SSS01-01

会場:102B

時間:5 月 24 日 14:15-14:30

確率密度比推定を用いた前震のリアルタイム識別Real-time Classifier of Foreshocks Using Probability Density Ratio Estimation
野村 俊一 1∗NOMURA, Shunichi1∗11

東京工業大学Tokyo Institute of Technology

前震は大地震の短期予測において一つの有効な手段である。過去多くの大地震について前震が観測されているが、本震が起こるより前に前震を識別することは困難な課題である。前震を事前に完全に識別することは困難であるものの、前震の位置情報や規模あるいは時間的情報などを利用して、前震であることを確率的に評価する研究はこれまでに多くなされてきた。
本研究では、確率密度比推定を用いて前震の確率的識別関数を構成する手法を提案する。確率密度比推定は統計的機械学習の一つの枠組みであり、高次元空間上での 2 クラス判別を確率的に与える手法である。更新されるカタログから随時追加的に学習することができ、リアルタイムでの前震識別を与えることが可能となる。識別関数にはカーネル関数を利用することで、空間的情報や時間的情報などを組み合わせた高次元空間上に非線形な判別境界を設けることができる。
本研究では、気象庁の一元化カタログに本手法を適用して、震源位置、時間、マグニチュードなどの情報から前震確率を評価する識別関数を推定する。また、推定された識別関数を独立した過去のカタログに適用して、予測性能の評価を行う。
キーワード: 前震, 確率的識別, 確率密度比推定, カーネル法
Keywords: foreshock, probabilistic recognition, probability density ratio estimation, kernel method

1/1

SSS01-02

会場:102B

時間:5 月 24 日 14:30-14:45

余震予測における不確定性
Forecast uncertainty in aftershock forecasting
近江 崇宏 1∗ ; 尾形 良彦 2 ; 平田 祥人 1 ; 合原 一幸 1
OMI, Takahiro1∗ ; OGATA, Yosihiko2 ; HIRATA, Yoshito1 ; AIHARA, Kazuyuki1
11

東京大学生産技術研究所, 2 統計数理研究所
The Institute of Industrial Science, The University of Tokyo, 2 Institute of Statistical Mathematics

Aftershock forecasting provides one of the important measures for mitigation of earthquake damages. For this purpose,
statistics- and physics- based models have been developed. When forecasting using these models, we usually adopt an optimal
single set of parameter values such as the maximum likelihood estimates, which is called as plug-in forecasting. However, for agiven small sized and incomplete data shortly after the main shock, the estimation of the model parameters may be accompaniedby large uncertainty. In such a case, the plug-in forecasting underestimates the predictive probability range, and sometimes
the range significantly biases the actual observations. Alternatively, more robust and unbiased forecasts can be obtained byconsidering the estimation uncertainty in an appropriate way. Bayesian forecasting provides a consistent statistical framework
for this, and enables us to assess the forecast uncertainty. In this talk, we will argue the importance of evaluating the forecast
uncertainty in probabilistic forecasting. As an example here, we employ the epidemic type aftershock sequence (ETAS) model
as a forecasting model, and we show how the plug-in forecasting can fail and how the Bayesian forecasting can improve theperformance. We will argue that the Bayesian predictors should also be tested in CSEP forecasting experiments.
Reference: T. Omi, Y. Ogata, Y. Hirata, & K. Aihara, ”Intermediate-term forecasting of aftershocks from an early aftershock
sequence: Bayesian and ensemble forecasting approaches”, JGR (in revision).
キーワード: 余震予測, 確率点過程, ベイズ予測
Keywords: Aftershock forecasting, Point process, Bayesian forecasting

