optimum interpolation method is adopted in data assimilation. However,
previous data assimilation method has a relatively high computational load,
as it is necessary to run numerical simulations to obtain the tsunami
wavefield. In
our research, we proposed a new tsunami data assimilation approach based on
Greenfs function to reduce the computation time for tsunami early warning.
Greenfs Function-based Tsunami Data Assimilation (GFTDA) forecasts the
waveforms at Points of Interest (PoIs) by
superposition of Greenfs functions between observation stations and PoIs. Unlike the previous assimilation approach, GFTDA
does not require the calculation of the tsunami wavefield for the whole
region during the assimilation process, because the Greenfs functions have
been calculated in advance. The forecasted waveforms can be calculated by a
simple matrix manipulation. This
approach greatly reduces the time cost for tsunami warning because it no
longer needs to run the tsunami propagation model, as long as the Greenfs
functions are calculated in advance. By combining with Huygens-Fresnel
Principle, this method could be applied to regions without a dense
observation network. The applications to the 2012 Haida Gwaii earthquake, the
2004 off the Kii Peninsula earthquake and the 2009
Dusky Sound earthquake revealed that GFTDA helped achieve a more accurate and
quicker tsunami early warning while saving the cost. The 71st
SpeakerF@Dr.
Harte, David iGNS
Science, New Zealand EStatistical
Seismologist and Hazard Modellerj DateF@6 November 2018@@@TimeF@16:00 -17:00 LocationF@Room D313 (Seminar Room), Institute of
Statistical Mathematics TitleF@Evaluation of Earthquake Stochastic
Models Based on Their Real-Time Forecasts: A Case Study of Kaikoura 2016 AbstractF@ The
M7.8 Kaikoura NZ earthquake started at 2016-11-13 11:02:56 (UTC) with epicentre (173.02 deg E, 42.69 deg S), 15km NE of Culverden, and lasted for about two minutes. It caused
multiple fault ruptures to the north as far as Seddon (150km from epicentre), the location of a large sequence in 2013.
Since the mainshock, the bulk of the aftershock activity has also migrated to
the north. We analyse real-time probability forecasts produced during
the Kaikoura 2016 aftershock sequence, based on a spatial ETAS model.
Forecasts were derived by simulating the model forward over the required time
interval multiple times. Each forecast was evaluated at the end of the
forecast time interval by comparing with the number of events that eventually
occurred. Further, the spatial and temporal forecast characteristics were
evaluated by comparing the actual log-likelihood with those of the
simulations. We
show that the model was forecasting too fewer aftershocks immediately after
the mainshock, and too many aftershocks in the later stages of the sequence.
The too fewer aftershocks is probably caused by many
missing smaller events early in the sequence and an initial large
under-estimate of the mainshock magnitude, being 6.6 with a final solution of
7.8 three days later. Various catalogue, model and methodological problems
become evident during such a real-time experiment and these are also
discussed. The 70th
SpeakerF@Dr.
Chen, Shi iInstitute
of Geophysics, China Earthquake Administration, China EAssociate Professorj DateF@28 August 2018@@@TimeF@16:00-17:00 LocationF@Room D312B (Seminar Room), Institute
of Statistical Mathematics TitleF@A new approach for terrestrial
relative gravity adjustment using smoothness priors of drift rate AbstractF@ The
relative gravimeter, which generally uses zero-length springs as the gravity
senor, is still as the first choice in the field of terrestrial gravity
measurement because of its efficiency and low-cost. Because the drift rate of
instrument can be changed with the time and meter, it is necessary for
estimating the drift rate to back to the base or known gravity value stations
for repeated measurement at regular hourfs interval during the practical
survey. However, the campaigned gravity survey for the large-scale region,
which the distance of stations is far away from serval or tens kilometers,
the frequent back to close measurement will highly reduce the gravity survey
efficiency and extremely time-consuming. In this study, we proposed a new
gravity data adjustment method for estimating the meter drift by means of
Bayesian statistical interference. In our approach, we assumed the change of
drift rate is a smooth function depend on the time-lapse. The trade-off
parameters were be used to control the fitting residuals. We employed the
Akaikefs Bayesian Information Criterion (ABIC) for the estimated these
trade-off parameters. The comparison and analysis of simulated data between
the classical and Bayesian adjustment show that our method is robust and has
self-adaptive ability for facing to the unregularly non-linear meter drift.
At last, we used this novel approach to process the realistic campaigned
gravity data at the North China. Our adjustment method is suitable to recover
the time-varied drift rate function of each meter, and also to detect the
meter abnormal drift during the gravity survey. We also defined an
alternative error estimation for the inversed gravity value at each station
on the basis of the marginal distribution theory. The 69th
SpeakerF@Dr.
Varini, Elisa iInstitute
of Applied Mathematics and Information Technology, National Research Council(CNR-IMATI), Italy EResearcherj DateF@20 March 2018@@@TimeF@13:30-14:30 LocationF@4F Lounge, Institute of Statistical
Mathematics TitleF@Identification of earthquake clusters
in Northeastern Italy by different approaches AbstractF@ Earthquakes
do not occur randomly in space and time; rather, they tend to group into
clusters that can be classified according to their different properties,
presumably related to the specific geophysical properties of a seismic
region. Thus, we aim at exploring the spatio-temporal
features of earthquake clusters in North- eastern Italy, based on a
systematic analysis of robustly and uniformly detected seismic clusters
reported in the local bulletins, compiled at the National Institute of
Oceanography and Experimental Geophysics since 1977. First, data are analysed by a method for detection of earthquake
clusters, based on gnearest-neighbor dis- tancesh
between events in space-time-energy domain (Baiesi
and Paczuski, 2004). Then they are analysed by applying a stochastic declustering
algorithm based on ETAS model (Zhuang, Ogata, and Vere-Jones, 2002), in which
events are associ- ated
to clusters in accordance with their estimated probability distributions.
Both methods allow for a robust data-driven identification of seismic
clusters, and permit to disclose possible complex features in the internal
structure of the identified clus- ters. By comparing these approaches, we take advantage of
a different description of the clustering process in order to assess
consistency and reliability of the findings. We found some evidence that
swarm-like sequences are mostly associated with the north-western part of the
study region, while burst-like sequences tend to occur in the south-eastern
part of it. Key
words: earthquake clustering, nearest-neighbor distance, stochastic decluster- ing, ETAS model. The 68th
SpeakerF@Prof.
Ma, Kuo-Fong iDepartment
of Earth Sciences, National Central University, Taiwan EProfessorj DateF@31 January 2018@@@TimeF@13:30-14:30 LocationF@Room A508 (Seminar Room), Institute of
Statistical Mathematics TitleF@Probability on Seismic Hazard
Assessment of Taiwan: Progress and Challenge AbstractF@ Taiwan
Earthquake Model published the first public PSHA map of Taiwan in late 2015,
and had been widely discussed and adopted in a way toward seismic hazard
mitigation and risk assessment. The model adopts the source parameters of 38 seismogenic structures under a single fault segment
basis, and shallow areal source for crustal events, and, intraplate, and interplate subduction events. To evaluate the potential
ground-shaking resulting from each seismic source, the corresponding
ground-motion prediction equations for crustal and subduction earthquakes are
adopted. The highest hazard probability is evaluated to be in Southwestern
Taiwan and the Longitudinal Valley of Eastern Taiwan. Right after the
publication of PSHA2015, a damaging earthquake of 2016 Meinong M6.6
earthquake occurred in southwestern Taiwan from non-identified seismogenic structure. Historically, significant crustal
damaging earthquakes in Taiwan mostly were from complicated fault system
rather than from a single fault segment (e.g. 1935 M7.5 Hsinchu-Taichung, and
1906 M7.1 Meishan earthquakes). Technically, the 2016 M6.6 Meinong earthquake
could be categorized into areal source event. The 1906 M7.1 Meishan
earthquake, recently, had been resolved to be from a fault system of blind NE
strike thrust with EW surface breaching fault (one of the identified seismogenic structures). These events suggest that a
single fault segment evaluation for seismic hazard might be inadequate.
Despite the difficulty in giving slip rate of a single segment into the probability
calculation, how to deal with the slip rate in probability from complex fault
system is a challenge. In the same time, PSHA evaluation of ground motion
from areal source and active fault might double count the hazard for an event
involved from the both category. How to determine
the maximum magnitude events from areal source, and the delineation of the
involvement of the areal source event to complex fault system brought another
attention on the source categorization and its partition in probability for
seismic hazard assessment. The 67th
SpeakerF@Dr.
Wu, Stephen iAssistant
Professor of ISMj DateF@3 October 2017@@@TimeF@16:30-17:30 LocationF@Room D312B (Seminar Room), Institute
of Statistical Mathematics TitleF@Review of earthquake early warning
from an engineering perspective AbstractF@ After
the concept of earthquake early warning (EEW) first appeared in the 1980s, we
now have officially working EEW systems around the world, such as, Japan,
Taiwan, Mexico, USA, Italy, and so on. The algorithms of EEW have evolved to
a large variety, including both on-site, regional and some hybrid methods.
The underlying seismic model ranges from simple point-source ground motion
prediction equations to sophisticated finite fault prediction models.
Recently, researchers have also proposed to develop real-time GPS based EEW
and purely data-driven seismic intensity prediction models. Besides the
scientific advances, engineering applications of EEW have became
another important research topic. In this talk, I will briefly go through all
the topics above in a practical implementation point of view, and highlight
some important challenge of EEW. The 66th
-1 SpeakerF@Dr.
Wu, Jing iInstitute
of Geology and Geophysics, Chinese Academy of Science, China E Associate Professorj DateF@29 August 2017@@@TimeF@16:00 -17:00 LocationF@Room D312B (Seminar Room), Institute
of Statistical Mathematics TitleF@Seismicity and Seismic Anisotropy
beneath eastern Tibet AbstractF@ Eastern
Tibet is one of the most tectonically active areas in Chinese Mainland. Songpan-Ganzi Block, Longmenshan
Orogenic Belt, and Sichuan Basin are located in this area from west to east.
The uplifting mechanisms of eastern Tibet are hot debated in recent years. In
addition, a
series of great earthquakes in eastern Tibet (2008 Wenchuan Mw7.9, 2013
Lushan Mw6.6, and the most recent 2017 Jiuzhaigou
Mw6.5) show the urgent need for accurate seismicity detection, as we are
still not clear how aftershocks evolve because of the poor station coverage
and overlapping of aftershocks. Here,
I would like to present our studies in eastern Tibet, including seismic
anisotropy and seismicity detection. Crustal anisotropy are inversed
according to shear-wave splitting of Pms phase from
permanent station, and we observed that tectonic escaping, crustal flow, and
crustal shortening may contribute to the tectonic evolution in various
sub-areas in eastern Tibet. We also concentrated on the seismicity detection
of 2013 Lushan earthquakes, and obtained details of the spatial and temporal
aftershock evolution with the help of matched filter technique, suggesting
that afterslip is the potential mechanism
triggering Lushan aftershocks. In
order to understand more about eastern Tibet, we would keep on working in
this area by focusing on the SKS, SKKS, PKS (hereafter, XKS phase) splitting
and repeating earthquakes, which may reveal geodynamic processes in mantle
and fault slip rate respectively. -2
SpeakerF@Dr.
