Augmenting heavy and power-hungry data collection equipment with lighter, smaller wireless sensor network nodes leads to faster, larger deployments. Arrays comprising dozens of wireless sensor nodes are now possible, allowing scientific studies that aren't feasible with traditional instrumentation. Designing sensor networks to support volcanic studies requires addressing the high data rates and high data fidelity these studies demand. The authors' sensor-network application for volcanic data collection relies on triggered event detection and reliable data retrieval to meet bandwidth and data-quality demands.

The implementation, characterization, and evaluation of a low-cost infrasound sensor developed at the Infrasound Laboratory at the New Mexico Institute of Mining and Technology (Infra-NMT) are described. This sensor is based on a commercial micromachined piezoresistive differential pressure transducer that uses a mechanical high-pass filter to reject low-frequency outband energy. The sensor features a low-noise, 2.02-mPa rms (0.5-2 Hz), 5.47-mPa rms (0.1-20 Hz), or 5.62-mPa rms (0.05-20 Hz), flat response between 0.01 and at least 40 Hz; inband sensitivity of 45.13 ± 0.23 /xV Pa"'; and a nominal linear range from -124.5 to +124.5 Pa. Intended for outdoor applications, the influence of thermal changes in the sensor's response has been minimized by using a thermal compensated pressure transducer powered by an ultralow drift (<5 ppm °C"') and noise {

[1] We use the continuous and intense ($10 7 W) infrasound produced by Volcan Villarrica (Chile) to invert for the local dynamic wind and temperature structure of the atmosphere. Infrasound arrays deployed in March 2011 at the summit (2826 m) and on the NNW flank ($8 km distant at 825 m) were used to track infrasound propagation times and signal power. We model an atmosphere with vertically varying temperature and horizontal winds and use propagation times (ranging from 23 to 24 s) to invert for horizontal slowness (2.75-2.94 s/km) and average effective sound speeds (328-346 m/s) for NNW propagating infrasound. The corresponding ratio of recorded acoustic power at proximal versus distal arrays was also variable (ranging between 0.15 to 1.5 for the peak 0.33-1 Hz infrasound band). Through application of geometrical ray theory in a uniform gradient atmosphere, these 'amplification factors' are modeled by effective sound speed lapse rates ranging from À15 to +4 m/s per km. NNW-projected wind speeds ranging from À20 m/s to +20 m/s at 2826 m and wind gradients ranging from À11 to +10 m/s per km are inferred from the difference between effective sound speed profiles and adiabatic sound speeds derived from local temperature observations. The sense of these winds is in general agreement with regional meteorological observations recorded with radiosondes. We suggest that infrasound probing can provide useful spatially averaged estimates of atmospheric wind structure that has application for both meteorological observation and volcanological plume dispersal modeling.

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Infrasound from a 60‐turbine wind farm was found to propagate to distances up to 90 km under nighttime atmospheric conditions. Four infrasound sensor arrays were deployed in central New Mexico in February 2014; three of these arrays captured infrasound from a large wind farm. The arrays were in a linear configuration oriented southeast with 13, 54, 90, and 126 km radial distances and azimuths of 166°, 119°, 113°, and 111° from the 60 1.6 MW turbine Red Mesa Wind Farm, Laguna Pueblo, New Mexico, USA. Peaks at a fundamental frequency slightly below 0.9 Hz and its harmonics characterize the spectrum of the detected infrasound. The generation of this signal is linked to the interaction of the blades, flow gradients, and the supporting tower. The production of wind‐farm sound, its propagation, and detection at long distances can be related to the characteristics of the atmospheric boundary layer. First, under stable conditions, mostly occurring at night, winds are highly stratified, which enhances the production of thickness sound and the modulation of other higher‐frequency wind turbine sounds. Second, nocturnal atmospheric conditions can create low‐altitude waveguides (with altitudes on the order of hundreds of meters) allowing long‐distance propagation. Third, night and early morning hours are characterized by reduced background atmospheric noise that enhances signal detectability. This work describes the characteristics of the infrasound from a quasi‐continuous source with the potential for long‐range propagation that could be used to monitor the lower part of the atmospheric boundary layer.