1/1

SSS01-03

会場:102B

時間:5 月 24 日 14:45-15:00

関東地方における 2011 年東北地方太平洋沖地震による静的クーロン応力変化と地震活動度変化の相関性
Correlation between Coulomb stress imparted by the 2011 Tohoku-Oki earthquake andseismicity rate change in Kanto, Japan
石辺 岳男 1∗ ; 佐竹 健治 1 ; 酒井 慎一 1 ; 島崎 邦彦 1 ; 鶴岡 弘 1 ; 横田 裕輔 2 ; 中川 茂樹 1 ; 平田 直 1
ISHIBE, Takeo1∗ ; SATAKE, Kenji1 ; SAKAI, Shin’ichi1 ; SHIMAZAKI, Kunihiko1 ; TSURUOKA, Hiroshi1 ;YOKOTA, Yusuke2 ; NAKAGAWA, Shigeki1 ; HIRATA, Naoshi1
1
1

東京大学地震研究所, 2 海上保安庁海洋情報部
Earthquake Research Institute, the University of Tokyo, 2 Japan Coast Guard, Hydrographic and oceanographic department

We show that the seismicity rate increase in the Kanto region around Tokyo following the 2011 Tohoku-Oki earthquake(M w9.0) was well correlated with the static increases in the Coulomb failure function (∆CFF) transferred from the Tohoku-Oki
earthquake sequence. Because earthquakes in the Kanto region exhibit various focal mechanisms, the receiver faults for the∆CFF were assumed to be reliable focal mechanism solutions of ˜3,000 earthquakes compiled from three networks (F-net, JMA
network, and MeSO-net).
The histograms of ∆CFF showed that more events in the postseismic period had positive ∆CFF values than those in thepreseismic period (2008 April 1 - 2011 March 10). Among the 928 receiver faults showing the significant ∆CFF with absolutevalues ≥ 0.1 bars in the preseismic period, 717 receiver faults (77.3 %) indicated positive ∆CFF. On the contrary, 1,334 (88.2%) out of 1,513 receiver faults indicated positive ∆CFF in the postseismic period. We confirmed that the result is similar for the
longer preseismic period, between 1997 October 1 and 2011 March 10.
To test the significance of the difference in the distribution of ∆CFF between preseismic and postseismic periods, we used a
Monte Carlo method with bootstrap resampling. As a result, the ratio of positive ∆CFF randomly resampled from ∆CFF values
in the preseismic period never exceeded 83.1%, even after 10,000 iterations. This supports the findings of Toda & Stein [2013];
however, our calculation is more reliable than theirs because we used a much larger number of focal mechanisms compiled
from the three networks. It also proves that the static stress changes transferred from the Tohoku-Oki earthquake sequence areresponsible for the changes in the seismicity rate in the Kanto region.
Earthquakes of focal mechanisms with positive ∆CFF values drastically increased, while those with negative ∆CFFs showedno obvious changes except for immediately after the mainshock. This fault-dependent seismicity rate change strongly supports
the contribution of the Coulomb stress transferred from the Tohoku-Oki sequence to the seismicity rate change in the Kanto
region. Immediately following the mainshock, earthquakes of all types of focal mechanisms were activated, but the increased
seismicity rate of earthquakes with negative ∆CFFs returned to the background level within a few months. This suggests that
there might be other contributing factors to the seismicity rate change such as dynamic stress triggering or pore-fluid pressurechanges.
Acknowledgements
This study was supported by the Special project for reducing vulnerability for urban mega earthquake disasters from the
Ministry of Education, Culture, Sports, Science and Technology of Japan.