Mak, Sum iGerman
Research Centre for Geosciences (GFZ-Potsdam), Germany E Research Assistantj DateF@29 August 2017@@@TimeF@17:00 -18:00 LocationF@Room D312B (Seminar Room), Institute
of Statistical Mathematics TitleF@Empirical Validation of Seismic Hazard
Models AbstractF@ Seismic
hazard, for applications such as engineering structural design and insurance
loss estimation, is represented as a probabilistic forecast. The most common
form of seismic hazard representation is in the probability for a certain
level of ground motion exceedance. The hazard also varies spatially, forming
a hazard map. As
the amount of observation accumulates, recently there are more and more
attempts to statistically evaluate the performance of probabilistic seismic
hazard prediction using ground motion observations. This talk presents the
general theory of this type of studies, using the United States Geological
Survey National Seismic Hazard Maps as an example. The 65th
SpeakerF@Prof.
Liu, Jann-Yenq iInstitute
of Space Science, National Central University, Taiwan EProfessorj DateF@13 June 2017@@@TimeF@16:00-17:00 LocationF@Room A508 (Seminar Room), Institute of
Statistical Mathematics TitleF@Statistical Analyses on seismo-ionospheric disturbances and precursors of the 11
March 2011 M9.0 Tohoku Earthquake AbstractF@ Ground-based
observations of the GPS TEC (total electron content) and satellite probing of
radio occultation (RO) of FORMOSAT-3/COSMIC (F3/C) are employed to study the
co-seismic disturbances and precursors of the 11 March 2011 M9.0 Tohoku
earthquake. It is for the first
time the tsunami origin observed.
The horizontal propagation of seismo-traveling
ionospheric disturbances (STIDs) induced by tsunami and seismic waves of the
Tohoku earthquake are observed by the GPS TEC, while the associated vertical
propagation is probed by multi ground-based observations and F3/C RO
sounding. The raytracing and
beamforming techniques are used to find the propagation and origin of the
STIDs triggered by the seismic and tsunami waves. Meanwhile, z test and the
Receiver Operating Characteristic (ROC) curve are employed to find the
characteristic of the temporal SIPs (seismo-ionospheric
precursor) of the GIM (global ionosphere map) TEC associated with earthquakes
in Japan during 1998-2014. It is
found that anomalies appearing 3 days before the Tohoku earthquake well agree
with the characteristic, which suggests that the SIPs of the earthquake have
been observed. A global study on
the distribution of anomalies shows that the SIPs specifically and
continuously occur over the epicenter on 8 March 2011, 3 days prior to the
Tohoku earthquake. Finally, a
physical model of the ionosphere is used to reproduce the observed anomalies
and find possible causal of the Tohoku SIPs. The 64th
-1 SpeakerF@Prof.
Jiang, Changsheng iInstitute
of Geophysics, China Earthquake Administration, China E Research Professorj DateF@29 March 2017@@@TimeF@13:30 -14:30 LocationF@Room D312B (Seminar Room), Institute
of Statistical Mathematics TitleF@Assessment of earthquake monitoring
capability and score of seismic station detection capability in China Seismic
Network (2008~2015) AbstractF@ In
order to scientifically assess the earthquake monitoring capability of China
Seismic Network (CSN), we investigated the seismic observation date of CSN
with total 1001 stations considered during the period from 2008/10/01 to
2015/09/17. The distribution of seismic detection probability (PE) and the
minimum magnitude of completeness (MP) were analyzed by using the method of
"Probability-based magnitude of completeness" (PMC). In addition to
mapping the seismic monitoring capability for entire CSN, we developed a new
method named gseismic monitoring capability scaleh, and defined the seismic
detection capability scale Dscore to analyze the
statistical characters and spatial distribution of the seismic detection
capabilities for each national and regional stations, which based on the
amplitude contour curves. Additionally, the method of setting the "best
objective function" of seismic detection capability was used to simulate
the seismic monitoring capability improvement of CSN obtained by improving
the conditions of observation. -2
SpeakerF@Prof.
Chen, Shi iInstitute
of Geophysics, China Earthquake Administration, China E Research Professorj DateF@29 March 2017@@@TimeF@14:30 -15:30 LocationF@Room D312B (Seminar Room), Institute
of Statistical Mathematics TitleF@Gravity changes before and after the
2015 Mw 7.8 Gorkha, Nepal and the 2008 Mw 7.9 Wenchuan, China earthquakes AbstractF@ Absolute
gravity measurements at four stations in southern Tibet show significant
gravity increase from 2011 to 2013, up to ~22 ΚGals
at the Shigatse station. Here we report new
measurements at the Shigatse station conducted in 2016, which show that the
gravity increase ended after the 2015 Nepal Mw 7.8 earthquake. Similar
gravity changes are measured at the Pixian absolute gravimetry station near
the epicenter of the 2008 Wenchuan Mw 7.9 earthquake, where 17 absolute
gravity measurements have been conducted since 2002, including four
pre-earthquake measurements that show ~30 ΚGals
increase from 2002 to 2008. The trend of gravity increase ended after the
Wenchuan earthquake. We analyzed the gravity effects from ground vertical
motions using data from continuous GPS stations collocated with these
absolute gravimetry stations, and surficial and hydrological processes using
local hydrological data. We found that these effects are much smaller than
the observed gravity increase before the earthquakes, and suggest that the
pre-earthquake gravity increase may be caused by strain and mass (fluid)
transfer in broad seismic source regions. Further studies are needed to
validate such pre-earthquake gravity changes, which however are difficult to
be resolved from space-based gravity models. The 63rd
SpeakerF@Prof.
Zhou, Shiyong iSchool
of Earth and Space Sciences, Peking University, China EProfessorj DateF@18 January 2017@@@TimeF@16:00-17:00 LocationF@Room A504 (Seminar Room), Institute of
Statistical Mathematics TitleF@Could the abnormal seismicity increase
triggered remotely by great earthquakes be used to judge the regional
earthquake risk? AbstractF@ We
study the possible dynamic triggering effect in Northern China, including
Tangshan area, when the Japan Tohoku M_w 9.0
earthquake happened at March 11th, 2011(In short, Japan Tohoku earthquake).
We use Time-Space Epidemic Type Aftershock Sequence Model (Time-Space ETAS
model) as the seismicity statistic model in this research, using Stochastic
Declustering method and Gauss Kernel function to get Time-Space background
seismicity variation image on the target area. Thus
this research may find out whether the area with large co-seismic
displacement would have sudden abnormal seismicity increase. As a result, the
Japan Tohoku earthquake has little effect on the total and background
seismicity of Tangshan area, which means that the seismic structure of Tangshan
area is fundamentally stable. However, when we did research on the possible
dynamic triggering effect in Southwestern China, we found that seismicity on
some place in Sichuan and Yunnan has sudden abnormally increased almost at
the same time when 2004 Sumatra M_w 9.2 earthquake
(In short, 2004 Sumatra earthquake) happened. That is the statistic
phenomenon which shows the existence of co-seismic dynamic triggering. This
research helps to find out the exact position of the high abnormal seismicity
area in its time image. Besides, this time image can also help to detect
whether this high gabnormalh seismicity in the picture is really abnormal or
is triggered by certain large earthquake or not. The 62nd
-1 SpeakerF@Dr.
Helmstetter, Agnès iInstitut des
Sciences de la Terre, France EResearch
fellowj DateF@26 October 2016@@@TimeF@15:00 -16:00 LocationF@Room D312B (Seminar Room), Institute
of Statistical Mathematics TitleF@Repeating icequakes AbstractF@ We
have detected repeating icequakes on three different sites
: an alpine glacier (Argentière, massif du
Mont-Blanc, France), near the base of the western margin of the Greenland Ice
Sheet, and on a rock-glacier (Gugla, Valais,
Switzerland). Repeating icequakes are events with very similar waveforms,
located at the base of a glacier, with quasi-periodic recurrence times of the
order of minutes or hours, and progressive changes in magnitude. The activity
of each cluster is intermittent. Burst-like episodes can last for a few hours
or months, and then disappear. In greenland,
temporal changes of inter-event times and magnitudes are correlated with
temperature, because surface meltwater yields an increase in basal water
pressure and in glacier flow velocity. But each cluster reacts differently to
temperature changes, probably because the connectivity to the subglacial
drainage system is different for each asperity. In contrast, we observed no
correlation between temperature and repeating icequakes at Glacier d'Argentière and at Gugla rock
Glacier. However, we observed bursts of repeating icequakes at Gugla triggered by snow falls. We suggest that the snow
weight may have induced a transition between aseismic slip and unstable
stick-slip. In addition to repeating basal icequakes, we also detected swarms
of icequakes induced by crevasse opening, probably promoted by melt-water
flow. These swarms of icequakes have very different statistical distributions
in time, space and magnitude compared with repeating icequakes. Their
recurrence times are power law distributed, their magnitudes obey the
Gutenberg-Richter law, and the size of each cluster is several tens of
meters. These different patterns may help to identify the triggering
mechanisms of earthquake swarms, and to discriminate between fluid flow and
aseismic slip. -2
SpeakerF@Dr.
Harte, David iGNS
Science, New Zealand EStatistical
Seismologist and Hazard Modellerj DateF@26 October 2016@@@TimeF@16:00 -17:00 LocationF@Room D312B (Seminar Room), Institute
of Statistical Mathematics TitleF@Determining the Uncertainty in
Earthquake Forecasts AbstractF@ Forecasts
based on a self-exciting model, like ETAS, are often produced by simulation.
From these simulations, an empirical probability distribution can be derived
for a forecast in a specified space-time-magnitude volume. We
will show that the forecast distribution can be characterised
by probability generating functions. This shows how deeply complex the
dependency structure is in such a model. While of theoretical interest, they
remain intractable to me in a practical sense. We
then consider whether the forecast distribution can be approximated, using
less computation than that required for simulation, by a "standard
" multi-parameter probability distribution. The multiple parameters gives us the ability to at least fit a distribution with
comparable mean and variance to that of the forecast distribution. One of the
main questions is how to determine the forecast mean, and then given the
mean, the variance. The 61st
SpeakerF@Dr.
