Geology topics

Clifford H. Thurber

Publications and source records attributed to Clifford H. Thurber.

12 recordsLinked to original sources

USGS2022

Complex magmatic-tectonic interactions during the 2020 Makushin Volcano, Alaska, earthquake swarm

On June 15, 2020, at 21:16 UTC, a locally-felt earthquake of magnitude 4.2 struck Unalaska Island, Alaska, ∼15 km west of the town of Unalaska and the large fishing port of Dutch Harbor. The event was followed by a M4.1 earthquake at 00:34 UTC and several M3+ aftershocks, initiating a prolific sequence with hundreds of earthquakes recorded into late December. The earthquakes all locate about 12 km southeast of the summit of Makushin Volcano at 7 to 10 km depth. To date, no eruptive activity or other surface changes have been observed at the volcano in webcam images, GPS or InSAR. Seismic bursts close to volcanoes are often associated with the onset of unrest that can lead to eruption. However, determining whether seismicity reflects magmatic rather than tectonic stresses is often challenging, although critical for hazard assessments and risk management strategies. To investigate the triggering mechanisms of the recent Makushin seismicity, we integrate information from space-time patterns of the earthquake hypocenters with their fault-plane solutions. We relocate the swarm events using double-difference relocation techniques and a 3D velocity model and find that the earthquakes, although they seem to follow two predominant orientations (NW-SE and SW-NE), do not show clear clustering into preferred alignments. Similarly, we do not observe pronounced migration in time and space. Fault-plane solutions (FPS) for all but one M2.5+ earthquakes have P-axis orientations consistent with subhorizontal NW-SE oriented regional maximum compression, whereas many of the lower-magnitude earthquakes have P-axes perpendicular to regional maximum compression. This provides evidence for the presence of a local stress field likely induced by magma intrusion. Results from Coulomb stress modeling are also consistent with dike inflation modulated by stresses induced by the M4+ earthquakes. The seismic swarm is thus likely linked to a superposition of driving stresses from both magmatic and tectonic processes on pre-existing faults. The case of the 2020 Makushin swarm, with its unusual characteristics, challenges traditional swarm classification schemes and suggests that a reconsideration of the definition of seismic swarms as having the maximum magnitude event in the middle of the swarm is warranted.

Alaska↗

USGS2020

Science plan for improving three-dimensional seismic velocity models in the San Francisco Bay region, 2019–24

This five-year science plan outlines short-term and long-term goals for improving three-dimensional seismic velocity models in the greater San Francisco Bay region as well as how to foster a community effort in reaching those goals. The short-term goals focus on improving the current U.S. Geological Survey San Francisco Bay region geologic and seismic velocity model using existing data. The long-term goals focus on acquiring new data and leveraging better analytic tools to improve the model and characterize the uncertainty. The plan describes opportunities for contributions by members of the community to develop these seismic velocity models, provides current and potential users with general information on where efforts will likely be focused to improve these models and how new versions of the models will be released, and outlines funding needs and obstacles for improving and maintaining such models. Several aspects of this plan, including how to foster a community effort, are independent of the geographic region and apply to other similar efforts.

California↗

USGS2018

Hypocenter relocation along the Sunda arc in Indonesia, using a 3D seismic velocity model

The tectonics of the Sunda arc region is characterized by the junction of the Eurasian and Indo‐Australian tectonic plates, causing complex dynamics to take place. High‐seismicity rates in the Indonesian region occur due to the interaction between these tectonic plates. The availability of a denser network of seismometers after the earthquakes of M w "> M w 9.1 in 2004 and M w "> M w 8.6 in 2005 supports various seismic studies, one of which regards the precise relocation of the hypocenters. In this study, hypocenter relocation was performed using a teleseismic double‐difference (DD) relocation method (teletomoDD) combining arrival times of P and S waves from stations at local, regional, and teleseismic distances. The catalog data were taken from the Agency of Meteorology, Climatology, and Geophysics (BMKG) of Indonesia, and the International Seismological Centre (ISC) for the time period of April 2009 to May 2015. The 3D seismic‐wave velocity model with a grid size 1 ° × 1 ° "> 1°×1° was used in the travel‐time calculations. Relocation results show a reduction in travel‐time residuals compared with the initial locations. The relocation results better illuminate subducted slabs and active faults in the region such as the Mentawai back thrust and the outer rise in the subduction zone south of Java. Focal mechanisms from the Global Centroid Moment Tensor catalog are analyzed in conjunction with the relocation results, and our synthesis of the results provides further insight into seismogenesis in the region.

