The overlap of aftershock coda waves and forecasting the first hour aftershocks

2020 ◽  
Author(s):  
Eugenio Lippiello ◽  
Giuseppe Petrillo ◽  
Cataldo Godano ◽  
Lucilla de Arcangelis ◽  
Anna Tramelli ◽  
...  
Keyword(s):  
Aftershock Sequence ◽  
Coda Waves ◽  
Statistical Features ◽  
Short Term ◽  
Geophysical Research ◽  
Ground Shaking ◽  
Epidemic Type Aftershock Sequence ◽  
Novel Approach ◽  
Single Station ◽  
Strong Ground

<p>We show that short term post-seismic incompleteness can be interpreted in terms of the overlap of aftershock coda waves. We use this information to develop a novel procedure which gives accurate occurrence probabilities of post-seismic strong ground shaking within 30 minutes after the mainshock. This novel approach uses, as only information, the ground velocity recorded at a single station without requiring that signals are transferred and elaborated by operational units. We will also discuss how this information can be implemented in the Epidemic-Type Aftershock Sequence model in order to reproduce statistical features in time and magnitude of recorded aftershocks.</p><p><strong>Main references </strong></p><p>de Arcangelis L., Godano C. & Lippiello E. (2018) <em>The Overlap of Aftershock Coda Waves and Short-Term Postseismic Forecasting. </em><strong>Journal of Geophysical Research: Solid Earth, </strong>123: 5661-5674,doi:10.1029/2018JB015518</p><p>Lippiello E., Petrillo G. , Godano G. , Tramelli A., Papadimitriou E. &, Karakostas V. (2019)<em> Forecasting of the first hour aftershocks by means of the perceived magnitude. </em><strong>Nature Communications</strong> , 10, 2953, doi:10.1038/s41467-019-10763-3</p>

scholarly journals Short-term earthquake forecasting experiment before and during the L’Aquila (central Italy) seismic sequence of April 2009

2015 ◽  
Vol 57 (6) ◽  
Author(s):  
Maura Murru ◽  
Jiancang Zhuang ◽  
Rodolfo Console ◽  
Giuseppe Falcone
Keyword(s):  
Central Italy ◽  
Aftershock Sequence ◽  
Earthquake Forecasting ◽  
Model Parameters ◽  
Short Term ◽  
Productivity Function ◽  
Epidemic Type Aftershock Sequence ◽  
Forecasting Performance ◽  
The One ◽  
Lower Magnitude

<div class="page" title="Page 1"><div class="layoutArea"><div class="column"><p>In this paper, we compare the forecasting performance of several statistical models, which are used to describe the occurrence process of earthquakes in forecasting the short-term earthquake probabilities during the L’Aquila earthquake sequence in central Italy in 2009. These models include the Proximity to Past Earthquakes (PPE) model and two versions of the Epidemic Type Aftershock Sequence (ETAS) model. We used the information gains corresponding to the Poisson and binomial scores to evaluate the performance of these models. It is shown that both ETAS models work better than the PPE model. However, in comparing the two types of ETAS models, the one with the same fixed exponent coefficient (<span>alpha)</span> = 2.3 for both the productivity function and the scaling factor in the spatial response function (ETAS I), performs better in forecasting the active aftershock sequence than the model with different exponent coefficients (ETAS II), when the Poisson score is adopted. ETAS II performs better when a lower magnitude threshold of 2.0 and the binomial score are used. The reason is found to be that the catalog does not have an event of similar magnitude to the L’Aquila mainshock (M<sub>w</sub> 6.3) in the training period (April 16, 2005 to March 15, 2009), and the (<span>alpha)</span>-value is underestimated, thus the forecast seismicity is underestimated when the productivity function is extrapolated to high magnitudes. We also investigate the effect of the inclusion of small events in forecasting larger events. These results suggest that the training catalog used for estimating the model parameters should include earthquakes of magnitudes similar to the mainshock when forecasting seismicity during an aftershock sequence.</p></div></div></div>

Testing of the foreshock hypothesis within an epidemic like description of seismicity

2020 ◽  
Author(s):  
G Petrillo ◽  
E Lippiello
Keyword(s):  
Seismic Activity ◽  
Good Description ◽  
Aftershock Sequence ◽  
Short Term ◽  
Etas Model ◽  
Temporal Clustering ◽  
Epidemic Type Aftershock Sequence ◽  
Preparatory Phase ◽  
Spatio Temporal ◽  
The One

