Infrasound Recordings Research Articles

Estimating stratospheric polar vortex strength using ambient ocean‐generated infrasound and stochastics‐based machine learning

AbstractThere are sparse opportunities for direct measurement of upper stratospheric winds, yet improving their representation in subseasonal‐to‐seasonal prediction models can have significant benefits. There is solid evidence from previous research that global atmospheric infrasound waves are sensitive to stratospheric dynamics. However, there is a lack of results providing a direct mapping between infrasound recordings and polar‐cap upper stratospheric winds. The global International Monitoring System (IMS), which monitors compliance with the Comprehensive Nuclear‐Test‐Ban Treaty, includes ground‐based stations that can be used to characterize the infrasound soundscape continuously. In this study, multi‐station IMS infrasound data were utilized along with a machine‐learning supported stochastic model, Delay‐SDE‐net, to demonstrate how a near‐real‐time estimate of the polar‐cap averaged zonal wind at 1‐hPa pressure level can be found from infrasound data. The infrasound was filtered to a temporal low‐frequency regime dominated by microbaroms, which are ambient‐noise infrasonic waves continuously radiated into the atmosphere from nonlinear interaction between counter‐propagating ocean surface waves. Delay‐SDE‐net was trained on 5 years (2014–2018) of infrasound data from three stations and the ERA5 reanalysis 1‐hPa polar‐cap averaged zonal wind. Using infrasound in 2019–2020 for validation, we demonstrate a prediction of the polar‐cap averaged zonal wind, with an error standard deviation of around 12 m·s compared with ERA5. These findings highlight the potential of using infrasound data for near‐real‐time measurements of upper stratospheric dynamics. A long‐term goal is to improve high‐top atmospheric model accuracy, which can have significant implications for weather and climate prediction.

Probing Gravity Waves in the Middle Atmosphere Using Infrasound From Explosions

AbstractThis study uses low‐frequency, inaudible acoustic waves (infrasound) to probe wind and temperature fluctuations associated with breaking gravity waves (GWs) in the middle atmosphere. Building on an approach introduced by Chunchuzov et al., infrasound recordings are used to retrieve effective sound‐speed fluctuations in an inhomogeneous atmospheric layer that causes infrasound backscattering. The infrasound was generated by controlled blasts at Hukkakero, Finland, and recorded at the IS37 infrasound station, Norway in the late summers 2014–2017. Our findings indicate that the analyzed infrasound scattering occurs at mesospheric altitudes of 50–75 km, a region where GWs interact under non‐linearity, forming thin layers of strong wind shear. The retrieved fluctuations were analyzed in terms of vertical wave number spectra, resulting in an approximate power law that corresponds to the “universal” saturated spectrum of atmospheric GWs. The power law wavenumber range corresponds to vertical atmospheric scales of 33–625 m. The fluctuation spectra were compared to theoretical GW saturation theories as well as to independent wind measurements by the Saura medium‐frequency radar near Andøya Space Center around 100 km west of IS37, yielding a good agreement in terms of vertical wavenumber spectrum amplitudes and slopes. This suggests that the radar and infrasound‐based effective sound‐speed profiles represent low‐ and high‐wavenumber regimes of the same “universal” GW spectrum. The results illustrate that infrasound allows for probing fine‐scale dynamics not well captured by other techniques, suggesting that infrasound can provide a complementary technique to probe atmospheric GWs.