Sunda arc↗

USGS2016

3-D P- and S-wave velocity structure and low-frequency earthquake locations in the Parkfield, California region

To refine the 3-D seismic velocity model in the greater Parkfield, California region, a new data set including regular earthquakes, shots, quarry blasts and low-frequency earthquakes (LFEs) was assembled. Hundreds of traces of each LFE family at two temporary arrays were stacked with time–frequency domain phase weighted stacking method to improve signal-to-noise ratio. We extend our model resolution to lower crustal depth with LFE data. Our result images not only previously identified features but also low velocity zones (LVZs) in the area around the LFEs and the lower crust beneath the southern Rinconada Fault. The former LVZ is consistent with high fluid pressure that can account for several aspects of LFE behaviour. The latter LVZ is consistent with a high conductivity zone in magnetotelluric studies. A new Vs model was developed with S picks that were obtained with a new autopicker. At shallow depth, the low Vs areas underlie the strongest shaking areas in the 2004 Parkfield earthquake. We relocate LFE families and analyse the location uncertainties with the NonLinLoc and tomoDD codes. The two methods yield similar results.

California↗

USGS2016

Volcano deformation source parameters estimated from InSAR: Sensitivities to uncertainties in seismic tomography

The eruption cycle of a volcano is controlled in part by the upward migration of magma. The characteristics of the magma flux produce a deformation signature at the Earth's surface. Inverse analyses use geodetic data to estimate strategic controlling parameters that describe the position and pressurization of a magma chamber at depth. The specific distribution of material properties controls how observed surface deformation translates to source parameter estimates. Seismic tomography models describe the spatial distributions of material properties that are necessary for accurate models of volcano deformation. This study investigates how uncertainties in seismic tomography models propagate into variations in the estimates of volcano deformation source parameters inverted from geodetic data. We conduct finite element model-based nonlinear inverse analyses of interferometric synthetic aperture radar (InSAR) data for Okmok volcano, Alaska, as an example. We then analyze the estimated parameters and their uncertainties to characterize the magma chamber. Analyses are performed separately for models simulating a pressurized chamber embedded in a homogeneous domain as well as for a domain having a heterogeneous distribution of material properties according to seismic tomography. The estimated depth of the source is sensitive to the distribution of material properties. The estimated depths for the homogeneous and heterogeneous domains are 2666 ± 42 and 3527 ± 56 m below mean sea level, respectively (99% confidence). A Monte Carlo analysis indicates that uncertainties of the seismic tomography cannot account for this discrepancy at the 99% confidence level. Accounting for the spatial distribution of elastic properties according to seismic tomography significantly improves the fit of the deformation model predictions and significantly influences estimates for parameters that describe the location of a pressurized magma chamber.

Journal of Geophysical Research B: Solid Earth↗

USGS2016

Along-strike variations in fault frictional properties along the San Andreas Fault near Cholame, California from joint earthquake and low-frequency earthquake relocations

Recent observations of low‐frequency earthquakes (LFEs) and tectonic tremor along the Parkfield–Cholame segment of the San Andreas fault suggest slow‐slip earthquakes occur in a transition zone between the shallow fault, which accommodates slip by a combination of aseismic creep and earthquakes (<15  km depth), and the deep fault, which accommodates slip by stable sliding (>35  km depth). However, the spatial relationship between shallow earthquakes and LFEs remains unclear. Here, we present precise relocations of 34 earthquakes and 34 LFEs recorded during a temporary deployment of 13 broadband seismic stations from May 2010 to July 2011. We use the temporary array waveform data, along with data from permanent seismic stations and a new high‐resolution 3D velocity model, to illuminate the fine‐scale details of the seismicity distribution near Cholame and the relation to the distribution of LFEs. The depth of the boundary between earthquakes and LFE hypocenters changes along strike and roughly follows the 350°C isotherm, suggesting frictional behavior may be, in part, thermally controlled. We observe no overlap in the depth of earthquakes and LFEs, with an &sim;5  km separation between the deepest earthquakes and shallowest LFEs. In addition, clustering in the relocated seismicity near the 2004 M w 6.0 Parkfield earthquake hypocenter and near the northern boundary of the 1857 M w 7.8 Fort Tejon rupture may highlight areas of frictional heterogeneities on the fault where earthquakes tend to nucleate.

