Academic literature on the topic 'Infrasound propagation modelling'

SUMMARY We propose a modelling technique to confidently estimate and optimize the performance of any infrasound network to remotely monitor sources of interest such as volcanic eruptions, while considering realistic atmospheric specifications along the propagation path, source frequency and noise levels at the station. To provide a more realistic picture of the network performance, we define a confidence level accounting for propagation and atmospheric uncertainties. Therefore, we consider ‘numerical’ uncertainties linked to the approximations made in the used propagation model, errors of the developed mathematical model and atmospheric uncertainties derived from measurement campaigns. In parallel, we perform a sensitivity analysis to determine how each input parameter contributes to the developed mathematical model output as well as to the attenuation model output. Such study is helpful for model simplification and uncertainty reduction by identifying, and thus paying more attention to the most influential model inputs. Below 1 Hz, the effect of ‘numerical’ errors on network performance modelling dominates. The same situation is observed during strong and stable downwind stratospheric winds along propagation paths. Conversely, when propagation occurs upwind, atmospheric uncertainties become predominant as the frequency increases. This method is then applied to assess the performance of the International Monitoring System (IMS) infrasound network in the Euro-Mediterranean and the Southeast Asian regions. We highlight a frequency, seasonal and spatial dependence of uncertainties in the modelling. Below 1 Hz, large errors are predicted in the shadow zone but the overall error is less than 20 dB. Above 1 Hz, errors with same order of magnitude are also observed, when strong stratospheric jets prevail. But during weak stratospheric duct, uncertainties associated to the modelled attenuation may exceed 30 dB. Such studies lead to significant improvement in assessing detection capability of infrasound network, which is of great interest for monitoring artificial or natural explosive sources like volcanic eruption. In particular this work will contribute into designing and prioritizing maintenance of any given infrasound network, in order to provide even better and more accurate predictions.

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.

Azimuthal variation in expected infrasonic signal strength is often modelled using Nx2D finite-frequency acoustic propagation models. Such simulations frequently exhibit rapid changes in transmission loss (>30 dB across 5°) at the lateral edges of stratospheric propagation ducts, due to the sensitivity of acoustic ducting to the along-path windspeed. The inclusion of microbarometers in the USArray Transportable Array, with an inter-station separation of ∼70 km, has provided improved resolution across the lateral extent of tropospheric and stratospheric ducts within which infrasound is propagated over local and near-regional distances (10s to 100s km). We analyse signals from two explosions that generated infrasound across a broad swath of USArray microbarometers. Signals from the October 2012 Camp Minden Ammunition Plant explosion, Louisiana, show smoothly varying amplitudes across the stratospheric duct edge while those from the October 2011 Atchison Grain Elevator explosion, Kansas, exhibit less azimuthal variation. These signals provide a basis for comparison with current numerical modelling methods. Understanding infrasonic amplitudes at the lateral duct edge is important for both accurate signal interpretation from events of interest and for detection capability assessments of infrasound sensor networks. UK Ministry of Defence © Crown Owned Copyright 2022/AWE

SUMMARY North Korea conducted its sixth underground nuclear explosion test (${m_\mathrm{ b}}$ 6.3) on 2017 September 3. The underground explosion produced substantial low-frequency atmospheric waves, which were detected by infrasound arrays located up to a distance of 566 km. These infrasound waves are formed by the conversion of seismic energy to acoustic energy across the lithosphere–atmosphere interface. While infrasound records at regional distances produce estimates of ground motion amplitude over spatially extended regions covering about 26 500 km2, 3-D full seismo-acoustic simulations within the lithosphere and atmosphere provide quantitative information about seismo-acoustic energy partitioning. Our results demonstrate the capability of remote infrasound observations combined with 3-D propagation modelling to further develop discrimination methods for underground sources. These results contribute to enhance the confidence of source identification and characterization in nuclear test monitoring research, which is essential for the enforcement of the Comprehensive Nuclear-Test-Ban Treaty.

Abstract. Infrasound generated during a seismic event upon reaching the ionospheric heights possesses the ability to perturb the ionosphere. Detailed modelling investigation considering 1-D dissipative linear dynamics, however, indicates that the magnitude of ionospheric perturbation strongly depends on the magnetic field inclination. Physics-based SAMI2 model codes have been utilized to simulate the ionosphere perturbations that are generated due to the action of the vertical wind perturbations associated with the seismic infrasound. The propagation of the seismic energy and the vertical wind perturbations associated with the infrasound in the model has been considered to be symmetric about the epicentre in the north–south directions. Ionospheric response to the infrasound wind, however, has been highly asymmetric in the model simulation in the north–south directions. This strong asymmetry is related to the variation in the inclination of the Earth's magnetic field north and south of the epicentre. Ionospheric monitoring generally provides an efficient tool to infer the crustal propagation of the seismic energy. However, the results presented in this paper indicate that the mapping between the crustal process and the ionospheric response is not a linear one. These results also imply that the lithospheric behaviour during a seismic event over a wide zone in low latitudes can be estimated through ionospheric imaging only after factoring in the magnetic field geometry. Keywords. Atmospheric composition and structure (pressure, density, and temperature) – history of geophysics (atmospheric sciences) – ionosphere (ionosphere–atmosphere interactions)

