TY - JOUR A1 - Aiken, John M. A1 - Aiken, Chastity A1 - Cotton, Fabrice T1 - A python library for teaching computation to seismology students JF - Seismological research letters N2 - Python is at the forefront of scientific computation for seismologists and therefore should be introduced to students interested in becoming seismologists. On its own, Python is open source and well designed with extensive libraries. However, Python code can also be executed, visualized, and communicated to others with "Jupyter Notebooks". Thus, Jupyter Notebooks are ideal for teaching students Python and scientific computation. In this article, we designed an openly available Python library and collection of Jupyter Notebooks based on defined scientific computation learning goals for seismology students. The Notebooks cover topics from an introduction to Python to organizing data, earthquake catalog statistics, linear regression, and making maps. Our Python library and collection of Jupyter Notebooks are meant to be used as course materials for an upper-division data analysis course in an Earth Science Department, and the materials were tested in a Probabilistic Seismic Hazard course. However, seismologists or anyone else who is interested in Python for data analysis and map making can use these materials. Y1 - 2018 U6 - https://doi.org/10.1785/0220170246 SN - 0895-0695 SN - 1938-2057 VL - 89 IS - 3 SP - 1165 EP - 1171 PB - Seismological Society of America CY - Albany ER - TY - JOUR A1 - Al Atik, Linda A1 - Abrahamson, Norman A. A1 - Bommer, Julian J. A1 - Scherbaum, Frank A1 - Cotton, Fabrice A1 - Kuehn, Nicolas T1 - The variability of ground-motion prediction models and its components Y1 - 2010 UR - http://srl.geoscienceworld.org/ U6 - https://doi.org/10.1785/gssrl.81.5.794 SN - 0895-0695 ER - TY - JOUR A1 - Bayona Viveros, Jose Antonio A1 - von Specht, Sebastian A1 - Strader, Anne A1 - Hainzl, Sebastian A1 - Cotton, Fabrice A1 - Schorlemmer, Danijel T1 - A Regionalized Seismicity Model for Subduction Zones Based on Geodetic Strain Rates, Geomechanical Parameters, and Earthquake-Catalog Data JF - Bulletin of the Seismological Society of America N2 - The Seismic Hazard Inferred from Tectonics based on the Global Strain Rate Map (SHIFT_GSRM) earthquake forecast was designed to provide high-resolution estimates of global shallow seismicity to be used in seismic hazard assessment. This model combines geodetic strain rates with global earthquake parameters to characterize long-term rates of seismic moment and earthquake activity. Although SHIFT_GSRM properly computes seismicity rates in seismically active continental regions, it underestimates earthquake rates in subduction zones by an average factor of approximately 3. We present a complementary method to SHIFT_GSRM to more accurately forecast earthquake rates in 37 subduction segments, based on the conservation of moment principle and the use of regional interface seismicity parameters, such as subduction dip angles, corner magnitudes, and coupled seismogenic thicknesses. In seven progressive steps, we find that SHIFT_GSRM earthquake-rate underpredictions are mainly due to the utilization of a global probability function of seismic moment release that poorly captures the great variability among subduction megathrust interfaces. Retrospective test results show that the forecast is consistent with the observations during the 1 January 1977 to 31 December 2014 period. Moreover, successful pseudoprospective evaluations for the 1 January 2015 to 31 December 2018 period demonstrate the power of the regionalized earthquake model to properly estimate subduction-zone seismicity. Y1 - 2019 U6 - https://doi.org/10.1785/0120190034 SN - 0037-1106 SN - 1943-3573 VL - 109 IS - 5 SP - 2036 EP - 2049 PB - Seismological Society of America CY - Albany ER - TY - JOUR A1 - Beauval, Celine A1 - Tasan, Hilal A1 - Laurendeau, Aurore A1 - Delavaud, Elise A1 - Cotton, Fabrice A1 - Gueguen, Philippe A1 - Kühn, Nicolas T1 - On the testing of ground-motion prediction equations against small-magnitude data JF - Bulletin of the Seismological Society of America N2 - Ground-motion prediction equations (GMPE) are essential in probabilistic seismic hazard studies for estimating the ground motions generated by the seismic sources. In low-seismicity regions, only weak motions are available during the lifetime of accelerometric