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Statistical Seismology Seminars 統計地震学セミナー ： Updated on 29 October 2024 NEW! 第99回
日 時： 2024年10月
31日(木)
13：30 – 15:30
場 所： 統計数理研究所 4階ラウンジ 及び オンライン -1 講演者： Dr. Hsieh, Ming-Che (謝 銘哲) （Earthquake
Disaster & Risk Evaluation and Management Center (E-DREaM),
National Central University, Taoyuan, Taiwan ・Associate Research Fellow / 統計数理研究所リスク解析戦略研究センター 地震予測解析プロジェクト ・外国人客員准教授） Title： 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 Abstract： 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 workflow’s 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 講演者： Petrillo, Giuseppe （Nanyang Technological University(NTU, Singapore)
・Visiting Researcher / 統計数理研究所リスク解析戦略研究センター Title： The Impact of Stress Redistribution on
the Spatial and Magnitude Patterns of Future Earthquakes Abstract： 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. 第98回
日 時： 2024年10月
1日(火) 14：30
– 17:00 場 所： 統計数理研究所 D312Bセミナー室4 及び オンライン -1 講演者： Dr. Wu, Stephen （統計数理研究所
先端データサイエンス研究系 ・准教授） Title： Potential of LLMs in seismology Abstract： 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 講演者： 詹
成祥 (Zhan, Chengxiang) （中国地質大学 (北京)
・大学院生 / 統計数理研究所リスク解析戦略研究センター 地震予測解析プロジェクト ・外来研究員） Title： Neural Point Process: A Modulated Renewal
Model for Temporal Event Modeling Abstract： 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 講演者： Prof. Zhuang, Jiancang
(庄 建倉) （統計数理研究所
統計基盤数理研究系・教授）
Title： Quantification of earthquake
predictability Abstract： 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 講演者： Dr. Clements, Timothy （U.S.
Geological Survey’s Earthquake Science Center in Moffett Field, CA, USA・ Postdoctoral fellow） Title： A Ground Motion-based Approach to
Earthquake Early Warning and Earthquake Statistics Abstract： 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; GRAPES’
internal activations, which I call “seismic vectors”, 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. 第97回 講演者： Dr. 郭 一村(Guo, Yicun) （中国科学院大学・助教/ 統計数理研究所リスク解析戦略研究センター 地震予測解析プロジェクト ・外来研究員） 日 時： 2024年 8月26日(月)
15：00 -16：00 場 所： 統計数理研究所 4階ラウンジ 及び オンライン Title： Statistical modeling of 3D seismicity
and its correlation with fault slips along major faults in California Abstract： 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. 第96回 講演者：雷 興林 (Lei, Xinglin) （国立研究開発法人産業技術総合研究所・上級研究員 日 時： 2024年8月5日(月)
15：00-16：00 場 所： 統計数理研究所 4階ラウンジ 及び オンライン Title： Can the extent of fluid involvement be
quantified by statistics for fluid-involved or fluid-driven seismicity? Abstract： 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. 第95回 講演者：Dr. Gerstenberger,
Matt （GNS
Science, New Zealand ・Seismologist/NSHM
Lead） 日 時： 2024年6月10日(月)
16：00-17：00 場 所： 統計数理研究所 4階ラウンジ 及び オンライン Title： The New Zealand National Seismic
Hazard Model： modelling
uncertainty and implications for its use Abstract： 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. 第94回 講演者：Dr. Koh, Jonathan （Oeschger Centre for Climate Change
Research(OCCR), University of Bern, Switzerland ・Post-doctoral researcher 日 時： 2024年4月16日(火)
16：00-17：00 場 所： 統計数理研究所 4階ラウンジ 及び オンライン Title： Estimating shared random effects
between model components in Bayesian hierarchical frameworks Abstract： 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. 第93回 講演者：上田 拓 （京都大学防災研究所・特定研究員(学振PD) / 統計数理研究所リスク解析戦略研究センター 地震予測解析プロジェクト ・外来研究員）
日 時： 2024年1月30日(火)
16：00 -17：00 オンライン Title： Spatial correlation of the shear
strain energy change and the number of declustered
crustal earthquakes in Japan Abstract： 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. 第92回
統計地震学セミナー ＆ 「STAR-Eおよび日伊共同プロジェクトの研究進捗状況に関するワークショップ」 日 時： 2023年11月