Summary The Epidemic Type Aftershock Sequence (ETAS) model provides a good description of the post-seismic spatio-temporal clustering of seismicity and is also able to capture some features of the increase of seismic activity caused by foreshocks. Recent results, however, have shown that the number of foreshocks observed in instrumental catalogs is significantly much larger than the one predicted by the ETAS model. Here we show that it is possible to keep an epidemic description of post-seismic activity and, at the same time, to incorporate pre-seismic temporal clustering, related to foreshocks. Taking also into-account the short-term incompleteness of instrumental catalogs, we present a model which achieves very good description of the southern California seismicity both on the aftershock and on the foreshock side. Our results indicate that the existence of a preparatory phase anticipating mainshocks represents the most plausible explanation for the occurrence of foreshocks.

scholarly journals The Relevance of Foreshocks in Earthquake Triggering: A Statistical Study

2018 ◽  
Author(s):  
Eugenio Lippiello ◽  
Cataldo Godano ◽  
Lucilla De Arcangelis
Keyword(s):  
Statistical Study ◽  
Aftershock Sequence ◽  
Statistical Features ◽  
Earthquake Triggering ◽  
Etas Model ◽  
Epidemic Type Aftershock Sequence ◽  
The One ◽  
Triggering Process ◽  
Large Earthquakes ◽  
Good Agreement

An increase of seismic activity is often observed before large earthquakes. Events responsible for this increase are usually named foreshock and their occurrence probably represents the most reliable precursory pattern. Many foreshocks statistical features can be interpreted in terms of the standard mainshock-to-aftershock triggering process and are recovered in the Epidemic Type Aftershock Sequence ETAS model. Here we present a statistical study of instrumental seismic catalogs from four different geographic regions. We focus on some common features of foreshocks in the four catalogs which cannot be reproduced by the ETAS model. In particular we find in instrumental catalogs a significantly larger number of foreshocks than the one predicted by the ETAS model. We show that this foreshock excess cannot be attributed to catalog incompleteness. We therefore propose a generalized formulation of the ETAS model, the ETAFS model, which explicitly includes foreshock occurrence. Statistical features of aftershocks and foreshocks in the ETAFS model are in very good agreement with instrumental results.

scholarly journals Long-term earthquake forecasts based on the epidemic-type aftershock sequence (ETAS) model for short-term clustering

2012 ◽  
Vol 2 (1) ◽  
pp. 8 ◽  
Author(s):  
Jiancang Zhuang
Keyword(s):  
Time Window ◽  
Space Time ◽  
Aftershock Sequence ◽  
Maximum Magnitude ◽  
Short Term ◽  
Magnitude Distribution ◽  
Seismicity Rate ◽  
Distribution Of The Maximum ◽  
Epidemic Type Aftershock Sequence ◽  
Term Clustering

Based on the ETAS (epidemic-type aftershock sequence) model, which is used for describing the features of short-term clustering of earthquake occurrence, this paper presents some theories and techniques related to evaluating the probability distribution of the maximum magnitude in a given space-time window, where the Gutenberg-Richter law for earthquake magnitude distribution cannot be directly applied. It is seen that the distribution of the maximum magnitude in a given space-time volume is determined in the longterm by the background seismicity rate and the magnitude distribution of the largest events in each earthquake cluster. The techniques introduced were applied to the seismicity in the Japan region in the period from 1926 to 2009. It was found that the regions most likely to have big earthquakes are along the Tohoku (northeastern Japan) Arc and the Kuril Arc, both with much higher probabilities than the offshore Nankai and Tokai regions.

scholarly journals The Relevance of Foreshocks in Earthquake Triggering: A Statistical Study

Entropy ◽  
2019 ◽  
Vol 21 (2) ◽  
pp. 173 ◽  
Author(s):  
Eugenio Lippiello ◽  
Cataldo Godano ◽  
Lucilla de Arcangelis
Keyword(s):  
Statistical Study ◽  
Aftershock Sequence ◽  
Statistical Features ◽  
Earthquake Triggering ◽  
Etas Model ◽  
Epidemic Type Aftershock Sequence ◽  
The One ◽  
Triggering Process ◽  
Large Earthquakes ◽  
Good Agreement

