Infrasound as upper atmospheric monitor

Understanding and specification of the higher altitudes of the atmosphere with global coverage over all local times is hampered by the challenges of obtaining direct measurements in the upper atmosphere. Methods to measure the properties of the atmosphere above the stratopause is an active area of scientific research. In this thesis, we revisit the use of infrasound as a passive remote sensing technique for the upper atmosphere. Signals from the Tungurahua volcano in Ecuador are used to investigate the behavior of the upper atmosphere. Depending on the atmospheric conditions, stratospheric, mesospheric and thermospheric arrivals are observed during intervals of explosive volcanic activity. It is found that the travel times and dominant frequencies of the thermospheric arrivals exhibit a coherent variability with periods equal to those of the tidal harmonics. Theoretical predictions using atmospheric specifications show that the stratospheric arrivals are predicted within 1% of the observed value. For thermospheric arrivals, this error can be as high as 10%. The error in thermospheric celerities is found to be in accord with the typical uncertainty in upper atmospheric winds. Given the observed response of the infrasound celerities to upper atmospheric tidal variability, it is suggested that infrasound observations may be used as an additional source of information to constrain the atmospheric specifications in the upper atmosphere. We present corrected wind profiles that have been obtained by minimizing misfits in traveltime and source location using a Bayesian statistics grid search algorithm. Also, a Levenberg-Marquardt search algorithm is developed. Additionally, a new numerical method has been developed to solve the problem of infrasound propagation in a stratified medium with (high Mach number) background flow, based on a modal expansion. The underlying mathematics is by no means new and has been earlier described. This solution goes beyond the effective sound speed approximation, which is typically used in infrasound propagation modeling for computational efficiency reasons. Using the wide-angle high Mach number modal solution, it is shown that traveltimes and shadow zones are under predicted using the effective sound speed approximation, with increasing grazing angle and Mach number

Estimates of plume height from infrasound for regional volcano monitoring

Present efforts in volcano monitoring, particularly in Southeast Asia, rely on the combination of local data (generally gathered at less than 100 km from the volcano), and satellite remote sensing. While this combination has its strengths, there are still weaknesses that the use of ground-based remote sensing data - such as distant infrasound measurements - could help alleviate. Infrasound offers tools for detecting and characterizing volcanic plumes independent of cloud cover and time of day. Larger volcanic eruptions generate infrasound that is related to the plume and offers a unique view into eruption dynamics within the context of monitoring. Past research has demonstrated that infrasound can be used to estimate source parameters, such as the rate at which material is ejected from volcanic vents during eruptions; these are key input parameters into empirical and numerical models to estimate the height of volcanic plumes, atmospheric ash transport and dispersion. Here, we demonstrate the use of remote infrasound in estimating the height of volcanic plumes, including a case study on the May 30, 2014 plume from the volcano Sangeang Api in Indonesia. We were able to determine the plume height using infrasound gathered from 2000 to over 5000 km distance from the volcano. During the January 2020 eruption of Taal volcano in the Philippines, this method was applied to remote infrasound recorded 1650 km to the east. We show that our workflow can be implemented in near real-time, offering an effective tool for rapid plume height measurement, including associated uncertainties, when volcanic clouds are not visible from the ground or space

Sex-specific effects of wind on the flight decisions of a sexually-dimorphic soaring bird

