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2013 Source Inversion Validation (SIV) Workshop Report
P. Martin Mai1, D. Schorlemmer2, Morgan Page3
1 KAUST, Division of Physical Sciences & Engineering 4700 King Abdullah University of Science and Technology
Thuwal 23955-‐6900, Kingdom of Saudi Arabia
2 GeoForschungszentrum Potsdam (GFZ) Telegrafenberg
14473 Potsdam, Germany
3 U.S. Geological Survey 525 S. Wilson Ave.
Pasadena CA, 91106, U.S.A Summary The Source Inversion Validation (SIV) group conducted its 8th workshop (since 2008) in conjunction with the Annual SCEC meeting in Palm Springs (Sept 8-‐11, 2013). There were approximately 50 participants in attendance during the 4-‐hr workshop, to discuss methods and approaches to source inversion, to share the latest results related to the SIV exercises, and to discuss the continuation of the SIV project. The detailed program of the workshop can be found at http://www.scec.org/workshops/2013/siv/index.html, with links to individual presentations. The “Notes” below summarize the presentation and subsequent discussion of the workshop. The main outcome of the 2013 SIV workshop was a plan for developing a benchmark exercise using teleseismic data for the source-‐inversion problem as well as for testing back-‐projection approaches, and to include additional tests at local & regional scale for ruptures embedded in 3D geological structure. It was also decided to hold a dedicated workshop in Southern California (Caltech/USC), presumably in March 2014, focusing on the teleseismic benchmarking as well as quantitative measures of “goodness-‐of-‐fit” of rupture-‐model solutions. Notes on Workshop Presentations The meeting opened with an introduction by Martin Mai, in which he presented results from the current suite of SIV benchmarks. First, new participants have completed the forward modeling tests. Among the submissions to date, one of the contributions has serious problems, and the remaining submissions have smaller differences. Work still needs to be done to fully understand the nature of these differences, since the forward problem is well-‐defined and has a correct solution, but most likely, solutions with small differences are due to slightly different parameter settings (or handling of code-‐
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internal parameters) in the forward-‐modeling engines. Second, the current benchmark inv2 was presented, for which also GPS synthetics are available. Four groups have submitted results so far. This benchmark uses a M~7 normal-‐faulting event, embedded in layered structure (inv2a, see Figure 1) and in a 3D heterogeneous velocity structure (inv2b). None of the groups used the provided GPS data. One of the four groups had a slip distribution that looked visually quite different than the target; all other groups, however, fit the data well (according to their own calculated synthetics) and seem to reproduce the target model. So far, no solutions have been submitted for inversion benchmark 2b, which contains Green’s function uncertainty. Yugi Yagi presented results from his inversion method that incorporates the effect of Green’s function errors that generate correlated errors in the data vector. By accounting for these errors, he is able to obtain plausible solutions without imposing a nonnegativity constraint on the slip. This methodology makes the solution more stable and less dependent on the sampling rate. Furthermore, it fits high-‐amplitude signals better than an inversion that does not account for these errors. Even though the resulting L2-‐norm data fit is worse, the more robust parts of the data signal are well-‐fit. This reinforces the notion that the L2 norm is not a good misfit criteria; solutions that fit the data well by this metric may not reproduce the parts of the solution that are stable with respect to Green’s function error. Yagi also presented results from a hybrid backprojection method that is similar to a heavily damped least-‐squares method. Next, Zacharie Duputel presented work that uses ensembles of models to capture uncertainty in the solution. His method also includes uncertainty in the Green’s function, and though the application of Sarah Minson’s Bayesian sampler (CATMIP) he is able to produce multiple models. Synthetic tests show that when uncertainty in the Earth model is included, the true parameter values are within the uncertainties given by the inversion method; not only are the estimated covariances realistic, but also the mean parameter values are approximately correct. Subsequently, Hoby Razafindrakoto discussed how choices for the source-‐time function and variations in the assumed 1D-‐velocity structure drive differences in inversion results. Her work uses a Bayesian approach, such that the final results can be examined in terms of variations in the a posteriori probability density functions (PDFs) of the kinematic source parameters. While there are methods that can account for uncorrelated errors in velocity structure, errors in layer depths are more difficult to incorporate – these types of errors lead to time shifts in the data, although aligning waveforms before inverting can mitigate this. Hoby reported that different slip-‐time function parameterizations led to different inverted rupture velocities because the inversion is sensitive to peak slip rather than initial slip. Compared to a regularized Yoffe slip-‐time function, Hoby finds that the triangle slip-‐time function has earlier rupture times and introduces an artificial correlation between rise time and rupture time. William Barnhart next discussed work with Gavin Hayes, Guangfu Shuo, and Chen Ji developing fast finite-‐fault inversions at the NEIC. Their fast finite-‐fault model is produced within 60-‐95 minutes of an event, and then revised with geodetic observations, a refined fault model, strong ground motion and intensity data, and manual wave picks in the following hours to months. Their fast finite-‐fault model is generated automatically with W-‐phase data and a fault location matching the best-‐fit CMT nodal plane. The total amount of slip is constrained by moment. This initial model requires 30-‐40 minuets of computation time (single processor). They are moving to improve the speed at which manual picks and fault geometry can be updated. They are also investigating using a non-‐uniform fault discretization that is based on the local model resolution and bootstrapping data to obtain an ensemble of models. In the future they plan to parallelize their code to speed up the computation time as well. Also, the NEIC is