networks, and the equations selected for the probabilistic studies are usually models established from foreign data. Although most GMPEs have been developed for magnitudes 5 and above, the minimum magnitude often used in probabilistic studies in low-seismicity regions is smaller. Disaggregations have shown that, at return periods of engineering interest, magnitudes less than 5 may be contributing to the hazard. This paper presents the testing of several GMPEs selected in current international and national probabilistic projects against weak motions recorded in France (191 recordings with source-site distances up to 300 km, 3:8 <= M-w <= 4:5). The method is based on the log-likelihood value proposed by Scherbaum et al. (2009). The best-fitting models (approximately 2:5 <= LLH <= 3:5) over the whole frequency range are the Cauzzi and Faccioli (2008), Akkar and Bommer (2010), and Abrahamson and Silva (2008) models. No significant regional variation of ground motions is highlighted, and the magnitude scaling could be the predominant factor in the control of ground-motion amplitudes. Furthermore, we take advantage of a rich Japanese dataset to run tests on randomly selected low-magnitude subsets, and confirm that a dataset of similar to 190 observations, the same size as the French dataset, is large enough to obtain stable LLH estimates. Additionally we perform the tests against larger magnitudes (5-7) from the Japanese dataset. The ranking of models is partially modified, indicating a magnitude scaling effect for some of the models, and showing that extrapolating testing results obtained from low-magnitude ranges to higher magnitude ranges is not straightforward. Y1 - 2012 U6 - https://doi.org/10.1785/0120110271 SN - 0037-1106 VL - 102 IS - 5 SP - 1994 EP - 2007 PB - Seismological Society of America CY - El Cerrito ER - TY - JOUR A1 - Bindi, Dino A1 - Cotton, Fabrice A1 - Spallarossa, Daniele A1 - Picozzi, Matteo A1 - Rivalta, Eleonora T1 - Temporal variability of ground shaking and stress drop in Central Italy BT - A Hint for Fault Healing? JF - Bulletin of the Seismological Society of America N2 - Ground‐motion prediction equations (GMPEs) are calibrated to predict the intensity of ground shaking at any given location, based on earthquake magnitude, source‐to‐site distance, local soil amplifications, and other parameters. GMPEs are generally assumed to be independent of time; however, evidence is increasing that large earthquakes modify the shallow soil conditions and those of the fault zone for months or years. These changes may affect the intensity of shaking and result in time‐dependent effects that can potentially be resolved by analyzing between‐event residuals (residuals between observed and predicted ground motion for individual earthquakes averaged over all stations). Here, we analyze a data set of about 65,000 recordings for about 1400 earthquakes in the moment magnitude range 2.5–6.5 that occurred in central Italy from 2008 to 2017 to capture the temporal variability of the ground shaking at high frequency. We first compute between‐event residuals for each earthquake in the Fourier domain with respect to a GMPE developed ad hoc for the analyzed data set. The between‐events show large changes after the occurrence of mainshocks such as the 2009 Mw 6.3 L'Aquila, the 2016 Mw 6.2 Amatrice, and Mw 6.5 Norcia earthquakes. Within the time span of a few months after the mainshocks, the between‐event contribution to the ground shaking varies by a factor 7. In particular, we find a large drop in the between‐events in the aftermath of the L'Aquila earthquake, followed by a slow positive trend that leads to a recovery interrupted by a new drop at the beginning of 2014. We also quantify the frequency‐dependent correlation between the Brune stress drop Δσ and the between‐events. We find that the temporal changes of Δσ resemble those of the between‐event residuals; in particular, during the period when the between‐events show the positive trend, the average logarithm of Δσ increases with an annual rate of 0.19 (i.e., the amplification factor for Δσ is 1.56 per year). Breakpoint analysis located a change in the linear trend coefficients of Δσ versus time in February 2014, although no large earthquakes occurred at that time. Finally, the temporal variability of Δσ mirrors the relative seismic‐velocity variations observed in previous studies