7日(火)
10：00 - 12：00 ・
14：00 - 16：30 場 所： 統計数理研究所 4階ラウンジ 及び オンライン 10：00 - 12：00 大学院生による発表 -1 講演者：李 永波 (Li, Yongbo) （中国地震局地球物理研究所
・大学院生 / 統計数理研究所リスク解析戦略研究センター 地震予測解析プロジェクト ・外来研究員） Title： 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 講演者：王 志峰 (Wang, Zhifeng) （中国地質大学 (武漢) ・大学院生
/ 統計数理研究所リスク解析戦略研究センター 地震予測解析プロジェクト ・外来研究員） Title： Bayesian inversion for finite fault
earthquake source models and uncertainty analysis
(Wang, Z.*, Zhuang, J. and Wang, D.) -3 講演者：司 政亜 (Si, Zhengya) （中国地震局地球物理研究所
・大学院生 / 統計数理研究所リスク解析戦略研究センター 地震予測解析プロジェクト ・外来研究員） Title： Bayesian merging of earthquake
magnitudes determined by multiple seismic networks
(Si, Z.*, Zhuang, J., Gentili, S., Jiang, C. and Wang, W.) -4 講演者：朴 健 (Piao, Jian) （北京大学, 中国 ・大学院生
/ 統計数理研究所リスク解析戦略研究センター 地震予測解析プロジェクト ・外来研究員） Title： On the spatial response kernel in the
ETAS model
(Piao, J.*, Zhuang, J. and Zhou, S.) -5 講演者：毛 寧 (Mao, Ning) （中国地震局地球物理研究所 ・大学院生
/ 統計数理研究所リスク解析戦略研究センター 地震予測解析プロジェクト ・外来研究員） Title： Extraction of secular variation
signals and estimation of transfer function from geomagnetic stations
(Mao, N.* and Chen, S.) 14：00 - 16：30 -6 講演者：彭 鴻 (Peng, Hong) （統計数理研究所 ・特任研究員）
Title： Constructing an empirical envelope
function of seismic waveforms for the evaluation of
EEW in Japan -7 講演者：Petrillo, Giuseppe （統計数理研究所 ・特任助教）
Title： Decoding the Puzzle of Earthquake
Magnitude Dependency -8 講演者：Dr. Guo, Yicun (郭
一村) （中国科学院大学
・助教 / 統計数理研究所リスク解析戦略研究センター 地震予測解析プロジェクト ・外来研究員） Title： Detection and Characterization of
Earthquake Swarms in Nankai and Its Association With Slow Slip Events -9 講演者：Dr. Gentili, Stefania（イタリア国立海洋学と実験地球物理学研究所 ・研究員 Title： 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 講演者：牛 源源 (Niu, Yuanyuan) （総合研究大学院大学 ・大学院生） Title： Nonparametric Bayesian inference for ETAS model (Niu, Y.* and Zhuang,
J.) 第91回 講演者：Prof. Guan, Yongtao （Department of Management Science,
School of Business Administration, University of Miami, USA ・教授） 日 時： 2023年10月3日(火)
16：00-17：00 オンライン Title： Group Network Hawkes Process Abstract： 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. 第90回 講演者：Dr. Hsieh, Ming-Che (謝 銘哲) （台湾 国立中央大学
地震災害・リスク評価管理センター(E-DREaM) ・副研究員） 日 時： 2023年8月29日(火)
16：30-17：30 オンライン Title： Seismic Hazard Assessment for
Metropolises and Sciences Parks in Taiwan：
Analyzing Ground Motions Using Deterministic and Probabilistic Methods Abstract： 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 第89回 講演者：Prof. Peng, Zhigang （School of Earth and Atmospheric
Sciences, Georgia Institute of Technology, Atlanta, USA ・教授） 日 時： 2023年6月16日(金)
16：00 - オンライン Title： What can ‘missing’ events tell us about
earthquake statistics and physical mechanism of earthquake triggering? Abstract： 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. 第88回 -1 講演者：
Dr. Hainzl, Sebastian （GFZ German Research Centre for
Geosciences, Germany ・Senior
Researcher 日 時： 2023年 3月
17日(金) 15：00
-16：00 場 所： 統計数理研究所 D313/314セミナー室5 及び オンライン Title： Stress-based seismicity modeling Abstract： 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 Dieterich‘s
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
講演者： Stockman, Sam （Computational
Statistics and Data Science, University of Bristol, UK ・大学院生） 日 時： 2023年 3月
17日(金) 16：00
-17：00 場 所： 統計数理研究所 D313/314セミナー室5 及び オンライン Title： Forecasting the 2016-2017 Central
Apennines Earthquake Sequence with a Neural Point Process Abstract： Point
processes have been dominant in modeling the evolution of seismicity for
decades, with the Epidemic Type Aftershock Sequence (ETAS) model being most
popular. Recent advances in machine learning have constructed highly flexible