キーワード: 2011 年東北地方太平洋沖地震, 地震活動度変化, 関東地方, 静的クーロン応力変化
Keywords: 2011 Tohoku-Oki earthquake, Seismicity rate change, Static changes in the Coulomb failure function, Kanto region

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SSS01-04

会場:102B

時間:5 月 24 日 15:00-15:15

CSEP-Japan testing results with multiple runs since 2009 including the 2011 Tohoku-oki
earthquake
CSEP-Japan testing results with multiple runs since 2009 including the 2011 Tohoku-oki
earthquake
鶴岡 弘 1∗ ; 平田 直 1
TSURUOKA, Hiroshi1∗ ; HIRATA, Naoshi1
1
1

東京大学地震研究所
ERI, Univ. Tokyo

It is 5 years since we have established the Japanese testing center for the Study of Earthquake Predictability (CSEP) in Earthquake Research Institute, the University of Tokyo. During the period of testing, in 2011 March, Tohoku-oki earthquake with
M9.0 occurred and seismic activity changed very much in entire part of Japanese Islands.
The CSEP Japan testing experiment consists of 12 categories, with 4 testing classes with different periods (1 day, 3 months, 1
year and 3 years) and 3 testing regions called AllJapan,
Mainland, and Kanto. Starting from 91 models in September
2009, a total of 160 models, as of January 2015, are currently under testing in the CSEP official suite with collaboration of CSEP
Testing Center at the Southern California Earthquake Center (SCEC) (Nanjo et al., 2011; Tsuruoka et al., 2012). For 3-monthand one-year testing experiments, more than 15 runs of fully prospective experiments have been operated. Probability gains oftested models with respective to a spatially uniform probability model show that some models have always better performancesin regions of AllJapan and Kanto, but the best model varies rounds by rounds for the region of Mainland.
In the testing period including the 2011 Tohoku-oki earthquake, a model which has wider spatial smoothing radius of 100km
of Relative Intensity Model (RI) shows larger probability gain than those with a narrow smoothing while in other periods a small
smoothing radius of 10 km shows better performance. Probability gains of models for 3-month and 1-year testing class for eachmodel are almost same although a magnitude of target events is different. A model of HISTETAS5PA (Ogata, 2011) shows best
performance for 1 day class and a region of AllJapan before the 2011 Tohoku-oki event but after the event ETAS (Zhuang, 2011) is better than HISTETAS5PA.

キーワード: CSEP, 地震予測
Keywords: CSEP, Earthquake Predictability

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SSS01-05

会場:102B

時間:5 月 24 日 15:15-15:30

東北地方太平洋沖地震後の地震活動の予測
Forecasting seismicity after the Tohoku-Oki earthquake
尾形 良彦 1∗
OGATA, Yosihiko1∗
1
1

統計数理研究所, 2 地震研究所、東京大学
The Institute of Statistical Mathematics, 2 Earthquake Research Institute, University of Tokyo

M9.0 の 2011 年東北沖地震が発生して以来 4 年が経たった。この超巨大地震は依然として日本周辺の現在および将来の地震活動に影響を与えている。この機会に、将来の地震活動のさまざまな予測について議論したい。さらに将来の地震をより細かく予測するための統計モデルの高度化の計画について説明したい。
キーワード: 確率予測, ETAS モデル, 誘発地震, 時空間 ETAS モデル, マグニチュード分布, 地震検出率
Keywords: Probability forecast, ETAS models, Triggering seismicity, Space-time ETAS model, Magnitude distributions, Earthquake detection rates

1/1

SSS01-06

会場:102B

時間:5 月 24 日 15:30-15:45

Post-Disaster Damage Mapping as Tool for Risk Testing
Post-Disaster Damage Mapping as Tool for Risk Testing
SCHORLEMMER, Danijel1∗ ; BEUTIN, Thomas1 ; FANSELOW, Florian1
SCHORLEMMER, Danijel1∗ ; BEUTIN, Thomas1 ; FANSELOW, Florian1
1
1

GFZ German Research Centre for Geosciences, 14473 Potsdam, Germany
GFZ German Research Centre for Geosciences, 14473 Potsdam, Germany

