Two Foreshock Sequences Post Gulia and Wiemer (2019)

Abstract

<jats:title>Abstract</jats:title> <jats:p>Recognizing earthquakes as foreshocks in real time would provide a valuable forecasting capability. In a recent study, Gulia and Wiemer (2019) proposed a traffic-light system that relies on abrupt changes in b-values relative to background values. The approach utilizes high-resolution earthquake catalogs to monitor localized regions around the largest events and distinguish foreshock sequences (reduced b-values) from aftershock sequences (increased b-values). The recent well-recorded earthquake foreshock sequences in Ridgecrest, California, and Maria Antonia, Puerto Rico, provide an opportunity to test the procedure. For Ridgecrest, our b-value time series indicates an elevated risk of a larger impending earthquake during the Mw 6.4 foreshock sequence and provides an ambiguous identification of the onset of the Mw 7.1 aftershock sequence. However, the exact result depends strongly on expert judgment. Monte Carlo sampling across a range of reasonable decisions most often results in ambiguous warning levels. In the case of the Puerto Rico sequence, we record significant drops in b-value prior to and following the largest event (Mw 6.4) in the sequence. The b-value has still not returned to background levels (12 February 2020). The Ridgecrest sequence roughly conforms to expectations; the Puerto Rico sequence will only do so if a larger event occurs in the future with an ensuing b-value increase. Any real-time implementation of this approach will require dense instrumentation, consistent (versioned) low completeness catalogs, well-calibrated maps of regionalized background b-values, systematic real-time catalog production, and robust decision making about the event source volumes to analyze.</jats:p>

B‐Positive: A Robust Estimator of Aftershock Magnitude Distribution in Transiently Incomplete Catalogs

“…The curious reader can investigate the impact of different parameter choices on the classical GR estimate in Dascher‐Cousineau et al. (2020), or on their own by inserting the b ‐positive estimator into the scripts provided by Gulia and Wiemer (2019) and Gulia et al. (2020).…”

Seismic and Aseismic Preparatory Processes Before Large Stick–Slip Failure

“…Fluctuation of b-values have also been observed prior to large earthquakes (Smith 1981). A significant bvalue decrease has been reported to precede the large 2014 Iquique and the 2011 Tohoku earthquakes (Nanjo et al 2012, Schurr et al 2014) and more recently the 2020, M W = 6.4 event in Puerto Rico (Dascher-Cousineau et al 2020).…”

“…Recently, Gulia and Wiemer (2019) suggested to estimate temporal trends in b-value before (b-value decrease) and after (b-value increase) large events to potentially identify foreshocks in real time. However, temporal changes of b-values as observed from foreshock-mainshock sequences observed in the field remain difficult to interpret (Dascher-Cousineau et al 2020;Gulia et al 2020).…”

Short-Term Foreshocks as Key Information for Mainshock Timing and Rupture: The Mw6.8 25 October 2018 Zakynthos Earthquake, Hellenic Subduction Zone

“…However, space-time clusters, which do not conclude with the generation of a stronger earthquake exceeding significantly the size of the rest cluster events, are transient seismicity swarms. Aftershock activity follows a mainshock, but the discrimination between foreshocks and other types of clusters is a puzzling issue [ 21 , 22 , 23 ]. On the other hand, strong or large earthquakes may happen without precursory seismicity anomalies.…”

“…Since no standard methods have been established so far to discriminate between foreshocks and other seismicity clusters at least in real time conditions, the a posteriori examination of case studies is of particular importance for better understanding geophysical and statistical features that may support discrimination of the various types of seismicity clusters, highlight the predictive value of foreshocks and reveal the foreshocks role in the mainshock rupture process. Proposed discriminants of various seismicity cluster types include statistical space-time-size patterns [ 16 , 19 , 21 , 22 , 23 ], waveform similarity [ 18 , 25 , 33 ] and changes in focal mechanism and stress field [ 34 , 35 ].…”