The motivation and objective of the EarthScope Transportable Array (TA) is to record earthquake signals and image the structure of the North American plate, however the observations collected by this National Science Foundation funded project have enabled unanticipated discoveries, innovative data analysis techniques, and ongoing investigations across many disciplines in the Earth and space sciences. The Transportable Array utilized a survey approach to collect data in which high-quality stations were systematically installed in a dense geospatial grid. From the very beginning of the deployment, this strategy allowed for data-driven discovery, such as using seismic data to map out extensive travel time curves for acoustic waves in the atmosphere (Hedlin et al., 2010). While the emplacement of the seismic sensors was kept uniform along with the core components for power and communications, the Transportable Array station design evolved over time to include additional barometric pressure and infrasound sensors and, eventually, meteorological sensors measuring external temperature, wind, and precipitation. As the array rolled across the Lower 48 and the TA became more recognized outside of seismology, collaborations were forged and strengthened with researchers in the infrasound and meteorological communities. Along with standard approaches using direct measurements, inventive techniques were used to apply environmental data for observing tectonic phenomena as well as applying seismic data for observing environmental phenomena. The value of integrated scientific infrastructure became even more apparent with the Transportable Array deployment in Alaska and western Canada, with autonomous and telemetered stations occupying sites within large swaths of previously unmonitored and inaccessible terrain. The majority of Alaska TA stations collect weather data and a subset also include a detached soil temperature probe. As a result, data collected by the Alaska Transportable Array have been used to observe throughout the ‘spheres: the lithosphere (earthquakes, volcanoes, landslides), the cryosphere (sea ice), the hydrosphere (precipitation, fire preparation), the atmosphere and biosphere (weather forecasting, storm systems, bolides), and even into the magnetosphere (space weather).

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.

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.

Observations of tropospheric gravity waves (GWs) made by the new and extensive USArray Transportable Array (TA) barometric network located east of the Rockies, in the central and eastern United States and of stratospheric (30–40 km above sea level) GWs made by the Atmospheric Infrared Sounder (AIRS) are compared over a 5 year time span from 2010 through 2014. GW detections in the period band from 2 to 6 h made at the Earth's surface during the thunderstorm season from May through August each year exhibit the same broad spatial and temporal patterns as observed at stratospheric altitudes. At both levels, the occurrence frequency of GWs is higher at night than during the day and is highest to the west of the Great Lakes. Statistically significant correlations between the variance of the pressure at the TA, which is a proxy for GWs at ground level, with 8.1 μm brightness temperature measurements from AIRS and rain radar precipitation data, which are both proxies for convective activity, indicate that GWs observed at the TA are related to convective sources. There is little, if any, time lag between the two. Correlations between GWs in the stratosphere and at ground level are weaker, possibly due to the AIRS observational filter effect, but are still statistically significant at nighttime. We conclude that convective activity to the west of the Great Lakes is the dominant source of GWs both at ground level and within the stratosphere.

Mesoscale gravity waves were observed by barometers deployed as part of the USArray Transportable Array on 29 June 2011 near two mesoscale convective systems in the Great Plains region of the United States. Simultaneously, AIRS satellite data indicated stratospheric gravity waves propagating away from the location of active convection. Peak perturbation pressure values associated with waves propagating outside of regions where there was precipitation reached amplitudes close to 400 Pa at the surface. Here the origins of the waves and their relationship to observed precipitation are investigated with a specialized model study. Simulations with a 4-km resolution dry numerical model reproduce the propagation characteristics and amplitudes of the observed waves with a high degree of quantitative similarity despite the absence of any boundary layer processes, surface topography, or moist physics in the model. The model is forced with a three-dimensional, time-dependent latent heating/cooling field that mimics the latent heating inside the precipitation systems. The heating is derived from the network of weather radar precipitation observations. This shows that deep, intense latent heat release within the precipitation systems is the key forcing mechanism for the waves observed at ground level by the USArray. Furthermore, the model simulations allow for a more detailed investigation of the vertical structure and propagation characteristics of the waves. It is found that the stratospheric and tropospheric waves are triggered by the same sources, but have different spectral properties. Results also suggest that the propagating tropospheric waves may potentially remotely interact with and enhance active precipitation.

We have developed a novel method to detect and locate geophysical events that makes use of any sufficiently dense sensor network. This method is demonstrated using acoustic sensor data collected in 2013 at the USArray Transportable Array (TA). The algorithm applies Delaunay triangulation to divide the sensor network into a mesh of three-element arrays, called triads. Because infrasound waveforms are incoherent between the sensors within each triad, the data are transformed into envelopes, which are cross-correlated to find signals that satisfy a consistency criterion. The propagation azimuth, phase velocity and signal arrival time are computed for each signal. Triads with signals that are consistent with a single source are bundled as an event group. The ensemble of arrival times and azimuths of detected signals within each group are used to locate a common source in space and time. A total of 513 infrasonic stations that were active for part or all of 2013 were divided into over 2000 triads. Low (0.5-2 Hz) and high (2-8 Hz) catalogues of infrasonic events were created for the eastern USA. The low-frequency catalogue includes over 900 events and reveals several highly active source areas on land that correspond with coal mining regions. The high-frequency catalogue includes over 2000 events, with most occurring offshore. Although their cause is not certain, most events are clearly anthropogenic as almost all occur during regular working hours each week. The regions to which the TA is most sensitive vary seasonally, with the direction of reception dependent on the direction of zonal winds. The catalogue has also revealed large acoustic events that may provide useful insight into the nature of long-range infrasound propagation in the atmosphere.

Abstract The USArray Transportable Array (TA), a component of the National Science Foundation’s EarthScope Initiative, has proven to be a successful model for large-scale real-time monitoring networks. Approximately 400 stations are deployed simultaneously in the continental United States on a nominal Cartesian grid across an area of approximately 2,000,000 km2. Each station was originally designed to operate autonomously as a seismic observing platform capable of recording and transmitting data at 1 and 40 samples per second in real time. The expansion of onboard instrumentation to include surface atmospheric pressure sensors improved the USArray’s real-time capability in monitoring the atmosphere and weather phenomena at the same sample rates. Though not a traditional weather monitoring station, the combination of these seismic and pressure sensors at each TA station can contribute to the observation of surface weather phenomena and has facilitated broader-scale observational applications. Twenty-five TA stations have a Vaisala WXT520 weather station installed in order to create an observational array of “full meteorological” (full-met) stations. Meteorological phenomena have been recorded in high detail, including a data quality comparison between a pair of TA and National Weather Service (NWS) stations, a gust-front passage, rainfall measurements following a squall-line passage, and a near pass of a tornado by one station. Additional products have been constructed from the TA data for visualization and research purposes. The large spatial extent and station configuration of the TA network increases the probability for making high-resolution recordings of data from rare encounters with atmospheric events.