The Post-Disaster Damage Mapping is part of the Global Dynamic Exposure project, in which we interpret and visualize
crowd-sourced and open geographic data and provide guidance to what is called the crowd in data collection. We base our work on
OpenStreetMap (www.openstreetmap.org) because of the fully open geographic data and the availability of open-source software
for processing the data. Because of the immense number and variety of buildings, exposure- and vulnerability-related data cannot
be compiled by a small group. Furthermore, the dynamic aspect of risk, namely rapid urbanization, requires monitoring of
exposure and vulnerability indicators, again a task that can only be achieved when distributing the work onto many shoulders.
The objective of the Global Dynamic Exposure project is to provide a high-resolution (on the building-by-building level) anddynamic (low-latency) exposure model for the world. It will build upon the Global Exposure Database for the Global Earthquake
Model (GED4GEM) and augment it where crowd-sourced and open data exists in high quality and high density. The exposureand vulnerability indicators are derived from geographic data (e. g. building footprint, land use), building properties (e. g.
type of building, occupancy), and semantic interpretation (e. g. regional types of architecture, cultural habits). Once a target
area is fully captured in OpenStreetMap, further changes in the dataset indicate the change of building stock or the processof urbanization. This dynamic aspect of data collection is used for the Post-Disaster Damage Mapping. Here, the so-called
Humanitarian OpenStreetMap Team (hot.openstreetmap.org), a crowd-sourced disaster mapping effort, is providing information
about the status of buildings and roads in the aftermath of a disaster. These data is retrieved mainly from aerial imagery but also
from mappers on the ground.
Combining the exposure and vulnerability data of buildings prior to a natural disaster with the post-disaster damage status will
provide a new dataset for better understanding risk and the societal impact of a catastrophe, but will also for the first time offer
an independent dataset for testing risk estimates.
キーワード: risk testing, seismic hazard, seismic risk, exposure, vulnerability
Keywords: risk testing, seismic hazard, seismic risk, exposure, vulnerability

1/1

SSS01-07

会場:102B

時間:5 月 24 日 15:45-16:00

USGS 全国地震動予測地図と DYFI 観測震度の比較
Comparing USGS national seismic hazard maps with DYFI intensity observations
Mak Sum1∗ ; Schorlemmer Danijel1
MAK, Sum1∗ ; SCHORLEMMER, Danijel1
1
1

ドイツ地学研GFZ-Potsdam

Verifying a nationwide seismic hazard assessment using data collected after the assessment has been made (i.e., prospectivedata) is a direct consistency check of the assessment. We directly compared the predicted rate of ground motion exceedance by
the four available versions of the USGS national seismic hazard map (NSHMP, 1996, 2002, 2008, 2014) with the actual observed
rate during 2000-2013. The data were prospective to the two earlier versions of NSHMP. We used three sets of somewhat independent data, namely 1) the USGS ”Did You Feel It?” (DYFI) intensity reports, 2) ShakeMap gridded ground motions, and 3)
instrumental ground motion records extracted from ShakeMap stations. The first two were not strictly observations but models
calibrated by observations. The third was true observation but the amount of data is limited.
Our results indicated that for California, the predicted and observed hazards are very comparable. Discrepancy lied generally
on the safe side (i.e., predicted hazard not lower than the observed one). The three sets of data gave consistent results, implying
robustness. The consistency also encourages the use of DYFI and ShakeMap data for hazard verification in the central and eastern
US (CEUS), where instrumental records are lacking. The result showed that the observed ground-motion exceedance was larger
than the predicted in CEUS, implying a possible underpredicted hazard.
The primary value of this study is to demonstrate the usefulness of DYFI and ShakeMap data, originally designed for community communication instead of scientific analysis, for the purpose of hazard verification. The large discrepancy between theobserved and predicted gorund-motion exceedance in CEUS implied that either the ground motions were not described correctly
by DYFI and ShakeMap for the region, or the hazard was actually underestimated. Induced seismicity could be the cause of thisunderestimation.
キーワード: 地震ハザード, 予測, 検証
Keywords: Earthquake Hazard, Prediction, Validation