point process models using neural networks to improve upon existing
parametric models. We investigate whether these flexible point process models
can be applied to short-term seismicity forecasting by extending an existing
temporal neural model to the magnitude domain and we show how this model can
forecast earthquakes above a target magnitude threshold. We first demonstrate
that the neural model can fit synthetic ETAS data, however, requiring less
computational time because it is not dependent on the full history of the
sequence. By artificially emulating short-term aftershock incompleteness in
the synthetic dataset, we find that the neural model outperforms ETAS. Using
a new enhanced catalog from the 2016-2017 Central Apennines earthquake
sequence, we investigate the predictive skill of ETAS and the neural model
with respect to the lowest input magnitude. Constructing multiple forecasting
experiments using the Visso, Norcia and Campotosto earthquakes to partition training and testing
data, we target M3+ events. We find both models perform similarly at
previously explored thresholds (e.g., above M3), but lowering the threshold
to M1.2 reduces the performance of ETAS unlike the neural model. We argue
that some of these gains are due to the neural model's ability to handle
incomplete data. The robustness to missing data and speed to train the neural
model present it as an encouraging competitor in earthquake forecasting. 第87回 講演者：佐藤大祐 （京都大学防災研究所・JSPS特別研究員） 日 時： 2022年12月26日(月)
16：00 -17：00 オンライン Title： Inventing appropriate solving methods
of hierarchical Bayesian inversions when using regularization priors Abstract： 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. 第86回 -1 講演者： Dr. Zhuang, Jiancang
(庄 建倉) （統計数理研究所
モデリング研究系・准教授） 日 時： 2022年 11月
14日(月) 16：00
-16：45 オンライン Title： Evaluating earthquake forecasts with
likelihood based marginal and conditional scores Abstract： 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
講演者： Sofiane Rahmani （Center
of Research in Astronomy, Astrophysics and Geophysics(CRAAG), Algeria ・大学院生） 日 時： 2022年 11月
14日(月) 16：45
-17：30 オンライン Title： Time-dependent and spatiotemporal
statistical analysis of Algerian seismicity Abstract： 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. 第85回 講演者：西川友章 （京都大学防災研究所・助教 / 統計数理研究所リスク解析戦略研究センター 地震予測解析プロジェクト ・外来研究員） 日 時： 2022年10月3日(月)
16：15 -18：15 オンライン Title： Application of the ETAS model to slow
earthquake research Abstract： 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). 第84回 講演者：彭 鴻(Peng,
Hong) （京都大学防災研究所附属地震予知研究センター・大学院生） 日 時： 2022年7月7日(木)
16：00 -18：00 オンライン Title： Characteristics of foreshocks
preceding the mainshocks in Japan Abstract： 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 ‘cascade model’
or rupture-controlled model is more reasonable for explaining the physical
mechanism of earthquakes in Japan. 第83回 講演者：Petrillo,
Giuseppe （統計数理研究所 ・外来研究員/ 日 時： 2022年4月26日(火)
16：00 -18：00 オンライン Title： Statistical mechanics models for
seismic occurrence Abstract： 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. 第82回 講演者：矢野恵佑 （統計数理研究所 数理・推論研究系 ・准教授）
日 時： 2022年2月1日(火)
16：30 -18：00 オンライン Title： l1 trend filtering based detection of
slow slip events Abstract： 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. 第81回 講演者：竹尾明子 （東京大学地震研究所・助教） 日 時： 2021年11月16日(火)
16：00 -18：00 オンライン Title： Observation, detection, evaluation and
interpretation of slow earthquakes：
is it episodic or chaotic? Abstract： 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. 第80回
講演者：沈 迅(Shen, Xun) （総合研究大学院大学・大学院生） 日 時： 2021年10月19日(火)
16：00 – 18：00 オンライン Title： Residual Analysis for State Space