Using Local Infrasound to Estimate Seismic Velocity and Earthquake Magnitudes

ABSTRACT Earthquake ground motions in the vicinity of receivers couple with the atmosphere to generate pressure perturbations that are detectable by infrasound sensors. These so-called local infrasound signals traverse very short source-to-receiver paths, so that they often exhibit a remarkable correlation with seismic velocity waveforms at collocated seismic stations, and there exists a simple relationship between vertical seismic velocity and pressure time series. This study leverages the large regional network of infrasound sensors in Alaska to examine local infrasound from several light to great Alaska earthquakes. We estimate seismic velocity time series from infrasound pressure records and use these converted infrasound recordings to compute earthquake magnitudes. This technique has potential utility beyond the novelty of recording seismic velocities on pressure sensors. Because local infrasound amplitudes from ground motions are small, it is possible to recover seismic velocities at collocated sites where the broadband seismometers have clipped. Infrasound-derived earthquake magnitudes exhibit good agreement with seismically derived values. This proof-of-concept demonstration of computing seismic magnitudes from infrasound sensors illustrates that infrasound sensors may be utilized as proxy vertical-component seismometers, making a new data set available for existing seismic techniques. Because single-sensor infrasound stations are relatively inexpensive and are becoming ubiquitous, this technique could be used to augment existing regional seismic networks using a readily available sensor platform.

Lava fountain jet noise during the 2018 eruption of fissure 8 of Kīlauea volcano

Real-time monitoring is crucial to assess hazards and mitigate risks of sustained volcanic eruptions that last hours to months or more. Sustained eruptions have been shown to produce a low frequency (infrasonic) form of jet noise. We analyze the lava fountaining at fissure 8 during the 2018 Lower East Rift Zone eruption of Kīlauea volcano, Hawaii, and connect changes in fountain properties with recorded infrasound signals from an array about 500 m from the fountain using jet noise scaling laws and visual imagery. Video footage from the eruption reveals a change in lava fountain dynamics from a tall, distinct fountain at the beginning of June to a low fountain with a turbulent, out-pouring lava pond surrounded by a tephra cone by mid-June. During mid-June, the sound pressure level reaches a maximum, and peak frequency drops. We develop a model that uses jet noise scaling relationships to estimate changes in volcanic jet diameter and jet velocity from infrasound sound pressure levels and peak frequencies. The results of this model indicate a decrease in velocity in mid-June which coincides with the decrease in fountain height. Furthermore, the model results suggest an increase in jet diameter, which can be explained by the larger width of the fountain that resembles a turbulent lava pond compared to the distinct fountain at the beginning of June. The agreement between the infrasound-derived and visually observed changes in fountain dynamics suggests that jet noise scaling relationships can be used to monitor lava fountain dynamics using infrasound recordings.

The Redmond Salt Mine Monitoring Experiment: Observations of Infrasound Resonance

ABSTRACT From October 2017 to July 2019, we collected seismic recordings of nighttime mining explosions occurring at Redmond Salt Mine. In addition to seismic data, infrasound recordings of the explosions were collected from October 2017 to June 2018. Mine operators provided logs of explosion locations during the period from May 2018 to November 2018, along with a detailed survey of the mine structure. Seismic signals from these explosions exhibit a very complex character resulting from the heterogeneous subsurface of the region. We were able to cluster the observed seismic waveforms into several groups based on waveform similarity, which were then associated with specific regions of active mining using the operator logs. Two of these clusters were associated with several explosive events that generated infrasound easily detected out to 20 km. Because all these events occurred at night, the observed similarity of the infrasound waveforms across all the stations may result from the presence of an inversion layer that traps acoustic energy near the surface. Fully understanding the influence of atmospheric and meteorological conditions on the propagation of these infrasound signals is not possible without additional surveys. However, the recorded infrasound signals exhibit a harmonic structure that appears to result from acoustic reverberations within the mine tunnels. Application of a simple model to explain these results gives a factor of two agreement between the actual and estimated dimension of a mine tunnel whose southern end is open to the atmosphere. The observation of harmonic infrasound signals highlights the increased usefulness of infrasound in monitoring at local distances, relative to monitoring at farther offsets. Although these signals cannot be reliably recorded, presumably due to the requirement of a relatively simple atmosphere at the time of recording, we nonetheless encourage the routine collection of infrasound data in local monitoring applications.