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SSS01-08

会場:102B

時間:5 月 24 日 16:15-16:30

Detecting spatial variations of earthquake clustering parameters via maximum weighted
likelihoods estimates
Detecting spatial variations of earthquake clustering parameters via maximum weighted
likelihoods estimates
庄 建倉 1∗ZHUANG, Jiancang1∗
11

統計数理研究所
Institute of Statistical Mathematics

The ETAS model has been used to describe the clustering features of seismicity with just several parameters. To see how theclustering parameters and background rates change spatially, in this study, the earthquake data from the JMA catalog are used
and these model parameters are estimated by using the maximum weighted likelihood estimate (MWLE) method. Even though
this MWLE method is not as sophisticated as the HIST-ETAS model, which is built on a more rigorous basis of the Bayesian
procedure with the smoothness prior, MWLE is simpler to implement, in both parallel and non-parallel computing environments,
without loss of detecting resolution of the spatial variation of earthquake clustering parameters.
The data analysis shows that the spatial variation of the MWLEs of each parameter shows different features between tectonic
regions. Also, applying the MWLE method has the potentials for improving the forecasting performance of the space-time ETAS
model in evaluating earthquake probabilities.

Figure 1: Spatial variations of the ETAS parameters estimated by using maximum weighted likelihood estimate (MWLE). (a)A, (b) α, (c) q, (d) γ.
キーワード: ETAS モデル, 地震クラスタ, 地震予測, 最大重み付き尤度推定値
Keywords: ETAS model, earthquake cluster, earthquake forecasting, weight likelihood estimator

1/1

SSS01-09

会場:102B

時間:5 月 24 日 16:30-16:45

地震発生回数の頻度分布
Frequency distribution of the number of earthquake occurrence
山科 健一郎 1∗ ; 鶴岡 弘 2 ; 姫野 哲人 3
YAMASHINA, Ken’ichiro1∗ ; TSURUOKA, Hiroshi2 ; HIMENO, Tetsuto3
1
1

元東京大学地震研究所, 2 東京大学地震研究所, 3 成蹊大学
Ex Earthquake Research Insitute, University of Tokyo, 2 Earthquake Research Institute, University of Tokyo, 3 Seikei University

前震や余震があることからも明らかなように，地震活動には，互いに相関のある活動が含まれる．そのため，地震数の頻度分布をポアソン分布で表すことは難しいと思われるが，実態に近い分布関数について検討した．これは，地震活動の一面を理解する上で必要なことであり，また，正しい頻度分布がわかっていないと適確な予測の評価を行うことができない．
地震数の頻度分布は，これまでしばしば負の２項分布で表されてきた．しかしそれは，概してデータセットの平均ｒが大きい場合（例えば r>>1 ）であり，希にしか地震が起こらないデータセットについては，疑問に思われる．小さな平均の場合，分布は負のべき分布に近い．そこで筆者らは先に，地震発生頻度の分布関数として，離散ガンマ分布を提案した（ f(x) = c (xˆ-a) exp(-bx): Yamashina et. al, 2012）．一方，もうひとつの候補として，ここでは負の離散ガンマ分布を取り上げる ( f(x) = c (xˆ-a) exp(-b/x) )．両関数は，大きな平均をもつデータセットから小さな平均のものまで，広い範囲でかなりよく実際の分布事例に当てはめることができるが，特に大きな平均をもつ場合について，後者の方が当てはまりがよい傾向がある．
ここで取り上げた関数は，ａが正のときにはｘ＝０で発散するが，ｘ＝１以上について適用する．これは，例えばｘ＝２の頻度はｘ＝１の頻度と関係するものの，ｘ＝０の頻度との相関は小さいと思われ，ｘ＝０，１，２を同じ分布関数で表現することは難しいと考えられたからである．ｘ＝０の頻度は，他の頻度を合計した残りとする．
ＣＳＥＰプロジェクトの地震活動予測において，予測値がどのくらい実状に合っていたかどうかを評価する際，現在は，地震発生回数の頻度がポアソン分布だとみなして行っている．しかし，実態を必ずしも反映しない頻度分布を前提にしたのでは，評価した結果に疑問を残す．今後，実態に合う頻度分布を評価に取り入れたときにどのような違いが生じるかなど，確かめることが望まれる．
キーワード: 頻度分布, 地震発生回数, CSEP
Keywords: frequency distribution, number of earthquake occurrence, CSEP

