Record-Breaking Intervals: Detecting Trends in the Incidence of Self-Similar Earthquake Sequences

We introduce a method of resolving temporal incidence trends in earthquake sequences. We have developed a catalog partitioning method based on canonical earthquake scaling relationships, and have further developed a metric based on record-breaking interval (RBI) statistics to resolve increasing and decreasing seismicity in time series of earthquakes. We calculated the RBI metric over fixed-length sequences of earthquake intervals and showed that the length of those sequences is related to the magnitude of the earthquake to which the method is sensitive—longer sequences resolve large earthquakes, shorter sequences resolve small-magnitude events. This sequence length effectively constitutes a local temporal catalog constraint, and we show that spatial constraints can be defined from rupture length scaling. We have applied the method to several high-profile earthquakes and have shown that it consistently resolves aftershock sequences after a period of accelerating seismicity before the targeted mainshock. The method also suggests a minimum detectable (forecastable) mainshock magnitude on the basis of the catalog’s minimum completeness magnitude $$m_{\rm c}$$mc.

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