Volcanic eruption source parameters may be estimated from acoustic pressure recordings dominant at infrasonic frequencies (< 20 Hz), yet uncertainties may be high due in part to poorly understood propagation dynamics. Linear acoustic propagation of volcano infrasound is commonly assumed, but nonlinear processes such as wave steepening may distort waveforms and obscure the sourcing process in recorded waveforms. Here we use a previously developed frequency-domain nonlinearity indicator to quantify spectral changes due to nonlinear propagation primarily in 80 signals from explosions at Yasur Volcano, Vanuatu. We find evidence for $$\le$$ 10−3 dB/m spectral energy transfer in the band 3–9 Hz for signals with amplitude on the order of several hundred Pa at 200–400 m range. The clarity of the nonlinear spectral signature increases with waveform amplitude, suggesting stronger nonlinear changes for greater source pressures. We observe similar results in application to synthetics generated through finite-difference wavefield simulations of nonlinear propagation, although limitations of the model complicate direct comparison to the observations. Our results provide quantitative evidence for nonlinear propagation that confirms previous interpretations made on the basis of qualitative observations of asymmetric waveforms.

Atmospheric acoustic waves from volcanoes at infrasonic frequencies (0.01–20 Hz) can be used to estimate source parameters for hazard modeling, but signals are often distorted by wavefield interactions with topography, even at local recording distances (<15 km). We present new developments toward a simple empirical approach to estimate attenuation by topographic diffraction at reduced computational cost. We investigate the applicability of a thin screen diffraction relationship developed by Maekawa [1968, doi: https://doi.org/10.1016/0003-682X(68)90020- 0]. We use a 2D axisymmetric finite-difference method to show that this relationship accurately predicts power losses for infrasound diffraction over an idealized kilometer-scale screen; thus validating the scaling to infrasonic wavelengths. However, the Maekawa relationship overestimates attenuation for realistic volcano topography (using Sakurajima Volcano as an example). The attenuating effect of diffraction may be counteracted by constructive interference of multiple reflections along concave volcano slopes. We conclude that the Maekawa relationship is insufficient as formulated for volcano infrasound, and suggest modifications that may improve the prediction capability.

Seismic Twaves, which result from transformation of hydroacoustic to seismic energy at coastlines, were investigated for two strong earthquakes. A 2014 Caribbean event generated seismic T waves that were detected at over 250 seismometers along the east coast of the U.S., primarily at seismic stations operated by the USArray Transportable Array. A 2006 Hawaiian event generated seismic T waves observed at over 100 seismometers along the west coast. Seismic T-wave propagation was treated as locally 2D where the incoming hydroacoustic wavefronts were nearly parallel to the coastlines. Along the east coast, seismic T-wave propagation velocities were consistent with surface waves and a polarization analysis indicated that they were transverse waves, supporting their interpretation as Love waves. They were observed at inland distances up to 1134 km from the east coast. Along the west coast, the propagation velocity was over 5 km/s and a polarization analysis confirmed that the seismic T waves propagated as seismic P waves. Differences between the modes of propagation along the east and west coasts are attributed to differences in the slope and thickness of the sediment coverage at the continental slopes where hydroacoustic to seismic conversion takes place.

We have discovered a new geophysical phenomenon involving the coupling of the atmosphere-ocean and solid Earth using a novel array method. An analysis of ten years of seismic data recorded in the continental United States, mainly at the USArray, shows that large storms such as hurricanes and Nor’easters can excite transient seismic surface waves in the 20–50 s band with amplitudes equivalent to those excited by M3.5 earthquakes. These sources, which we label stormquakes, can produce transcontinental coherent Rayleigh wave packets observable in the time domain and are thus fundamentally different from previously reported atmosphere-ocean solid Earth couplings that produce incoherent seismic noise. We present unique observations and methods to pinpoint the source locations and timing, which clearly shows that these seismic waves are from interactions of seafloor bathymetry and ocean waves that are energized by large storms. Stormquakes migrate along continental shelfbreak, tracking the leading edge of large storms. We have documented features and identified a possible physical mechanism explaining the stormquake excitation. Stormquakes have potential use in oceanography and meteorology as a remote monitoring tool with high spatial and temporal resolution with which to investigate ocean wave dynamics during large storms.