Helmstetter, Agnès iInstitut des
Sciences de la Terre, France EResearch
fellowj DateF@11 October 2016@@@TimeF@16:00-17:00 LocationF@Room A504 (Seminar Room), Institute of
Statistical Mathematics TitleF@Adaptive smoothing of seismicity in
time, space and magnitude for long-term and short-term earthquake forecasts AbstractF@ We
present new methods for long-term and short-term earthquake forecasting that
employ space, time, and magnitude kernels to smooth seismicity. These
forecasts are applied to Californian and Japan seismicity and compared with
other models. Our models are purely statistical and rely on very few
assumptions about seismicity. In particular, we do not use Omori-Utsu law. The magnitude distribution is either assumed to
follow the
Gutenberg-Richter law or is estimated non-parametrically with kernels. We
employ adaptive kernels of variable bandwidths to estimate seismicity in
space, time, and magnitude bins. For long-term forecasts, the long-term rate
in each spatial cell is defined as the median value of the temporal history
of the smoothed seismicity rate in this cell, circumventing the relatively
subjective choice of a declustering algorithm. For
short-term forecasts, we simply assume persistence, that is, a constant rate
over short time windows. Our long-term forecast performs slightly better than
our previous forecast based on spatially smoothing a declustered
catalog. Our short-term forecasts are compared with those of the
epidemic-type aftershock sequence (ETAS) model. Although our new methods are
simpler and require fewer parameters than ETAS, the obtained probability
gains are surprisingly close. Nonetheless, ETAS performs significantly better
in most comparisons,
and the kernel model with a Gutenberg-Richter law attains
larger gains than the kernel model that non-parametrically estimates the
magnitude distribution. Finally, we show that combining ETAS and kernel model
forecasts, by simply averaging the expected rate in each bin, can provide
greater predictive skill than ETAS or the kernel models can achieve
individually. The 60th
SpeakerF@Dr.
Hasih Pratiwi iSebelas
Maret University, Surakarta, Indonesia E
Lecturerj DateF@30 August 2016@@@TimeF@16:00-17:00 LocationF@Room A504 (Seminar Room), Institute of
Statistical Mathematics TitleF@ESTIMATING EARTHQUAKE RISK BY USING
EPIDEMIC TYPE AFTERSHOCK SEQUENCE MODEL APPROACH (Case Study in Java Island,
Indonesia) (Hasih
Pratiwi and Respatiwulan) AbstractF@ Physical
losses caused by earthquakes are death or casualties and damage to buildings
and areas. Therefore, efforts to reduce the risk of earthquake are very
necessary. Relating to risk or loss generated by earthquake it is of course
does not get out of insurance world. Insurance as nonbank financial
institution can give guarantee or protection as done by banking sector. This
research discusses a method to estimate earthquake risk by using epidemic
type aftershock sequence model. Calculation of earthquake risk can be
determined through a damage probability matrix. The information contained in
the damage probability matrix and in the damage ratios can be combined for
defining the mean damage ratio. Then, based on the estimation of intensity
function in epidemic type aftershock sequence model we can formulate the
expected annual damage ratio, and the existing method for calculating
earthquake risk is modified to obtain earthquake insurance premium rates. We
use earthquakes data in Java Island obtained from U.S. Geological Survey
which consists of time of occurrence, longitude, latitude, magnitude, depth,
and catalogue source. The time span of this research is from January 1, 1973,
to December 31, 2010. Zonation map of earthquake generated in this research
is different from the zonation map SNI 2010 issued by Indonesian Ministry of
Public Works. The difference lies on the distribution of earthquake zone,
especially in regencies and cities with high risk. The earthquake insurance
premium rates for high and medium intensities obtained from this research are
significantly greater than the premium rates issued by PT Reasuransi
Maipark Indonesia. The current premium rates are
relatively small when compared with the rates in Turkey and from this
research. Keywords:
earthquake insurance, intensity function, epidemic type aftershock sequence
model, damage probability matrix. The 59th
SpeakerF@Prof.
Chen, Yuh-Ing iInstitute
of Statistics, National Central University, Taiwan E Distinguished Professorj DateF@19 July 2016@@@TimeF@16:00-17:00 LocationF@Room D312A (Seminar Room), Institute
of Statistical Mathematics TitleF@Statistical evaluation of short-term
hazard of earthquakes after 1999 M 7.3 Chi-Chi shock in Taiwan AbstractF@ The
temporal-spatial hazard of the earthquakes in a continental region of Taiwan
after the 1999 September 21 MW =7.7 Chi-Chi shock is investigated. The Reasenberg-Jones (RJ) model (Reasenberg
and Jones, 1989) that combines the frequency-magnitude distribution
(Gutenberg and Richter, 1944) and time-decaying occurrence rate (Utsu et al., 1995) is conventionally employed for
assessing the earthquake hazard after a large shock (Wiemer, 2000). However,
it is found that the b values in the frequency-magnitude distribution of the
earthquakes in the studyregion dramatically
decreased from background values after the Chi-Chi shock, and then gradually
increased up. The observation of a time-dependent distribution of magnitude
motivated us to propose a modified RJ model (MRJ) to assess the earthquake
hazard (Chen et al. 2015). To incorporate the possible impact of previous
large earthquakes on thefollowing ones, a
simplified epidemic-type aftershock sequence (ETAS) model (Ogata, 1988, Ogata
and Zhunag, 2006) is further considered. A modified
ETAS (METAS) model that combines the simplified ETAS model and the
time-dependent distribution of magnitude is then suggested for the hazard
evaluation. The MRJ and METAS models are further separately used to make
one-day forecast of large earthquakes in the study region. To depict the
potential rupture area for future large earthquakes, we also develop the
space-time MRJ and METAS models and construct the corresponding relative
hazard (RH) maps. The Receiver Operating Characteristics (ROC) curves (Swets,
1988) demonstrate that the RH map based on the MRJ model is as good as the
one based on the METAS model for exploring the spatial hazard of earthquakes
in a short time after the Chi-Chi shock. The 58th
SpeakerF@Dr.
Zhuang, Jiancang iAssociate Prof. of ISMj DateF@29 June 2016@@@TimeF@16:00-16:40 LocationF@Room D313ED314 (Seminar Room), Institute of
Statistical Mathematics @ISM@Statistical
Mathematics Seminar 2016 TitleF@Replenishing missing data in the
observation record of mark point processes AbstractF@ This
presentation illustrates a fast approach for replenishing missing data in the
record of a temporal point process with time independent marks. The basis of
this method is that, if such a point process is completely observed, it can
be transformed into a homogeneous Poisson process by using a biscale empirical transformation. This approach includes
three key steps: (1) Obtain the transformed process by using the empirical
transformation and find a time-mark range that likely contains missing
events; (2) Estimate a new empirical distribution function based on the data
in the time-mark range inside which the events are supposed to be completely
observed; (3) Generate events in the missing region. This method is tested on
a synthetic dataset and applied to the data missing problem in the JMA record
of the Kumamoto aftershock sequence, occurring from 2016-4-15 in Japan. The
influence of missing data on the MLE of the ETAS parameters is studied by
comparing the analysis results on the original and replenished datasets. The
results show that the MLEs of the ETAS parameters vary when the ETAS model is
fitted to the recorded catalog with different cut-off magnitudes, while when
the replenished dataset is used the MLE of the ETAS parameters keep stable. The 57th SpeakerF@Dr.
Shcherbakov, Robert iDepartment
of Earth Sciences, Western University(Ontario), Canada E Associate Professor DateF@22 June 2016@@@TimeF@16:40-17:20 LocationF@Room D313ED314 (Seminar Room), Institute of
Statistical Mathematics @ISM@Statistical
Mathematics Seminar 2016 TitleF@Statistics and physics of aftershocks AbstractF@ Aftershocks
are ubiquitous in nature. They are the manifestation of relaxation phenomena
observed in various physical systems. In the studies of seismicity,
aftershock sequences are observed after moderate to large main shocks.
Empirical observations reveal that aftershocks obey power-law scaling with
respect to their energies (seismic moments) which in magnitude domain can be
modelled by the Gutenberg-Richter law. The decay rate of aftershocks above a
certain magnitude is typically inversely proportional to the time since the
main shock and is approximated by the modified Omori law. The largest
aftershocks in a sequence constitute significant hazard and can inflict
additional damage to infrastructure that is already affected by the main
shock. Therefore, the estimation of the magnitude of a possible largest
aftershock in a sequence is of high importance. In this presentation, a
Bayesian predictive distribution and the corresponding confidence intervals
for the magnitude of the largest expected aftershock in a sequence are
derived using the framework of Bayesian analysis and extreme value
statistics. The analysis is applied to several well-known aftershock
sequences world-wide to construct retrospectively the confidence intervals
for the magnitude of the subsequent largest aftershock by using the
statistics of early aftershocks in the sequences. In order to infer the
physical mechanisms of triggering and time delays responsible for the
occurrence of aftershocks, a nonlinear viscoelastic slider-block model is considered.
It is shown that nonlinear viscoelasticity plays a critical role in the
triggering of aftershocks. The model reproduces several empirical laws
describing the statistics of aftershocks, which are observed in the studies
of systems with relaxation dynamics, specifically, for earthquakes. The 56th
SpeakerF@Dr.
Strader, Anne iGFZ German
Research Centre for Geosciences, Germany E
Post-doctoral fellowj DateF@7 June 2016@@@TimeF@16:00-17:00 LocationF@Room A508 (Seminar Room), Institute of
Statistical Mathematics TitleF@Evaluation of Current CSEP Testing
Methods: Case Studies for Japan and California AbstractF@ The
Collaboratory for the Study of Earthquake Predictability (CSEP) was developed
to rigorously test earthquake forecasts retrospectively and prospectively
through reproducible, completely transparent experiments within a controlled
environment (Zechar et al., 2010).
Forecasts are individually evaluated using a set of likelihood-based
consistency tests, which measure the consistency between the number, spatial
and magnitude distribution of the observed and forecasted seismicity during
the testing period (Schorlemmer et al., 2007; Zechar et al., 2010).
Additionally, the classical paired t-test and non-parametric w-test are used
to directly compare two forecasts' performances at target earthquake
locations. These tests rely on a hypothesis testing framework, resulting in a
final decision (to reject or not reject a forecast), rather than quantifying
the model's lack-of-fit or localized performance. Residual methods are
employed by the CSEP to discern spatial variation in model performance
compared to the observed seismicity distribution and other models, but are
not currently incorporated into decision-making processes. To illustrate what
can be learned from commonly utilized current CSEP tests, we present two case
studies. The first is a retrospective evaluation of a rate-and-state forecast
for the Japan CSEP testing classes, where spatiotemporal seismicity rate
fluctuations are inverted for Coulomb stress changes. Although the model
underestimates the number of earthquakes following the M9.0 Tohoku mainshock,
it displays positive information gain over baseline ETAS seismicity rates
(Ogata, 2011) within the rupture region. The second forecasting experiment is
a continued prospective evaluation of the time-independent California
earthquake forecasts tested in the Regional Earthquake Likelihood Model
(RELM) experiment, from 2011-2016. Additionally, we test two models developed
by the United States Geological Survey (USGS): the time-dependent Uniform
California Earthquake Rupture Forecast (UCERF2) and time-independent National
Seismic Hazard Mapping Project (NSHMP) models. To reduce bias from expert-based
decision making utilized in current testing methods, we introduce the
framework of a Dynamic Risk Quantification (DRQ) platform, that will be
developed to combine and optimize ensemble forecasts and hazard models using
a data-driven approach, and updated as new data become available. The 55th
-1 SpeakerF@Guo,
Yicun iSchool
of Earth and Space Sciences, Peking University, China E PhD studentj DateF@22 March 2016@@@TimeF@16:00 -17:00 LocationF@Room D312B (Seminar Room), Institute
of Statistical Mathematics TitleF@Iterative finiteETAS
model and some results of the histETAS model of the
North China Craton AbstractF@ We
introduce a iterative algorithm to refine the finite
sources of main shocks in the finite ETAS model, in which the weight of
triggering ability for each subfault is its
productivity divided by the whole productivity of the main shock. Also we apply histETAS model to
North China Craton. It turns out that the b value and background seismicity
patterns coincide with the static coulomb stress change induced by historical
big earthquakes, and p value variation in space is in agreement with velocity
structure of the lithosphere under major fault zones. Therefore
we infer the statistical characteristics of seismicity reflect the properties
of medium to some extent, and make some discussion of future earthquake
hazard. -2
SpeakerF@Prof.
