Debi Kilb

A strong correlation between induced peak dynamic Coulomb stress change from the 1992 M7.3 Landers, California, earthquake and the hypocenter of the 1999 M7.1 Hector Mine, California, earthquake

The 1992 M7.3 Landers earthquake may have played a role in triggering the 1999 M7.1 1 Hector Mine earthquake as suggested by their close spatial (∼20 km) proximity. Current investigations of triggering by static stress changes produce differing conclusions when small variations in parameter values are employed. Here I test the hypothesis that large-amplitude dynamic stress changes, induced by the Landers rupture, acted to promote the Hector Mine earthquake. I use a flat layer reflectivity method to model the Landers earthquake displacement seismograms. By requiring agreement between the model seismograms and data, I can constrain the Landers main shock parameters and velocity model. A similar reflectivity method is used to compute the evolution of stress changes. I find a strong positive correlation between the Hector Mine hypocenter and regions of large (>4 MPa) dynamic Coulomb stress changes (peak Δσ f (t)) induced by the Landers main shock. A positive correlation is also found with large dynamic normal and shear stress changes. Uncertainties in peak Δσ f (t) (1.3 MPa) are only 28% of the median value (4.6 MPa) determined from an extensive set (160) of model parameters. Therefore the correlation with dynamic stresses is robust to a range of Hector Mine main shock parameters, as well as to variations in the friction and Skemptons coefficients used in the calculations. These results imply dynamic stress changes may be an important part of earthquake trigging, such that large-amplitude stress changes alter the properties of an existing fault in a way that promotes fault failure.

The initial subevent of the 1994 Northridge, California, earthquake: Is earthquake size predictable?

We examine the initial subevent (ISE) of the M 6.7, 1994 Northridge, California, earthquake in order to discriminate between two end-member rupture initiation models: the ‘preslip’ and ‘cascade’ models. Final earthquake size may be predictable from an ISEs seismic signature in the preslip model but not in the cascade model. In the cascade model ISEs are simply small earthquakes that can be described as purely dynamic ruptures. In this model a large earthquake is triggered by smaller earthquakes; there is no size scaling between triggering and triggered events and a variety of stress transfer mechanisms are possible. Alternatively, in the preslip model, a large earthquake nucleates as an aseismically slipping patch in which the patch dimension grows and scales with the earthquakes ultimate size; the byproduct of this loading process is the ISE. In this model, the duration of the ISE signal scales with the ultimate size of the earthquake, suggesting that nucleation and earthquake size are determined by a more predictable, measurable, and organized process. To distinguish between these two end-member models we use short period seismograms recorded by the Southern California Seismic Network. We address questions regarding the similarity in hypocenter locations and focal mechanisms of the ISE and the mainshock. We also compare the ISEs waveform characteristics to those of small earthquakes and to the beginnings of earthquakes with a range of magnitudes. We find that the focal mechanisms of the ISE and mainshock are indistinguishable, and both events may have nucleated on and ruptured the same fault plane. These results satisfy the requirements for both models and thus do not discriminate between them. However, further tests show the ISEs waveform characteristics are similar to those of typical small earthquakes in the vicinity and more importantly, do not scale with the mainshock magnitude. These results are more consistent with the cascade model.

A Comparison of Spectral Parameter Kappa from Small and Moderate Earthquakes Using Southern California ANZA Seismic Network Data

Kappa is a one-parameter estimator of the spectral amplitude decay with frequency of a seismogram. Low values (∼5 ms) indicate limited attenuation of high- frequency energy whereas higher values (∼40 ms) indicate high-frequency energy has been removed. Kappa is often assumed to be a site term and used in seismic designs. We address two key questions about kappa: (1) how to identify source, path, and site contributions to kappa; and (2) can kappa estimates from smaller earthquakes, and more readily accessible weak-motion recordings, be reasonably extrapolated to esti- mate kappa of larger earthquakes? The use of small earthquakes (ML 3:5 earthquakes inside the network. We find kappa from small earthquakes predicts the relative values of kappa for larger earthquakes (e.g., measurements at stations PFO and KNW are small compared with those at stations TRO and SND). For the SND and TRO data, however, kappa values from small earth- quakes overpredict those from moderate and large earthquakes. Site effects are the most important contributor to kappa estimates, but the scatter within kappa measure- ments at a given station is likely caused by a significant contribution from near the source, perhaps related to near-source scattering. Because of this source-side varia- bility, care is recommended in using individual small events as Greens functions to study source-time effects of moderate and large events.