The Automated Event Location Using a Mesh of Arrays (AELUMA) method, originally developed for detection of atmospheric sources using infrasonic data, is modified here to detect and locate seismic events. A key feature of AELUMA is that it does not require a detailed velocity model to locate events. The new method was applied to vertical-component seismic data recorded by the USArray Transportable Array to (1) test its efficacy when applied to a very large dataset, (2) test its ability to detect and accurately locate distinct event types across a geologically diverse region without analyst oversight, and (3) assess the sensitivity and accuracy of the method. Using data filtered from 1 to 8 Hz, 9996 events were detected in clusters within the central United States-with most events located near areas known for anthropogenic activity. The method was compared with three catalogs in Oklahoma-a region known for small anthropogenic events. In comparison with accurate locations from a template study, AELUMA detected all events from M-L >= 1.9 but none below M-L 1.3. The median absolute origin time and location offset were 9.5 s and 6.0 km, respectively. Comparisons of AELUMA's catalog in Oklahoma with two others (produced by Oklahoma Geological Survey [OGS] and the Array Network Facility) showed that AELUMA found more events than either catalog, including clusters of emergent events that were largely missed by the other methods. However, most of the smaller magnitude events detected by OGS were missed by AELUMA, mainly due to the sparser network used by AELUMA.

Surface waves recorded by global arrays have proven useful for locating tectonic earthquakes and in detecting slip events depleted in high frequency, such as glacial quakes. We develop a novel method using an aggregation of small-to continental-scale arrays to detect and locate seismic sources with Rayleigh waves at 20-50 s period. The proposed method is a hybrid approach including first dividing a large aperture aggregate array into Delaunay triangular subarrays for beamforming, and then using the resolved surface wave propagation directions and arrival times from the subarrays as data to formulate an inverse problem to locate the seismic sources and their origin times. The approach harnesses surface wave coherence and maximizes resolution of detections by combining measurements from stations spanning the whole U.S. continent. We tested the method with earthquakes, glacial quakes and landslides. The results show that the method can effectively resolve earthquakes as small as similar to M3 and exotic slip events in Greenland. We find that the resolution of the locations is non-uniform with respect to azimuth, and decays with increasing distance between the source and the array when no calibration events are available. The approach has a few advantages: the method is insensitive to seismic event type, it does not require a velocity model to locate seismic sources, and it is computationally efficient. The method can be adapted to real-time applications and can help in identifying new classes of seismic sources.

In deriving equations relating to the amplitude of infrasound signals from large explosions to the energy of the source, the assumption is generally made that the amplitude scales linearly with the source yield. However, results from experiments with large-yield detonations carried out at the Utah Test and Training Range (UTTR) west of Salt Lake City have cast doubt on that assumption, at least within the near field. In 2016, acoustic and infrasound sensors were placed at ranges up to 90 km east of the UTTR test site, and sources with yield ranging from 1700–17700 kg were detonated during the summertime. In several cases, detonations occurred only several hours apart. Predictable changes in amplitude might be expected, given that only small-scale spatial variations in the atmosphere occur over that time. The fact that this is not observed may be attributable to frequency dependent effects in atmospheric scattering. I report on the observations and show the degree to which amplitude variations can be predicted with numerical modeling. Numerical computations of the Navier-Stokes equations governing acoustic propagation are performed to investigate infrasound propagation for these events. The modeling allows for nonlinear propagation within an azimuthally symmetric atmospheric model, and incorporates accurate weather information.

Sound waves generated by erupting volcanoes can be used to infer important source dynamics, yet acoustic source-time functions may be distorted during propagation, even at local recording distances (<15 km). The resulting uncertainty in source estimates can be reduced by improving constraints on propagation effects. We aim to quantify potential distortions caused by wave steepening during nonlinear propagation, with the aim of improving the accuracy of volcano-acoustic source predictions. We hypothesize that wave steepening causes spectral energy transfer away from the dominant source frequency. To test this, we apply a previously developed single-point, frequency domain, quadspectral density-based nonlinearity indicator to 30 acoustic signals from Vulcanian explosion events at Sakurajima Volcano, Japan, in an 8-day data set collected by five infrasound stations in 2013 with 2.3- to 6.2-km range. We model these results with a 2-D axisymmetric finite-difference method that includes rigid topography, wind, and nonlinear propagation. Simulation results with flat ground indicate that wave steepening causes up to similar to 2 dB (1% of source level) of cumulative upward spectral energy transfer for Sakurajima amplitudes. Correction for nonlinear propagation may therefore provide a valuable second-order improvement in accuracy for source parameter estimates. However, simulations with wind and topography introduce variations in the indicator spectra on order of a few decibels. Nonrandom phase relationships generated during propagation or at the source may be misinterpreted as nonlinear spectral energy transfer. The nonlinearity indicator is therefore best suited to small source-receiver distances (e.g., <2 km) and volcanoes with simple sources (e.g., gas-rich strombolian explosions) and topography.