Describing the statistics of gravity wave (GW) fields represents a major motivation for both current research on atmospheric GWs and long-range infrasound propagation. In practice, the probability density functions (PDF) of the momentum fluxes are estimated combining observations, numerical modelling, and theory. Numerical models (such as WRF) show that the PDFs vary in a robust way relative to the background local wind speed. For non-orographic GWs, these PDFs are approximated as lognormal distributions, with characteristics found to depend on the background wind speed. Studies show that some trends are not observed using a state-of-the-art stochastic parameterization of GWs, unless the phase velocities of GW sources (essentially tropospheric) are dramatically changed. As the vertical wavelength and the phase velocity are related to each other, such changes also affect the interaction between infrasound and lower-stratospheric GWs. Consequently, significant efforts have been made to use ground-based acoustic sensors for characterizing the GW sources, including the use of neural networks. This approach provides a promising way to describe the statistics of GW sources from ground-truth infrasound events and an additional constraint to tune stochastic parameterizations of GWs.

We discuss the use of reverse time migration (RTM) with dense seismic networks for the detection and location of sources of atmospheric infrasound. Seismometers measure the response of the Earth's surface to infrasound through acoustic-to-seismic coupling. RTM has recently been applied to data from the USArray network to create a catalogue of infrasonic sources in the western US. Specifically, several hundred sources were detected in 2007–2008, many of which were not observed by regional infrasonic arrays. The influence of the east–west stratospheric zonal winds is clearly seen in the seismic data with most detections made downwind of the source. We study this large-scale anisotropy of infrasonic propagation, using a winter and summer source in Idaho. The bandpass-filtered (1–5 Hz) seismic waveforms reveal in detail the two-dimensional spread of the infrasonic wavefield across the Earth's surface within approximately 800 km of the source. Using three-dimensional ray tracing, we find that the stratospheric winds above 30 km altitude in the ground-to-space (G2S) atmospheric model explain well the observed anisotropy pattern. We also analyse infrasound from well-constrained explosions in northern Utah with a denser IRIS PASSCAL seismic network. The standard G2S model correctly predicts the anisotropy of the stratospheric duct, but it incorrectly predicts the dimensions of the shadow zones in the downwind direction. We show that the inclusion of finer-scale structure owing to internal gravity waves infills the shadow zones and predicts the observed time durations of the signals. From the success of this method in predicting the observations, we propose that multipathing owing to fine scale, layer-cake structure is the primary mechanism governing propagation for frequencies above approximately 1 Hz and infer that stochastic approaches incorporating internal gravity waves are a useful improvement to the standard G2S model for infrasonic propagation modelling.

Anti-resonant hollow core fibers (AR-HCFs) provide a promising solution for photothermal spectroscopy and photoacoustic imaging applications. Here, the AR-HCF serves as a micro platform to induce the photothermal/photoacoustic effect. Since the Bragg structure can induce multiple AR effects compared with the general AR-HCF, we proposed a novel device, the AR-BHCF (AR-HCF with Bragg cladding), to enhance the excitation efficiency. The simulation and experimental results validate that the AR-BHCF dominates in having a stronger ability to confine the optical field in the air core indeed. Then, the acoustic signal stimulated by the photoacoustic effect will propagate along with the fiber axial, and part of it will penetrate out of the AR-BHCF. The results revealed that the transmission bandwidth of the acoustic wave in the AR-BHCF ranges from 1 Hz to 1 MHz, covering infrasound to ultrasound. In particular, a constant coefficient of 0.5 exists in the acoustic wave fading process, related to the propagation frequency and time. The acoustic signal can be monitored in real time, assisted by the ultra-highly sensitive sensor head. Therefore, BHCF-based devices combined with photoacoustic techniques may accelerate their sensing applications. Meanwhile, this scheme shines a light on the theoretical foundation of novel short-haul distributed acoustic sensing.

