Geology topics

Matthew M. Haney

Publications and source records attributed to Matthew M. Haney.

84 records · Page 5Linked to original sources

USGS2014

Distinguishing high surf from volcanic long-period earthquakes

Repeating long-period (LP) earthquakes are observed at active volcanoes worldwide and are typically attributed to unsteady pressure fluctuations associated with fluid migration through the volcanic plumbing system. Nonvolcanic sources of LP signals include ice movement and glacial outburst floods, and the waveform characteristics and frequency content of these events often make them difficult to distinguish from volcanic LP events. We analyze seismic and infrasound data from an LP swarm recorded at Pagan volcano on 12–14 October 2013 and compare the results to ocean wave data from a nearby buoy. We demonstrate that although the events show strong similarity to volcanic LP signals, the events are not volcanic but due to intense surf generated by a passing typhoon. Seismo-acoustic methods allow for rapid distinction of volcanic LP signals from those generated by large surf and other sources, a critical task for volcano monitoring.

Pagan Volcano↗

USGS2014

Shaking up volcanoes

Most volcanic eruptions that occur shortly after a large distant earthquake do so by random chance. A few compelling cases for earthquake-triggered eruptions exist, particularly within 200 km of the earthquake, but this phenomenon is rare in part because volcanoes must be poised to erupt in order to be triggered by an earthquake (1). Large earthquakes often perturb volcanoes in more subtle ways by triggering small earthquakes and changes in spring discharge and groundwater levels (1, 2). On page 80 of this issue, Brenguier et al. (3) provide fresh insight into the interaction of large earthquakes and volcanoes by documenting a temporary change in seismic velocity beneath volcanoes in Honshu, Japan, after the devastating Tohoku-Oki earthquake in 2011.

Science↗

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↗

USGS2013

Source characterization for an explosion during the 2009 eruption of Redoubt Volcano from very-long-period seismic waves

The 2009 eruption of Redoubt produced several very-long-period (VLP) signals associated with explosions. We invert for the source location and mechanism of an explosion at Redoubt volcano using waveform methods applied to broadband recordings. Such characterization of the source carries information on the geometry of the conduit and the physics of the explosion process. Inversions are carried out assuming the volcanic source can be modeled as a point source, with mechanisms described by a) a set of 3 orthogonal forces, b) a moment tensor consisting of force couples, and c) both forces and moment tensor components. We find that the source of the VLP seismic waves during the explosion is well-described by either a combined moment/force source located northeast of the crater and at an elevation of 1.6 km ASL or a moment source at an elevation of 800 m to the southwest of the crater. The moment tensors for the solutions with moment and force and moment-only share similar characteristics. The source time functions for both moment tensors begin with inflation (pressurization) and execute two cycles of deflation-reinflation (depressurization–repressurization). Although the moment/force source provides a better fit to the data, we find that owing to the limited coverage of the broadband stations at Redoubt the moment-only source is the more robust and reliable solution. Based on the moment-only solution, we estimate a volume change of 19,000 m 3 and a pressure change of 7 MPa in a dominant sill and an out-of-phase volume change of 5000 m 3 and pressure change of 1.8 MPa in a subdominant dike at the source location. These results shed new light on the magmatic plumbing system beneath Redoubt and complement previous studies on Vulcanian explosions at other volcanoes.

Alaska↗

USGS2013

Seismic observations of Redoubt Volcano, Alaska - 1989-2010 and a conceptual model of the Redoubt magmatic system

Seismic activity at Redoubt Volcano, Alaska, has been closely monitored since 1989 by a network of five to ten seismometers within 22 km of the volcano's summit. Major eruptions occurred in 1989-1990 and 2009 and were characterized by large volcanic explosions, episodes of lava dome growth and failure, pyroclastic flows, and lahars. Seismic features of the 1989-1990 eruption were 1) weak precursory tremor and a short, 23-hour-long, intense swarm of repetitive shallow long-period (LP) events centered 1.4 km below the crater floor, 2) shallow volcano-tectonic (VT) and hybrid earthquakes that separated early episodes of dome growth, 3) 13 additional swarms of LP events at shallow depths precursory to many of the 25 explosions that occurred over the more than 128 day duration of eruptive activity, and 4) a persistent cluster of VT earthquakes at 6 to 9 km depth. In contrast the 2009 eruption was preceded by a pronounced increase in deep-LP (DLP) events at lower crustal depths (25 to 38 km) that began in mid-December 2008, two months of discontinuous shallow volcanic tremor that started on January 23, 2009, a strong phreatic explosion on March 15, and a 58-hour-long swarm of repetitive shallow LP events. The 2009 eruption consisted of at least 23 major explosions between March 23 and April 5, again accompanied by shallow VT earthquakes, several episodes of shallow repetitive LP events and dome growth continuing until mid July. Increased VT earthquakes at 4 to 9 km depth began slowly in early April, possibly defining a mid-crustal magma source zone. Magmatic processes associated with the 2009 eruption seismically activated the same portions of the Redoubt magmatic system as the 1989-1990 eruption, although the time scales and intensity vary considerably among the two eruptions. The occurrence of precursory DLP events suggests that the 2009 eruption may have involved the rise of magma from lower crustal depths. Based on the evolution of seismicity during the 1989-1990 and 2009 eruptions the Redoubt magmatic system is envisioned to consist of a shallow system of cracks extending 1 to 2 km below the crater floor, a magma storage or source region at roughly 3 to 9 km depth, and a diffuse magma source region at 25 to 38 km depth. Close tracking of seismic activity allowed the Alaska Volcano Observatory to successfully issue warnings prior to many of the hazardous explosive events that occurred in 2009.