A meteor that burst above Michigan in early 2018 was recorded by nearby seismometers, regional infrasonic microphones, and optical sensors. The relatively large, but sparse, infrasonic network provided a location and time for the event that was consistent with ground-truth data from the optical sensors, although uncertainty regarding the infrasonic location was large. Seismic arrival times from four local seismometers constrain the location and height of the burst to within kilo-meters and agree with the optical data. A widely used period-yield relation applied to 40 high signal-to-noise recordings of infrasound signals from the event at distances from 2 degrees to 12 degrees indicates a preferred yield of 2.2 tons of trinitrotoluene (TNT) equivalent with a likely range from 0.8 to 8.1 tons. The successful recording of this relatively small meteor suggests that moderate-density infrasonic networks can be used to refine occurrence statistics of bolides, although such studies will likely be complicated by uncertain source yield estimates.

EON-ROSE (Earth-System Observing Network - Réseau d’Observation du Système terrestrE) is a new initiative for a pan-Canadian research collaboration to holistically examine Earth systems from the ionosphere into the core. The Canadian Cordillera Array (CC Array) is the pilot phase, and will extend across the Cordillera from the Beaufort Sea to the U.S. border. The vision for EON-ROSE is to install a network of telemetered observatories to monitor solid Earth, environmental and atmospheric processes. EON-ROSE is an inclusive, combined effort of Canadian universities, federal, provincial and territorial government agencies, industry, and international collaborators. Brainstorming sessions and several workshops have been held since May 2016. The first station will be installed at Kluane Lake Research Station in southwestern Yukon during the summer of 2018. The purpose of this report is to provide a framework for continued discussion and development.RÉSUMÉEON-ROSE (Earth-System Observing Network - Réseau d’Observation du Système terrestrE) est une nouvelle initiative de collaboration de recherche pancanadienne visant à étudier de manière holistique les systèmes terrestres, depuis l’ionosphère jusqu’au noyau. Le Réseau canadien de la cordillère (CC Array) en est la phase pilote, laquelle couvrira toute la Cordillère, de la mer de Beaufort jusqu’à la frontière étasunienne. L’objectif d’EON-ROSE est d’installer un réseau d’observatoires télémétriques pour suivre en continu les processusterrestres, environnementaux et atmosphériques. EON-ROSE est un effort combiné et inclusif des universités canadiennes, des organismes gouvernementaux fédéraux, provinciaux et territoriaux, de l’industrie et de collaborateurs internationaux. Des séances de remue-méninges et plusieurs ateliers ont été tenus depuis mai 2016. La première station sera installée à la station de recherche du lac Kluane, dans le sud-ouest du Yukon, au cours de l’été 2018. Le but du présent rapport est de fournir un cadre de discussion et de développement continu.

We report observations of waveforms in surface pressure made over several years by a network of ground‐level barometers in the eastern United States. The waveforms can be reconstructed by superimposing the 4th through 10th subharmonics of the solar day. Some of these solar harmonics are likely generated by the temperature and pressure gradients across the solar terminators. The measurements presented here enable a wave detection analysis which indicates that some waveforms are coherent between stations with a median speed of 49.7 m/s to the southeast. We interpret these propagating signals, which are interference patterns created by internal gravity waves with periods that are subharmonics of a solar day, as a previously undiscovered type of terminator wave. The waveforms appear predominantly postsunrise during winter and postsunset in summer. Their quasi‐eastward propagation direction suggests an analogy with “stern” waves left behind by the faster, westward‐moving terminator.

New, massive, datasets can be used to examine atmospheric phenomena in more detail than before but require analytical methods that are both efficient and capable of extracting useful information from faint signals immersed in noise. We have developed the AELUMA (Automated Event Location Using a Mesh of Arrays) method that recasts any dense network of sensors as a distributed mesh of triangular arrays. Each array provides a local estimate of signal properties. This information from arrays across the network is combined to estimate the source origin time and location. The process is repeated without oversight to catalog events. A key challenge in attributing signals to their source occurs when a large number of signals are detected nearly concurrently from different sources. We apply a cluster (decision tree) analysis that takes the results of array processing at all arrays to iteratively parse out subsets of detections from distinct sources. We used recordings of infrasound signals made at an extensive network of sensors to build a catalog of infrasonic activity across the continental United States. The accuracy of AELUMA is assessed using events for which the origin time and location are well known.