California↗

USGS2014

Dynamics of a large, restless, rhyolitic magma system at Laguna del Maule, southern Andes, Chile

Explosive eruptions of large-volume rhyolitic magma systems are common in the geologic record and pose a major potential threat to society. Unlike other natural hazards, such as earthquakes and tsunamis, a large rhyolitic volcano may provide warning signs long before a caldera-forming eruption occurs. Yet, these signs—and what they imply about magma-crust dynamics—are not well known. This is because we have learned how these systems form, grow, and erupt mainly from the study of ash flow tuffs deposited tens to hundreds of thousands of years ago or more, or from the geophysical imaging of the unerupted portions of the reservoirs beneath the associated calderas. The Laguna del Maule Volcanic Field, Chile, includes an unusually large and recent concentration of silicic eruptions. Since 2007, the crust there has been inflating at an astonishing rate of at least 25 cm/yr. This unique opportunity to investigate the dynamics of a large rhyolitic system while magma migration, reservoir growth, and crustal deformation are actively under way is stimulating a new international collaboration. Findings thus far lead to the hypothesis that the silicic vents have tapped an extensive layer of crystal-poor, rhyolitic melt that began to form atop a magmatic mush zone that was established by ca. 20 ka with a renewed phase of rhyolite eruptions during the Holocene. Modeling of surface deformation, magnetotelluric data, and gravity changes suggest that magma is currently intruding at a depth of ~5 km. The next phase of this investigation seeks to enlarge the sets of geophysical and geochemical data and to use these observations in numerical models of system dynamics.

Laguna del Maule Volcanic Field↗

USGS2014

Seismicity and seismic structure at Okmok Volcano, Alaska

Okmok volcano is an active volcanic caldera located on the northeastern portion of Umnak Island in the Aleutian arc, with recent eruptions in 1997 and 2008. The Okmok area had ~900 locatable earthquakes between 2003 and June 2008, and an additional ~600 earthquakes from the beginning of the 2008 eruption to mid 2009, providing an adequate dataset for seismic tomography. To image the seismic velocity structure of Okmok, we apply waveform cross-correlation using bispectrum verification and double-difference tomography to a subset of these earthquakes. We also perform P-wave attenuation tomography using a spectral decay technique. We examine the spatio-temporal characteristics of seismicity in the opening sequence of the 2008 eruption to investigate the path of magma migration during the establishment of a new eruptive vent. We also incorporate the new earthquake relocations and three-dimensional (3D) velocity model with first-motion polarities to compute focal mechanisms for selected events in the 2008 pre-eruptive and eruptive periods. Through these techniques we obtain precise relocations, a well-constrained 3D P-wave velocity model, and a marginally resolved S-wave velocity model. We image a main low Vp and Vs anomaly directly under the caldera consisting of a shallow zone at 0–2 km depth connected to a larger deeper zone that extends to about 6 km depth. We find that areas of low Qp are concentrated in the central to southwestern portion of the caldera and correspond fairly well with areas of low Vp. We interpret the deeper part of the low velocity anomaly (4–6 km depth) beneath the caldera as a magma body. This is consistent with results from ambient noise tomography and suggests that previous estimates of depth to Okmok's magma chamber based only on geodetic data may be too shallow. The distribution of events preceding the 2008 eruption suggest that a combination of overpressure in the zone surrounding the magma chamber and the introduction of new material from below were jointly responsible for the explosive eruption. Magma escaping from the top of the main magma chamber likely reacted with both a smaller shallow pod of magma and groundwater on its way up below the Cone D area. The earthquakes in the 2008 pre-eruptive and eruptive periods are found to have a mixture of strike-slip, oblique normal, and oblique thrust mechanisms, with a dominant P-axis orientation that is nearly perpendicular to the regional tectonic stress. This may indicate that the stresses related to magmatic activity locally dominated regional tectonic forces during this time period.

Alaska↗

USGS2013

Ambient seismic noise interferometry in Hawai'i reveals long-range observability of volcanic tremor