Ogata, Yosihiko iEmeritus
Professor of ISM; Project Researcher of Earthquake Research Institute,
University of Tokyoj DateF@22 March 2016@@@TimeF@17:00 -18:00 LocationF@Room D312B (Seminar Room), Institute of
Statistical Mathematics TitleF@3D spatial models for seismicity
beneath Kanto region AbstractF@ Development
of point-process models for the seismicity in 3D space (longitude, latitude
and depth) beneath Kanto area down to 100km depth is more required than for
seismicity in the rest of the world. This is because the three tectonic
plates meet beneath Kanto plain; and interactions among the interplate and intraplate earthquakes are too complex to
make detailed analysis and forecasts in 2D space that ignores the depths. We
consider the 3D hierarchical space-time ETAS (epidemic-type aftershock
sequence) model. Among the characterizing parameters, the background
seismicity rate \mu and aftershock productivity K are highly sensitive to the
locations, so that these parameters should be location-dependent.
Furthermore, the impact of the 2011 Tohoku-Oki earthquake of M9.0 to the
seismicity beneath the Kanto region has been so large that we need a
space-time function for representing the amount of the induced seismicity
beneath Kanto by this giant earthquake. Specifically, we adopt the Omori-Utsu function as the effect of induced earthquakes,
started after the occurrence time of the Tohoku-Oki earthquake, where we
assume that the aftershock productivity parameter KM9 of the Omori-Utsu function is also location-dependent. For forecasting
future large earthquakes, we further need to estimate the location-dependent
b-value of the Gutenberg-Richter law. The
spatial variations of the characteristic parameters \mu(x,y,z), K(x,y,z) , KM9(x,y,z) and b(x,y,z) of our
model are inverted to visualize the regional changes of the seismic activity.
For this objective, we make 3D Delaunay tessellation of the Kanto volume,
where every earthquake belongs to vertices of a tetrahedron. Each of the above mentioned parameter function is a 3-dimensional
piecewise linear function defined by the values at the four Delaunay
tetrahedral vertices. The
estimates of the focal parameter functions are obtained by an optimal
trade-off between the goodness of fit to the earthquake data and the
smoothness constraints (or roughness penalties) of the variations of
parameter values. Strengths of the constraints of or the penalties to
respective parameter functions can be simultaneously adjusted from the data
by means of an empirical Bayesian method using the Akaikefs Bayesian
information criterion (ABIC). Key
words: ABIC, aftershock productivity, background seismicity rate, b-values,
Delaunay function, Delaunay tessellation, empirical Bayesian method, Omori-Utsu function for induced seismicity, penalized
log-likelihood. The 54th
SpeakerF@Dr.
Wang, Ting iDepartment
of Mathematics and Statistics, University of Otago, New Zealand ELecturerj
DateF@9 February 2016@@@TimeF@16:00 -17:00 LocationF@Room D312B (Seminar Room), Institute
of Statistical Mathematics TitleF@Identification of seismic phases using
Markov-modulated marked Hawkes processes AbstractF@ Based
on a temporal Markov-modulated Hawkes process that we developed earlier to
investigate long-term patterns of seismic activity with multiple mainshocks,
we made extensions to this temporal model to include spatial variation of the
seismic activity and the earthquake magnitudes. Our aim is to categorize
spatiotemporal seismic hazards holistically, using the entire earthquake
record in a selected region to identify patterns correlated with subsequent
large earthquakes, rather than the traditional way of selecting individual
foreshock-mainshock or mainshock-aftershock sequences. I will use several
case studies to illustrate how this model works and discuss about the
problems that we had with the model fitting. The 53rd
-1 SpeakerF@Dr.
Yin, Fengling iInstitute
of Geophysics, China Earthquake Administration, China EAssistant Professorj DateF@27 January 2016@@@TimeF@13:30 -14:30 LocationF@Room D312B (Seminar Room), Institute
of Statistical Mathematics TitleF@Coulomb stress evolution along the
middle segment of Redriver fault zone over the past
180 Years due to coseismic, postseismic
and interseismic deformation iYin,Fengling, Jiang,
Changsheng and Han, Liboj AbstractF@ The Redriver fault zone, for it being as the boundary of
Sichuan-Yunnan rhombic block and southeastern margin of the Tibetan plateau,
and near the Central Yunnan city group, its seismic activity deserves
attention. The Redriver fault zone within Yunnan
has experienced at least 9 earthquakes of M≥6 in recent 180 years. Using
stratified viscoelastic lithospheric model, we calculate the coulomb failure
stress evolution along the redriver fault zone over
the past 180 years due to coseismic, postseismic and interseismic
deformation. By analyzing 25 earthquakes occurred along the Redriver fault zone and ajacent
faults, we find that the middle segment of Redriver
fault zone remains low seismic activity in recent two hundred years. This is
consistent with the observed eseismic gapf as earthquake catalog shows.
Assuming there is no earthquake within about 30 years around the Redriver fault zone, this fseismic gapf may remain due to
postseismic and interseismic
deformation. -2
SpeakerF@Dr.
Taroni, Matteo iIstituto Nazionale
di Geofisica e Vulcanologia,
Rome, Italy E
Post-doctoral fellowj DateF@27 January 2016@@@TimeF@14:30 -15:30 LocationF@Room D312B (Seminar Room), Institute
of Statistical Mathematics TitleF@Some recent techniques to improve
earthquake forecasting (Taroni, Matteo, Marzocchi, Warner, Zechar, Jeremy and
Werner, Maximilian) AbstractF@ In
this presentation I will show some recent results regarding the earthquake
forecasting techniques. In particular I will show: i) How
to consider aftershocks and foreshocks in the seismic hazard computation,
with an application to the Italian case. ii)
How to merge different catalogues to obtain a better estimation of the
Tapered Gutenberg-Richter distribution parameters, with an application to the
global and Italian case. iii)
How to create an ensemble model to improve the performance of the short-term
earthquake forecasting models, with an application to the New Zealand case. The 52nd SpeakerF@Dr.
Guillas, Serge iDepartment of Statistical Science,
University College London, U.K. E
Readerj DateF@17 November 2015@@@TimeF@16:00-17:00 LocationF@Room A508 (Seminar Room), Institute of
Statistical Mathematics TitleF@Dimension reduction for the
quantification of uncertainties in tsunami and climate models AbstractF@ VOLNA,
a nonlinear shallow water equations solver, produces high resolution
simulations of earthquake-generated tsunamis. However, the uncertainties in
the bathymetry (from irregularly-spaced observations) have an impact on
tsunami waves. We first employ a stochastic partial differential equation
(SPDE) approach to quantify uncertainties in these boundary fields. These
uncertainties are then parametrized to be used as inputs of an emulator of
VOLNA. However, the dimension of these boundary fields is large and must be
reduced. We apply the gradient-based kernel dimension reduction approach (gKDR) by Fukumizu and Leng
(2014) and construct an Gaussian Process emulator on
this reduced input space. We propagate uncertainties in the bathymetry to
obtain an improved probabilistic assessment of tsunami hazard. In a
separate climate application, we employ the Bayesian calibration of complex
computer models using Gaussian Processes, introduced by Kennedy and O'Hagan
(2001), that has proven to be effective in a wide range of applications.
However, the size of the outputs, such as climate models' spherical outputs,
leads to computational challenges in implementing this framework. Covariance
models for data distributed on the sphere also present additional challenges
compared to covariance models for data distributed over an
Euclidean space. To overcome these various challenges, we make use of the
spherical harmonics (SHs) decomposition of the computer model output, and
then apply a Gaussian process assumption to the coefficients in the
decomposition. Furthermore, using the SPDE approach, we can capture
non-stationarity in the spatial process. Hence, we generalize further the
spherical correlation framework by expanding the SPDE parameters used to
quantify the nonstationary behavior in the functional space spanned by the
SHs. We illustrate our findings on several synthetic examples. In particular,
our method can outperform the calibration based on principal components. Finally we show that our technique has the potential to
calibrate the Whole Atmosphere Community Climate Model (WACCM). The 51st
-1 SpeakerF@Dr.
Gerstenberger, Matthew iGNS
Science, New Zealand ERisk and
Engineering Team Leader, Senior Seismologistj
DateF@1 September 2015@@@TimeF@16:00-17:00 LocationF@Room D312B (Seminar Room), Institute
of Statistical Mathematics TitleF@The New Zealand National Seismic
Hazard Model: Rethinking PSHA AbstractF@ We
are currently revising the New Zealand National Seismic Hazard Model. In this
revision we are exploring some of the fundamental assumptions of the model
and investigating how uncertainties in earthquake source and ground motion
estimation propagate through to the end uses of the model. Uncertainties
related to the source modelling that come from a paucity of data and from
different methods that can be used to model the seismic sources are currently
not fully quantified in the way we model seismic hazard. Additionally,
seismic sources are generally assumed to be a stationary Poisson process and
earthquake clustering is ignored. Including these uncertainties in the way
risk is modelled based on the outputs of the National Seismic Hazard Model
will likely lead to more robust estimates of risk for use by industry and in
the development of design standards. Notice:
This email and any attachments are confidential. If received in error please
destroy and immediately notify us. Do not copy or disclose the contents. -2
SpeakerF@Dr.
Chen, Shi iInstitute of
Geophysics, China Earthquake Administration, China EAssociate Professorj DateF@1 September 2015@@@TimeF@17:00-18:00 LocationF@Room D312B (Seminar Room), Institute
of Statistical Mathematics TitleF@A study on the regional gravity
changes before large earthquakes from the statistical perspectives AbstractF@ The
repeated gravity surveys, also called mobile gravity measurements, have been
carried out for decades in the Chinese mainland. Significant gravity changes
have been detected before some cases of great earthquakes, such as the 1976
Tangshan Ms7.8 Earthquake, 2008 Wenchuan Ms8.0 earthquake, etc. The main aim
of the repeated gravity surveys is to monitor the geophysical field
variations in some major seismic hazard zones. By this sort of in-situ
gravimetric network, the yearly changes of regional gravity can be obtained.
Through the Molchan Error Diagram tests, we found that observed gravity
changes are statistically correlated to the occurrence of future large
earthquakes, i.e., the gravity changes are more powerful than a seismicity
rate model in forecasting large earthquakes. These results imply that gravity
changes before earthquake include precursory information of future large
earthquakes. Key
words: Gravity changes, Earthquake prediction, Molchan error diagram,
Repeated gravity measurement, Chinese mainland. The 50th
SpeakerF@Dr.