Models Abstract： 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. 第79回 講演者： Dr. 王 婷(Wang, Ting) （Otago Univeristy
(Department of Mathematics and Statistics), New Zealand・准教授） 日 時： 2021年9月21日(火)
13：00 –14：00 オンライン Title： A time series model for forecasting
earthquake energy release Abstract： 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. 第78回 講演者： Dr. 熊 子瑶(Xiong, Ziyao) （統計数理研究所・特任助教） 日 時： 2021年7月27日(火)
16：00 – 18：00 オンライン Title： The Research of Long-Term Earthquake
Hazard Estimated from a Modern Catalog Abstract： 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.’s 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. 第77回 講演者： 山田真澄 （京都大学防災研究所・助教） 日 時： 2021年6月24日(木)
16：00 -18：00 オンライン Title： IPFx： a new source determination algorithm
for earthquake early warning Abstract： 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. 第76回 講演者： Dr. 常 莹(Chang, Ying) （南方科学技術大学 地球空間科学学院・特別研究員）
日 時： 2020年1月14日(火)
13：30 -14：30 場 所： 統計数理研究所 D313/314セミナー室5 Title： Differences between mantle wedge
earthquakes and intraslab intermediate-depth
earthquakes from spatial b-value image Abstract： 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. 第75回 -1 講演者： Dr. 李 紅蕾(Li, Honglei) （中国地震局 地球物理研究所
・助教） 日 時： 2019年 8月
28日(水) 13：00
-13：45 場 所： 統計数理研究所 D313/314セミナー室5 Title： Bayesian assimilation inversion of
gravity anomalies and parameters optimization Abstract： 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 Akaike’s 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
講演者： Prof. 陳 石(Chen, Shi) （中国地震局 地球物理研究所
・教授） 日 時： 2019年 8月
28日(水) 13：45
-15：00 場 所： 統計数理研究所 D313/314セミナー室5 Title： A Bayesian approach of network
adjustment for campaigned gravity survey：
methodology and model test Abstract： 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
Akaike’s 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
講演者： Dr. Bayona, Jose Antonio （GFZ German Research Center for
Geosciences ・特別研究員） 日 時： 2019年 8月
28日(水) 15：30
-16：15 場 所： 統計数理研究所 D313/314セミナー室5 Title： An updated global hybrid earthquake
model obtained from the optimal combination of interseismic
strain rates and smoothed-seismicity data Abstract： 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. 第74回 講演者： Dr. Chen, Feng （School
of Mathematics and Statistics, University of New South Wales, Australia・Senior Lecturer(准教授相当)） 日 時： 2019年5月21日(火)
15：00 -16：00 場 所： 統計数理研究所 D312Bセミナー室4 Title： Direct Likelihood Evaluation for the
Renewal Hawkes Process Abstract： 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/. 第73回
講演者： Prof. Wang, Baoshan （名古屋大学大学院環境学研究科附属 地震火山研究センター・外来研究員 (中国 科学技術大学・教授)） 日 時： 2019年4月23日(火)
15：00 -16：00 場 所： 統計数理研究所 D312Bセミナー室4 Title： Migration of micro-earthquakes during
cyclic operation of Underground Gas Storage and the Changdao
earthquake swarm Abstract： 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. 第72回 -1 講演者： Prof. 陳 暁非(Chen, Xiaofei) （中国 南方科技大学
地球・宇宙科学系 ・教授）
日 時： 2019年 1月
22日(火) 13：30
-14：30 場 所： 統計数理研究所 A504セミナー室7 Title： Phase diagram of earthquakes and
implications -2
講演者： 楠城 一嘉 （静岡県立大学 グローバル地域センター ・特任准教授）
日 時： 2019年 1月
22日(火) 14：30
-15：30 場 所： 統計数理研究所 A504セミナー室7 Title： An investigation into the relation
between the occurrence of large earthquakes and time-dependent decrease in b
value Abstract： 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
講演者： Dr. Wang, Yuchen （東京大学 地震研究所
・特別研究員） 日 時： 2019年 1月
22日(火) 15：30
-16：30 場 所： 統計数理研究所 A504セミナー室7 Title： Tsunami Data Assimilation in Disaster
Mitigation Abstract： 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
Green’s function to reduce the computation time for tsunami early warning.
