- journal_title：Bulletin of the Seismological Society of America
- Contributor：Tom Parsons ; Eric L. Geist
- Publisher：Seismological Society of America
- Date：2012-
- Format：text/html
- Language：en
- Identifier：10.1785/0120110282
- journal_abbrev：Bulletin of the Seismological Society of America
- issn：0037-1106
- volume：102
- issue：4
- firstpage：1583
- section：Articles
The pattern of great earthquakes during the past ∼100 yr raises questions whether large earthquake occurrence is linked across global distances, or whether temporal clustering can be attributed to random chance. Great‐earthquake frequency during the past decade in particular has engendered media speculation of heightened global hazard. We therefore examine interevent distributions of Earth’s largest earthquakes at one‐year resolution, and calculate how compatible they are with a random‐in‐time Poisson process. We show, using synthetic catalogs, that the probability of any specific global interevent distribution happening is low, and that short‐term clusters are the least repeatable features of a Poisson process. We examine the real catalog and find, just as expected from synthetic catalogs, that the least probable M≥8.3 earthquake intervals during the past 111 yr were the shortest (t<1 yr) if a Poisson process is active (mean rate of 3.2%). When we study an M≥8.3 catalog with locally triggered events removed, we find a higher mean rate of 9.5% for 0–1 yr intervals, comparable to the value (11.1%) obtained for simulated catalogs drawn from random‐in‐time exponential distributions. We emphasize short interevent times here because they are the most obvious and have led to speculation about physical links among global earthquakes. We also find that comparison of the whole 111‐yr observed M≥8.3 interevent distribution (including long quiescent periods) to a Poisson process is not significantly different than the same comparison made with synthetic catalogs. We therefore find no evidence that global great‐earthquake occurrence is not a random‐in‐time Poisson process.