Alaska↗

USGS2013

Catalog of earthquake hypocenters at Alaskan volcanoes: January 1 through December 31, 2012

Between January 1 and December 31, 2012, the Alaska Volcano Observatory located 4,787 earthquakes, of which 4,211 occurred within 20 kilometers of the 33 volcanoes monitored by a seismograph network. There was significant seismic activity at Iliamna, Kanaga, and Little Sitkin volcanoes in 2012. Instrumentation highlights for this year include the implementation of the Advanced National Seismic System Quake Monitoring System hardware and software in February 2012 and the continuation of the American Recovery and Reinvestment Act work in the summer of 2012. The operational highlight was the removal of Mount Wrangell from the list of monitored volcanoes. This catalog includes hypocenters, magnitudes, and statistics of the earthquakes located in 2012 with the station parameters, velocity models, and other files used to locate these earthquakes.

Alaska↗

USGS2012

Casual instrument corrections for short-period and broadband seismometers

Of all the filters applied to recordings of seismic waves, which include source, path, and site effects, the one we know most precisely is the instrument filter. Therefore, it behooves seismologists to accurately remove the effect of the instrument from raw seismograms. Applying instrument corrections allows analysis of the seismogram in terms of physical units (e.g., displacement or particle velocity of the Earth’s surface) instead of the output of the instrument (e.g., digital counts). The instrument correction can be considered the most fundamental processing step in seismology since it relates the raw data to an observable quantity of interest to seismologists. Complicating matters is the fact that, in practice, the term “instrument correction” refers to more than simply the seismometer. The instrument correction compensates for the complete recording system including the seismometer, telemetry, digitizer, and any anti‐alias filters. Knowledge of all these components is necessary to perform an accurate instrument correction. The subject of instrument corrections has been covered extensively in the literature (Seidl, 1980; Scherbaum, 1996). However, the prospect of applying instrument corrections still evokes angst among many seismologists—the authors of this paper included. There may be several reasons for this. For instance, the seminal paper by Seidl (1980) exists in a journal that is not currently available in electronic format and cannot be accessed online. Also, a standard method for applying instrument corrections involves the programs TRANSFER and EVALRESP in the Seismic Analysis Code (SAC) package (Goldstein et al. , 2003). The exact mathematical methods implemented in these codes are not thoroughly described in the documentation accompanying SAC.

Seismological Research Letters↗

USGS2012

Extension of the spatial autocorrelation (SPAC) method to mixed-component correlations of surface waves

Using ambient seismic noise for imaging subsurface structure dates back to the development of the spatial autocorrelation (SPAC) method in the 1950s. We present a theoretical analysis of the SPAC method for multicomponent recordings of surface waves to determine the complete 3 × 3 matrix of correlations between all pairs of three-component motions, called the correlation matrix. In the case of isotropic incidence, when either Rayleigh or Love waves arrive from all directions with equal power, the only non-zero off-diagonal terms in the matrix are the vertical–radial (ZR) and radial–vertical (RZ) correlations in the presence of Rayleigh waves. Such combinations were not considered in the development of the SPAC method. The method originally addressed the vertical–vertical (ZZ), RR and TT correlations, hence the name spatial autocorrelation. The theoretical expressions we derive for the ZR and RZ correlations offer additional ways to measure Rayleigh wave dispersion within the SPAC framework. Expanding on the results for isotropic incidence, we derive the complete correlation matrix in the case of generally anisotropic incidence. We show that the ZR and RZ correlations have advantageous properties in the presence of an out-of-plane directional wavefield compared to ZZ and RR correlations. We apply the results for mixed-component correlations to a data set from Akutan Volcano, Alaska and find consistent estimates of Rayleigh wave phase velocity from ZR compared to ZZ correlations. This work together with the recently discovered connections between the SPAC method and time-domain correlations of ambient noise provide further insights into the retrieval of surface wave Green’s functions from seismic noise.