Green’s Function-based Tsunami Data Assimilation (GFTDA) forecasts the
waveforms at Points of Interest (PoIs) by
superposition of Green’s 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 Green’s 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 Green’s
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. 第71回
講演者： Dr. Harte, David （GNS
Science, New Zealand ・Statistical
Seismologist and Hazard Modeller(上席研究員)） 日 時： 2018年 11月
6日(火)
16：00 -17：00 場 所： 統計数理研究所 D313セミナー室5 Title： Evaluation of Earthquake Stochastic Models
Based on Their Real-Time Forecasts：
A Case Study of Kaikoura 2016 Abstract： 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. 第70回 講演者： Dr. 陳 石(Chen, Shi) （中国地震局 地球物理研究所
・准教授） 日 時： 2018年 8月28日(火)
16：00 -17：00 場 所： 統計数理研究所 D312Bセミナー室4 Title： A new approach for terrestrial relative
gravity adjustment using smoothness priors of drift rate Abstract： 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 hour’s 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
Akaike’s 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. 第69回 講演者： Dr. Varini, Elisa （Institute
of Applied Mathematics and Information Technology, National Research
Council(CNR-IMATI), Italy ・ 日 時： 2018年3月
20日(火) 13：30
-14：30 場 所： 統計数理研究所 4階ラウンジ Title： Identification of earthquake clusters
in Northeastern Italy by different approaches Abstract： 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 “nearest-neighbor dis- tances”
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. 第68回
講演者： Prof. 馬 國鳳 (Ma, Kuo-Fong) （台湾国立中央大学 地球科学系
・教授） 日 時： 2018年 1月31日(火)
13：30 -14：30 場 所： 統計数理研究所 A508セミナー室6 Title： Probability on Seismic Hazard
Assessment of Taiwan： Progress
and Challenge Abstract： 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. 第67回 講演者： Dr. Wu, Stephen （統計数理研究所
モデリング研究系 ・助教）
日 時： 2017年 10月
3日(火)
16：30 -17：30 場 所： 統計数理研究所 D312Bセミナー室4 Title： Review of earthquake early warning
from an engineering perspective Abstract： 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. 第66回
-1 講演者： Dr. 吴(呉) 晶（Wu,
Jing） （中国科学院地質・地球物理研究所 ・准教授） 日 時： 2017年 8月
29日(火) 16：00
-17：00 場 所： 統計数理研究所 D312Bセミナー室4 Title： Seismicity and Seismic Anisotropy
beneath eastern Tibet Abstract： 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
講演者： Dr. Mak, Sum （German Research Centre for Geosciences
(GFZ-Potsdam), Germany ・リサーチ・アシスタント(RA)） 日 時： 2017年 8月
29日(火) 17：00
-18：00 場 所： 統計数理研究所 D312Bセミナー室4 Title： Empirical Validation of Seismic Hazard
Models Abstract： 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. 第65回
講演者： Prof. 劉 正彦 (Liu,Jann-Yenq) （台湾国立中央大学 太空科学研究所
・教授） 日 時： 2017年 6月
13日(火) 16：00
-17：00 場 所： 統計数理研究所 A508セミナー室6 Title： Statistical Analyses on seismo-ionospheric disturbances and precursors of the 11
March 2011 M9.0 Tohoku Earthquake Abstract： 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. 第64回
-1 講演者： Prof. 蒋 長勝（Jiang, Changsheng） （中国地震局地球物理研究所 ・研究員(教授相当)） 日 時： 2017年 3月
29日(水) 13：30
-14：30 場 所： 統計数理研究所 D312Bセミナー室4 Title： Assessment of earthquake monitoring capability
and score of seismic station detection capability in China Seismic Network