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improving the latency of the geodetic data, so in the future the first fast finite-‐fault model could be generated from a joint geodetic and seismic inversion. Finally, Shenji Wei next presented results from a CalTech/USGS/JPL collaboration on high-‐resolution inversions for M≥4.8 earthquakes in the 2012 Brawley swarm. They use a M3.9 earthquake for path calibration to reduce the effect of errors in the assumed velocity structure. Using a synthetic checkerboard test they determine that a joint seismic and geodetic inversion is best – the seismic data improves the resolution at depth significantly, while the static data improves the resolution at shallow depths. They found that the two largest events, a M5.3 and M5.4, had complementary slip distributions. Notes on Workshop Discussions Following the talks, several hours were budgeted for detailed discussion. There was much interest in bringing in researchers working on backprojection into the SIV project. Backprojection can help delineate the rupture fault plane, and hence provide important a priori information for conventional finite-‐fault inversions. A prime example for this „modeling chain“ is the 2012 M8.6 Indian Ocean earthquake. There was discussion which physical quantities backprojection is imaging – its strength is not slip amplitude, but related to the location of high-‐frequency, coherent patches of slip. Peter Shearer remarked that backprojection is not imaging the rupture front, but rather general regions with high-‐frequency bursts, potentially on the edges of high-‐slip patches; Jim Rice countered that theoretical models suggest that the rupture front should have fast slip-‐rate changes and releated high frequencies should be seen by backprojection. Backprojection seems insensitive to stopping phases (perhaps because it is buried by the coda). However, finite-‐fault inversions often show ruptures with multiple sub-‐events rather than a single smooth rupture, hence multiple episodes of rupture acceleration and de-‐accleration that should radiate high-‐frequency waves. To further complicate matters, there are steady-‐state models with fast slip-‐rate changes that do not radiate seismically. There is agreement among participants that more work is needed i sunderstand what exactly backprojection is imaging. Dave Jackson proposed to focus the SIV project and its goals on the needs of the seismic hazard community, such as the UCERF project. These include the depth of rupture (particularly for the largest earthquakes), the prevalence of multi-‐fault ruptures, and the functional form for slip along strike (particularly for multi-‐fault ruptures). Bill Ellsworth said the goal should be to predict ground motion, since that is what is important for hazard. Higher frequencies are also important for building response, yet the current benchmarks do not have much high-‐frequency content. Future benchmarks should therefore ensure that the ruptures also radiate high-‐frequency waves suffciently (realistically). In addition, the forward problems need to be revisited. Even though the forward problem benchmarks are several years old, work is required to completely understand why different codes/modeling groups are getting different results. Previous submission should be revisited and revised. It was suggested that we could provide Green’s functions or input parameter files to modeling groups to eliminate this difference. It was also mentioned that a teleseismic forward problem may be needed. John Vidale suggested that the SIV project move to more complex problems. Chen Ji agreed with this comment and thought we should include a realistic benchmark, perhaps based on the Southern California ShakeOut scenario (to “make it meaningful” for modelers). It was thought that this would help to generate more interest in the community since this is a well-‐studied, highly visible earthquake model. Furthermore, a complex model is needed to generate teleseismic data usable by the
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backprojection modelers (the model needs to have coherent high frequencies, which is different than the stochastic high frequencies that the CyberShake platform adds). Leveraging the work being done by other groups in SCEC (e.g., the 3D velocity model for Southern California) could aid the SIV effort. In this context, Carl Tape suggested that the next benchmark should extend a high-‐resolution near-‐field model to a teleseismic, low-‐resolution model, and, as part of this benchmark, create a 3D Green’s function catalog for modelers and the broader SCEC community to use. Conclusions and Decisions The importance of the SIV effort was underscored by a comment from Peter Shearer – „When reading a paper on finite-‐fault modeling one doesn’t know what to trust“. The fit to the data, while routinely presented, is not sufficient to understand which parts of the solution are robust. The next benchmark will focus on teleseismic source inversion, with an attempt to generate far-‐field synthetics that are appropriate for back-‐projection imaging of the rupture process. Further emphasis will be placed on accounting for uncertainty in Earth structure. For this purpuse, we may design a benchmark exercise on regional/local scale for ruptures embedded in 3D geological structure (e.g. Soufthern California / L.A. Basin) A dedicated modeling-‐centered SIV workshop is planned for Spring 2014, to be held at USC / CalTech. Figure 1: Submitted inversion solutions from four teams, shown in the graphical represenation provided by the SIV online collaboration platform (http://equake-‐rc.info/SIV/sivtools/list_benchmarks/), and the actual „target model“ for which synthetic near-‐field data at 40 sites were computed and distributed
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