for the same area and period, suggesting that both crack healing along the main fault system and healing of microcracks distributed at shallow depths throughout the surrounding region might be necessary to explain the wider observations of postearthquake recovery. Y1 - 2018 U6 - https://doi.org/10.1785/0120180078 SN - 0037-1106 SN - 1943-3573 VL - 108 IS - 4 SP - 1853 EP - 1863 PB - Seismological Society of America CY - Albany ER - TY - JOUR A1 - Bindi, Dino A1 - Kotha, Sreeram Reddy A1 - Weatherill, Graeme A1 - Lanzano, Giovanni A1 - Luzi, Lucia A1 - Cotton, Fabrice T1 - The pan-European engineering strong motion (ESM) flatfile BT - consistency check via residual analysis JF - Bulletin of earthquake engineering : official publication of the European Association for Earthquake Engineering N2 - We present the results of a consistency check performed over the flatfile extracted from the engineering strong motion (ESM) database. The flatfile includes 23,014 recordings from 2179 earthquakes in the magnitude range from 3.5 to 7.8 that occurred since the 1970s in Europe and Middle East, as presented in the companion article by Lanzano et al. (Bull Earthq Eng, 2018a). The consistency check is developed by analyzing different residual distributions obtained from ad-hoc ground motion prediction equations for the absolute spectral acceleration (SA), displacement and Fourier amplitude spectra (FAS). Only recordings from earthquakes shallower than 40 km are considered in the analysis. The between-event, between-station and event-and-station corrected residuals are computed by applying a mixed-effect regression. We identified those earthquakes, stations, and recordings showing the largest deviations from the GMPE median predictions, and also evaluated the statistical uncertainty on the median model to get insights on the applicable magnitude–distance ranges and the usable period (or frequency) range. We observed that robust median predictions are obtained up to 8 s for SA and up to 20 Hz for FAS, although median predictions for Mw ≥ 7 show significantly larger uncertainties with ‘bumps’ starting above 5 s for SA and below 0.3 Hz for FAS. The between-station variance dominates over the other residual variances, and the dependence of the between-station residuals on logarithm of Vs30 is well-described by a piece-wise linear function with period-dependent slopes and hinge velocity around 580 m/s. Finally, we compared the between-event residuals obtained by considering two different sources of moment magnitude. The results show that, at long periods, the between-event terms from the two regressions have a weak correlation and the overall between-event variability is dissimilar, highlighting the importance of magnitude source in the regression results. KW - Ground motion prediction equation KW - Residual analysis KW - European strong motion data Y1 - 2018 U6 - https://doi.org/10.1007/s10518-018-0466-x SN - 1570-761X SN - 1573-1456 VL - 17 IS - 2 SP - 583 EP - 602 PB - Springer CY - Dordrecht ER - TY - JOUR A1 - Bindi, Dino A1 - Picozzi, Matteo A1 - Spallarossa, Daniele A1 - Cotton, Fabrice A1 - Kotha, Sreeram Reddy T1 - Impact of Magnitude Selection on Aleatory Variability Associated with Ground-Motion Prediction Equations BT - Part II-Analysis of the Between-Event Distribution in Central Italy JF - Bulletin of the Seismological Society of America N2 - We derive a set of regional ground-motion prediction equations (GMPEs) in the Fourier amplitude spectra (FAS-GMPE) and in the spectral acceleration (SA-GMPE) domains for the purpose of interpreting the between-event residuals in terms of source parameter variability. We analyze a dataset of about 65,000 recordings generated by 1400 earthquakes (moment magnitude 2: 5 <= M-w <= 6: 5, hypocentral distance R-hypo <= 150 km) that occurred in central Italy between January 2008 and October 2017. In a companion article (Bindi, Spallarossa, et al., 2018), the nonparametric acceleration source spectra were interpreted in terms of omega-square models modified to account for deviations from a high-frequency flat plateau through a parameter named k(source). Here, the GMPEs are derived considering the moment (M-w), the local (M-L), and the energy (M-e) magnitude scales, and the between-event residuals are computed as random effects. We show that the between-event residuals for the FAS-GMPE implementing M-w