Site-specific variations in air-to-ground coupled seismic arrivals from the 2012 October 16 explosion at Camp Minden, Louisiana, United States

SUMMARY Air-to-ground coupled seismic arrivals, resulting from infrasound interacting with the ground surface, can be identified on seismometers co-located with microbarometers. Dense networks of co-located sensors provide detailed spatial information about the infrasonic wavefield, allowing investigation of infrasonic propagation and an assessment of the variability in air-to-ground coupling mechanisms. Signals generated by an explosion at Camp Minden, Louisiana, United States, on 2012 October 16 were recorded across the eastern United States on the USArray Transportable Array. 233 infrasound signals were identified at distances of up to 1566 km from the source, with 105 of these sites, at distances of up to 1147 km from the source, recording above-noise air-to-ground coupled seismic arrivals in the 2–4 Hz passband (chosen to maximise seismic arrival signal-to-noise ratios). The spatially dense infrasound recordings allowed a unique investigation of the azimuthal variation in infrasound amplitudes, showing that stratospheric arrival amplitudes increased by a factor greater than 4 between the edge and centre of the stratospheric propagation duct. Air-to-ground coupling coefficients, calculated as the ratios of temporally coincident peak-to-trough seismic and infrasound time-domain amplitudes, span over two orders of magnitude ([9.0 × 10−8, 5.0 × 10−5] ms−1 Pa−1). Sites exhibiting high coupling coefficients are predominantly located on alluvial sediments that support the generation of air-to-ground coupled Rayleigh waves, resulting in poor coherence between the seismic and infrasonic waveforms. In contrast, sites exhibiting low coupling coefficients are predominantly located on chemically weathered bedrock and only support direct coupling, leading to high coherence between air-to-ground coupled seismic and infrasonic recordings. The Camp Minden explosion observations, and a consideration of expected seismic noise and air-to-ground coupled arrival amplitudes, suggest that co-located pairs of seismometers and microbarometers are likely to record signals from small (tens of tons) explosions at distances of over 1000 km under favourable propagation conditions. Co-located deployments may therefore provide a cost-effective method for augmenting current state-of-the-art infrasound array networks, by providing a higher spatial density of recordings; this may assist in correctly associating recorded signals with, and estimating the location of, source events.

Influence of atmospheric conditions on measured infrasound from wind turbines

Scientific interest towards low frequencies and infrasound from wind turbines has renewed over the last decade as the size of wind turbines and the number of wind farms have continuously increased. However, few comprehensive studies are found assessing such noise emitted by wind turbines in response to meteorological parameters, including turbulent characteristics of the atmospheric boundary layer. The current work presents a detailed long-term measurement campaign combining infrasound recordings close to wind turbines and high-resolution meteorological parameters at three heights. An artificial neural network (ANN) model, developed based on the measurement data, was able to adequately predict both blade passing frequency levels and broadband infrasonic noise. The model allowed discriminating between the broadband inflow noise emitted by the wind turbines and the remaining microphone-induced wind noise under the wind-shielding dome for a wide range of atmospheric conditions. At the same time, the ANN allowed deriving physically plausible relationships between meteorological and turbulence parameters and wind turbine emitted infrasound components. Dominant predictors for the infrasound production were mean wind speed, turbulence intensity and turbulent vertical heat flux.

Infrasound direction of arrival determination using a balloon-borne aeroseismometer.

Free-floating balloons are an emerging platform for infrasound recording, but they cannot host arrays sufficiently wide for multi-sensor acoustic direction finding techniques. Because infrasound waves are longitudinal, the balloon motion in response to acoustic loading can be used to determine the signal azimuth. This technique, called "aeroseismometry," permits sparse balloon-borne networks to geolocate acoustic sources. This is demonstrated by using an aeroseismometer on a stratospheric balloon to measure the direction of arrival of acoustic waves from successive ground chemical explosions. A geolocation algorithm adapted from hydroacoustics is then used to calculate the location of the explosions.