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SSS01-10

会場:102B

時間:5 月 24 日 16:45-17:00

History of network detection completeness in Japan
History of network detection completeness in JapanSCHORLEMMER, Danijel1∗ ; HIRATA, Naoshi2 ; ISHIGAKI, Yuzo3 ; NANJO, Kazuyoshi4 ; TSURUOKA, Hiroshi2 ;BEUTIN, Thomas1 ; EUCHNER, Fabian5
SCHORLEMMER, Danijel1∗ ; HIRATA, Naoshi2 ; ISHIGAKI, Yuzo3 ; NANJO, Kazuyoshi4 ; TSURUOKA, Hiroshi2 ;BEUTIN, Thomas1 ; EUCHNER, Fabian5
1

GFZ German Research Centre for Geosciences, 14473 Potsdam, Germany, 2 Earthquake Research Institute, University of Tokyo,
Tokyo 113-0032, Japan, 3 Seismological and Volcanological Department, Japan Meteorological Agency, Tokyo 100-8122, Japan,
4
Institute of Advanced Science, Yokohama National University, Yokohama 240-8501, Japan, 5 Institute of Geophysics, ETH
Zurich, Switzerland
1
GFZ German Research Centre for Geosciences, 14473 Potsdam, Germany, 2 Earthquake Research Institute, University of Tokyo,
Tokyo 113-0032, Japan, 3 Seismological and Volcanological Department, Japan Meteorological Agency, Tokyo 100-8122, Japan,
4
Institute of Advanced Science, Yokohama National University, Yokohama 240-8501, Japan, 5 Institute of Geophysics, ETH
Zurich, Switzerland
An important characteristic of any seismic network is its detection completeness, which should be considered a function of
space and time. Many researchers rely on robust estimates of detection completeness, especially when investigating statisticalparameters of earthquake occurrence like earthquake rates. Contrary to traditional approaches, we do not estimate completenessusing methods in which the completeness magnitude is defined as the deviation of the frequency-magnitude distribution fromthe linear Gutenberg-Richter relation. Here, we present a method based on empirical data only: phase data, station information,and the network-specific attenuation relation. For each station of the network we estimate a time-dependent distribution function
describing the detection capability depending on magnitude and distance to the earthquake. For each point in time, maps ofdetection probabilities for certain magnitudes or overall completeness levels are compiled based on these distributions. Therefore, this method allows for inspection of station performances and their evolution as well as investigations on local detection
probabilities even in regions without seismic activity.
We present a full history of network detection completeness for Japan and discuss details of this evolution. These results arecompared with estimated completeness levels of other methods and with completeness levels in other regions of the World. We
present scenario computations showing the impact of different possible network failures. All presented results are published on
the CompletenessWeb (www.completenessweb.org) from which the user can download completeness data from all investigatedregions, software codes for reproducing the results, and publication-ready and customizable figures.
キーワード: catalog completeness, earthquake recording, statistical seismology, earthquake statistics, earthquake forecasting,seismic hazard
Keywords: catalog completeness, earthquake recording, statistical seismology, earthquake statistics, earthquake forecasting,seismic hazard

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SSS01-11

会場:102B

時間:5 月 24 日 17:00-17:15

Assessment of optimal short-term earthquake forecasts based on ULF seismo-magnetic
data
Assessment of optimal short-term earthquake forecasts based on ULF seismo-magnetic
data
Han Peng1∗ ; Hattori Katsumi1 ; Zhuang Jiancang2
HAN, Peng1∗ ; HATTORI, Katsumi1 ; ZHUANG, Jiancang2
1
1