(2008~2015) Abstract： 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 “seismic monitoring capability scale”, 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
講演者： Prof. 陳 石（Chen, Shi） （中国地震局地球物理研究所・研究員(教授相当)） 日 時： 2017年 3月
29日(水) 14：30
-15：30 場 所： 統計数理研究所 D312Bセミナー室4 Title： Gravity changes before and after the
2015 Mw 7.8 Gorkha, Nepal and the 2008 Mw 7.9 Wenchuan, China earthquakes Abstract： Absolute
gravity measurements at four stations in southern Tibet show significant
gravity increase from 2011 to 2013, up to ~22 μGals
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 μGals 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. 第63回
講演者： Prof. 周 仕勇
(Zhou, Shiyong) （北京大学
地球空間科学学院 ・教授） 日 時： 2017年 1月
18日(水) 16：00
-17：00 場 所： 統計数理研究所 A504セミナー室7 Title： Could the abnormal seismicity increase
triggered remotely by great earthquakes be used to judge the regional
earthquake risk? Abstract： 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
“abnormal” seismicity in the picture is really abnormal or is triggered by
certain large earthquake or not. 第62回
-1 講演者： Dr. Helmstetter, Agnès （Institut des Sciences de la
Terre, France ・Research
fellow(上席研究員)）
日 時： 2016年 10月
26日(水) 15：00
-16：00 場 所： 統計数理研究所 D312Bセミナー室4 Title： Repeating icequakes Abstract： 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
講演者： Dr. Harte, David （GNS
Science, New Zealand ・Statistical
Seismologist and Hazard Modeller(上席研究員)） 日 時： 2016年 10月
26日(水) 16：00
-17：00 場 所： 統計数理研究所 D312Bセミナー室4 Title： Determining the Uncertainty in
Earthquake Forecasts Abstract： 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. 第61回
講演者： Dr. Helmstetter, Agnès （Institut des Sciences de la
Terre, France ・Research
fellow(上席研究員)） 日 時： 2016年 10月
11日(火) 16：00
-17：00 場 所： 統計数理研究所 A504セミナー室7 Title： Adaptive smoothing of seismicity in
time, space and magnitude for long-term and short-term earthquake forecasts Abstract： 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. 第60回
講演者： Dr. Hasih Pratiwi （Sebelas Maret University, Surakarta,
Indonesia ・ Lecturer） 日 時： 2016年 8月
30日(火) 16：00
-17：00 場 所： 統計数理研究所 A504セミナー室7 Title： ESTIMATING EARTHQUAKE RISK BY USING
EPIDEMIC TYPE AFTERSHOCK SEQUENCE MODEL APPROACH (Case Study in Java Island,
Indonesia) (Hasih
Pratiwi and Respatiwulan) Abstract： 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. 第59回
講演者： Prof. 陳 玉英（Chen,
Yuh-Ing） （台湾国立中央大学, 統計研究所・特聘教授） 日 時： 2016年 7月
19日(火) 16：00
-17：00 場 所： 統計数理研究所 D312Aセミナー室3 Title： Statistical evaluation of short-term
hazard of earthquakes after 1999 M 7.3 Chi-Chi shock in Taiwan Abstract： 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. 第58回 講演者： Dr. Zhuang, Jiancang
(庄 建倉) （統計数理研究所
モデリング研究系・准教授） 日 時： 2016年 6月
29日(水) 16：00
-16：40 場 所： 統計数理研究所 D313・D314セミナー室5
統計数理研究所・統計数理セミナー平成２８年度 (2016年度) Title： 欠測のあるマーク付き点過程時系列データの補充法(Replenishing
missing data in the observation record of mark point processes) Abstract： 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. 第57回 講演者： Dr. Shcherbakov, Robert （Department
of Earth Sciences, Western University(Ontario), Canada ・ Associate Professor 日 時： 2016年 6月
22日(水) 16：40
-17：20 場 所： 統計数理研究所 D313・D314セミナー室5