Modeling of acoustic and gravity wave interactions, coupling, and observables above meteorological systems

Meteorology, especially strong tropospheric convection, is widely appreciated to generate broad spectra of acoustic and gravity waves (AWs and GWs or, together, AGWs). These include GWs with scales of tens to hundreds of kilometers and periods of ∼5 min to hours, that readily propagate upward, reach high altitudes (often to the lower-thermosphere), and grow to large amplitudes so that they may evolve nonlinearly prior to being overcome by dissipation. Strong convective dynamics, e.g., thunderstorms and tornadoes, are also known to radiate AWs at very low infrasonic frequencies (e.g., 0.1 Hz down to ∼4 mHz) that reach high altitudes and may be detectable in fluctuations of the atmosphere and ionosphere [e.g., Nishioka et al. (2013); Heale et al. (2019)]. The breaking of strong GW fields may also generate secondary AWs and, more generally, AGWs [Snively (2017); Heale et al. (2021)]. Together, convection and secondary AGW processes contribute to a broad spectrum of AWs with ∼mHz periods that are readily detectable at high altitudes and in pressure signals also measured at ground. Although AWs are excluded from traditional numerical weather prediction models, we report on models and simulation experiments designed to capture AW/AGW evolutions and their resulting observable signatures. In particular, we review and highlight scenarios by which ∼mHz AWs may reveal source processes of interest, as well as the opportunities to use atmospheric and ionospheric signals of AWs/AGWs as complement to ground-based infrasound recordings.

Structural infrasound from a barge collision with the Mississippi river bridge.

The Mississippi River Bridge in Vicksburg, Mississippi, is a seven-span cantilever bridge that is 1033 m long by 20.9 m wide and is part of the Interstate-20 corridor. On March 23, 2011, at approximately 14:30 CST, a barge moving downstream struck a pier of the bridge. An infrasound array located at the U.S. Army Engineer Research and Development Center (ERDC) detected the impact. Finite Element (FE) models were developed to investigate the structural behavior of the bridge due to the impact. The FE models identified events within the infrasound record that were possibly produced by the different modes of vibration of the bridge structure. The emerging technology of structural infrasound monitoring and the potential for using infrasound as a forensic tool is demonstrated with the results of the bridge-barge collision event and capability of deployment in the future.

A Bird’s‐Eye View on Ambient Infrasonic Soundscapes

AbstractA method is introduced to reconstruct microbarom soundscapes in absolute values. The soundscapes are compared to remote infrasound recordings from infrasound array I23FR (Kerguelen Island) and in situ recordings by the INFRA‐EAR, a biologger deployed near the Crozet Islands. The reconstruction method accounts for all‐acoustic contributions, divided into evanescent microbaroms (detectable directly above the source) and propagating microbaroms (detectable over long ranges). It is computed by integrating acoustic intensities over the ocean surface, convolved with the transfer function quantifying the propagation losses and propagation time. The reconstructed soundscapes are found within 2.7 dB for of the measurements in the microbarom band of 0.1–0.3 Hz. Infrasonic soundscapes are essential for understanding the ambient infrasonic noise field and are a basic need for applications, such as atmospheric remote sensing, natural hazard monitoring, and verification of the Comprehensive Nuclear‐Test‐Ban Treaty.

Benchmarking microbarom radiation and propagation model against infrasound recordings: a vespagram-based approach

Abstract. This study investigates the use of a vespagram-based approach as a tool for multi-directional comparison between simulated microbarom soundscapes and infrasound data recorded at ground-based array stations. Data recorded at the IS37 station in northern Norway during 2014–2019 have been processed to generate vespagrams (velocity spectral analysis) for five frequency bands between 0.1 and 0.6 Hz. The back azimuth resolution between the vespagram and the microbarom model is harmonized by smoothing the modeled soundscapes along the back azimuth axis with a kernel corresponding to the frequency-dependent array resolution. An estimate of similarity between the output of the microbarom radiation and propagation model and infrasound observations is then generated based on the image-processing approach of the mean square difference. The analysis reveals that vespagrams can monitor seasonal variations in the microbarom azimuthal distribution, amplitude, and frequency, as well as changes during sudden stratospheric warming events. The vespagram-based approach is computationally inexpensive, can uncover microbarom source variability, and has the potential for near-real-time stratospheric diagnostics and atmospheric model assessment.