Graduate School of Science, Chiba University, 2 Institute of Statistical Mathematics, Tokyo, Japan
Graduate School of Science, Chiba University, 2 Institute of Statistical Mathematics, Tokyo, Japan

Our previous statistical studies have indicated that the ULF seismo-magnetic phenomena contain precursory information andcan be useful in short-term forecasting of sizable earthquakes. In practice, for given series of precursory signals and related
earthquake events, the efficiency of forecast is a function of the leading time of alarms (Δ) and the length of alarm window(L). To find out the best prediction strategies, Molchan s error diagram has been employed. The same as our previous study,
we utilized geomagnetic data and earthquake events registered in Kakioka (KAK), Japan during 2001-2010. Ratios of observed
energy to modeled background are applied to indentify precursory signals. A modified area skill score, which measures thearea between actual prediction curve and random prediction line, is introduced to assess the efficiency of different prediction
strategies. The results indicate that ULF magnetic data at KAK contains higher precursory information when Δ is around 1
week and L is less than 4 days or Δ is 13-14 days and L is less than 1 week; the optimal strategy of short-term forecasts is: Δ =8
days and L =1 day. The methodology proposed in this study could help to evaluate the prediction policy and find out the optimal
solution of other different measurements for short-term earthquake forecasting.
キーワード: ULF seismo-magnetic phenomena, Molchan’s error diagram, optimal short-term earthquake forecast
Keywords: ULF seismo-magnetic phenomena, Molchan’s error diagram, optimal short-term earthquake forecast

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SSS01-12

会場:102B

時間:5 月 24 日 17:15-17:30

Earthquake mechanism in post-megathrust intraplate stress
Earthquake mechanism in post-megathrust intraplate stress
HONG, Tae-kyung1∗ ; LEE, Junhyung1 ; HOUNG, Soung eil1
HONG, Tae-kyung1∗ ; LEE, Junhyung1 ; HOUNG, Soung eil111

Yonsei University, Department of Earth System Sciences, Seoul 120-749, South Korea
Yonsei University, Department of Earth System Sciences, Seoul 120-749, South Korea
Megathrusts produce large permanent lithosphericdisplacements as well as strong transient ground shaking
up to regional distances. The lateral permanent
displacements construct stress shadows in a wide backarc
region. The Korean Peninsula is placed in the far-eastern
Eurasian plate that belongs to a stable intraplate region
with a low earthquake occurrence rate and diffusedseismicity, and is located in the backarc at ˜1300
km in the west from the epicenter of the 11 March 2011
M9.0 Tohoku-Oki earthquake. The seismicity around the
Korean Peninsula was increased significantly after the2011 M9.0 Tohoku-Oki earthquake, which is not consistent
with the expected seismic-quiescence. Strong seismic
waves cause large dynamic stress changes, incurring fluid
migration and increasing pore fluid pressure in the
media. The lithospheric displacements directing to theepicenter on the convergent plate boundary developtransient radial tension field over the backarc
lithospheres, which is subparallel with the preseismic
ambient compressional field. The pore pressure growth andradial tension field decrease the Coulomb failure stress,
increasing episodic increases of seismicity in both fault
zones and intact media. The ambient stress field isrecovered gradually as the induced stress fielddiminishes with time by tectonic loading. The seismicity
changes with the temporal evolution of stress field. A
series of moderate-size earthquakes and earthquake swarms
occur as a consequence of medium response to the temporal
evolution of stress field. The long-term evolution ofseismicity is expected to continue until the preseismic
ambient stress field is fully recovered.

キーワード: stress shadow, intraplate, megathrust, long-term evolution, Korean Peninsula
Keywords: stress shadow, intraplate, megathrust, long-term evolution, Korean Peninsula

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