Surface Rupture Effects on Earthquake Moment-Area Scaling Relations

Author(s):  
Yingdi Luo ◽  
Jean-Paul Ampuero ◽  
Ken Miyakoshi ◽  
Kojiro Irikura
2017 ◽  
Vol 174 (9) ◽  
pp. 3331-3342 ◽  
Author(s):  
Yingdi Luo ◽  
Jean-Paul Ampuero ◽  
Ken Miyakoshi ◽  
Kojiro Irikura

2017 ◽  
Vol 175 (3) ◽  
pp. 1219-1219
Author(s):  
Yingdi Luo ◽  
Jean-Paul Ampuero ◽  
Ken Miyakoshi ◽  
Kojiro Irikura

2020 ◽  
Author(s):  
Arthur J. Merschat ◽  
◽  
Mark W. Carter ◽  
Corey M. Scheip ◽  
Richard M. Wooten ◽  
...  

2020 ◽  
Author(s):  
Sinan O. Akciz ◽  
◽  
Salena Padilla ◽  
James F. Dolan ◽  
Alex E. Hatem

2021 ◽  
Vol 13 (4) ◽  
pp. 685
Author(s):  
Marco Polcari ◽  
Mimmo Palano ◽  
Marco Moro

We evaluated the performances of different SAR-based techniques by analyzing the surface coseismic displacement related to the 2019 Ridgecrest seismic sequence (an Mw 6.4 foreshock on July 4th and an Mw 7.1 mainshock on July 6th) in the tectonic framework of the eastern California shear zone (Southern California, USA). To this end, we compared and validated the retrieved SAR-based coseismic displacement with the one estimated by a dense GNSS network, extensively covering the study area. All the SAR-based techniques constrained the surface fault rupture well; however, in comparison with the GNSS-based coseismic displacement, some significant differences were observed. InSAR data showed better performance than MAI and POT data by factors of about two and three, respectively, therefore confirming that InSAR is the most consolidated technique to map surface coseismic displacements. However, MAI and POT data made it possible to better constrain the azimuth displacement and to retrieve the surface rupture trace. Therefore, for cases of strike-slip earthquakes, all the techniques should be exploited to achieve a full synoptic view of the coseismic displacement field.


2020 ◽  
Vol 15 (S359) ◽  
pp. 62-66
Author(s):  
Carlo Cannarozzo ◽  
Carlo Nipoti ◽  
Alessandro Sonnenfeld ◽  
Alexie Leauthaud ◽  
Song Huang ◽  
...  

AbstractThe evolution of the structural and kinematic properties of early-type galaxies (ETGs), their scaling relations, as well as their stellar metallicity and age contain precious information on the assembly history of these systems. We present results on the evolution of the stellar mass-velocity dispersion relation of ETGs, focusing in particular on the effects of some selection criteria used to define ETGs. We also try to shed light on the role that in-situ and ex-situ stellar populations have in massive ETGs, providing a possible explanation of the observed metallicity distributions.


2020 ◽  
Vol 500 (3) ◽  
pp. 3123-3141
Author(s):  
Swagat R Das ◽  
Jessy Jose ◽  
Manash R Samal ◽  
Shaobo Zhang ◽  
Neelam Panwar

ABSTRACT The processes that regulate star formation within molecular clouds are still not well understood. Various star formation scaling relations have been proposed as an explanation, one of which is to formulate a relation between the star formation rate surface density $\rm \Sigma _{SFR}$ and the underlying gas surface density $\rm \Sigma _{gas}$. In this work, we test various star formation scaling relations, such as the Kennicutt–Schmidt relation, the volumetric star formation relation, the orbital time model, the crossing time model and the multi free-fall time-scale model, towards the North American Nebula and Pelican Nebula and in the cold clumps associated with them. Measuring stellar mass from young stellar objects and gaseous mass from CO measurements, we estimate the mean $\rm \Sigma _{SFR}$, the star formation rate per free-fall time and the star formation efficiency for clumps to be 1.5 $\rm M_{\odot}\, yr^{-1}\, kpc^{-2}$, 0.009 and 2.0 per cent, respectively, while for the whole region covered by both nebulae (which we call the ‘NAN’ complex) the values are 0.6 $\rm M_{\odot}\, yr^{-1}\, kpc^{-2}$, 0.0003 and 1.6 per cent, respectively. For the clumps, we notice that the observed properties are in line with the correlation obtained between $\rm \Sigma _{SFR}$ and $\rm \Sigma _{gas}$, and between $\rm \Sigma _{SFR}$ and $\rm \Sigma _{gas}$ per free-fall time and orbital time for Galactic clouds. At the same time, we do not observe any correlation with $\rm \Sigma _{gas}$ per crossing time and multi free-fall time. Even though we see correlations in the former cases, however, all models agree with each other within a factor of 0.5 dex. It is not possible to discriminate between these models because of the current uncertainties in the input observables. We also test the variation of $\rm \Sigma _{SFR}$ with the dense gas but, because of low statistics, a weak correlation is seen in our analysis.


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