Autocorrelation Infrasound Interferometry

AbstractSeismic and infrasound multistation ambient‐noise interferometry has been widely used to infer ground and atmospheric properties, and single‐station and autocorrelation seismic interferometry has also shown potential for characterizing Earth structure at multiple scales. We extend autocorrelation seismic interferometry to ambient atmospheric infrasound recordings that contain persistent local noise from waterfalls and rivers. Across a range of geographic settings, we retrieve relative sound‐speed changes that exhibit clear diurnal oscillations consistent with temperature and wind variations. We estimate ambient air temperatures from variations in relative sound speeds. The frequency band from 1 to 2 Hz appears most suitable to retrieve weather parameters as nearby waterfalls and rivers may act as continuous and vigorous sources of infrasound that help achieve convergence of coherent phases in the autocorrelation codas. This frequency band is also appropriate for local sound‐speed variations because it has infrasound with wavelengths of ∼170–340 m, corresponding to a typical atmospheric boundary layer height. After applying array analysis to autocorrelation functions derived from a three‐element infrasound array, we find that autocorrelation codas are composed of waves reflected off nearby topographic features, such as caldera walls. Lastly, we demonstrate that autocorrelation infrasound interferometry offers the potential to study the atmosphere over at least several months and with a fine time resolution.

Registration of avalanches in the Khibiny Mountains by the geophysical methods

In the winter months of 2018-2020 the Kola Branch of the Unified Geophysical Service RAS conducted experiments on the joint registration of avalanches in the Khibiny mountain range using seismic and infrasonic sensors during work on the forced descent of the snow mass. The aim of the experiments is to assess the possibility of avalanche detection using the geophysical methods. The lack of representative statistics on the frequency and regularity of avalanches is the reason for the relevance of developing methods of their remote registration. The difficulty of registering avalanches is due to their occurrence often in hard-to-reach areas and in poor visibility conditions. To record signals generated by avalanches, different configurations of infrasound panels consisting of three spatially separated sensors (MPA 201 or Hyperion IFS-4000 microbarographs) and a portable seismic station Guralp CMG-6TD were used. As a result of the experiments, infrasound recordings were obtained at different distances from the avalanche source. The infrasound group recordings collected from the experiments were processed using an automatic detector implementing amplitude and cross-correlation signal detection methods. The spectral composition of the recordings and their characteristic appearance were analyzed. Avalanche-induced signals are characterized by long duration and changes in azimuth to the source. The dominant frequencies of the signal lie in the region of 1-10 Hz. Conclusions are made about the insufficient sensitivity of the seismic method when the seismometer is located at a distance of the first kilometers from the avalanche source, as well as the high applicability of the infrasound method for recording the facts of avalanches. The results obtained will make it possible to develop a methodology for automatic detection of signals generated by avalanches using the data of infrasound registration. This is the necessary basis for building a system for continuous monitoring of avalanche activity.

An investigation of the 27 July 2018 bolide and meteorite fall over Benenitra, southwestern Madagascar

Several dozen stones of an ordinary chondrite meteorite fell in and around the town of Benenitra in southwestern Madagascar during the early evening of 27 July 2018, minutes after a widely observed meteor fireball (bolide) transit and detonation. The event was confirmed by low-frequency infrasound recordings received at ~17h15 UTC (Coordinated Universal Time; 19h15 local time) at the Comprehensive Nuclear Test Ban Treaty Organization (CTBTO) infrasound station I33MG near Antananarivo, 542 km north-northeast of Benenitra. An energy release equivalent to 2.038 kt of TNT was calculated from the infrasound signals. Seismograph readings at the SKRH station 77 km north-northwest of Benenitra recorded a twostage signal consistent with the arrivals of an initial air-coupled ground wave at 16h48:08 UTC and a stronger pulse at 16h49:22 UTC linked directly to the atmospheric pressure wave. The infrasound and seismic signal arrival times suggest that the bolide entry and detonation occurred at approximately 18h46 local time (16h46 UTC), entry was from the northwest, and the detonation hypocentre was located within ~20 km of Benenitra. Despite meteorite debris being found among buildings within Benenitra, there was no damage to structures or injuries reported. Eyewitness accounts and photographic records indicate that approximately 75 mostly intact stones were collected; however, the remoteness of the area, the rugged nature of the terrain and sales of fragments to meteorite collectors have limited scientific analysis of the fall and the extent of the strewn field. The total mass of recovered stones is estimated at between 20 kg and 30 kg, with one fragment of 11.2 kg and several of ~1 kg. Petrographic and mineral chemical analyses indicate that the stones belong to the L6 class of ordinary chondrites. Cosmogenic radionuclide analysis confirms that the fall is linked to the bolide event. The name Benenitra has been officially accepted by the Meteoritical Bulletin Database.Significance:
 
