Long-term clustering, scaling, and universality in the temporal occurrence of earthquakes.

Analyzing diverse seismic catalogs, we have determined that the probability densities of the earthquake recurrence times for different spatial areas and magnitude ranges can be described by a unique universal distribution if the time is rescaled with the rate of seismic occurrence, which therefore fully governs seismicity. The shape of the distribution shows the existence of clustering beyond the duration of aftershock bursts, and scaling reveals the self-similarity of the clustering structure in the space-time-magnitude domain. This holds from worldwide to local scales, for quite different tectonic environments and for all the magnitude ranges considered.

[1]  P. Reasenberg,et al.  Earthquake Hazard After a Mainshock in California , 1989, Science.

[2]  Robert W. Simpson,et al.  A physically-based earthquake recurrence model for estimation of long-term earthquake probabilities , 1999 .

[3]  L. Knopoff,et al.  Is the sequence of earthquakes in Southern California, with aftershocks removed, Poissonian? , 1974, Bulletin of the Seismological Society of America.

[4]  Yan Y. Kagan,et al.  Spatial distribution of earthquakes: the two-point correlation function , 1980 .

[5]  Yan Y. Kagan,et al.  Long-term earthquake clustering , 1991 .

[6]  P. Steerenberg,et al.  Targeting pathophysiological rhythms: prednisone chronotherapy shows sustained efficacy in rheumatoid arthritis. , 2010, Annals of the rheumatic diseases.

[7]  Yan Y. Kagan,et al.  The longer it has been since the last earthquake, the longer the expected time till the next? , 1989 .

[8]  Jean-Luc Chatelain,et al.  A fractal approach to the clustering of earthquakes: Applications to the seismicity of the New Hebrides , 1987 .

[9]  Ian G. Main,et al.  Is the reliable prediction of individual earthquakes a realistic scientific goal , 1999 .

[10]  B. Gutenberg,et al.  Seismicity of the Earth , 1970, Nature.

[11]  David M. Raup,et al.  How Nature Works: The Science of Self-Organized Criticality , 1997 .

[12]  Shinji Toda,et al.  Evidence from the ad 2000 Izu islands earthquake swarm that stressing rate governs seismicity , 2002, Nature.

[13]  Kim Christensen,et al.  Unified scaling law for earthquakes. , 2001, Physical review letters.

[14]  Per Bak,et al.  How Nature Works , 1996 .

[15]  Ian Main,et al.  Long odds on prediction , 1997, Nature.

[16]  Y. Kagan,et al.  Earthquakes Cannot Be Predicted , 1997, Science.

[17]  P. Bak,et al.  Unified scaling law for earthquakes , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[18]  D Sornette,et al.  Diffusion of epicenters of earthquake aftershocks, Omori's law, and generalized continuous-time random walk models. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[19]  Y. Ogata.  Seismicity Analysis through Point-process Modeling: A Review , 1999 .

[20]  Jeen‐Hwa Wang,et al.  On the frequency distribution of interoccurrence times of earthquakes , 1998 .

[21]  Alvaro Corral.  Local distributions and rate fluctuations in a unified scaling law for earthquakes. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[22]  E. Bonabeau.  How nature works: The science of self-organized criticality (copernicus) , 1997 .

[23]  A. Barka,et al.  Heightened odds of large earthquakes near istanbul: An interaction-based probability calculation , 2000, Science.

[24]  Y. Ogata,et al.  The Centenary of the Omori Formula for a Decay Law of Aftershock Activity , 1995 .

[25]  D. Sornette,et al.  The paradox of the expected time until the next earthquake , 1997, Bulletin of The Seismological Society of America (BSSA).