TY - JOUR
T1 - The Earthquake-Source Inversion Validation (SIV) Project
AU - Mai, Paul Martin
AU - Schorlemmer, Danijel
AU - Page, Morgan
AU - Ampuero, Jean-Paul
AU - Asano, Kimiyuki
AU - Causse, Mathieu
AU - Custodio, Susana
AU - Fan, Wenyuan
AU - Festa, Gaetano
AU - Galis, Martin
AU - Gallovic, Frantisek
AU - Imperatori, Walter
AU - Käser, Martin
AU - Malytskyy, Dmytro
AU - Okuwaki, Ryo
AU - Pollitz, Fred
AU - Passone, Luca
AU - Razafindrakoto, Hoby
AU - Sekiguchi, Haruko
AU - Song, Seok Goo
AU - Somala, Surendra N.
AU - Thingbaijam, Kiran Kumar
AU - Twardzik, Cedric
AU - van Driel, Martin
AU - Vyas, Jagdish Chandra
AU - Wang, Rongjiang
AU - Yagi, Yuji
AU - Zielke, Olaf
N1 - KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: We thank Juerg Hauser for developing the initial Source Inversion Validation (SIV) benchmark platform. Constructive criticism by and inspiring discussion with Ralph Archuleta, Greg Beroza, Bill Ellsworth, Chen Ji, Ruth Harris, Thorne Lay, Lingsen Meng, Peter Shearer, and others helped to steer the SIV initiative. Constructive criticism by three anonymous reviewers helped to improve the manuscript. We are grateful to the SRL editorial staff for their support and guidance. This research was supported by the Southern California Earthquake Center (Contribution Number 6159). Southern California Earthquake Center (SCEC) is funded by National Science Foundation (NSF) Cooperative Agreement EAR-1033462 and U.S. Geological Survey (USGS) Cooperative Agreement G12AC20038. F. G. was supported by the Czech Science Foundation project 14-04372S. This study is also funded by King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia. Earthquake-rupture simulations were carried out using the KAUST Supercomputing Laboratory (KSL), and we acknowledge support by KSL staff.
PY - 2016/4/6
Y1 - 2016/4/6
N2 - Finite-fault earthquake source inversions infer the (time-dependent) displacement on the rupture surface from geophysical data. The resulting earthquake source models document the complexity of the rupture process. However, multiple source models for the same earthquake, obtained by different research teams, often exhibit remarkable dissimilarities. To address the uncertainties in earthquake-source inversion methods and to understand strengths and weaknesses of the various approaches used, the Source Inversion Validation (SIV) project conducts a set of forward-modeling exercises and inversion benchmarks. In this article, we describe the SIV strategy, the initial benchmarks, and current SIV results. Furthermore, we apply statistical tools for quantitative waveform comparison and for investigating source-model (dis)similarities that enable us to rank the solutions, and to identify particularly promising source inversion approaches. All SIV exercises (with related data and descriptions) and statistical comparison tools are available via an online collaboration platform, and we encourage source modelers to use the SIV benchmarks for developing and testing new methods. We envision that the SIV efforts will lead to new developments for tackling the earthquake-source imaging problem.
AB - Finite-fault earthquake source inversions infer the (time-dependent) displacement on the rupture surface from geophysical data. The resulting earthquake source models document the complexity of the rupture process. However, multiple source models for the same earthquake, obtained by different research teams, often exhibit remarkable dissimilarities. To address the uncertainties in earthquake-source inversion methods and to understand strengths and weaknesses of the various approaches used, the Source Inversion Validation (SIV) project conducts a set of forward-modeling exercises and inversion benchmarks. In this article, we describe the SIV strategy, the initial benchmarks, and current SIV results. Furthermore, we apply statistical tools for quantitative waveform comparison and for investigating source-model (dis)similarities that enable us to rank the solutions, and to identify particularly promising source inversion approaches. All SIV exercises (with related data and descriptions) and statistical comparison tools are available via an online collaboration platform, and we encourage source modelers to use the SIV benchmarks for developing and testing new methods. We envision that the SIV efforts will lead to new developments for tackling the earthquake-source imaging problem.
UR - http://hdl.handle.net/10754/621585
UR - https://pubs.geoscienceworld.org/srl/article/87/3/690-708/315693
UR - http://www.scopus.com/inward/record.url?scp=84975862686&partnerID=8YFLogxK
U2 - 10.1785/0220150231
DO - 10.1785/0220150231
M3 - Article
SN - 0895-0695
VL - 87
SP - 690
EP - 708
JO - Seismological Research Letters
JF - Seismological Research Letters
IS - 3
ER -