 Eyewitness reports, CTBTO infrasound records, seismograph records and cosmogenic radionuclide analysis confirm a meteorite fall over Benenitra on 27 July 2018.
 Petrographic and geochemical analyses confirm that the meteorite is an L6 ordinary chondrite.
 Recovery of meteorite falls is rare; this is Madagascar’s second known meteorite fall and the first that can be linked to a bolide.
 Regional and global science monitoring networks can be interrogated to improve the understanding of bolide events.
 Interaction of scientists with local communities is important to dispel misunderstandings around scientific phenomena, and can improve collection of data.

Volcano video data characterized and classified using computer vision and machine learning algorithms

Video cameras are common at volcano observatories, but their utility is often limited during periods of crisis due to the large data volume from continuous acquisition and time requirements for manual analysis. For cameras to serve as effective monitoring tools, video frames must be synthesized into relevant time series signals and further analyzed to classify and characterize observable activity. In this study, we use computer vision and machine learning algorithms to identify periods of volcanic activity and quantify plume rise velocities from video observations. Data were collected at Villarrica Volcano, Chile from two visible band cameras located ~17 ​km from the vent that recorded at 0.1 and 30 frames per second between February and April 2015. Over these two months, Villarrica exhibited a diverse range of eruptive activity, including a paroxysmal eruption on 3 March. Prior to and after the eruption, activity included nighttime incandescence, dark and light emissions, inactivity, and periods of cloud cover. We quantify the color and spatial extent of plume emissions using a blob detection algorithm, whose outputs are fed into a trained artificial neural network that categorizes the observable activity into five classes. Activity shifts from primarily nighttime incandescence to ash emissions following the 3 March paroxysm, which likely relates to the reemergence of the buried lava lake. Time periods exhibiting plume emissions are further analyzed using a row and column projection algorithm that identifies plume onsets and calculates apparent plume horizontal and vertical rise velocities. Plume onsets are episodic, occurring with an average period of ~50 ​s and suggests a puffing style of degassing, which is commonly observed at Villarrica. However, the lack of clear acoustic transients in the accompanying infrasound record suggests puffing may be controlled by atmospheric effects rather than a degassing regime at the vent. Methods presented here offer a generalized toolset for volcano monitors to classify and track emission statistics at a variety of volcanoes to better monitor periods of unrest and ultimately forecast major eruptions.

Global Monitoring and Characterization of Infrasound Signatures by Large Fireballs

Large meteoroids can be registered in infrasound recordings during their entry into the Earth’s atmosphere. A comprehensive study of 10 large fireball events of the years 2018 and 2019 highlights their detection and characterization using global infrasound arrays of the International Monitoring System (IMS) of the Comprehensive Nuclear-Test-Ban Treaty (CTBT). The study focuses on the observation and event analysis of the fireballs to estimate their respective location, yield, trajectory, and entry behavior. Signal characteristics are derived by applying the Progressive Multi-Channel Correlation method as an array technique. The comparison of the events with a NASA reference database as well as the application of atmospheric propagation modeling allows to draw conclusions about infrasound-based detection capability, localization accuracy, yield estimation, and source characterization. The infrasound technique provides a time- and location-independent remote monitoring opportunity of impacting near-Earth objects (NEOs), either independent or complementary to other fireball observation methods. Additionally, insights about the detection and localization capability of IMS infrasound stations can be gained from using large fireballs as reference events, being of importance for the continuous monitoring and verification of atmospheric explosions in a CTBT context.

How Can the International Monitoring System Infrasound Network Contribute to Gravity Wave Measurements?