The use of seismic noise interferometry to retrieve Green's functions and the analysis of volcanic tremor are both useful in studying volcano dynamics. Whereas seismic noise interferometry allows long-range extraction of interpretable signals from a relatively weak noise wavefield, the characterization of volcanic tremor often requires a dense seismic array close to the source. We here show that standard processing of seismic noise interferometry yields volcanic tremor signals observable over large distances exceeding 50 km. Our study comprises 2.5 yr of data from the U.S. Geological Survey Hawaiian Volcano Observatory short period seismic network. Examining more than 700 station pairs, we find anomalous and temporally coherent signals that obscure the Green's functions. The time windows and frequency bands of these anomalous signals correspond well with the characteristics of previously studied volcanic tremor sources at Pu'u 'Ō'ō and Halema'uma'u craters. We use the derived noise cross-correlation functions to perform a grid-search for source location, confirming that these signals are surface waves originating from the known tremor sources. A grid-search with only distant stations verifies that useful tremor signals can indeed be recovered far from the source. Our results suggest that the specific data processing in seismic noise interferometry—typically used for Green's function retrieval—can aid in the study of both the wavefield and source location of volcanic tremor over large distances. In view of using the derived Green's functions to image heterogeneity and study temporal velocity changes at volcanic regions, however, our results illustrate how care should be taken when contamination by tremor may be present.

Hawai'i↗

USGS2012

Volcanoes: observations and impact

Volcanoes are critical geologic hazards that challenge our ability to make long-term forecasts of their eruptive behaviors. They also have direct and indirect impacts on human lives and society. As is the case with many geologic phenomena, the time scales over which volcanoes evolve greatly exceed that of a human lifetime. On the other hand, the time scale over which a volcano can move from inactivity to eruption can be rather short: months, weeks, days, and even hours. Thus, scientific study and monitoring of volcanoes is essential to mitigate risk. There are thousands of volcanoes on Earth, and it is impractical to study and implement ground-based monitoring at them all. Fortunately, there are other effective means for volcano monitoring , including increasing capabilities for satellite-based technologies.

Book chapter↗

USGS2010

High‐resolution locations of triggered earthquakes and tomographic imaging of Kilauea Volcano's south flank

The spatiotemporal patterns of seismicity beneath Kilauea's south flank give insight to the structure and geometry of the decollement on which large, tsunamigenic earthquakes have occurred, and its relation to slow slip events (SSEs), which have been observed every 1 to 2 years since 1997. In order to record earthquakes triggered by a SSE that was predicted to occur in March 2007, a temporary network of 20 seismometers was deployed on Kilauea's south flank, termed the SEQ network. While the SSE did not occur until 17 June 2007, theSEQ network recorded over 3000 earthquakes, including those triggered by the SSE. We relocate hypocenters of volcano‐tectonic earthquakes and invert for P and S wave velocity structure using waveform cross‐correlation and double‐difference tomography using data from the SEQ network and the permanent Hawaii Volcano Observatory network (HVO) data, with additional data from other previous temporary arrays. The best‐constrained hypocenters, recorded by both the SEQ and HVO networks, indicate the decollement as a subhorizontal layer of seismicity at 8 km depth less than 1 km thick in most areas, with the western portion of the decollement dipping to the southeast. The seismicity triggered by the June 2007 SSE includes over 400 earthquakes overlapping with the southern edge of the decollement seismicity. A shallower swarm of earthquakes also occurred between 2 and 7 km depth in April 2007 near Apua Point, and may have been indirectly triggered by the M w 8.1 Solomon Islands earthquake at ∼6000 km distance, which occurred 48 h prior to the beginning of the swarm.

Hawaii↗

USGS2010

Earthquake waveform similarity and evolution at Augustine Volcano from 1993 to 2006: Chapter 5 in The 2006 eruption of Augustine Volcano, Alaska

Temporal changes in waveform characteristics and earthquake locations associated with the 2006 Augustine eruption and preeruptive seismicity provide constraints on eruptive processes within the edifice. Volcano-tectonic earthquakes occur within the upper 1 to 2 km at Augustine between and during eruptive cycles, and we use the Alaska Volcano Observatory hypocenter and waveform catalog from 1993 to 2006 to constrain changes in event similarity and location over time. Waveform crosscorrelation with bispectrum verification improves the pick accuracy of the catalog data to yield better locations and allows for identification of families of similar earthquakes. Event waveform similarity is low at Augustine, with ~60 to 70 percent of events failing to form event families of more than 10 events. The remaining earthquakes form event families over multiple time scales. Events prior to the 2006 eruption exhibit a high degree of similarity over multiple years. Earthquakes recorded during the precursory and explosive phases of the 2006 eruption form swarms of similar earthquakes over periods of days or hours. Seismicity rate and event similarity decrease rapidly during the explosive and effusive eruption phases. The largest recorded swarms accompany reports of increased steaming and explosive eruptions at the summit. Relative relocation of some event families indicates upward migration of activity over time, consistent with magma transport by way of an ascending dike. Multiple regions of the edifice generate seismicity simultaneously, however, suggesting the edifice contains a network of fractures and/or dikes.

Alaska↗