A Lithospheric Attenuation Model of North America

The κ parameter (Anderson and Hough, 1984), and namely its sitespecific component (κ 0 ), is important for predicting and simulating high-frequency ground motion. We develop a framework for estimating κ 0 and addressing uncertainties under the challenging conditions often imposed in practice: (1) low seismicity (limited, poor-quality, distant records); (2) limited-bandwidth data from the Transportable Array (TA; maximum usable frequency 16 Hz); and (3) low magnitudes (M L 1.2-3.4) and large uncertainty in stress drop (corner frequency). We cannot resolve stress drop within the bandwidth, so we propose an approach that only requires upper and lower bounds on its regional values to estimate κ 0 . To address uncertainties, we combine three measurement approaches (acceleration spectrum slope [AS]; displacement spectrum slope [DS]; and broadband spectral fit). We also examine the effect of crustal amplification, and find that neglecting it can affect κ 0 by up to 35%. DS estimates greatly exceed AS estimates. We propose a reason behind this bias, related to the residual effect of the corner frequency on κ AS and κ DS . For our region, we estimate a frequency-independent mean S-wave Q of 900 300 at 9-16 Hz, and an ensemble mean κ 0 over all sites of 0:033 0:014 s. This value is similar to the native κ 0 of the Next Generation Attenuation-West 2 ground-motion prediction equations, indicating that these do not need to be adjusted for κ 0 for use in southern Arizona. We find that stress-drop values in this region may be higher compared to estimates of previous studies, possibly due to trade-offs between stress drop and κ 0 . For this dataset, the within-approach uncertainty is much larger than the between-approach uncertainty, and it cannot be reduced if the data quality is not improved. The challenges discussed here will be relevant in studies of κ for other regions with bandlimited data; for example, any region where data come primarily from the TA.

Section: Bb Approachsupporting

confidence: 61%

Section: Combining the As And Ds Approachmentioning

confidence: 90%

Squeezing Kappa (κ) Out of the Transportable Array: A Strategy for Using Bandlimited Data in Regions of Sparse Seismicity

Ktenidou

Silva

Darragh

et al. 2017

“…The synthetics from the three methods are compared with observations using several metrics including: (1) the character of time-domain waveforms; (2) overall Fourier and response spectral bias (from 0.1 to 10 Hz); (3) residuals for GMRotI50 PGA, PGV, and PSA at various periods; and (4) the mean USGS2014-GridSrc GMPE for the eastern United States. The comparison shows that the three methods can provide acceptable estimations for periods less than 2 s. The systematic underestimation of data to the northeast of the epicenter may be the result of local site effects or propagation path effects as suggested by Catchings et al (2012), Pasyanos (2013), andMcNamara et al (2014). The synthetics for the three methods show a similar fall-off with distance to the estimates by the USGS2014-GridSrc GMPE and comparable PGA and PSA amplitudes only for the physicsbased and stochastic site-based models.…”

Section: Discussionmentioning

confidence: 73%

“…This azimuthal dependence of amplitudes has been attributed to an increase in ground motion to the northeast of the epicenter caused by fault-guided waves and Moho reflections amplified by a shallowing Moho to the northeast (Catchings et al, 2012). In addition, azimuthally dependent attenuation (Pasyanos, 2013;McNamara et al, 2014) and rupture directivity to the northeast (Hartzell et al, 2013) may also be factors. This discrepancy is not as obvious in the stochastic site-based synthetics, except for the longest period of 5.0 s, because we have chosen the synthetic that most closely matches the data out of 50 realizations at each station and the breadth in amplitudes between the realizations is sufficient to absorb the azimuthal differences.…”

Section: Orientation-independent Intensity Measuresmentioning

confidence: 99%

Ground‐Motion Simulation for the 23 August 2011, Mineral, Virginia, Earthquake Using Physics‐Based and Stochastic Broadband Methods

Sun

Hartzell

Rezaeian

2015

Three broadband simulation methods are used to generate synthetic ground motions for the 2011 Mineral, Virginia, earthquake and compare with observed motions. The methods include a physics-based model by Hartzell et al. (1999Hartzell et al. ( , 2005, a stochastic source-based model by Boore (2009), and a stochastic site-based model by Der Kiureghian (2010, 2012). The ground-motion dataset consists of 40 stations within 600 km of the epicenter. Several metrics are used to validate the simulations: (1) overall bias of response spectra and Fourier spectra (from 0.1 to 10 Hz);(2) spatial distribution of residuals for GMRotI50 peak ground acceleration (PGA), peak ground velocity, and pseudospectral acceleration (PSA) at various periods; (3) comparison with ground-motion prediction equations (GMPEs) for the eastern United States. Our results show that (1) the physics-based model provides satisfactory overall bias from 0.1 to 10 Hz and produces more realistic synthetic waveforms; (2) the stochastic site-based model also yields more realistic synthetic waveforms and performs superiorly for frequencies greater than about 1 Hz; (3) the stochastic source-based model has larger bias at lower frequencies (< 0:5 Hz) and cannot reproduce the varying frequency content in the time domain. The spatial distribution of GMRotI50 residuals shows that there is no obvious pattern with distance in the simulation bias, but there is some azimuthal variability. The comparison between synthetics and GMPEs shows similar fall-off with distance for all three models, comparable PGA and PSA amplitudes for the physicsbased and stochastic site-based models, and systematic lower amplitudes for the stochastic source-based model at lower frequencies (< 0:5 Hz).

“…The value for Q 0 varies regionally and is about 650-1000 for CENA (Mitchell and Hwang, 1987;Erickson et al, 2004;Pasyanos, 2013). Based on my previous tests (Graizer, 2014a), I concluded that it is reasonable to use a constant Q Q 0 typical for a given region/ path (usually that for Lg or coda waves).…”

Section: Anelastic Attenuationmentioning

confidence: 99%

Ground‐Motion Prediction Equations for Central and Eastern North America

Graizer

2016

A new ground-motion prediction equation (GMPE) model for central and eastern North America (CENA) is presented. The Graizer 2016 (G-16) model is based on the Next Generation Attenuation-East (NGA-East) database for this horizontal peak ground acceleration and 5% damped pseudospectral acceleration RotD50 component (Goulet et al., 2014). The CENA database is not sufficient for creating purely empirical GMPE with recordings covering mostly a range of moment magnitudes M < 6:0 and a limited number of near-fault recordings. The functional forms of the G-16 model are derived from filters representing a particular physical phenomenon affecting the seismic-wave radiation from the source, following the approach developed by Graizer and Kalkan (2007 for active tectonic environment. Main changes in the functional forms for CENA relative to the western United States model (Graizer and Kalkan, 2015) are a shift of maximum frequency of the acceleration response spectrum (RS) toward higher frequencies and an increase in RS amplitudes at high frequencies. The developed site correction is based on multiple runs of representative V S30 profiles through SHAKE-type equivalent-linear codes. Site amplifications are calculated relative to the hard-rock definition used in nuclear industry (V S 2800 m=s). The number of model predictors is limited to a few measurable parameters such as moment magnitude M, closest distance to fault rupture plane R rup , V S30 , and anelastic attenuation factor Q 0 . Incorporating Q 0 as an input parameter allows adjustments based on the regional crustal properties. The model is applicable for the stable continental regions and covers the following range: 4:0 ≤ M ≤ 8:5, 0 ≤ R rup ≤ 1000 km, 450 ≤ V S30 ≤ 2800 m=s, and frequencies 0:1 ≤ f ≤ 100 Hz.