Gravity waves (GWs) propagate horizontally and vertically in the atmosphere. They transport energy and momentum, and therefore GWs can affect the atmospheric circulation at different altitude layers when dissipating. Thus knowledge about the occurrence of GWs is essential for Numerical Weather Prediction (NWP). However, uniform networks for covering GW measurements globally are rare, especially in the troposphere. It has been shown that an infrasound station of the International Monitoring System (IMS) infrasound network is capable of measuring GWs at the Earth’s surface. The IMS was deployed for monitoring the atmosphere to verify compliance with the Comprehensive Nuclear-Test-Ban-Treaty. In this study, the Progressive Multi-Channel Correlation Method (PMCC) is used for re-processing up to 20 years of IMS infrasound recordings in order to derive GW detections. For this purpose, two alternative PMCC configurations are discussed, covering GW frequencies equivalent to periods of between 5 min and 150 min. These detections mainly reflect sources of deep convection, particularly in the tropics. At mid-latitudes, coherent wind noise more often produces spurious detections. Combining the results of both configurations provides a global dataset of ground-based GW measurements, which enables the calculation of GW parameters. These can be used for improving NWP models.

Infrasound explosion and coda signal investigated with joint analysis of video at Mount Erebus, Antarctica

Mount Erebus is a natural laboratory where lava lake strombolian activity can be directly observed from the crater rim, allowing for a unique opportunity to study infrasound generated during explosive bubble bursting. Erebus lava lake eruptions occur when pressurized bubble slugs distend the lava lake surface and then burst within a few tenths of seconds. Data from two infrasound stations and one video camera were used to study 13 explosions occurring in January of 2006. Infrasound recordings from the two stations at ~330 m from the source exhibit variable amplitudes (40–160 Pa), but similar shapes composed of high-amplitude ~1 s bipolar pulses followed by codas exhibiting 3 or 4 decaying oscillations and lasting ~3 s. Infrasound pulses and infrasound-inferred source volumes are compared to video imagery, which is used to quantify the expanding volumes of distending bubbles and subsequent erupted pyroclasts. Video-inferred volumes scale well with infrasound-inferred volumes during the first few tenths of a second of an eruption, assuming a monopole source. Afterwards, an inflection in infrasound waveform, corresponding to a more rapid increase in the pressure record, indicates the fragmentation of the bubble membrane. At this point, infrasound is still produced by expanding gases and pyroclasts, but infrasound-inferred volumes are smaller than the image processing suggests. This is due to the fact that the image processing tracks ballistics, which expand inertially and without exerting a significant volume change. After 0.5 to 1.5 s the volumetric expansion is no longer evident in the infrasound record, which is now comprised of a coda characterized by decaying ~1 Hz oscillations. Because the coda does not correspond to any motions evident in the video, we conclude that it represents an acoustic resonance of the void left in the lava lake. This resonance is modulated by echoes off crater topography giving rise to two peak frequencies that dominate the coda spectra and are different for the two infrasound recording sites. The two coda spectral peaks are well explained by site-dependent propagation effects. Deconvolving crater topography effects, which are different for the two stations, reveals a single frequency peak at 1.5 Hz and is attributed to resonance of the void left in the lava lake, which we model as an open cylindrical pipe or Helmholtz resonance.

Infrasound from the 2009 and 2017 DPRK rocket launches

SummarySupersonic rockets generate low-frequency acoustic waves, that is, infrasound, during the launch and re-entry. Infrasound is routinely observed at infrasound arrays from the International Monitoring System, in place for the verification of the Comprehensive Nuclear-Test-Ban Treaty. Association and source identification are key elements of the verification system. The moving nature of a rocket is a defining criterion in order to distinguish it from an isolated explosion. Here, it is shown how infrasound recordings can be associated, which leads to identification of the rocket. Propagation modelling is included to further constrain the source identification. Four rocket launches by the Democratic People's Republic of Korea in 2009 and 2017 are analysed in which multiple arrays detected the infrasound. Source identification in this region is important for verification purposes. It is concluded that with a passive monitoring technique such as infrasound, characteristics can be remotely obtained on sources of interest, that is, infrasonic intelligence, over 4500+ km.