Fault parameter constraints using relocated earthquakes: A validation of first-motion focal-mechanism data

We estimate the strike and dip of three California fault segments (Calaveras, Sargent, and a portion of the San Andreas near San Jaun Bautistia) based on principle component analysis of accurately located microearthquakes. We compare these fault orientations with two different first-motion focal mechanism catalogs: the Northern California Earthquake Data Center (ncedc) catalog, calculated using the fpfit algorithm (Reasenberg and Oppenheimer, 1985), and a catalog created using the hash algorithm that tests mechanism stability relative to seismic velocity model variations and earthquake location (Hardebeck and Shearer, 2002). We assume any disagreement (misfit >30° in strike, dip, or rake) indicates inaccurate focal mechanisms in the catalogs. With this assumption, we can quantify the parameters that identify the most optimally constrained focal mechanisms. For the ncedc/fpfit catalogs, we find that the best quantitative discriminator of quality focal mechanisms is the station distribution ratio (stdr) parameter, an indicator of how the stations are distributed about the focal sphere. Requiring stdr > 0.65 increases the acceptable mechanisms from 34%–37% to 63%–68%. This suggests stations should be uniformly distributed surrounding, rather than aligning, known fault traces. For the hash catalogs, the fault plane uncertainty (fpu) parameter is the best discriminator, increasing the percent of acceptable mechanisms from 63%–78% to 81%–83% when fpu ≤ 35°. The overall higher percentage of acceptable mechanisms and the usefulness of the formal uncertainty in identifying quality mechanisms validate the hash approach of testing for mechanism stability. Online material: 3D visualization of relocated earthquakes and accuracy of focal mechanisms.

Spatiotemporal Analyses of Earthquake Productivity and Size Distribution: Observations and Simulations

We use relocated catalogs of microearthquakes to investigate earthquake interaction along sections of the Sargent, Calaveras, and San Andreas faults in Cali- fornia. We examine the stress dependence of seismicity rate change along the three fault segments and find that the seismicity rate following a mainshock decays ap- proximately as 1/time, the duration of the aftershock activity seems to be independent of distance from the mainshock, and the seismicity rate at lag times of up to about 100 sec is nearly constant. In the San Andreas and the Calaveras catalogs, where the return of the seismicity rate to the background level is well resolved, we find that the return to the background in the distance range of 1-2 rupture radii from a previous earthquake is preceded by a period during which the seismicity rate falls about 30% below the background rate. We also examine the effect of a stress step on earthquake size distribution along these faults and find that the exponent of the power-law dis- tribution of earthquake magnitudes within 10 4 sec of a previous earthquake is sig- nificantly lower than that of the long term. While the 1/time decay of seismicity rate, the independence of aftershock duration from distance from the mainshock, and the constant seismicity rate at short lag times are predicted by Dieterichs (1994) model, the decrease of seismicity rate below the background level and the changes in earth- quake size distribution are not. For comparison with our observations, we simulate earthquake activity on an in- herently discrete fault model that is governed by an approximate constitutive friction law similar to the one used by Dieterich (1994). We find that the observed response of earthquake productivity and size distribution to a stress step are produced by these simulations. The effect of the mainshock is not only to raise the local seismicity rate, but also to systematically modify the earthquake size distribution. This is because fault patches that are near failure at the time of the stress step are strengthened, whereas fault patches that at the same time were far from failure are weakened. As a result, similar to what is observed for the Calaveras and the San Andreas segments, late during the aftershock sequence the seismicity rate may decrease below the back- ground rate. We suggest that the time-dependent modification of the earthquake size distribution by a stress step can explain observations of lower b-values immediately following a stress step.

Collaborative data visualization for earth sciences with the OptIPuter

Collaborative visualization of large-scale datasets across geographically distributed sites is becoming increasingly important for Earth Sciences. Not only does it enhance our understanding of the geological systems, but also enables near-real-time scientific data acquisition and exploration across distant locations. While such a collaborative environment is feasible with advanced optical networks and resource sharing in the form of Grid, many technical challenges remain: (1) on-demand discovery, selection and configuration of supporting end and network resources; (2) construction of applications on heterogeneous, distributed environments; and (3) use of novel exotic transport protocols to achieve high performance. To address these issues, we describe the multi-layered OptIPuter middleware technologies, including simple resource abstractions, dynamic network provisioning, and novel data transport services. In this paper, we present an evaluation of the first integrated prototype of the OptIPuter system software recently demonstrated at iGrid 2005, which successfully supports real-time collaborative visualizations of 3D multigigabyte earth science datasets.

Aftershock Detection Thresholds as a Function of Time: Results from the anza Seismic Network following the 31 October 2001 ML 5.1 Anza, California, Earthquake

We examine aftershock detectability thresholds for events in the initial part of the 31 October 2001, M L 5.1 sequence in southern California. This sequence occurred directly below the broadband anza seismic network, which recorded continuous waveform data at 13 azimuthally well-distributed stations within the study region (seven had epicentral distances < 20 km). Of the 608 aftershocks (0 < M L < ∼2.8) in the initial 2 hr of this sequence, the first five aftershocks recorded were only identifiable at stations within 30 km after applying a high-pass filter. Using a cluster (radius ≤ 1.1 km) of 200 representative aftershocks, we track the maximum seismogram amplitude versus earthquake magnitude. This relationship helps us quantify the visibility of aftershocks within the mainshock coda and assess our detection capabilities. We estimate that detectable aftershocks within the mainshock coda include (1) those over magnitude ∼3 that are within 15 km of the network centroid that occur 12 sec or more into the sequence, and (2) those over magnitude ∼2 that are within 30 km of the centroid of the network that occur 60 sec or more into the sequence. We find a lack of large aftershocks in this sequence. The largest aftershock ( M L ∼2.8) is substantially smaller than the mainshock ( M L 5.1). We suggest this relatively large-magnitude differential is dictated by a combination of factors that includes complexity of the San Jacinto fault system and the lack of large earthquakes in the region in the past ∼20 years. Online material: Quicktime movies juxtaposing a 3.2 aftershock in the coda of a 5.1 mainshock.