are correlated with stress drop, with correlation coefficients increasing with increasing frequency up to about 10 Hz. Contrariwise, the correlation is weak for the FAS-GMPEs implementing M-L and M-e, in particular between 2 and 5 Hz, where most of the corner frequencies lie. At higher frequencies, all models show a strong correlation with k(source). The correlation with the source parameters reflects in a different behavior of the standard deviation tau of the between-event residuals with frequency. Although tau is smaller for the FAS-GMPE using M-w below 1.5 Hz, at higher frequencies, the model implementing either M-L or M-e shows smaller values, with a reduction of about 30% at 3 Hz (i.e., from 0.3 for M-w to 0.1 for M-L). We conclude that considering magnitude scales informative for the stress-drop variability allows to reduce the between-event variability with a significant impact on the hazard assessment, in particular for studies in which the ergodic assumption on site is removed. Y1 - 2019 U6 - https://doi.org/10.1785/0120180239 SN - 0037-1106 SN - 1943-3573 VL - 109 IS - 1 SP - 251 EP - 262 PB - Seismological Society of America CY - Albany ER - TY - JOUR A1 - Bindi, Dino A1 - Spallarossa, D. A1 - Picozzi, M. A1 - Scafidi, D. A1 - Cotton, Fabrice T1 - Impact of magnitude selection on aleatory variability associated with ground-motion prediction equations BT - Part I-Local, Energy, and Moment Magnitude Calibration and Stress-Drop Variability in Central Italy JF - Bulletin of the Seismological Society of America N2 - In this study, we analyzed 10 yrs of seismicity in central Italy from 2008 to 2017, a period witnessing more than 1400 earthquakes in the magnitude range 2.5≤Mw≤6.5⁠. The data set includes the main sequences that have occurred in the area, including those associated with the 2009 Mw 6.3 L'Aquila earthquake and the 2016–2017 sequence (⁠Mw 6.2 Amatrice, Mw 6.1 Visso, and Mw 6.5 Norcia earthquakes). We calibrated a local magnitude scale, investigating the impact of changing the reference distance at which the nonparametric attenuation is tied to the zero‐magnitude attenuation function for southern California. We also developed an attenuation model to compute the radiated seismic energy (⁠Es⁠) from the time integral of the squared ground‐motion velocity. Seismic moment (⁠M0⁠) and stress drop (⁠Δσ⁠) were estimated for each earthquake by fitting a ω‐square model to the source spectra obtained by applying a nonparametric spectral inversion. The Δσ‐values vary over three orders of magnitude from about 0.1 to 10 MPa, the larger values associated with the mainshocks. The Δσ‐values describe a lognormal distribution with mean and standard deviation equal to log(Δσ)=(−0.25±0.45) (i.e., the mean Δσ is 0.57 MPa, with a 95% confidence interval from 0.08 to 4.79 MPa). The Δσ variability introduces a spread in the distribution of seismic energy versus moment, with differences in energy up two orders of magnitudes for earthquakes with the same moment. The variability in the high‐frequency spectral levels is captured by the local magnitude (⁠ML⁠), which scales with radiated energy as ML=(−1.59+0.52logEs) for logEs≤10.26 and ML=(−1.38+0.50logEs) otherwise. As the peak ground velocity increases with increasing Δσ⁠, local and energy magnitudes perform better than moment magnitude as predictors for the shaking potential. The availability of different magnitude scales and source parameters for a large earthquake population will help characterize the between‐event ground‐motion variability in central Italy. Y1 - 2018 U6 - https://doi.org/10.1785/0120170356 SN - 0037-1106 SN - 1943-3573 VL - 108 IS - 3A SP - 1427 EP - 1442 PB - Seismological Society of America CY - Albany ER - TY - JOUR A1 - Bommer, Julian J. A1 - Abrahamson, Norman A. A1 - Strasser, F. O. A1 - Pecker, Alain A1 - Bard, Pierre-Yves A1 - Bungum, Hilmar A1 - Cotton, Fabrice A1 - Fäh, Donat A1 - Sabetta, F. A1 - Scherbaum, Frank A1 - Studer, Jost T1 - The challenge of defining upper bounds on earthquake ground motions Y1 - 2004 SN - 0895-0695 ER - TY - JOUR A1 - Bommer, Julian J. A1 - Douglas, John A1 - Scherbaum, Frank A1 - Cotton, Fabrice A1 - Bungum, Hilmar A1 - Faeh, Donat T1 - On the selection of ground-motion prediction equations for seismic hazard analysis Y1 - 2010 UR - http://srl.geoscienceworld.org/ U6 - https://doi.org/10.1785/gssrl.81.5.783 SN - 0895-0695 ER -