1. In a highly dynamic airspace, flying animals are predicted to adjust foraging behaviour to variable wind conditions to minimize movement costs. 2. Sexual size dimorphism is widespread in wild animal populations, and for large soaring birds which rely on favourable winds for energy‐efficient flight, differences in morphology, wing loading and associated flight capabilities may lead males and females to respond differently to wind. However, the interaction between wind and sex has not been comprehensively tested. 3. We investigated, in a large sexually dimorphic seabird which predominantly uses dynamic soaring flight, whether flight decisions are modulated to variation in winds over extended foraging trips, and whether males and females differ. 4. Using GPS loggers we tracked 385 incubation foraging trips of wandering albatrosses Diomedea exulans , for which males are c . 20% larger than females, from two major populations (Crozet and South Georgia). Hidden Markov models were used to characterize behavioural states—directed flight, area‐restricted search (ARS) and resting—and model the probability of transitioning between states in response to wind speed and relative direction, and sex. 5. Wind speed and relative direction were important predictors of state transitioning. Birds were much more likely to take off (i.e. switch from rest to flight) in stronger headwinds, and as wind speeds increased, to be in directed flight rather than ARS. Males from Crozet but not South Georgia experienced stronger winds than females, and males from both populations were more likely to take‐off in windier conditions. 6. Albatrosses appear to deploy an energy‐saving strategy by modulating taking‐off, their most energetically expensive behaviour, to favourable wind conditions. The behaviour of males, which have higher wing loading requiring faster speeds for gliding flight, was influenced to a greater degree by wind than females. As such, our results indicate that variation in flight performance drives sex differences in time–activity budgets and may lead the sexes to exploit regions with different wind regimes

Infrasound as a cue for seabird navigation

Seabirds are amongst the most mobile of all animal species and spend large amounts of their lives at sea. They cross vast areas of ocean that appear superficially featureless, and our understanding of the mechanisms that they use for navigation remains incomplete, especially in terms of available cues. In particular, several large-scale navigational tasks, such as homing across thousands of kilometers to breeding sites, are not fully explained by visual, olfactory or magnetic stimuli. Low-frequency inaudible sound, i.e., infrasound, is ubiquitous in the marine environment. The spatio-temporal consistency of some components of the infrasonic wavefield, and the sensitivity of certain bird species to infrasonic stimuli, suggests that infrasound may provide additional cues for seabirds to navigate, but this remains untested. Here, we propose a framework to explore the importance of infrasound for navigation. We present key concepts regarding the physics of infrasound and review the physiological mechanisms through which infrasound may be detected and used. Next, we propose three hypotheses detailing how seabirds could use information provided by different infrasound sources for navigation as an acoustic beacon, landmark, or gradient. Finally, we reflect on strengths and limitations of our proposed hypotheses, and discuss several directions for future work. In particular, we suggest that hypotheses may be best tested by combining conceptual models of navigation with empirical data on seabird movements and in-situ infrasound measurements

Global quieting of high-frequency seismic noise due to COVID-19 pandemic lockdown measures

Human activity causes vibrations that propagate into the ground as high-frequency seismic waves. Measures to mitigate the COVID-19 pandemic caused widespread changes in human activity, leading to a months-long reduction in seismic noise of up to 50%. The 2020 seismic noise quiet period is the longest and most prominent global anthropogenic seismic noise reduction on record. While the reduction is strongest at surface seismometers in populated areas, this seismic quiescence extends for many kilometers radially and hundreds of meters in depth. This provides an opportunity to detect subtle signals from subsurface seismic sources that would have been concealed in noisier times and to benchmark sources of anthropogenic noise. A strong correlation between seismic noise and independent measurements of human mobility suggests that seismology provides an absolute, real-time estimate of population dynamics

Long-range atmospheric infrasound propagation from subsurface sources

In seismology and ocean acoustics, the interface with the atmosphere is typically represented as a free surface. Similarly, these interfaces are considered as a rigid surface for infrasound propagation. This implies that seismic or acoustic waves are not transmitted into the atmosphere from subsurface sources, and vice versa. Nevertheless, infrasound generated by subsurface sources has been observed. In this work, seismo-acoustic modeling of infrasound propagation from underwater and underground sources will be presented. The fast field program (FFP) is used to model the seismo-acoustic coupling between the solid earth, the ocean, and the atmosphere under the variation of source and media parameters. The FFP model allows for a detailed analysis of the seismo-acoustic coupling mechanisms in frequency-wavenumber space. A thorough analysis of the coupling mechanisms reveals that evanescent wave coupling and leaky surface waves are the main energy contributors to long-range infrasound propagation. Moreover, it is found that source depth affects the relative amplitude of the tropospheric and stratospheric phases, which allows for source depth estimation in the future.Applied Geophysics and Petrophysic

Assessing and optimizing the performance of infrasound networks to monitor volcanic eruptions