Kagan, Yan Y. iDepartment
of Earth and Space Sciences, University of California, Los Angeles (UCLA) E Researcherj DateF@4 August 2015@@@TimeF@16:00-18:00 LocationF@Room D208 (Conference room), Institute
of Statistical Mathematics TitleF@Statistics of earthquake focal
mechanisms AbstractF@ I.
Double-couple earthquake source: symmetry and rotation We
analyze earthquake focal mechanisms and their forecast both analytically and
statistically. This problem is complex because source mechanisms are
tensor-valued variables, thus their analysis requires applying sophisticated
mathematical and statistical tools, many of which are not yet fully
developed. We describe general and statistical properties of the seismic
moment tensor, in particular, its most important form -- the double-couple
(DC) mechanism. We establish a method for the analysis of a DC source, based
on the quaternion technique, and then apply quaternions for the statistical
analysis of earthquake catalogs. The important property of the focal
mechanism is its symmetry. We describe the classification of the mechanism
symmetry and the dependence of the DC orientation on its symmetry. Four
rotations exist in a general case of a DC with the nodal-plane ambiguity,
there are two transformations if the fault plane is known, and there is one
rotation if the sides of the fault plane are known. A statistical analysis of
symmetrical objects has long been the subject of crystallographic texture
investigations. We describe the application of crystallographic methods to
focal mechanism analysis and consider theoretical statistical distributions
appropriate for the DC orientation approximation. Uniform random rotation
distributions for various DC sources are discussed, as well as two
non-uniform distributions: the rotational Cauchy and von Mises-Fisher. We
discuss how the parameters of these rotations can be estimated by a
statistical analysis of earthquake source properties in global seismicity
using the GCMT catalog. We also show how earthquake focal mechanism
orientations can be displayed on the Rodrigues vector space. II.
Statistical earthquake focal mechanism forecasts In
the focal mechanism forecast, the sum of normalized seismic moment tensors
within a 1000 km radius is calculated and the P- and T-axes for the predicted
focal mechanism are evaluated on the basis of the sum (Kagan and Jackson
1994, JGR). Simultaneously we calculate an average rotation angle between the
forecasted mechanism and all the surrounding mechanisms. This average angle
shows tectonic complexity of a region and indicates the accuracy of the
prediction. Recent interest by CSEP and GEM has motivated some improvements,
particularly a desire to extend the previous forecast to polar and near-polar
regions. The major problem in extending the forecast is the focal mechanism
calculation on a spherical surface. In a modified program focal mechanisms
have been projected on a plane tangent to a sphere at a forecast point. A
comparison with the old 75S-75N forecast shows that in equatorial regions the
forecasted focal mechanisms are almost the same, and the difference in the
forecasted focal mechanisms rotation angle is close to zero. However, closer
to the 75 latitude degree the difference in the
rotation angle is large (around a factor 1.5 in some places). The Gamma-index
was calculated for the average focal mechanism moment. A non-zero Index
indicates that earthquake focal mechanisms around the forecast point have different
orientations. Thus deformation complexity displays
itself both in the average rotation angle and in the Index. However,
sometimes the rotation angle is close to zero, whereas the Index is large,
testifying to a large CLVD presence. Both new 0.5x0.5 and 0.1x0.1 degree forecasts are posted at
http://eq.ess.ucla.edu/~kagan/glob_gcmt_index.html III.
Evaluating focal mechanisms forecast skill We
discuss the ways to test the focal mechanism forecast efficiency. We start
with several verification methods, first based on ad-hoc, empirical
assumptions. However their performance is
questionable. In the new work we apply a conventional likelihood method to
measure the skill of a forecast. The advantage of such an approach is that an
earthquake rate prediction can be adequately combined with a focal mechanism
forecast, if both are based on the likelihood scores. This results in a
general forecast optimization. To calculate the likelihood score we need to
compare actual forecasts or occurrences of predicted events with the null
hypothesis that the mechanism's 3-D orientation is random. To better
understand the resulting complexities we calculate
the information (likelihood) score for two rotational distributions (Cauchy
and von Mises-Fisher), which are used to approximate earthquake source
orientation patterns. We then calculate the likelihood score for earthquake
source forecasts and for their validation by future seismicity data. Several
issues need to be explored when analyzing observational results: their
dependence on the forecast and data resolution, internal dependence of scores
on the forecasted angle, and random variability of likelihood scores. We
propose a preliminary solution to these complex problems, as these issues
need to be explored by a more extensive theoretical and statistical analysis. IV.
Future focal mechanisms studies 1.
Statistical earthquake focal mechanism forecasts, rigorous likelihood methods for
evaluating forecast skill. 2.
Likelihood analysis of GCMT catalog, including focal mechanisms. 3.
Focal mechanism clustering. 4.
Collapsing focal mechanism patterns. 5.
Influence of Earth surface on focal mechanisms interaction
(Morawiec,Ch8). 6. Integrating
Cauchy distribution on Rodrigues space, Morawiec, pp.116-119. 7.
Calculating Cauchy and von Mises-Fisher distributions for 120 degrees
rotation limit. 8.
Investigating the sign-change symmetry of a DC earthquake source. 9.
Studies of statistics of earthquake focal mechanisms in the Rodrigues space. 10.
Rotation-translation distribution of double-couples as different from
arbitrary symmetric deviatoric second-rank tensor. The 49th
SpeakerF@Prof.
Künsch, Hans R. iDepartment of Mathematics, ETH Zurich,
Switzerland E Emeritus
Professorj DateF@7 April 2015@@@TimeF@16:00-17:00 LocationF@Room D312B (Seminar Room), Institute
of Statistical Mathematics TitleF@Data assimilation in seismology ? AbstractF@ The accuracy
of weather forecasts has increased substantially over the past decades. This
is due to at least three factors: The increase in computing power which
allows a higher accuracy in solving the equations of the underlying physical
model, a denser set of observations of the state of the atmosphere and better
methods for data assimilation, that is the use of these observations to
adjust the initial conditions of the model sequentially. In order to
represent the uncertainty in assimilation and forecasting, ensembles are used
whose members represent different states of the atmosphere that are
compatible with the observations and the physical dynamics. Such ensemble
methods should be viewed as Monte Carlo methods which provide the link to
statistics. Recently
there has been interest in using these data assimilation tools also in
seismology in order to improve forecasts and quantify their uncertainty. In
this talk I will discuss some of the attempts in this direction. Time
permitting, I will also present some new ideas for ensemble data
assimilation. The 48th
SpeakerF@Dr.
Ishibe, Takeo iEarthquake Research Institute, The
University of Tokyo E Project
Researcherj DateF@24 February 2015@@@TimeF@16:00-17:00 LocationF@Room A508 (Seminar Room), Institute of
Statistical Mathematics TitleF@Overview of Seismicity Changes in
Inland Japan after the 2011 Tohoku-Oki Earthquake and Its Interpretation AbstractF@ In
this presentation, I overview the widespread changes in seismicity rate and
distribution of focal mechanism after the Tohoku-Oki earthquake (Mw9.0) and
summarize the possible contributing factors. In Tohoku, westward from the
Tohoku-Oki source, significant increases in seismicity rate were observed in
N. and S. Akita, SW off Oga peninsula, and Yamagata/Fukushima and
Ibaraki/Fukushima boundary regions as well as other surrounding areas. On the
other hand, aftershock activities in the source regions of recent large
earthquakes such as the 2008 Iwate-Miyagi earthquake have been suppressed. In
Kanto, southwest of the Tohoku-Oki source, interplate
earthquakes were typically activated, while belt-like seismicity along the
western edge of slab-slab contact zone and shallow earthquakes in some areas
were also activated. The
most plausible factor is the static changes in the Coulomb stress, which
seems to be valid for retrospectively forecasting the changes in seismicity
on some level, while some activated seismicity showed clear counter-evidence.
Remotely triggered local events, whose origin times are well coincided with
the arrivals of mainshock seismic waves, suggest that dynamic stress changes
also contribute. Some swarm-like activities, showing temporal expansion of
the focal area which is attributed to fluid diffusion, suggest that changes
in pore fluid pressure should be another possible factor. The contribution of
indirectly triggered earthquakes might be important in some regions because
stress changes imparted by neighboring indirect aftershocks could be comparable
with those from a distant mainshock. Postseisimc
slip and viscoelastic effect would play an important role for long-term
hazard assessments. The 47th
SpeakerF@Dr.
Segou, Margaret iNational
Observatory of Athens (Greece) E
Researcherj DateF@10 February 2015@@@TimeF@16:00-17:00 LocationF@4F Lounge, Institute of Statistical
Mathematics TitleF@The Future of Earthquake
Predictability AbstractF@ The
last decade dense seismological networks around the world provide the
opportunity to study more aftershock sequences in seismically active areas
across the world such as California (San Andreas Fault), Japan, New Zealand
(Canterbury Fault, Christchurch) and continental rift systems (Corinth Gulf,
Greece). The importance behind that is evident; the 2008 M7.9 Sichuan event
continues having catastrophic aftershocks (2013 Lushan M6.6) after five
years. The above provide the necessary motivation for geophysicists to develop
short and long-term earthquake forecasts for providing to scientists and the
public authoritative information on seismic hazard and answer ultimately the
question When the next big earthquake will occur. Static and dynamic
triggering are often described as the two primary mechanisms for earthquake
clustering in time and space. Recent studies have provided evidence that
physics-based earthquake forecast models, combining fault aging laws and the
static stress triggering hypothesis, can accurately predict (80%) transient
seismicity rates. Static triggering plays an important role in spatial
clustering at distances 2-3 rupture lengths away from the seismic source
whereas dynamic triggering studies usually focus on larger distances
(>1000 km). But how dependent are our calculations on our incomplete
knowledge of the ambient stress of a region? What are the implications behind
the time dependent fault behavior? The last two questions are the key for
reducing the uncertainties of physical forecast models. Quite often the
development of such quantitative and testable models is followed by extensive
statistical performance evaluation, which is critical for understanding their
merits and pitfalls. In
this seminar I focus on recent development on physics-based earthquake models
using worldwide examples and how they compare with statistical models.
Furthermore, I discuss how we can reduce their uncertainties and sketch the
future of our scientific predictability. Is it possible to hope on higher
information gains in the near future? and, How these
forecast models could be most effective in Japan? The 46th
-1 SpeakerF@Dr.
