Overview of the first earthquake forecast testing experiment in Japan

The Collaboratory for the Study of Earthquake Predictability (CSEP) is an international partnership to support research on rigorous earthquake prediction in multiple tectonic environments. This paper outlines the first earthquake forecast testing experiment for the Japan area conducted within the CSEP framework. We begin with some background and briefly describe efforts in setting up the experiment. The experiment, which closely follows CSEP concepts, is of a prospective sort and is highly objective. Its major feature consists in using Japan, one of the most seismically active and well-instrumented regions in the world, as a natural laboratory. To make full use of this location and of the earthquake catalog maintained by the Japan Meteorological Agency, rules for this experiment have been set up. The experiment consists of 12 categories, with four testing classes each with different time spans (1 day, 3 months, 1 year, and 3 years, respectively) and three testing regions called “All Japan,” “Mainland,” and “Kanto.” A total of 91 models were submitted; these are currently under the CSEP official suite of tests for evaluating the performance of forecasts. This paper briefly describes each model but does not attempt to pass judgment on individual models. Comparative appraisal of the different models will be presented in future publications. Moreover, this is only the first experiment, and more trials are forthcoming. Our aim is to describe what has turned out to be the first occasion for setting up a research environment for rigorous earthquake forecasting in Japan. We argue that now is the time to invest considerably more efforts in related research fields.

[1]  A. Hasegawa,et al.  Interplate quasi‐static slip off Sanriku, NE Japan, estimated from repeating earthquakes , 2003 .

[2]  Danijel Schorlemmer,et al.  First Results of the Regional Earthquake Likelihood Models Experiment , 2010 .

[3]  Philip J. Maechling,et al.  The Collaboratory for the Study of Earthquake Predictability perspective on computational earthquake science , 2010 .

[4]  Chung-Pai Chang,et al.  A study on the background and clustering seismicity in the Taiwan region by using point process models : Stress transfer, earthquake triggering, and time-dependent seismic hazard , 2005 .

[5]  S. Toda,et al.  Rate/state Coulomb stress transfer model for the CSEP Japan seismicity forecast , 2011 .

[6]  W. Marzocchi,et al.  A double-branching model applied to long-term forecasting of Italian seismicity (ML≥5.0) within the CSEP project , 2010 .

[7]  Rodolfo Console,et al.  Real Time Forecasts through an Earthquake Clustering Model Constrained by the Rate-and- State Constitutive Law: Comparison with a Purely Stochastic ETAS Model , 2007 .

[8]  S. Wiemer,et al.  Earthquake Likelihood Model Testing , 2007 .

[9]  K. Mogi Recent Earthquake Prediction Research in Japan , 1986, Science.

[10]  Walter H. F. Smith,et al.  New, improved version of generic mapping tools released , 1998 .

[11]  Danijel Schorlemmer,et al.  ALM: An Asperity-based Likelihood Model for California , 2007 .

[12]  D. Rhoades Application of a long-range forecasting model to earthquakes in the Japan mainland testing region , 2011 .

[13]  A. Takeuchi,et al.  A new algorithm for the detection of seismic quiescence: introduction of the RTM algorithm, a modified RTL algorithm , 2011 .

[14]  N. Uchida,et al.  Statistical forecasts and tests for small interplate repeating earthquakes along the Japan Trench , 2012, Earth, Planets and Space.

[15]  H. Fujiwara,et al.  Conventional N-, L-, and R-tests of earthquake forecasting models without simulated catalogs , 2011 .

[16]  Shinji Toda,et al.  12 May 2008 M = 7.9 Wenchuan, China, earthquake calculated to increase failure stress and seismicity rate on three major fault systems , 2008 .

[17]  Jian Lin,et al.  Change in Failure Stress on the Southern San Andreas Fault System Caused by the 1992 Magnitude = 7.4 Landers Earthquake , 1992, Science.

[18]  J. D. Zechar,et al.  Likelihood-Based Tests for Evaluating Space–Rate–Magnitude Earthquake Forecasts , 2009 .

[19]  J. Douglas Zechar,et al.  Simple smoothed seismicity earthquake forecasts for Italy , 2010 .

[20]  S. Wiemer,et al.  Asperity-based earthquake likelihood models f or Italy , 2010 .

[21]  Matthew C. Gerstenberger,et al.  New Zealand Earthquake Forecast Testing Centre , 2010 .

