Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/4296
Authors: Marzocchi, W.* 
Selva, J.* 
Title: Long-term influence of giant earthquakes: backward empirical evidence and forward test
Journal: Bulletin of the Seismological Society of America 
Series/Report no.: 3/98 (2008)
Publisher: Seismological Society of America
Issue Date: Jun-2008
DOI: 10.1785/0120070203
URL: http://www.bssaonline.org/cgi/content/full/98/3/1102?maxtoshow=&HITS=10&hits=10&RESULTFORMAT=&author1=selva&searchid=1&FIRSTINDEX=0&sortspec=relevance&resourcetype=HWCIT
Keywords: Long-term earthquake interaction
Forward Test
Subject Classification04. Solid Earth::04.06. Seismology::04.06.02. Earthquake interactions and probability 
Abstract: We investigate the capability of the strongest earthquakes to modify sig- nificantly the seismicity in a wide spatiotemporal window. In particular, we show that the strongest earthquakes of last century were probably able to influence the seismicity at large spatiotemporal distances, extending their reach over thousands of kilometers and decades later. We report statistically significant differences in worldwide seismi- city before and after the occurrence of the strongest earthquakes of the last century, whose perturbation is modeled by means of coseismic and postseismic stress varia- tions. This long-term coupling has produced time variations in worldwide seismic activity that appear related to the physical coupling between the focal mechanism of source earthquakes and the tectonic setting of each zone. These results could provide new important insights on seismic hazard assessment because they raise doubts on the validity of two paradigms; that is, the steadiness of the mainshock rate and the iso- lation of a seismic region from the surrounding areas. Finally, in addition to this back- ward analysis, we also provide a formal forward test by forecasting the effects on global seismicity of the recent Sumatra–Andaman earthquakes; this is maybe a unique chance to test the long-term hypothesis with an independent dataset that avoids, by definition, any kind of (often unconscious) optimization of the results that is an un- avoidable possibility in backward analyses.
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