統計数理研究所・統計数理セミナー平成２８年度 (2016年度) Title： Statistics and Physics of Aftershocks Abstract： 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. 第56回 講演者： Dr. Strader, Anne （GFZ
German Research Centre for Geosciences, Germany ・ 特別研究員） 日 時： 2016年 6月
7日(火)
16：00 -17：00 場 所： 統計数理研究所 A508セミナー室6 Title： Evaluation of Current CSEP Testing
Methods： Case
Studies for Japan and California Abstract： 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. 第55回
-1 講演者： Dr. 郭 一村（Guo, Yicun） （北京大学 地球宇宙科学研究科
・ 博士後期課程）
日 時： 2016年 3月
22日(火) 16：00
-17：00 場 所： 統計数理研究所 D312Bセミナー室4 Title： Iterative finiteETAS
model and some results of the histETAS model of the
North China Craton Abstract： 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
講演者： 尾形 良彦 （統計数理研究所 ・
名誉教授／東京大学地震研究所
地震火山情報センター ・特任研究員） 日 時： 2016年 3月
22日(火) 17：00
-18：00 場 所： 統計数理研究所 D312Bセミナー室4 Title： 3D spatial models for seismicity
beneath Kanto region Abstract： 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 Akaike’s 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. 第54回
講演者： Dr. 王 婷（Wang, Ting） （Department
of Mathematics and Statistics, University of Otago, New Zealand ・Lecturer）
日 時： 2016年 2月
9日(火)
16：00 -17：00 場 所： 統計数理研究所 D312Bセミナー室4 Title： Identification of seismic phases using
Markov-modulated marked Hawkes processes Abstract： 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. 第53回
-1 講演者： Dr. 尹 凤玲（Yin, Fengling） （中国地震局 地球物理研究所・助理研究員(助教相当)） 日 時： 2016年 1月
27日(水) 13：30
-14：30 場 所： 統計数理研究所 D312Bセミナー室4 Title： Coulomb stress evolution along the
middle segment of Redriver fault zone over the past
180 Years due to coseismic, postseismic
and interseismic deformation （Yin,Fengling, Jiang,
Changsheng and Han, Libo） Abstract： 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 ‘seismic gap’ as earthquake catalog shows.
Assuming there is no earthquake within about 30 years around the Redriver fault zone, this ’seismic gap’ may remain due to
postseismic and interseismic
deformation. -2
講演者： Dr. Taroni, Matteo （Istituto Nazionale di Geofisica e Vulcanologia, Rome,
Italy ・
Post-doctoral fellow） 日 時： 2016年 1月
27日(水) 14：30
-15：30 場 所： 統計数理研究所 D312Bセミナー室4 Title： Some recent techniques to improve
earthquake forecasting (Taroni, Matteo, Marzocchi, Warner, Zechar, Jeremy and
Werner, Maximilian) Abstract： 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. 第52回 講演者： Dr. Guillas, Serge （Department of Statistical Science,
University College London, U.K. ・
Reader／東京大学地震研究所・特任准教授） 日 時： 2015年 11月
17日(火) 16：00
-17：00 場 所： 統計数理研究所 A508セミナー室6 Title： Dimension reduction for the
quantification of uncertainties in tsunami and climate models Abstract： 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). 第51回
-1 講演者： Dr. Gerstenberger, Matthew （GNS Science, New Zealand ・Risk and Engineering Team Leader,
Senior Seismologist） 日 時： 2015年 9月
1日(火)
16：00 -17：00 場 所： 統計数理研究所 D312Bセミナー室4 Title： The New Zealand National Seismic
Hazard Model：
Rethinking PSHA Abstract： 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
講演者： Dr. 陳 石（Chen, Shi） （中国地震局地球物理研究所・准教授） 日 時： 2015年 9月
1日(火)
17：00 -18：00 場 所： 統計数理研究所 D312Bセミナー室4 Title： A study on the regional gravity changes