Kumazawa, Takao iProject Researcher of ISMj DateF@27 January 2015@@@TimeF@15:00-16:00 LocationF@Room D312B (Seminar Room), Institute
of Statistical Mathematics TitleF@Predicting Offshore Swarm Rate by
Volumetric Strain Changes in Izu Peninsula, Japan AbstractF@ The
eastern offshore of Izu peninsula is one of the well known
volcanic active regions in Japan, where magma intrusions have been observed
several times since 1980s monitored by strain-meters located nearby. Major
swarm activities have been synchronously associated with coseismic
and preseismic significant sizes of volumetric
strain changes (Earthquake Research Committee, 2010). We investigated the background
seismicity changes during these earthquake swarms using the nonstationary
ETAS model (Kumazawa and Ogata, 2013, 2014), and
have found the followings. The volumetric strain change data, modified by
removing the effect of earth tides and precipitation as well as removing coseismic jumps, have much higher cross-correlations to
the background rates of the ETAS model than to the whole seismicity rate
change of the ETAS. Furthermore the strain changes
precede the background seismicity by lag of about half a day. This relation
suggests an enhanced prediction of earthquakes in this region using
volumetric strain measurements. Thus we propose an
extended ETAS model where the background seismicity rate is predicted by the
time series of preceding volumetric strain changes. Our numerical results for
Izu region show consistent outcomes throughout the major swarms. -2
SpeakerF@Dr.
Wang, Ting iDepartment
of Mathematics and Statistics, University of Otago, New Zealand ELecturerj
DateF@27 January 2015@@@TimeF@16:30-17:30 LocationF@Room D312B (Seminar Room), Institute
of Statistical Mathematics TitleF@Marked point process modeling with
missing data in volcanic eruption records AbstractF@ Despite
ongoing efforts to compile new data, eruption records, particularly those of
earlier time periods, are pervasively incomplete. The probability of missing
an ancient eruption is much higher than a recent eruption. We consider
modeling both the times and sizes of the eruptions using a marked point
process. We propose to model the marks (the sizes of the events) as having a
time-varying distribution which takes the higher proportion of missing
smaller events in earlier records into consideration. We then estimate the
proportion of detected events over time based on the assumption that the most
recent record is complete and that the record of eruptions with the largest
size in the considered catalog is complete. With this information, we can
then estimate the true intensity of volcanic eruptions. The 45th
SpeakerF@Dr.
Schehr, Grégory iLaboratoire de
Physique Théorique et Modèles
Statistiques, Orsay-University Paris-Sud E CNRS-Researcherj DateF@14 October 2014@@@TimeF@11:00-12:00 LocationF@Room D312B (Seminar Room), Institute
of Statistical Mathematics TitleF@Exact Statistics of the Gap and Time
Interval Between the First Two Maxima of Random Walks and Lévy Flights AbstractF (PDF)
The 44th
-1 SpeakerF@Prof.
Zhou, Shiyong iSchool
of Earth and Space Sciences, Peking University, China EProfessor; Visiting Professor of ISM,
2014j DateF@5 August 2014@@@TimeF@16:00-17:00 LocationF@Room D312B (Seminar Room), Institute
of Statistical Mathematics TitleF@Seismicity simulation in Western
Sichuan of China based on the fault interactions and its implication on the
estimation of the regional earthquake risk AbstractF@ Seismicity
over 10000 years in Western Sichuan of China has been simulated based on the
mechanical synthetic seismicity model we developed. According to the analysis
of the simulated synthetic seismic catalogue , the
occurrence of strong earthquakes with Ms ≥710 in
the whole region of Western Sichuan is rather random , very close to the
Poisson process with seismic rate 010454Pyear , which means it is reasonable
to estimate the regional earthquake risk with Poisson model in Western
Sichuan. However, the occurrence of strong earthquakes with Ms ≥710 on the individual faults of Western Sichuan is
far from Poisson process
and could be predicted with a time2dependent prediction model. The fault
interaction matrices and earthquake transfer possibility matrices among the
faults in Western Sichuan have been calculated based on the analysis of the
simulated synthetic catalogues. We have also calculated the static change in
Coulomb failure stress (CFS) on one fault induced by a strong earthquake on
another fault in Western Sichuan to discuss the physical implications of the
earthquake transfer possibility matrices inferred from the synthetic
catalogue. Keywords:
Simulation of earthquake generation , Poisson model
, Coulomb stress , Seismic hazard -2
SpeakerF@Dr.
Wang, Dun iEarthquake
Research Institute, University of Tokyo E
JSPS Postdoctoralj DateF@5 August 2014@@@TimeF@17:00-18:00 LocationF@Room D312B (Seminar Room), Institute
of Statistical Mathematics TitleF@Rupture speeds for recent large
earthquakes AbstractF@ Studying
the rupture speeds of earthquakes is of broad interesting for earthquake
research because it has a large effect on the strong near-field shaking that
causes damage during earthquakes. Also rupture speed is a key observation for
understanding the controlling stresses and friction during an earthquake, yet
the speed and its variations are usually difficult to determine. Using only
far-field seismic waveforms, which is the only data available for many large
earthquakes, there are problems for estimating the rupture speed with
standard waveform inversions, due to trade-off between the rupture speed and
the slip location. Here
we applied a back projection method to estimate the rupture speeds of Mw ≥
7.5 strike-slip earthquakes since 2001 which could be analyzed using Hi-net
in Japan. We found that all events had very fast average rupture speeds of
3.0-6.0 km/s, which are near or greater than the local shear wave velocity (supershear). These values are faster than for thrust and
normal faulting earthquakes that generally rupture with speeds of 1.0-3.0
km/s. Considering the depth-dependent shear-wave velocity, the average
propagation speeds for all of the strike-slip events are closer to or greater
than the shear wave velocity. For large strike-slip events, transition from subshear to supershear usually
occurs within distances of 15 to 30 km from the initiation, which is probably
the reason for the scarcity of observed supershear
earthquakes for smaller magnitudes. Earthquakes
with supershear ruptures can cause more damage than
events with subshear ruptures because of the
concentration of energy in the forward direction of the rupture. Numerical
modeling shows strong focusing and other effects of energy at the rupture
front which can intensify the ground motions. A recent example is the April
13, 2010 Qinghai, China earthquake (Mw 6.9), where a moderate-size event
caused extensive damage in the Yushu region at the southeastern end of the
fault. Careful evaluation of long and straight strike-slip faults should be
emphasized for predicting strong ground motions due to supershear
rupture. The 43rd
SpeakerF@Dr.
Aiken, Chastity iGeorgia
Institute of Technology, U.S.A. E
National Science Foundation Graduate Fellow, ARCS Scholarj
DateF@8 July 2014@@@TimeF@16:00-18:00 LocationF@Room D312B (Seminar Room), Institute
of Statistical Mathematics TitleF@Triggered Seismic Activity in
Geothermal Regions and on Strike-Slip Faults AbstractF@ Dynamic
stresses caused by large earthquakes are capable of triggering a wide range
of seismic/aseismic responses at remote distances. These responses include
instantaneously triggered microearthquakes, deep tectonic tremor, earthquake
swarms, slow-slip events, and near-surface icequakes. Systematic studies of these triggered
phenomena not only help us to understand how large earthquakes affect
seismic/aseismic processes at remote distances but also help improve our
understanding of the necessary physical conditions responsible for the
generation of seismic activity.
In this talk I present two recent studies: (1) a comparison of triggered
microearthquakes in three geothermal regions of California and (2) a
comparison of triggered tremor on four strike-slip faults in the Western
Hemisphere. Triggered seismic
activity is characterized as being triggered by the surface waves of large,
distant earthquakes. Triggered
earthquakes in geothermal regions are generally small magnitude (M<4) and
have distinct P and S waves, whereas triggered tremor is a low-amplitude,
emergent signal with no distinct P wave.
After identifying the large earthquakes that trigger seismic activity,
we analyze and compare the peak ground velocities, seismic wave incidence
angles, amplitude spectra of all distant earthquakes we examined, as well as
the background activity in each region to determine the factors that promote
triggering in geothermal regions and on strike-slip faults. The 42nd
SpeakerF@Dr.
Aranha, Claus iGraduate
School of Systems and Information Engineering, University of Tsukuba E Assistant Professorj
DateF@27 May 2014@@@TimeF@16:00-17:00 LocationF@Room D312B (Seminar Room), Institute
of Statistical Mathematics TitleF@Using Evolutionary Algorithms to
optimize earthquake risk models: Early Ideas AbstractF@ Evolutionary
Algorithms are a class of meta-heuristics that use genetic principles to
sample good solutions from a search space. They have shown great promise in a
wide variety of optimization problems, specially in
problem domains where the search space is multi modal and/or non-continuous.
However, evolutionary algorithms have not yet seen a lot of use in the
optimization of statistical models for earthquake forecasting. Our goal is to
explore this combination. In
this talk, we will (briefly) explain what evolutionary algorithms are, and
then proceed to outline our early proposals and results regarding their use
for the generation of an RELM based earthquake forecast model. The 41st
-1 SpeakerF@Dr.
Wang, Min-Zhen iProject Researcher
of ISMj DateF@4 March 2014@@@TimeF@15:00 -16:00 LocationF@Room D312-B (Seminar Room), Institute
of Statistical Mathematics TitleF@Distributions on Torus, Cylinder and
Disc iWang, Min-Zhen and Shimizu, Kunioj AbstractF@ Statistics
for data which include angular observations is known as directional
statistics. Bivariate circular data such as wind directions measured at two
points in time are modeled by using bivariate circular distributions or
distributions on the torus. Likewise circular-linear data are modeled by
using distributions on the cylinder and disc. We propose some extensions of
distributions on the torus, cylinder and disc in the framework of directional
statistics.@A new
circular distribution (Wang and Shimizu, 2012) is also introduced, which is
obtained by applying the Mӧbius
transformation to a univariate cardioid random variable. The distribution
function, trigonometric moments, and conditions for unimodality and symmetry
are studied. Kato and Jones (2010) study a family of distributions which is
obtained by applying the Mӧbius
transformation to a von Mises random variable, and we discuss the
relationship between our model and the Kato--Jones model. The bivariate
circular case (Wang and Shimizu, 2012) which is generated from a
circular-circular structural model linked with Mӧbius
transformation or a method of trivariate reduction.
The joint probability density function, trigonometric moments and
circular-circular correlation coefficient are explicitly expressed. An
illustration is given for wind direction data at 6 a.m. and noon as an
application of the bivariate cardioid distribution. The distributions on the
cylinder we proposed is generated from a combination of von Mises and
transformed Kumaraswamy distributions. It is an extension of the Johnson and
Wehrly (1978) model. The marginal and conditional
distributions of the proposed distribution are given. A distribution using
the method of generating a cylindrical distribution with specified marginals
is also proposed. We generate skew or asymmetric distributions on the disc by
using the Mӧbius
transformation and modified Mӧbius
transformations as extensions of the Mӧbius
distribution proposed by Jones (2004). The new distributions called the
modified Mӧbius
distributions have six parameters. They can be reduced to the Mӧbius and
uniform distributions as special cases, but many members of the family are
skew distributions for both the linear and the angular random variables. Some
properties such as the joint probability and marginal density functions of
the proposed distributions are obtained. References:
[1] Johnson, R.
A. and Wehrly, T. E. (1978). Some angular-linear distributions and related
regression models. Journal of the
American Statistical Association, 73, 602–606. [2]
Jones, M. C. (2004). The Mӧbius
distribution on the disc. Annals of the
Institute of Statistical Mathematics, 56, 733–742. [3] Kato, S. and
Jones, M. C. (2010). A family of distributions on the circle with links to,
and applications arising from, Mӧbius
transformation. Journal of the American
Statistical Association, 105, 249–262. [4]
Wang, M.-Z. and Shimizu, K. (2012). On applying Mӧbius
transformation to cardioid random variables. Statistical Methodology, 9, 604–614. -2 SpeakerF@Dr.
