Mainshock‐Aftershock Clustering in Volcanic Regions

Abstract

Earthquakes break their general Poissonean behavior through two types of seismic bursts: swarms and mainshock‐aftershock sequences. The former is commonly thought to dominate in volcanic and geothermal regions, but aftershock production, including within swarms, is not well studied in volcanic regions. Here we compare mainshock‐aftershock clustering in active volcanic regions in Japan to nearby nonvolcanic regions. We find that aftershock production is similar in both areas by two separate metrics: (1) Both volcanic and nonvolcanic regions have similar proportions of areas that cluster into mainshock‐aftershock sequences. (2) Volcanic areas with mainshock‐aftershock sequences have aftershock productivity at least as high as nonvolcanic regions. We also find that volcano‐tectonic events that are precursors to an eruption are more common at volcanoes without mainshock‐aftershock clusters than at volcanoes with well‐defined mainshock‐aftershock clusters. This last finding hints at a strategy to identify volcanic systems where cataloged earthquakes are good predictors of behavior.

Indicators of Volcanic Eruptions Revealed by Global M4+ Earthquakes

“…In contrast, our global analysis of M4+ events is not capable of deciphering such detailed changes but may instead inform us about the deviations in aftershock productivity near volcanoes, above the M4 level. In general, we find that aftershock productivity for M4+ events in volcanic areas to be broadly similar to nonvolcanic areas, in agreement with other recent findings (Garza-Giron et al, 2018), and overall the b-values for the M4+ events do not differ significantly in preeruptive or syneruptive periods compared to others ( Figure S5). Thus, we find no deviations in the frequency-magnitude distributions that might help to distinguish M4+ eruptive seismicity from tectonic seismicity.…”

“…For example, the relations provided by Lolli et al (2014) are only directly applicable to magnitudes computed by the ISC, while Md requires local calibration and is generally not well suited for larger magnitude events. Previous studies have avoided similar issues by limiting their analyses to uniformly produced catalogs (e.g., Garza-Giron et al, 2018;Pesicek et al, 2018;Shuler et al, 2013aShuler et al, , 2013bVidale et al, 2006 . In our preference for data quantity over quality, we retain all available events and show that the effects of nonuniformly computed magnitudes on our results are minimal (Figure S1; Supporting Information).…”

What Controls Variations in Aftershock Productivity?

“…We balance these trade‐offs to find window selection criteria that yield as many aftershocks as possible without incurring a significant contribution from background activity (Figure ). We assess the performance of each space‐time window by comparing the results to the median of 100 time‐shuffled catalogs that preserve the original spatial distribution but break the actual time sequence of the catalog (Garza‐Giron et al, ). The shuffled catalog effectively represents an upper bound on the contribution from background activity since it includes all events in the catalog (including potential aftershocks).…”

“…For our primary windowing method, we classify earthquakes as foreshocks, mainshocks, or aftershocks in a hierarchical sense (following, Felzer & Brodsky, ; Brodsky, ; Wetzler et al, ; Garza‐Giron et al, ). We define the largest earthquake in the catalog as a mainshock and then mark as foreshocks and aftershocks earthquakes within magnitude‐dependent space and fixed time windows before and after the mainshock.…”

Prevalence of Seismic Rate Anomalies Preceding Volcanic Eruptions in Alaska

“…Volcanic earthquake swarms often have large b-values and no clear mainshock (McNutt, 1996(McNutt, , 2005, potentially distinguishing them from tectonic mainshock-aftershock sequences. Yet many counter-examples exist (Mori et al, 1996;Roman et al, 2004;Pesicek et al, 2008;Garza-Giron et al, 2018). Other general characteristics of pre-eruptive VT swarms are (1) the number of events and average energy increases over time, (2) the largest events occur in the middle of the swarm, and (3) the swarm includes several events within 1 /2 magnitude unit of the largest event (White and McCausland, 2016).…”