Geophysical Journal International↗

USGS2012

Monitoring glacier surface seismicity in time and space using Rayleigh waves

Sliding glaciers and brittle ice failure generate seismic body and surface wave energy characteristic to the source mechanism. Here we analyze continuous seismic recordings from an array of nine short-period passive seismometers located on Bench Glacier, Alaska (USA) (61.033°N, 145.687°W). We focus on the arrival-time and amplitude information of the dominant Rayleigh wave phase. Over a 46-hour period we detect thousands of events using a cross-correlation based event identification method. Travel-time inversion of a subset of events (7% of the total) defines an active crevasse, propagating more than 200 meters in three hours. From the Rayleigh wave amplitudes, we estimate the amount of volumetric opening along the crevasse as well as an average bulk attenuation ( = 42) for the ice in this part of the glacier. With the remaining icequake signals we establish a diurnal periodicity in seismicity, indicating that surface run-off and subglacial water pressure changes likely control the triggering of these surface events. Furthermore, we find that these events are too weak (i.e., too noisy) to locate individually. However, stacking individual events increases the signal-to-noise ratio of the waveforms, implying that these periodic sources are effectively stationary during the recording period.

Journal of Geophysical Research F: Earth Surface↗

USGS2012

Earthquake studies reveal the magmatic plumbing system of the Katmai volcanoes

The 1912 eruption of Novarupta was the largest of the 1900s (Fierstein and Hildreth 2001, Hildreth et al. 2003). A century later, fundamental questions remain regarding the source of the magma for that eruption. A previous seismic study of the Katmai area (Jolly et al. 2007) identified a single large area of anomalous structure in the subsurface centered beneath Katmai Pass (Figure 2), but the magma source for the 1912 eruption is thought to have been beneath Mt. Katmai (Hildreth et al. 2003). This mystery was a prime motivation for the research project described here. In summer 2008, scientists and staff from the Alaska Volcano Observatory (AVO) and the University of Wisconsin- Madison installed 11 temporary seismic recording instruments around the Katmai Pass area, complementing the existing AVO seismic network stations (Figure 3). The primary goal of the deployment was to record data from local earthquakes in order to yield an improved model of the three-dimensional structure of the upper crust beneath and surrounding Katmai Pass, using an analysis method known as double-difference seismic tomography (Zhang and Thurber 2003). The method yields a threedimensional image of the velocity of seismic waves in the subsurface, and also produces improved estimates of the locations of the earthquakes beneath the seismic stations. Our main finding is that there is not a single large anomalous zone centered beneath Katmai Pass; rather there are several separate anomalous zones, one each beneath Katmai, Trident-Novarupta, and Martin-Mageik. Furthermore, the earthquakes are tightly clustered beneath the various volcanic centers, and are found to be systematically deeper than previously thought. Linear trends of earthquakes are also revealed, similar to features observed at other volcanoes, possibly outlining previously unidentified fault structures or indicating the path of migrating magma or magmatic fluids and gases.

Alaska↗

USGS2010

Rheologic and structural controls on the deformation of Okmok volcano, Alaska: FEMs, InSAR, and ambient noise tomography

Interferometric synthetic aperture radar (InSAR) data indicate that the caldera of Okmok volcano, Alaska, subsided more than a meter during its eruption in 1997. The large deformation suggests a relatively shallow magma reservoir beneath Okmok. Seismic tomography using ambient ocean noise reveals two low‐velocity zones (LVZs). The shallow LVZ corresponds to a region of weak, fluid‐saturated materials within the caldera and extends from the caldera surface to a depth of 2 km. The deep LVZ clearly indicates the presence of the magma reservoir beneath Okmok that is significantly deeper (>4 km depth) compared to previous geodetic‐based estimates (3 km depth). The deep LVZ associated with the magma reservoir suggests magma remains in a molten state between eruptions. We construct finite element models (FEMs) to simulate deformation caused by mass extraction from a magma reservoir that is surrounded by a viscoelastic rind of country rock embedded in an elastic domain that is partitioned to account for the weak caldera materials observed with tomography. This configuration allows us to reduce the estimated magma reservoir depressurization to within lithostatic constraints, while simultaneously maintaining the magnitude of deformation required to predict the InSAR data. More precisely, the InSAR data are best predicted by an FEM simulating a rind viscosity of 7.5 × 10 16 Pa s and a mass flux of −4.2 × 10 9 kg/d from the magma reservoir. The shallow weak layer within the caldera provides a coeruption stress regime and neutral buoyancy horizon that support lateral magma propagation from the central magma reservoir to extrusion near the rim of the caldera.

Alaska↗

USGS2009

Observation and modeling of source effects in coda wave interferometry at Pavlof volcano

Sorting out source and path effects for seismic waves at volcanoes is critical for the proper interpretation of underlying volcanic processes. Source or path effects imply that seismic waves interact strongly with the volcanic subsurface, either through partial resonance in a conduit (Garces et al., 2000; Sturton and Neuberg, 2006) or by random scattering in the heterogeneous volcanic edifice (Wegler and Luhr, 2001). As a result, both source and path effects can cause seismic waves to repeatedly sample parts of the volcano, leading to enhanced sensitivity to small changes in material properties at those locations. The challenge for volcano seismologists is to detect and reliably interpret these subtle changes for the purpose of monitoring eruptions.

Alaska↗