Llenos, Andrea L. iUS Geological Survey, Earthquake
Science Center E
Postdoctoralj DateF@4 March 2014@@@TimeF@16:30 -17:30 LocationF@Room D312-B (Seminar Room), Institute
of Statistical Mathematics TitleF@Statistical modeling and
identification of potentially induced seismicity rate changes AbstractF@ iTBAj The 40th
-1 SpeakerF@Dr.
Varini, Elisa iInstitute
of Applied Mathematics and Information Technology, National Research Council
(IMATI-CNR), Italy E DateF@18 February 2014@@@TimeF@15:00 -16:00 LocationF@Room D312-B (Seminar Room), Institute
of Statistical Mathematics TitleF@Bayesian estimation of doubly
stochastic Poisson processes: a particle filtering approach AbstractF@ iTBAj -2 SpeakerF@Dr.
Harte, David iGNS
Science, New Zealand EStatistical
Seismologist and Hazard Modellerj DateF@18 February 2014@@@TimeF@16:30 -17:30 LocationF@Room D312-B (Seminar Room), Institute
of Statistical Mathematics TitleF@Stochastic Earthquake Models: Ways to
Improve and Insights into the Physical Process AbstractF@ 1. Bayesian estimation of doubly
stochastic Poisson processes: a particle filtering approach We aim
to explore the hypothesis that the earthquakes of a seismic region occur
under different physical conditions, corresponding to as many seismicity
phases characterized by different occurrence rates. This
hypothesis can be modeled by doubly stochastic Poisson processes in which the
observed process of the occurrence times of the earthquakes is a point
process whose conditional intensity function is assumed to be dependent on
both the past history and the current hidden state. By
assuming some of the possible choices for the observed point process and the
hidden state process, a Bayesian analysis is carried out in which the
likelihood function is approximated by the particle filtering method. 2. Stochastic Earthquake Models: Ways to
Improve and Insights into the Physical Process We
present a version of the ETAS model where the offspring rates vary both
spatially and temporally. This is in response to deficiencies discussed in
[1]. This is achieved by distinguishing between those space-time volumes
where the interpoint space-time distances are small, and those where they are
considerably larger. In the process of modifying a stochastic earthquake
model, one needs to justify assumptions made, and these in turn raise
questions about the nature of the underlying physical process. We will use
this version of the ETAS model as the basis for our discussion, and by focussing on aspects where the model does not perform so
well, attempt to find physical explanations for such lack of fit. Some
possible discussion points are as follows. What
is the nature of the so called background process in
the ETAS model? Is it simply a temporal boundary (t=0) correction or does it
represent an additional tectonic process not described by the aftershock
component? Or are these two alternatives on completely different time scales? An
epidemic (the basic analogy underpinning the ETAS model), or a living
organism, can evolve by reproducing offspring that are slightly different to
that of their parents - randomness or gene mutation. Certain
"modified" individuals will be able to adapt to the environment
better and tend to survive over others. In the ETAS context, a lower value of
$\alpha$ will cause more "generations" in the aftershock sequence.
This allows for a richer and more complex evolution of the process, both
spatially and temporally. Alternatively, if alpha is large, then more of the
aftershocks are direct offspring of the mainshock. In the epidemic context,
this implies that the mainshock contains much more of the "DNA"
which governs the evolution of the overall sequence. What
is the relationship between fractal dimension and clustering? Does the
fractal dimension provide a better discrimination between those space-time
volumes with higher offspring rates and the others? If so, does the fractal
dimension provide a more obvious physical description of the difference
between these high rate volumes and the lower rate
volumes, and hence a suggestive physical explanation? [1]
Harte, D.S. (2013). Bias in Fitting the ETAS Model: A Case Study Based on New
Zealand Seismicity. Geophys. J. Int. 192(1),
390-412. The 39th
-1 SpeakerF@Prof.
Matsufura, Mitsuhiro iVisiting Researcher of ISMj DateF@14 January 2014@@@TimeF@13:00 -14:00 LocationF@Room D312-B (Seminar Room), Institute
of Statistical Mathematics TitleF@Inversion of GPS Data using ABIC AbstractF@ To
monitor crustal movements of the Japanese Islands, a nation-wide dense GPS
network (GEONET) has been operated by Geographical Survey Institute of Japan
(now Geospatial Information Authority of Japan) since 1996. We developed an
inversion method to estimate unbiased interseismic
slip-deficit rates at plate interfaces from GPS displacement rate (velocity)
data with an elastic dislocation model. In this method, first, we subtract
theoretical surface velocities due to known steady relative plate motion from
the observed GPS data, and presume the residuals to be caused by slip deficit
at plate interfaces. However, the observed GPS data always include rigid
block translation and rotation, which cannot be explained by the elastic
dislocation model. We treated the rigid block translation and rotation as
systematic errors in the analysis, and removed them by transforming the
velocity data into the average strain rates of triangle elements composed of
adjacent GPS stations. By this transformation, original information about
intrinsic deformation is preserved. Applying a general inversion formula
using ABIC to the GPS strain data, we can obtain unbiased slip-deficit rate
distribution. We demonstrate the applicability of the GPS strain data
inversion method through the analyses of coseismic
and interseismic GPS data in the Japan region,
where the North American, Pacific, Philippine Sea, and Eurasian plates are
interacting with each other in a complicated way. -2 SpeakerF@Prof.
Zhou, Shiyong iSchool of Earth and Space Sciences,
Peking University, China EProfessorj DateF@14 January 2014@@@TimeF@14:10 -15:10 LocationF@Room D312-B (Seminar Room), Institute
of Statistical Mathematics TitleF@Detecting the regional tectonic stress
variations in background seismicity data through statistical earthquake
modeling
iYajun Peng, Shiyong Zhou, Jiancang Zhuang
and Jia Shij AbstractF@ Large
earthquakes could perturb the stress field in regions even thousands of
kilometers away, leading to abrupt changes in background seismicity. We have
developed a probability based approach, based on the
epidemic-type aftershock sequence model and the stochastic declustering method, to invert the smoothed temporal
variation of background seismicity rate and to extract useful physical
signals from complex seismicity patterns. An iterative algorithm is
constructed to estimate the background seismicity simultaneously by using a
combination of maximum likelihood estimate and weighted variable kernel
estimate. We verify this approach through simulations and confirm that it can
sensitively recover the onset of dynamic triggering. The
algorithm is applied to an earthquake catalog in Yunnan Province, China, and
successfully identifies a rapid increment of background seismicity rate
following the occurrence of the 2004 Sumatra Mw 9.2 earthquake, whereas no
remote triggering effect is detected following the occurrence of the 2005
Sumatra Mw 8.7 earthquake. This phenomenon agrees with GPS observations. It
is found that the elevated seismic activity within 15 d after the Sumatra
earthquake is mostly composed by shallow events, and direct triggering
relationship is well established. We
also studied the possible dynamic triggering effect in Northern China,
including Tangshan area, when the Japan Tohoku Mw 9.0 earthquake happened at
March 11th, 2011 and found out whether the area with large co-seismic
displacement would have sudden abnormal seismicity increase. As a result, the
Japan Tohoku earthquake has little effect on the total and background
seismicity of Tangshan area, which means that the seismic structure of
Tangshan area is fundamentally stable. -3 SpeakerF@Dr.
Wang, Ting iUniversity
of Otago, New Zealand ELecturerj DateF@14 January 2014@@@TimeF@15:30 -16:30 LocationF@Room D312-B (Seminar Room), Institute
of Statistical Mathematics TitleF@Estimating the likelihood of volcanic
eruptions with incomplete eruption record AbstractF@ iTBAj
-4 SpeakerF@Prof.
Ogata, Yosihiko iEmeritus
Professor of ISM; Visiting Professor of Institute of Industrial Science,
University of Tokyoj DateF@14 January 2014@@@TimeF@16:40 -17:40 LocationF@Room D312-B (Seminar Room), Institute
of Statistical Mathematics TitleF@Foreshocks and short-term forecasting:
comparisons between in real seismicity and synthetic catalogs
iYosihiko Ogata and Koichi Katsuraj AbstractF@ Some
statistical characteristics of foreshocks in the JMA earthquake catalog are
quantitatively different from those in the catalogs simulated by the
space-time epidemic-type aftershock sequence (ETAS) model associated with the
Gutenberg-Richter (GR) law. Also, the information gain of a foreshock
probability forecasting in the real seismicity is significantly large in
comparison with in synthetic catalogs. The 38th
SpeakerF@Prof.
Huang, Qinghua iDepartment
of Geophysics, Peking University, China EProfessorj
DateF@12 November 2013@@@TimeF@16:00-17:00 LocationF@Room A508 (Seminar Room), Institute of
Statistical Mathematics TitleF@Seismicity changes revealed by the
Region-Time-Length (RTL) algorithm AbstractF@ The
Region-Time-Length (RTL) algorithm, which takes into account the epicenter,
time, and magnitude of earthquakes, is an effective technique in detecting
seismicity changes, especially the seismic quiescence. Based on the RTL
algorithm and the Q-parameter (an average RTL parameter over a certain time
window), we can quantify the spatio-temporal
characteristics of seismicity changes. In order to reduce the possible
ambiguity due to the selection of model parameters in the RTL algorithm, we
proposed an improved technique of searching for the optimal model parameters.
The applications of the RTL algorithm in various tectonic regions indicated
that seismic quiescence anomalies generally started a few years prior to the
occurrence of the mainshock. The linear dimension of the seismic quiescence
zone could be a few to several times of the rupture dimension of the
mainshock. The significance of the seismic quiescence anomalies revealed by
the RTL algorithm was supported by the close investigations of model parameter
effects and the stochastic test based on randomized earthquake catalogs. The 37th
SpeakerF@Herrmann,
Marcus iETH
Zurich, Swiss Seismological Servise E PHD studentj
DateF@27 August 2013@@@TimeF@16:00-17:00 LocationF@Room D312A (Seminar Room), Institute
of Statistical Mathematics TitleF@Forecasting Losses Caused by a M6.6
Scenario Earthquake Sequence in Basel, Switzerland AbstractF@ When
people and their environment are not properly prepared, earthquakes pose a
serious threat. Recently, the SEISMO-12 earthquake scenario exercise
simulated the repeat of the 1356 Basel earthquake. This gave officials,
organizations, and the general public an idea of what may be expected in case
of a M6.6 earthquake. The present work relates to the scenario and
contributes to loss reduction by expressing the potential impact through
seismic risk. Reducing the short-term seismic risk requires the evacuation of
vulnerable buildings. However, one cannot always evacuate in times of an
ongoing seismic sequence. Based on information of the continuous seismicity,
probabilistic forecasts show increasing benefit for short-term defense
against earthquakes. Forecast probabilities subsequently allow time-varying
seismic hazard calculation. Only another combination with time-invariant loss
estimation permits the assessment of short-term seismic risk. Seismic risk
delivers a more direct expression of the socio-economic impact than seismic
hazard, but one must characterize vulnerability and exposure to estimate
risk. Risk assessment brings together a variety of data, models and
assumptions. Based on the specific earthquake scenario, I perform a
probabilistic forecast of human losses. Seismologists may not be responsible
for communicating short-term risk information to the public, but they have to
support decision-makers to take worthwhile actions that may save lives.