A Case Study of Two M ∼5 Mainshocks in Anza, California: Is the Footprint of an Aftershock Sequence Larger Than We Think?

It has been traditionally held that aftershocks occur within one to two fault lengths of the mainshock. Here we demonstrate that this perception has been shaped by the sensitivity of seismic networks. The 31 October 2001 Mw 5.0 and 12 June 2005 Mw 5.2 Anza mainshocks in southern California occurred in the middle of the densely instrumented ANZA seismic network and thus were unusually well recorded. For the June 2005 event, aftershocks as small as M 0.0 could be observed stretching for at least 50 km along the San Jacinto fault even though the mainshock fault was only ∼4:5 km long. It was hypothesized that an observed aseismic slipping patch produced a spatially extended aftershock-triggering source, presumably slowing the decay of aftershock density with distance and leading to a broader aftershock zone. We find, however, the decay of aftershock density with distance for both Anza se- quences to be similar to that observed elsewhere in California. This indicates there is no need for an additional triggering mechanism and suggests that given widespread dense instrumentation, aftershock sequences would routinely have footprints much larger than currently expected. Despite the large 2005 aftershock zone, we find that the probability that the 2005 Anza mainshock triggered the M 4.9 Yucaipa mainshock, which occurred 4.2 days later and 72 km away, to be only 14% 1%. This probability is a strong function of the time delay; had the earthquakes been separated by only an hour, the probability of triggering would have been 89%. Online Material: Movies exploring the spatial extent of aftershocks from the 2001 and 2005 Anza sequences.

Exploring remote earthquake triggering potential across EarthScopes' Transportable Array through frequency domain array visualization

To better understand earthquake source processes involved in dynamically triggering remote aftershocks, we use data from the EarthScope Transportable Array (TA) that provide uniform station sampling, similar recording capabilities, large spatial coverage, and, in many cases, repeat sampling at each site. To avoid spurious detections, which are an inevitable part of automated time domain amplitude threshold detection methods, we develop a frequency domain earthquake detection algorithm that identifies coherent signal patterns through array visualization. This method is tractable for large data sets, ensures robust catalogs, and delivers higher resolution observations than what are available in current catalogs. We explore seismicity rate changes local to the TA stations following 18 global main shocks (M ≥ 7) that generate median peak dynamic stress amplitudes of 0.001–0.028 MPa across the array. From these main shocks, we find no evidence of prolific or widespread remote dynamic triggering in the continental U.S. within the main shocks wave train or following main shock stress transients within 2 days. However, limited evidence for rate increases exist in localized source regions. These results suggest that for these data, prolific, remote earthquake triggering is a rare phenomenon throughout a wide range of observable magnitudes. We further conclude that within the lower range of previously reported triggering thresholds, surface wave amplitude does not correlate well with observed cases of dynamic triggering. We propose that other characteristics of the triggering wavefield, in addition to specific conditions at the site, will drive the occurrence of triggering at these amplitudes.

Quantifying the remote triggering capabilities of large earthquakes using data from the ANZA Seismic Network catalog (southern California)

Received 24 August 2006; revised 22 June 2007; accepted 13 August 2007; published 3 November 2007. [1] Various studies have examined remote earthquake triggering in geothermal areas, but few studies have investigated triggering in nongeothermal areas. We search the ANZA (southern California) network catalog for evidence of remote triggering. Using three statistical tests (binomial, Kolmogorov-Smirnov, and Wilcoxon rank sum), we determine the significance of the rates and timing of earthquakes in southern California following large teleseismic events. To validate our statistical tests, we identify 20 local main shocks (ML � 3.1) with obvious aftershock sequences and 22 local main shocks (ML � 3.0) that lack obvious aftershock sequences. Our statistical tests quantify the ability of these local main shocks to trigger aftershocks. Assuming that the same triggering characteristic (i.e., a particular seismic wave amplitude, perhaps in a specific frequency band) is evident for both local and remote main shocks, we apply the same tests to 60 remote main shocks (mb � 7.0) and assess the ability of these events to trigger seismicity in southern California. We find no obvious signature of remote triggering. We find minimal differences between the spectral amplitudes and maximum ground velocities of the local triggering and nontriggering earthquakes. Similar analysis of a select few of our remote earthquakes shows that the related ground motion regularly exceeds that of local earthquakes both at low frequencies and in maximum velocity. This evidence weakly suggests that triggering requires larger amplitudes at high frequencies and that a maximum ground velocity alone is not the primary factor in remote triggering. Our results are complex, suggesting that a triggering threshold, if it exists, may depend on several factors.