Urgent Supercomputing of Earthquakes: Use Case for Civil Protection

Deadly earthquakes are events that are unpredictable, relatively rare and have a huge impact upon the lives of those who suffer their consequences. Furthermore, each earthquake has specific characteristics (location, magnitude, directivity) which, combined to local amplification and de-amplification effects, makes their outcome very singular. Empirical relations are the main methodology used to make early assessment of an earthquake's impact. Nevertheless, the lack of sufficient data registers for large events makes such approaches very imprecise. Physics-based simulators, on the other hand, are powerful tools that provide highly accurate shaking information. However, physical simulations require considerable computational resources, a detailed geological model, and accurate earthquake source information. A better early assessment of the impact of earthquakes implies both technical and scientific challenges. We propose a novel HPC-based urgent seismic simulation workflow, hereafter referred to as Urgent Computing Integrated Services for EarthQuakes (UCIS4EQ), which can deliver, potentially, much more accurate short-time reports of the consequences of moderate to large earthquakes. UCIS4EQ is composed of four subsystems that are deployed as services and connected by means of a workflow manager. This paper describes those components and their functionality. The main objective of UCIS4EQ is to produce ground-shaking maps and other potentially useful information to civil protection agencies. The first demonstrator will be deployed in the framework of the Center of Excellence for Exascale in Solid Earth (ChEESE, https://cheese.coe.eu/, last access: 12 Feb. 2020).

[1]  D. Komatitsch,et al.  Introduction to the spectral element method for three-dimensional seismic wave propagation , 1999 .

[2]  J. Douglas,et al.  A Survey of Techniques for Predicting Earthquake Ground Motions for Engineering Purposes , 2008 .

[4]  R. J. Walters,et al.  A Bayesian Method for Incorporating Self‐Similarity Into Earthquake Slip Inversions , 2018, Journal of Geophysical Research: Solid Earth.

[5]  G. Atkinson,et al.  Ground-Motion Prediction Equations for the Average Horizontal Component of PGA, PGV, and 5%-Damped PSA at Spectral Periods between 0.01 s and 10.0 s , 2008 .

[6]  Jordi Torres,et al.  PyCOMPSs: Parallel computational workflows in Python , 2016, Int. J. High Perform. Comput. Appl..

[7]  Leon Bieber The Mechanics Of Earthquakes And Faulting , 2016 .

[8]  A. Pitarka,et al.  Broadband Ground-Motion Simulation Using a Hybrid Approach , 2010 .

[9]  John H. Woodhouse,et al.  Determination of earthquake source parameters from waveform data for studies of global and regional seismicity , 1981 .

[10]  Nikolaos Triantafyllis,et al.  Scisola: Automatic Moment Tensor Solution for SeisComP3 , 2016 .

[11]  Seiji Tsuboi,et al.  The International Federation of Digital Seismograph Networks (FDSN): An Integrated System of Seismological Observatories , 2008, IEEE Systems Journal.

[12]  Benjamin Edwards,et al.  Ground motion prediction equations , 2014 .

[13]  Karin Rothschild,et al.  Seismic Waves And Sources , 2016 .

[14]  Dhabaleswar K. Panda,et al.  Scalable Earthquake Simulation on Petascale Supercomputers , 2010, 2010 ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis.

[15]  M. Dumbser,et al.  An arbitrary high-order discontinuous Galerkin method for elastic waves on unstructured meshes — II. The three-dimensional isotropic case , 2006 .

[16]  Michael Dumbser,et al.  ExaHyPE: An Engine for Parallel Dynamically Adaptive Simulations of Wave Problems , 2019, Comput. Phys. Commun..

[17]  K. Shiomi,et al.  Centroid Moment Tensor Inversion of Shallow Very Low Frequency Earthquakes Off the Kii Peninsula, Japan, Using a Three‐Dimensional Velocity Structure Model , 2018, Geophysical Research Letters.

[18]  E. Boschi,et al.  European–Mediterranean Regional Centroid Moment Tensor catalog: Solutions for 2005–2008 , 2011 .

[19]  Robert W. Graves,et al.  Kinematic Ground‐Motion Simulations on Rough Faults Including Effects of 3D Stochastic Velocity Perturbations , 2016 .

[20]  Julian J. Bommer,et al.  On the Selection of Ground-Motion Prediction Equations for Seismic Hazard Analysis , 2010 .

[21]  A. Zollo,et al.  Quick Determination of the Earthquake Focal Mechanism from the Azimuthal Variation of the Initial P‐Wave Amplitude , 2019, Seismological Research Letters.

[22]  C. Böhm,et al.  Automated Large‐Scale Full Seismic Waveform Inversion for North America and the North Atlantic , 2018, Journal of Geophysical Research: Solid Earth.

[23]  Göran Ekström,et al.  The global CMT project 2004–2010: Centroid-moment tensors for 13,017 earthquakes , 2012 .