However, the low-probability environment and the complexity of involved
processes challenge decision-makers. A final cost--benefit analysis
constitutes greater benefit than pure statistical approaches by providing
objective statements that may justify evacuations. To deliver supportive
information in the simplest reasonable form, I propose a warning approach ---
in terms of alarm levels --- which allows one to explore worthwhile
mitigation actions for each district of the Basel region. The 36th
SpeakerF@Dr.
Enescu, Bogdan iTsukuba
University, Japan E Associate
Professorj DateF@23 July 2013@@@TimeF@16:00-17:00 LocationF@Room D313 (Seminar Room), Institute of
Statistical Mathematics TitleF@Dynamic triggering of earthquakes in
Japan due to the 2011 Tohoku-oki earthquake: some
observations, stress modeling and interpretation AbstractF@ iTBAj The 35th
SpeakerF@Dr.
Marzocchi, Warner iIstituto Nazionale
di Geofisica e Vulcanologia,
Rome, Italy E Chief
scientistj DateF@3 July 2013@@@TimeF@16:00-16:40 LocationF@Room D313 (Seminar Room), Institute of
Statistical Mathematics TitleF@Operational Earthquake Forecasting and
Decision Making AbstractF@ Traditionally,
seismic risk reduction is achieved only through a sound earthquake building code.
Nonetheless, some recent seismic disasters have highlighted the need for
enlarging the range of risk mitigation actions beyond that. In particular,
the occurrence of a seismic sequence may increase the weekly probability of a
large shock by orders of magnitude, although the absolute probability usually
remains below 1/100. Here, we summarize the state of the art in short-term
earthquake forecasting and discuss how these forecasts may be used to
mitigate seismic risk in this time horizon. Because of the low probabilities
and high false alarm rates of possible advisories, mandatory mitigation
actions would not be an effective practical strategy to reduce risk.
Alternatively, we propose some low cost strategies,
such as increasing vigilance and preparedness, for using probabilistic
forecasting to mitigate seismic risk. These are based on the enudgingf
principle of devolving decision-making down from civic authorities to the
individual level. The 34th
SpeakerF@Dr.
Chen, Xiaowei iScripps
Institution of Oceanography, University of California, San Diego E Post-Doctoral Fellowj
DateF@16 April 2013@@@TimeF@16:00-17:00 LocationF@Room D312B (Seminar Room), Institute
of Statistical Mathematics TitleF@Aspects of earthquake triggering and
seismicity clustering AbstractF@ Earthquakes
strongly cluster in space and time, driven both by earthquake-to-earthquake
triggering and underlying physical processes, such as tectonic stress
loading, increased pore pressure, etc. To
understand the general characteristics of earthquake clustering from a large
dataset of earthquakes, I analyze seismicity in southern California. I use a
high-resolution earthquake catalog based on waveform cross-correlation to
study the spatial-temporal distribution of earthquakes. Parameters based on
event location, magnitude and occurrence time are computed for isolated
seismicity clusters. Spatial migration behavior is modeled using a
weighted-L1-norm method. Aftershock-like event clusters do not exhibit
significant spatial migration compared with earthquake swarms. Two triggering
processes are considered for swarms: slow slip and fluid diffusion, which are
distinguished based on a statistical analysis of event migration. The results
suggest fluid-induced seismicity is found across southern California,
particularly within geothermal areas. In the Salton Sea geothermal field
(SSGF), a correlation between seismicity and fluid injection activities is
seen. Spatial-temporal variations of earthquake stress drops are investigated
in different regions, and a distance-dependence of stress drop from the
injection source is found in the SSGF, suggesting the influence of increased
pore pressure. Temporal variation of stress drops within mainshock source
regions shows that foreshocks and earthquake swarms have lower stress drops
than background seismicity and aftershocks. These results, combined with the
spatial migration observed for some large foreshock sequences, suggests an
aseismic transient process is likely involved in foreshock triggering. The 33rd
SpeakerF@Dr.
Han, Peng iChiba
University, Japan EPh.D.
Studentj DateF@14 February 2013@@@TimeF@16:00-18:00 LocationF@Room D312A (Seminar Room), Institute
of Statistical Mathematics TitleF@Investigation of ULF seismo-magnetic phenomena in Kanto, Japan during 2000 –
2010 AbstractF@ Earthquakes
are one the most destructive natural hazards, causing huge damages and high
casualties. Especially during the past decade, huge/mega earthquakes have hit
many countries. Thus, effective earthquake forecasting is important and
urgent. Since the end of last century, ULF seismo-magnetic
phenomena have been intensively studied. Recently, it has been considered a
promising candidate for short-term earthquake prediction as a number of case
studies have been reported. However, scientists also found that
sometimes a sizeable earthquake happened without magnetic anomalies and
sometimes magnetic anomalies followed by no earthquakes. Thus, the relation
between magnetic anomalies and seismicity has been queried. Moreover, there
are two essential problems puzzling the researchers: (1) what is the exact
waveform of electro-magnetic signals associated with earthquakes or
underground activities; (2) how are the signals generated. These two
questions have not yet been answered clearly and fully. There are still
active debates in the geophysical community on the seismo-electromagnetic
phenomena. In order to verify, clarify, and evaluate the ULF seismo-magnetic phenomena, long-term continuous
monitoring of ULF magnetic field in a seismically active area is required.
Therefore, a sensitive observation network has been established in
Kanto-Tokai area since the year 2000. Based on eleven yearsf observation,
plenty of geomagnetic data have been accumulated, which provides an excellent
opportunity to find answers to the questions above. Thus, in this study I
have conducted an investigation of ULF seismo-magnetic
phenomena in Izu and Boso Peninsulas, Japan, based on the data observed from
2000-2010. First, case studies of major events
have been applied. Energy of ULF geomagnetic signals at the frequency around
0.01 Hz has been investigated by wavelet transform analysis. In order to
minimize the influences of artificial noises, only the midnight time data (LT
1:00 ~ 4:00) have been utilized. To indentify
anomalous changes from ionospheric disturbances, the standard station Memabutsu has been chosen as a reference station. (1)
Case studies of the 2000 Izu Islands earthquake swarm have indicated that there
are unusual geomagnetic energy enhancements in vertical component before and
during the earthquake swarm. (2) Case studies of the 2005 Boso M 6.1
earthquake have also shown clear geomagnetic energy enhancements in vertical
component before the earthquake. (3) Case studies of the 2002 and 2007 slow
slip events have demonstrated that there are geomagnetic energy enhancements
in both vertical and horizontal components during the slip events. Then,
to verify and clarify the relation between ULF geomagnetic anomalies and
seismicity, statistical studies by superposed epoch analysis (SEA) have been
carried out. The results have indicated that before a sizeable earthquake
there are clearly higher probabilities of ULF anomalies than after the
earthquake: for Seikoshi (SKS) station in Izu,
about 20~30 days before, one week and few days before, and one day after the
event statistical results of daily counts are significant; for Kiyosumi (KYS) station in Boso around two weeks before,
few days before, and one day after the event. Finally, to find out the detailed
waveform of anomalous magnetic signals, waveform analysis has been performed.
The results show that there are mainly two kinds of seismo-magnetic
signature. (1) Noise-like signals: Compared with the background, the signals
exhibit small increases of amplitudes at a wide frequency range. (2)
Transient/quasi-rectangular signals: the signals have
transient/quasi-rectangular waveforms with amplitudes of several nT (~ 10-9 T). The noise-like signals usually
persist for several days or even a few weeks, and are mainly associated with
large earthquakes; the transient/quasi-rectangular signals have durations of
few seconds to few ten seconds, and are registered mainly during slow slip
events. Based on the results obtained above,
we conclude that: (1) there is a correlation between ULF geomagnetic
anomalies and local sizeable earthquakes in Izu and Boso Peninsulas, Japan,
and the common period of significant results is few days before and one day
after a sizeable earthquake; (2) there are mainly two kinds of seismo-magnetic signature registered in Izu and Boso
Peninsulas: noise-like signals and transient/quasi-rectangular signals. The
mechanisms of the anomalous geomagnetic signals are still unclear and need
further studies. The 32nd
SpeakerF@Prof.
Savage, Martha iSchool of
Geography, Environment and Earth Sciences, Victoria University of Wellington,
New Zealand EProfessorj
DateF@13 November 2012@@@TimeF@16:00-18:00 LocationF@Room D312A (Seminar Room), Institute
of Statistical Mathematics TitleF@Towards Predicting Earthquakes and
Volcanic Eruptions using Statistical Techniques AbstractF@ Predicting
natural hazards is fraught and statistical techniques are necessary to put
such studies on a firm standing.
Here we discuss two methods that we have applied to volcanic areas. Analysis of the rates of earthquake
activity (CURATE) is used to determine the characteristics of earthquake
swarms to try to determine how they develop over time. The technique compares favourably to other declustering
techniques and allows us to consider whether some swarms are triggered by
underlying processes that create diffuse seismicity that is not well modelled
by Omorifs law. We also analyse waveforms of
earthquakes to determine seismic anisotropy, which depends upon stress
orientation and magnitude, which in turn can be influenced by earthquake and
volcanic activity. Seismic waves
travel faster when their particle motion is along the cracks, which orient
with the principal stress direction.
At volcanoes around the world, we discovered significant changes in
seismic anisotropy strength and orientation that correlate with magma
movement. Detecting and
evaluating such changes is complicated by scattered measurements, which
sometimes have 90 degree ambiguities and we have
been considering ways to make the techniques more robust. These observations will provide the
data that may eventually lead to prediction tools. The 31st
SpeakerF@Dr.
Omi, Takahiro iUniversity
of Tokyo E JST
Postdoctoral Researcherj DateF@25 October 2012@@@TimeF@16:00-17:00 LocationF@4F lounge, Institute of Statistical
Mathematics TitleF@A state-space model for estimating the
time-varying detection rate of earthquakes and its application to immediate
probabilistic prediction of aftershocks AbstractF@ After
a large earthquake, the detection rate of earthquakes temporarily decreases,
and a lot of earthquakes are missed from a catalog. Such incompleteness of
the catalog prevents us from estimating statistical models of aftershock
activity accurately. To overcome this difficulty, Ogata and Katsura (2005)
modeled the incomplete catalog by using a parametric model of a time-varying
detection rate of earthquakes. In this talk, we propose a state space model for estimating the time-varying detection rate. In our model, the estimation problem is recursively solved, by using Kalman filter and a Gaussian approximation of the posterior probability distribution. Thus our model has an advantage in real-time computation. Finally our model is combined with the Omori-Utsu< | |||