An increase of seismic activity is often observed before large earthquakes. Events responsible for this increase are usually named foreshock and their occurrence probably represents the most reliable precursory pattern. Many foreshocks statistical features can be interpreted in terms of the standard mainshock-to-aftershock triggering process and are recovered in the Epidemic Type Aftershock Sequence ETAS model. Here we present a statistical study of instrumental seismic catalogs from four different geographic regions. We focus on some common features of foreshocks in the four catalogs which cannot be reproduced by the ETAS model. In particular we find in instrumental catalogs a significantly larger number of foreshocks than the one predicted by the ETAS model. We show that this foreshock excess cannot be attributed to catalog incompleteness. We therefore propose a generalized formulation of the ETAS model, the ETAFS model, which explicitly includes foreshock occurrence. Statistical features of aftershocks and foreshocks in the ETAFS model are in very good agreement with instrumental results.

ETAS-Approach Accounting for Short-Term Incompleteness of Earthquake Catalogs

2021 ◽  
Author(s):  
Sebastian Hainzl
Keyword(s):  
Aftershock Sequence ◽  
Additional Parameter ◽  
Spatiotemporal Evolution ◽  
Short Term ◽  
Seismicity Rate ◽  
Detection Algorithms ◽  
Estimated Parameters ◽  
Epidemic Type Aftershock Sequence ◽  
Aftershock Sequences ◽  
Completeness Magnitude

ABSTRACT The epidemic-type aftershock sequence (ETAS) model is a powerful statistical model to explain and forecast the spatiotemporal evolution of seismicity. However, its parameter estimation can be strongly biased by catalog deficiencies, particularly short-term incompleteness related to missing events in phases of high-seismic activity. Recent studies have shown that these short-term fluctuations of the completeness magnitude can be explained by the blindness of detection algorithms after earthquakes, preventing the detection of events with a smaller magnitude. Based on this assumption, I derive a direct relation between the true and detectable seismicity rate and magnitude distributions, respectively. These relations only include one additional parameter, the so-called blind time Tb, and lead to a closed-form maximum-likelihood formulation to estimate the ETAS parameters directly accounting for varying completeness. Tests using synthetic simulations show that the true parameters can be resolved from incomplete catalogs. Finally, I apply the new model to California’s most prominent mainshock–aftershock sequences in the last decades. The results show that the model leads to superior fits with Tb decreasing with time, indicating improved detection algorithms. The estimated parameters significantly differ from the estimation with the standard approach, indicating higher b-values and larger trigger potentials than previously thought.

scholarly journals Combining a Locally Restricted Anisotropic Spatial Kernel with an ETAS Incomplete Model for Better Forecasts of the 2019 Ridgecrest Sequence

2021 ◽  
Author(s):  
Christian Grimm ◽  
Sebastian Hainzl ◽  
Martin Käser ◽  
Helmut Küchenhoff
Keyword(s):  
Aftershock Sequence ◽  
Large Area ◽  
Short Term ◽  
Aftershock Activity ◽  
Time Model ◽  
Strong Earthquakes ◽  
Etas Model ◽  
Incomplete Model ◽  
Epidemic Type Aftershock Sequence ◽  
Aftershock Sequences

Abstract Strong earthquakes cause aftershock sequences that are clustered in time according to a power decay law, and in space along their extended rupture, shaping a typically elongate pattern of aftershock locations. A widely used approach to model seismic clustering is the Epidemic Type Aftershock Sequence (ETAS) model, that shows three major biases: First, the conventional ETAS approach assumes isotropic spatial triggering, which stands in conflict with observations and geophysical arguments for strong earthquakes. Second, the spatial kernel has unlimited extent, allowing smaller events to exert disproportionate trigger potential over an unrealistically large area. Third, the ETAS model assumes complete event records and neglects inevitable short-term aftershock incompleteness as a consequence of overlapping coda waves. These three effects can substantially bias the parameter estimation and particularly lead to underestimated cluster sizes. In this article, we combine the approach of Grimm (2021), which introduced a generalized anisotropic and locally restricted spatial kernel, with the ETAS-Incomplete (ETASI) time model of Hainzl (2021), to define an ETASI space-time model with flexible spatial kernel that solves the abovementioned shortcomings. We apply different model versions to a triad of forecasting experiments of the 2019 Ridgecrest sequence, and evaluate the prediction quality with respect to cluster size, largest aftershock magnitude and spatial distribution. The new model provides the potential of more realistic simulations of on-going aftershock activity, e.g.~allowing better predictions of the probability and location of a strong, damaging aftershock, which might be beneficial for short term risk assessment and desaster response.