before large earthquakes from the statistical perspectives Abstract： 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. 第50回
講演者： Dr. Kagan, Yan Y. （Department
of Earth and Space Sciences, University of California, Los Angeles (UCLA),
U.S.A. ・
Researcher） 日 時： 2015年 8月
4日(火)
16：00 -18：00 場 所： 統計数理研究所 D208会議室2 Title： Statistics of earthquake focal
mechanisms Abstract： 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. 第49回
講演者： Prof. Künsch, Hans R. （Department of Mathematics, ETH Zurich,
Switzerland ・
Emeritus Professor） 日 時： 2015年 4月
7日(火)
16：00 -17：00 場 所： 統計数理研究所 D312Bセミナー室4 Title： Data assimilation in seismology ? Abstract： 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. 第48回 講演者： 石辺 岳男 （東京大学地震研究所 地震火山情報センター ・特任研究員）
日 時： 2015年 2月
24日(火) 16：00
-17：00 場 所： 統計数理研究所 A508セミナー室6 Title： Overview of Seismicity Changes in
Inland Japan after the 2011 Tohoku-Oki Earthquake and Its Interpretation Abstract： 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. 第47回
講演者： Dr. Segou, Margaret （National
observatory of Athens, Greece ・ Researcher）
日 時： 2015年 2月
10日(火) 16：00
-17：00 場 所： 統計数理研究所 4階ラウンジ Title： The Future of Earthquake
Predictability Abstract： 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? 第46回
-1 講演者： 熊澤 貴雄 （統計数理研究所 リスク解析戦略研究センター 地震予測解析プロジェクト
・特任研究員） 日 時： 2015年 1月
27日(火) 15：00
-16：00 場 所： 統計数理研究所 D312Bセミナー室4 Title： Predicting Offshore Swarm Rate by
Volumetric Strain Changes in Izu Peninsula, Japan Abstract： 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
講演者： Dr. 王 婷（Wang, Ting） （Department
of Mathematics and Statistics, University of Otago, New Zealand ・ Lecturer） 日 時： 2015年 1月
27日(火) 16：30
-17：30 場 所： 統計数理研究所 D312Bセミナー室4 Title： Marked point process modeling with missing
data in volcanic eruption records Abstract： 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. 第45回
講演者： Dr. Schehr, Grégory （Laboratoire de Physique Théorique et Modèles Statistiques, Orsay-University Paris-Sud, France ・ 日 時： 2014年 10月
14日(火) 11：00
-12：00 場 所： 統計数理研究所 D312Bセミナー室4 Title： Exact Statistics of the Gap and Time
Interval Between the First Two Maxima of Random Walks and Lévy Flights Abstract： (PDF) 第44回
-1 講演者： Prof. 周 仕勇
(Zhou, Shiyong) （北京大学
地球空間科学学院 ・教授）
日 時： 2014年 8月
5日(火)
16：00 -17：00 場 所： 統計数理研究所 D312Bセミナー室4 Title： Seismicity simulation in Western
Sichuan of China based on the fault interactions and its implication on the
estimation of the regional earthquake risk Abstract： 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
講演者： Dr. 王 墩 (Wang, Dun) （東京大学地震研究所／日本学術振興会 ・ 特別研究員）
日 時： 2014年 8月
5日(火)
17：00 -18：00 場 所： 統計数理研究所 D312Bセミナー室4 Title： Rupture speeds for recent large
earthquakes Abstract： 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. 第43回
講演者： Dr. Aiken, Chastity （Georgia
Institute of Technology, U.S.A. ・ National
Science Foundation Graduate Fellow, ARCS Scholar） 日 時： 2014年 7月
8日(火)
16：00 -18：00 場 所： 統計数理研究所 D312Bセミナー室4 Title： Triggered Seismic Activity in
Geothermal Regions and on Strike-Slip Faults Abstract： 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. 第42回
講演者： Dr. Aranha, Claus （筑波大学大学院システム情報工学研究科 ・ 助教）
日 時： 2014年 5月 27 | |||
