The April–May 2010 summit eruption of Eyjafjallajökull, Iceland, was recorded by 14 atmospheric infrasound sensor arrays at ranges between 1,700 and 3,700 km, indicating that infrasound from modest‐size eruptions can propagate for thousands of kilometers in atmospheric waveguides. Although variations in both atmospheric propagation conditions and background noise levels at the sensors generate fluctuations in signal‐to‐noise ratios and signal detectability, array processing techniques successfully discriminate between volcanic infrasound and ambient coherent and incoherent noise. The current global infrasound network is significantly more dense and sensitive than any previously operated network and signals from large volcanic explosions are routinely recorded. Because volcanic infrasound is generated during the explosive release of fluid into the atmosphere, it is a strong indicator that an eruption has occurred. Therefore, long‐range infrasonic monitoring may aid volcanic explosion detection by complementing other monitoring technologies, especially in remote regions with sparse ground‐based instrument networks.

This paper reviews recent progress toward understanding the dynamics of the middle atmosphere in the framework of the Atmospheric Dynamics Research InfraStructure in Europe (ARISE) initiative. The middle atmosphere, integrating the stratosphere and mesosphere, is a crucial region which influences tropospheric weather and climate. Enhancing the understanding of middle atmosphere dynamics requires improved measurement of the propagation and breaking of planetary and gravity waves originating in the lowest levels of the atmosphere. Inter-comparison studies have shown large discrepancies between observations and models, especially during unresolved disturbances such as sudden stratospheric warmings for which model accuracy is poorer due to a lack of observational constraints. Correctly predicting the variability of the middle atmosphere can lead to improvements in tropospheric weather forecasts on timescales of weeks to season. The ARISE project integrates different station networks providing observations from ground to the lower thermosphere, including the infrasound system developed for the Comprehensive Nuclear-Test-Ban Treaty verification, the Lidar Network for the Detection of Atmospheric Composition Change, complementary meteor radars, wind radiometers, ionospheric sounders and satellites. This paper presents several examples which show how multi-instrument observations can provide a better description of the vertical dynamics structure of the middle atmosphere, especially during large disturbances such as gravity waves activity and stratospheric warming events. The paper then demonstrates the interest of ARISE data in data assimilation for weather forecasting and re-analyzes the determination of dynamics evolution with climate change and the monitoring of atmospheric extreme events which have an atmospheric signature, such as thunderstorms or volcanic eruptions.

S U M M A R YSeismic arrays are employed in the global monitoring of earthquakes and explosions because of their superior ability to detect and estimate the direction of incident seismic arrivals. Traditional beamforming and f -k analysis require waveform semblance over the full array aperture and cannot be applied in many situations where signals are incoherent between sensors. The NORSAR and MJAR arrays are two primary IMS stations where this is the case for highfrequency regional phases. Large intersite distances and significant geological heterogeneity at these arrays result in waveform dissimilarity which precludes coherent array processing in the frequency bands with optimal SNR. Multitaper methods provide low variance spectral estimates over short time-windows and seismic arrivals can be detected on single channels using a non-linear spectrogram transformation which attains local maxima at times and frequencies characterized by an energy increase. This detection procedure requires very little a priori knowledge of the spectral content of the signal. The transformed spectrograms can be beamformed over large-aperture arrays or networks according to theoretical time-delays resulting in an incoherent detection system which does not require waveform semblance at any frequencies. We outline a real-time automatic detection system for regional phase arrivals on the NORSAR array and demonstrate how stable and accurate slowness and azimuth estimates can be obtained for quite marginal signals. In the case of partially coherent arrays, the procedure described may provide stable, if low resolution, estimates which can subsequently be refined using coherent processing over subsets of sensors. In particular, we illustrate how the spectrogram beamforming method facilitates a stable and accurate slowness estimate for the incoherent high-frequency Pn arrival at the MJAR array in Japan from the 2006 October 9 underground nuclear test in North Korea.

The receiver-to-source backazimuth of atmospheric infrasound signals is biased when cross-winds are present along the propagation path. Infrasound from 598 surface explosions from over 30 years in northern Finland is measured with high spatial resolution on an array 178 km almost due North. The array is situated in the classical shadow-zone distance from the explosions. However, strong infrasound is almost always observed, which is most plausibly due to partial reflections from stratospheric altitudes. The most probable propagation paths are subject to both tropospheric and stratospheric cross-winds, and our wave-propagation modelling yields good correspondence between the observed backazimuth deviation and cross-winds from the ERA-Interim reanalysis product.We demonstrate that atmospheric cross-winds can be estimated directly from infrasound data using propagation time and backazimuth deviation observations. We find these cross-wind estimates to be in good agreement with the ERA-Interim reanalysis.

S U M M A R YScattering and refraction of seismic waves can be exploited with empirical-matched field processing of array observations to distinguish sources separated by much less than the classical resolution limit. To describe this effect, we use the term 'superresolution', a term widely used in the optics and signal processing literature to denote systems that break the diffraction limit. We illustrate superresolution with Pn signals recorded by the ARCES array in northern Norway, using them to identify the origins with 98.2 per cent accuracy of 549 explosions conducted by closely spaced mines in northwest Russia. The mines are observed at 340-410 km range and are separated by as little as 3 km. When viewed from ARCES many are separated by just tenths of a degree in azimuth. This classification performance results from an adaptation to transient seismic signals of techniques developed in underwater acoustics for localization of continuous sound sources. Matched field processing is a potential competitor to frequency-wavenumber (FK) and waveform correlation methods currently used for event detection, classification and location. It operates by capturing the spatial structure of wavefields incident from a particular source in a series of narrow frequency bands. In the rich seismic scattering environment, closely spaced sources far from the observing array nonetheless produce distinct wavefield amplitude and phase patterns across the small array aperture. With observations of repeating events, these patterns can be calibrated over a wide band of frequencies (e.g. 2.5-12.5 Hz) for use in a power estimation technique similar to frequency-wavenumber analysis. The calibrations enable coherent processing at high frequencies at which wavefields normally are considered incoherent under a plane-wave model.