[22]  David A. Rhoades Application of the EEPAS Model to Forecasting Earthquakes of Moderate Magnitude in Southern California , 2007 .

[23]  T. Jordan Earthquake Predictability, Brick by Brick , 2006 .

[24]  K. Nanjo,et al.  Analysis of the completeness magnitude and seismic network coverage of Japan , 2010 .

[25]  J. Dieterich A constitutive law for rate of earthquake production and its application to earthquake clustering , 1994 .

[26]  Danijel Schorlemmer,et al.  Setting up an earthquake forecast experiment in Italy , 2010 .

[27]  Warner Marzocchi,et al.  A double branching model for earthquake occurrence , 2008 .

[28]  Rodolfo Console,et al.  Short-term and long-term earthquake occurrence models for Italy: ETES, ERS and LTST , 2010 .

[29]  Jiancang Zhuang,et al.  Next-day earthquake forecasts for the Japan region generated by the ETAS model , 2011 .

[30]  Jiancang Zhuang,et al.  Space–time ETAS models and an improved extension , 2006 .

[31]  K. Shimazaki,et al.  Correlation between Coulomb stress changes imparted by large historical strike-slip earthquakes and current seismicity in Japan , 2011 .

[32]  D. Vere-Jones,et al.  Analyzing earthquake clustering features by using stochastic reconstruction , 2004 .

[33]  Naoshi Hirata,et al.  CSEP Testing Center and the first results of the earthquake forecast testing experiment in Japan , 2012, Earth, Planets and Space.

[34]  Y. Ogata Significant improvements of the space-time ETAS model for forecasting of accurate baseline seismicity , 2011 .

[35]  Earthquake forecasting and its verification , 2005, cond-mat/0508476.

[36]  N. Hirata Japanese National Research Program for Earthquake Prediction , 2009 .

[37]  Y. Ogata Space-Time Point-Process Models for Earthquake Occurrences , 1998 .

[38]  J. Douglas Zechar,et al.  The Area Skill Score Statistic for Evaluating Earthquake Predictability Experiments , 2010 .

[39]  C. Smyth,et al.  Statistical models for temporal variations of seismicity parameters to forecast seismicity rates in Japan , 2011 .

[40]  Naoshi Hirata Past, current and future of Japanese national program for earthquake prediction research , 2004 .

[41]  K. Nanjo,et al.  An improved relative intensity model for earthquake forecasts in Japan , 2012, Earth, Planets and Space.

[42]  D. Vere-Jones,et al.  Stochastic Declustering of Space-Time Earthquake Occurrences , 2002 .

[43]  M. Imoto Performance of a seismicity model for earthquakes in Japan (M ≥ 5.0) based on P-wave velocity anomalies , 2011 .

[44]  K. Nanjo Earthquake forecasts for the CSEP Japan experiment based on the RI algorithm , 2011 .

[45]  Edward H. Field,et al.  Overview of the Working Group for the Development of Regional Earthquake Likelihood Models (RELM) , 2005 .

[46]  S. Toda Coulomb stresses imparted by the 25 March 2007 Mw=6.6 Noto-Hanto, Japan, earthquake explain its ‘butterfly’ distribution of aftershocks and suggest a heightened seismic hazard , 2008 .

[47]  B. Gutenberg,et al.  Frequency of Earthquakes in California , 1944, Nature.

[48]  Kristy F. Tiampo,et al.  Mean-field threshold systems and phase dynamics: An application to earthquake fault systems , 2002 .

[49]  David A. Rhoades,et al.  Long-range Earthquake Forecasting with Every Earthquake a Precursor According to Scale , 2004 .

[50]  Testing various seismic potential models for hazard estimation against a historical earthquake catalog in Japan , 2012, Earth, Planets and Space.

[51]  David A. Rhoades,et al.  Mixture Models for Improved Short-Term Earthquake Forecasting , 2009 .

[52]  Y. Kaneda,et al.  Migration process of very low-frequency events based on a chain-reaction model and its application to the detection of preseismic slip for megathrust earthquakes , 2012, Earth, Planets and Space.

[53]  Danijel Schorlemmer,et al.  RELM Testing Center , 2007 .

[54]  W. Marzocchi,et al.  The double branching model for earthquake forecast applied to the Japanese seismicity , 2011 .

[55]  F. Hirose,et al.  Earthquake forecast models for inland Japan based on the G-R law and the modified G-R law , 2011 .