skip to main content

Title: Responding to Media Inquiries about Earthquake Triggering Interactions
Abstract In the aftermath of a significant earthquake, seismologists are frequently asked questions by the media and public regarding possible interactions with recent prior events, including events at great distances away, along with prospects of larger events yet to come, both locally and remotely. For regions with substantial earthquake catalogs that provide information on the regional Gutenberg–Richter magnitude–frequency relationship, Omori temporal aftershock statistical behavior, and aftershock productivity parameters, probabilistic responses can be provided for likelihood of nearby future events of larger magnitude, as well as expected behavior of the overall aftershock sequence. However, such procedures generally involve uncertain extrapolations of parameterized equations to infrequent large events and do not provide answers to inquiries about long-range interactions, either retrospectively for interaction with prior remote large events or prospectively for interaction with future remote large events. Dynamic triggering that may be involved in such long-range interactions occurs, often with significant temporal delay, but is not well understood, making it difficult to respond to related inquiries. One approach to addressing such inquiries is to provide retrospective or prospective occurrence histories for large earthquakes based on global catalogs; while not providing quantitative understanding of any physical interaction, experience-based guidance on the (typically very low) chances of causal interactions can inform public understanding of likelihood of specific scenarios they are commonly very interested in.  more » « less
Award ID(s):
Author(s) / Creator(s):
; ; ;
Date Published:
Journal Name:
Seismological Research Letters
Page Range / eLocation ID:
3035 to 3045
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract

    Seismology is witnessing explosive growth in the diversity and scale of earthquake catalogs. A key motivation for this community effort is that more data should translate into better earthquake forecasts. Such improvements are yet to be seen. Here, we introduce the Recurrent Earthquake foreCAST (RECAST), a deep‐learning model based on recent developments in neural temporal point processes. The model enables access to a greater volume and diversity of earthquake observations, overcoming the theoretical and computational limitations of traditional approaches. We benchmark against a temporal Epidemic Type Aftershock Sequence model. Tests on synthetic data suggest that with a modest‐sized data set, RECAST accurately models earthquake‐like point processes directly from cataloged data. Tests on earthquake catalogs in Southern California indicate improved fit and forecast accuracy compared to our benchmark when the training set is sufficiently long (>104events). The basic components in RECAST add flexibility and scalability for earthquake forecasting without sacrificing performance.

    more » « less
  2. Abstract 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. 
    more » « less
  3. Abstract

    We introduce an algorithm for declustering earthquake catalogs based on the nearest‐neighbor analysis of seismicity. The algorithm discriminates between background and clustered events by random thinning that removes events according to a space‐varying threshold. The threshold is estimated using randomized‐reshuffled catalogs that are stationary, have independent space and time components, and preserve the space distribution of the original catalog. Analysis of catalog produced by the Epidemic Type Aftershock Sequence model demonstrates that the algorithm correctly classifies over 80% of background and clustered events, correctly reconstructs the stationary and space‐dependent background intensity, and shows high stability with respect to random realizations (over 75% of events have the same estimated type in over 90% of random realizations). The declustering algorithm is applied to the global Northern California Earthquake Data Center catalog with magnitudesm≥ 4 during 2000–2015; a Southern California catalog withm≥ 2.5, 3.5 during 1981–2017; an area around the 1992 Landers rupture zone withm≥ 0.0 during 1981–2015; and the Parkfield segment of San Andreas fault withm≥ 1.0 during 1984–2014. The null hypotheses of stationarity and space‐time independence are not rejected by several tests applied to the estimated background events of the global and Southern California catalogs with magnitude ranges Δm< 4. However, both hypotheses are rejected for catalogs with larger range of magnitudes Δm> 4. The deviations from the nulls are mainly due to local temporal fluctuations of seismicity and activity switching among subregions; they can be traced back to the original catalogs and represent genuine features of background seismicity.

    more » « less
  4. Abstract

    Remote earthquake triggering is a well-established phenomenon. Triggering is commonly identified from statistically significant increases in earthquake rate coincident with the passage of seismic energy. In establishing rate changes, short duration earthquake catalogs are commonly used, and triggered sequences are not typically analyzed within the context of background seismic activity. Using 500 mainshocks and four western USA 33-yearlong earthquake catalogs, we compare the ability of three different statistical methods to identify remote earthquake triggering. Counter to many prior studies, we find remote dynamic triggering is rare (conservatively, <2% of the time). For the mainshocks associated with remote rate increases, the spatial and temporal signatures of triggering differ. We find that a rate increase coincident in time with mainshock energy alone is insufficient to conclude that dynamic triggering occurred. To classify dynamically triggered sequences, we suggest moving away from strict statistical measurements and instead use a compatibility assessment that includes multiple factors, like spatial and temporal indicators.

    more » « less
  5. Abstract

    Clustering of earthquake magnitudes is still actively debated, compared to well-established spatial and temporal clustering. Magnitude clustering is not currently implemented in earthquake forecasting but would be important if larger magnitude events are more likely to be followed by similar sized events. Here we show statistically significant magnitude clustering present in many different field and laboratory catalogs at a wide range of spatial scales (mm to 1000 km). It is universal in field catalogs across fault types and tectonic/induced settings, while laboratory results are unaffected by loading protocol or rock types and show temporal stability. The absence of clustering can be imposed by a global tensile stress, although clustering still occurs when isolating to triggered event pairs or spatial patches where shear stress dominates. Magnitude clustering is most prominent at short time and distance scales and modeling indicates >20% repeating magnitudes in some cases, implying it can help to narrow physical mechanisms for seismogenesis.

    more » « less