Nonlinear behavior of soil sediments identified by using borehole records observed at the Ashigra Valley, Japan

1995 ◽  
Vol 85 (6) ◽  
pp. 1821-1834
Author(s):  
Toshimi Satoh ◽  
Toshiaki Sato ◽  
Hiroshi Kawase
Keyword(s):  
Shear Strain ◽  
Main Part ◽  
Nonlinear Behavior ◽  
Strong Motion ◽  
S Wave ◽  
Ground Shaking ◽  
Wave Velocities ◽  
The One ◽  
Soil Sediments ◽  
Strong Ground

Abstract We evaluate the nonlinear behavior of soil sediments during strong ground shaking based on the identification of their S-wave velocities and damping factors for both the weak and strong motions observed on the surface and in a borehole at Kuno in the Ashigara Valley, Japan. First we calculate spectral ratios between the surface station KS2 and the borehole station KD2 at 97.6 m below the surface for the main part of weak and strong motions. The predominant period for the strong motion is apparently longer than those for the weak motions. This fact suggests the nonlinearity of soil during the strong ground shaking. To quantify the nonlinear behavior of soil sediments, we identify their S-wave velocities and damping factors by minimizing the residual between the observed spectral ratio and the theoretical amplification factor calculated from the one-dimensional wave propagation theory. The S-wave velocity and the damping factor h (≈(2Q)−1) of the surface alluvial layer identified from the main part of the strong motion are about 10% smaller and 50% greater, respectively, than those identified from weak motions. The relationships between the effective shear strain (=65% of the maximum shear strain) calculated from the one-dimensional wave propagation theory and the shear modulus reduction ratios or the damping factors estimated by the identification method agree well with the laboratory test results. We also confirm that the soil model identified from a weak motion overestimates the observed strong motion at KS2, while that identified from the strong motion reproduces the observed. Thus, we conclude that the main part of the strong motion, whose maximum acceleration at KS2 is 220 cm/sec2 and whose duration is 3 sec, has the potential of making the surface soil nonlinear at an effective shear strain on the order of 0.1%. The S-wave velocity in the surface alluvial layer identified from the part just after the main part of the strong motion is close to that identified from weak motions. This result suggests that the shear modulus recovers quickly as the shear strain level decreases.

scholarly journals Earthquakes on the surface: earthquake location and area based on more than 14 500 ShakeMaps

2018 ◽  
Vol 18 (6) ◽  
pp. 1665-1679
Author(s):  
Stephanie Lackner
Keyword(s):  
Ground Motion ◽  
Strong Ground Motion ◽  
Earthquake Location ◽  
Primary Concern ◽  
Ground Acceleration ◽  
Ground Shaking ◽  
Geographic Context ◽  
The Social ◽  
Strong Ground

Abstract. Earthquake impact is an inherently interdisciplinary topic that receives attention from many disciplines. The natural hazard of strong ground motion is the reason why earthquakes are of interest to more than just seismologists. However, earthquake shaking data often receive too little attention by the general public and impact research in the social sciences. The vocabulary used to discuss earthquakes has mostly evolved within and for the discipline of seismology. Discussions on earthquakes outside of seismology thus often use suboptimal concepts that are not of primary concern. This study provides new theoretic concepts as well as novel quantitative data analysis based on shaking data. A dataset of relevant global earthquake ground shaking from 1960 to 2016 based on USGS ShakeMap data has been constructed and applied to the determination of past ground shaking worldwide. Two new definitions of earthquake location (the shaking center and the shaking centroid) based on ground motion parameters are introduced and compared to the epicenter. These definitions are intended to facilitate a translation of the concept of earthquake location from a seismology context to a geographic context. Furthermore, the first global quantitative analysis on the size of the area that is on average exposed to strong ground motion – measured by peak ground acceleration (PGA) – is provided.

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