International audienceWe propose a numerical modeling technique based on a frequency-dependent attenuation relation to assess, quantify and optimize the performance of any arbitrary infrasound network to monitor explosive sources such as volcanic eruptions. Simulations are further enhanced by including realistic sources and propagation effects. We apply our approach to both hemispheres by considering the Euro-Mediterranean and the Eastern Australian regions. In these regions, we use quasi-permanent infrasound signals from Mt. Etna recorded in Tunisia and from Mt. Yasur recorded in New Caledonia. These well-instrumented volcanoes offer a unique opportunity to validate our attenuation model. In particular, accurate comparisons between near-and far-field recordings demonstrate the potential of the proposed methodology to remotely monitor volcanoes. A good agreement is found between modeled and observed results, especially when incorporating representative 10 m s −1 wind perturbations in the atmospheric specifications according to previous campaign measurements. To optimize the network layout in order to ensure the best monitoring of the volcanoes, we proceed through a grid search to find optimum locations of an additional array. We show that adding one array at an appropriate location in both regions under study could significantly improve detections half of the year. The application of the proposed methodology can provide in near real-time a realistic confidence level of volcanic eruption detections, useful to mitigate the risk of aircrafts encountering volcanic ash

The INFRA-EAR: A low-cost mobile multidisciplinary measurement platform for monitoring geophysical parameters

Geophysical studies and real-time monitoring of natural hazards, such as volcanic eruptions or severe weather events, benefit from the joint analysis of multiple geophysical parameters. However, typical geophysical measurement platforms still provide logging solutions for a single parameter, due to different community standards and the higher cost per added sensor. In this work, the Infrasound and Environmental Atmospheric data Recorder (INFRA-EAR) is presented, which has been designed as a low-cost mobile multidisciplinary measurement platform for geophysical monitoring. In particular, the platform monitors infrasound but concurrently measures barometric pressure, accelerations, and wind flow and uses the Global Positioning System (GPS) to position the platform. Due to its digital design, the sensor platform can be readily integrated with existing geophysical data infrastructures and be embedded in geophysical data analysis. The small dimensions and low cost per unit allow for unconventional, experimental designs, for example, high-density spatial sampling or deployment on moving measurement platforms. Moreover, such deployments can complement existing high-fidelity geophysical sensor networks. The platform is designed using digital micro-electromechanical system (MEMS) sensors embedded on a printed circuit board (PCB). The MEMS sensors on the PCB are a GPS, a three-component accelerometer, a barometric pressure sensor, an anemometer, and a differential pressure sensor. A programmable microcontroller unit controls the sampling frequency of the sensors and data storage. A waterproof casing is used to protect the mobile platform against the weather. The casing is created with a stereolithography (SLA) Formlabs 3D printer using durable resin. Thanks to low power consumption (9Wh over 25 d), the system can be powered by a battery or solar panel. Besides the description of the platform design, we discuss the calibration and performance of the individual sensors.</p

Extracting low signal-to-noise ratio events with the Hough transform from sparse array data

Low-frequency acoustic, i.e., infrasound, waves are measured by sparse arrays of microbarometers. Recorded data are processed by automatic detection algorithms based on array-processing techniques such as time-domain beam forming and f-k analysis. These algorithms use a signal-to-noise ratio (S/N) value as a detection criterion. In the case of high background noise or in the presence of multiple coinciding signals, the event's S/N decreases and can be missed by automatic processing. In seismology, detecting low-S/N events with geophone arrays is a well-known problem. Whether it is in global earthquake monitoring or reservoir microseismic activity characterization, detecting low-S/N events is needed to better understand the sources or the medium of propagation. We use an image-processing technique as a postprocessing step in the automatic detection of low S/N events. In particular, we consider the use of the Hough transform (HT) technique to detect straight lines in beam-forming results, i.e., a back azimuth (BA) time series. The presence of such lines, due to similar BA values, can be indicative of a low-S/N event. A statistical framework is developed for the HT parameterization, which includes defining a threshold value for detection as well as evaluating the false alarm rate. The method is tested on synthetic data and five years of recorded infrasound from glaciers. It is shown that the automatic detection capability is increased by detecting low-S/N events while keeping a low false-alarm rate.Applied Geophysics and Petrophysic