Les ondes infrasonores, aussi appelées infrasons, sont des ondes acoustiques comprises entre 0 et 20 Hz émises par une large variété de sources. Leurs basses fréquences font que les gradients verticaux de vent et de température conduisent à la formation de guides d'ondes au sein desquels ces ondes peuvent se propager sur des milliers de kilomètres en étant très peu atténuées. Comme ce type de propagation est intrinsèquement lié à la circulation atmosphérique, ces ondes peuvent être utilisées comme traceurs. La circulation générale dans la stratosphère et la mésosphère, que l'on regroupe sous le terme générique de moyenne atmosphère, constitue pour les infrasons les guides d'ondes les plus efficaces. On se propose ici d'exploiter les signaux infrasons reçus au sol pour apporter de l'information nouvelle sur la circulation de la moyenne atmosphère. Elle pourra être utilisée afin d'améliorer l'initialisation des modèles de prévisions numériques du temps (PNT). Pour qu'une observation puisse être assimilée, il est nécessaire de définir un opérateur d'observation, capable de la simuler à partir des prévisions du modèle. L'objectif de cette thèse est d'examiner comment assimiler les infrasons en construisant un opérateur d'observation dédié. Après avoir présenté l'état de connaissance sur la circulation atmosphérique et le principe de l'assimilation de données, nous examinons les données infrasons du système de surveillance international. Ce système est maintenu par l'Organisation du Traité d'Interdiction Complète des Essais nucléaires (OTICE). Un opérateur d'observation compatible avec les besoins de l'assimilation peut être construit à partir d'un modèle de propagation en tirant parti de méthodes de propagation rapide et des sources naturelles connues comme les volcans. Compte tenu des limitations associées à ces méthodes et ces sources, il est difficile de construire un opérateur d'observation permettant l'assimilation directe des données infrasons. Nous proposons alors de résoudre le problème inverse pour obtenir des profils verticaux de vent et de température cohérents avec les signaux infrasons mesurés. Dans un premier temps nous avons mis en évidence la nécessité d'ajouter une perturbation aux profils atmosphériques pour restituer des signaux acoustiques réels par tracés de rayons ou décomposition modale. Ensuite, dans le cadre d'une atmosphère simplifiée à deux degrés de liberté et des signaux synthétiques, nous avons examiné la capacité des méthodes locales d'optimisation à estimer la perturbation atmosphérique minimisant l'écart entre les signaux modélisés et observés. Les résultats de cette étude montrent la difficulté d'obtenir une perturbation optimale sans information a priori sur celle-ci. Ce constat nous a amené à développer une approche bayésienne, en prenant pour a priori un ensemble d'analyses et de prévisions à courte échéance du modèle global de PNT de Météo-France. On utilise l'écart entre les résultats de simulations par un code de tracés de rayons et les détections infrasons pour évaluer la vraisemblance de chacun des membres de l'ensemble. Cette méthode a été évaluée sur une base de détections de signaux infrasons issus des éruptions du Mont Etna en mai 2016. Nous montrons que cette méthode permet de sélectionner les membres de l'ensemble les plus vraisemblables, et ainsi fournir des profils atmosphériques, en accord avec les infrasons observés. Ils pourront ensuite être considérés comme des pseudo-observations dans un système d'assimilation de données
Infrasounds are acoustic waves between 0 and 20 Hz emitted by a wide variety of sources. Due to their low frequencies, vertical gradients of winds and temperature lead to the formation of waveguides in which they can propagate over thousands of kilometers with little attenuation. Since this type of propagation is intrinsically linked to the atmospheric circulation, these waves can be used as tracers. The general circulation in the stratosphere and the mesosphere, which forms the middle atmosphere, provides the most efficient acoustic waveguides. It is proposed here to use ground-based infrasound signals to provide new information on the circulation of the middle atmosphere. It can be used to improve the initialization of numerical weather prediction (NWP) models. For an observation to be assimilated, it is necessary to define an observation operator, able to simulate it from model predictions. The aim of this thesis is to examine how to assimilate infrasounds by designing a dedicated observation operator. After presenting the state of knowledge on atmospheric circulation and the principle of data assimilation, we examine the infrasound data of the international monitoring system. This system is maintained by the Comprehensive Nuclear Test Ban Treaty Organization (CTBTO). An observation operator compatible with the needs of assimilation can be designed from a propagation model by taking advantage of fast propagation methods and well-known natural sources such as volcanoes. Given the limitations associated with these methods and sources, it is difficult to design an observation operator allowing the direct assimilation of infrasound data. We propose then to solve the inverse problem by retrieving vertical profiles of winds and temperature consistent with the recorded infrasound signals. Firstly, we have highlighted the need to superimpose a disturbance onto the atmospheric profiles in order to simulate real acoustic signals using ray tracing or modal decomposition methods. Then, within the frame of a simplified atmosphere with two degrees of freedom and simulated signals, we examined the ability of local optimization methods to estimate the atmospheric disturbance minimizing the discrepancies between modelled and observed signals. The results of this study show the difficulty in obtaining an optimal disturbance without prior information on it. This led us to develop a Bayesian approach, taking as prior information an ensemble of analyzes and short-term forecasts of the Météo-France global NWP model. The differences between the simulation results from a ray tracing code and the infrasound measurements are used to compute the likelihood of each member of the ensemble. This method was assessed using infrasound signals emitted by Mount Etna eruptions during May 2016. We show that this method allows to select the most likely members of the ensemble, and thus to provide atmospheric profiles, in agreement with observed infrasounds. These profiles could then be considered as pseudo-observations in a data assimilation system