Felt Intensity versus Instrumental Ground Motion: A Difference between California and Eastern North America?

Dangkua, Donny T.; Cramer, Chris H.

doi:10.1785/0120100133

Cited by 21 publications

(37 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We assembled a global database from active crustal regions, including the observations of and Worden et al (2012) from California (Wa99 and Wo12 datasets, respectively), an updated version of Tselentis and Danciu (2008) from Greece (TD08 dataset), Faenza and Michelini (2010) from Italy (FM10 dataset), and a selection of the Dangkua and Cramer (2011) data from the New Madrid region in CEUS (DC11 dataset). The original dataset from Dangkua and Cramer (2011) contains data from CEUS, Canada, and Bhuj; however, only the pairs from CEUS contained all the information we required (e.g., both distances between source and station and between station and measured intensity), so we only used that portion of their data.…”

Section: Datamentioning

confidence: 99%

“…The original dataset from Dangkua and Cramer (2011) contains data from CEUS, Canada, and Bhuj; however, only the pairs from CEUS contained all the information we required (e.g., both distances between source and station and between station and measured intensity), so we only used that portion of their data. We also used a subset of intensity-PGM pairs extracted from the ShakeMap Atlas dataset from , used by Cua et al (2010), including 1516 intensity-PGM pairs, as a test to see how the derived global GMICE performs on tectonically active regions from a completely independent database.…”

Section: Datamentioning

confidence: 99%

“…We also used a subset of intensity-PGM pairs extracted from the ShakeMap Atlas dataset from , used by Cua et al (2010), including 1516 intensity-PGM pairs, as a test to see how the derived global GMICE performs on tectonically active regions from a completely independent database. Hereafter, for brevity, we refer to the subset of intensity-ground-motion pairs extracted from the ShakeMap Atlas as the Atlas dataset, and emphasize that the Atlas data were used in verification, and not in derivation, of the relations We combined ground-motion-intensity pairs extracted from different studies: and Worden et al (2012) from California (Wa99 and W12, respectively), Faenza and Michelini (2010) from Italy (FM10; IMD, Italian Macroseismic Database), Tselentis and Danciu (2008) from Greece (TD08), and Dangkua and Cramer (2011) from central-eastern United States (DC11). Dataset obtained by gathering all the others.…”

Section: Datamentioning

confidence: 99%

“…Dangkua and Cramer (2011) and Tselentis and Danciu (2008) do not give information about the intensity-toground-motion distances; in this case, we did not apply any restriction to these data.…”

Section: Datamentioning

confidence: 99%

“…With the development of seismic networks and the growing abundance of strong-motion records, the tendency is reversed, now associating intensity to a given ground-motion value with ground motion to intensity conversion equations (GMICEs; Atkinson and Sonley, 2000;Kaka and Atkinson, 2004;Atkinson and Kaka, 2007;Tselentis and Danciu, 2008;Dangkua and Cramer, 2011). The limit of these studies for both GMICEs and IGMCEs is the nonreversibility of the aforementioned relationships.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Ground Motion to Intensity Conversion Equations (GMICEs): A Global Relationship and Evaluation of Regional Dependency

Caprio¹,

Tarigan²,

Worden³

et al. 2015

Bulletin of the Seismological Society of America

103

View full text Add to dashboard Cite

We analyzed the regional dependence of ground motion to intensity conversion equations and derived a new global relationship to improve ground motion and intensity estimates for earthquake hazard applications, including those related to the ShakeMap system. For this purpose, we merged several databases collected by other authors in different geographical regions to highlight any systematic regional effects in the relationship between macroseismic intensities and both peak ground velocity and peak ground acceleration. Our database contains macroseismic intensities derived from expert assignments or from the "Did You Feel It?" database, paired with peak ground motions (PGM) from seismic stations. We constrain our intensity-ground-motion pairs to those with a maximum 2 km separation. For each region, we derived invertible relationships between intensities and ground motion using an orthogonal regression. We also derived a global relationship to quantify the regional differences. We investigated the dependence of intensity on predictor variables such as PGM, magnitude, and hypocentral distance. Our analyses indicate that PGM is the most robust predictor variable of intensity. Within one standard deviation, our regional and global results are in agreement with the relations of Worden et al. (2012) for California, Faenza and Michelini (2010) for Italy, Tselentis and Danciu (2008) for Greece, and Atkinson and Kaka (2007) for central-eastern United States. The earthquakes in the study ranged in magnitude from 2.5 to 7.3, and the distances ranged from less than a kilometer to about 200 km from the epicenter.

show abstract

Section: Datamentioning

confidence: 99%

Section: Datamentioning

confidence: 99%

Section: Datamentioning

confidence: 99%

Section: Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Ground Motion to Intensity Conversion Equations (GMICEs): A Global Relationship and Evaluation of Regional Dependency

Caprio¹,

Tarigan²,

Worden³

et al. 2015

Bulletin of the Seismological Society of America

103

View full text Add to dashboard Cite

show abstract

Ground-motion models for earthquakes occurring in the United Kingdom

Douglas,

Aldama-Bustos,

Tallett-Williams

et al. 2024

Bull Earthquake Eng

View full text Add to dashboard Cite

This article presents models to predict median horizontal elastic response spectral accelerations for 5% damping from earthquakes with moment magnitudes ranging from 3.5 to 7.25 occurring in the United Kingdom. This model was derived using the hybrid stochastic-empirical method based on an existing ground-motion model for California and a stochastic model for the UK that was developed specifically for this purpose. The model is presented in two consistent formats, both for two distance metrics, with different target end-users. Firstly, we provide a complete logic tree with 162 branches, and associated weights, capturing epistemic uncertainties in the depth to the top of rupture, geometric spreading, anelastic path attenuation, site attenuation and stress drop, which is more likely to be used for research. The weights for these branches were derived using Bayesian updating of a priori weights from expert judgment. Secondly, we provide a backbone model with three and five branches corresponding to different percentiles, with corresponding weights, capturing the overall epistemic uncertainty, which is tailored for engineering applications. The derived models are compared with ground-motion observations, both instrumental and macroseismic, from the UK and surrounding region (northern France, Belgium, the Netherlands, western Germany and western Scandinavia). These comparisons show that the model is well-centred (low overall bias and no obvious trends with magnitude or distance) and that the branches capture the body and range of the technically defensible interpretations. In addition, comparisons with ground-motion models that have been previously used within seismic hazard assessments for the UK show that ground-motion predictions from the proposed model match those from previous models quite closely for most magnitudes and distances. The models are available as computer subroutines for ease of use.

show abstract