An official website of the United States government
Abstract A high‐sensitivity pressure sensor was deployed as part of the Mars Interior Exploration using Seismic Investigations, Geodesy and Heat Transport lander on Elysium Planitia in November 2018. We use pressure records from 1 October to 31 December 2019 (Sol 301–389) for frequencies between 0.1 and 0.5 Hz to infer relative sound‐speed changes in the Martian atmosphere using the autocorrelation infrasound interferometry method. We find that relative sound‐speed changes are up to ±15%, follow a similar pattern to Martian‐daily variations of atmospheric temperature and horizontal wind velocity, and are similar to those inferred from in‐situ observations and Martian climatology. The relative sound‐speed changes and horizontal wind speed variations are synchronous, while temperature peaks ∼1.88 hr after these time series. The strong and continuous emergence of coherent phases in the autocorrelation codas suggests the presence of continuous infrasound on Mars.
more »
« less
Autocorrelation Infrasound Interferometry
Abstract Seismic and infrasound multistation ambient‐noise interferometry has been widely used to infer ground and atmospheric properties, and single‐station and autocorrelation seismic interferometry has also shown potential for characterizing Earth structure at multiple scales. We extend autocorrelation seismic interferometry to ambient atmospheric infrasound recordings that contain persistent local noise from waterfalls and rivers. Across a range of geographic settings, we retrieve relative sound‐speed changes that exhibit clear diurnal oscillations consistent with temperature and wind variations. We estimate ambient air temperatures from variations in relative sound speeds. The frequency band from 1 to 2 Hz appears most suitable to retrieve weather parameters as nearby waterfalls and rivers may act as continuous and vigorous sources of infrasound that help achieve convergence of coherent phases in the autocorrelation codas. This frequency band is also appropriate for local sound‐speed variations because it has infrasound with wavelengths of ∼170–340 m, corresponding to a typical atmospheric boundary layer height. After applying array analysis to autocorrelation functions derived from a three‐element infrasound array, we find that autocorrelation codas are composed of waves reflected off nearby topographic features, such as caldera walls. Lastly, we demonstrate that autocorrelation infrasound interferometry offers the potential to study the atmosphere over at least several months and with a fine time resolution.
more »
« less
- Award ID(s):
- 1847736
- PAR ID:
- 10359862
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Solid Earth
- Volume:
- 126
- Issue:
- 4
- ISSN:
- 2169-9313
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract Ambient infrasound noise contains an abundance of information that is typically overlooked due to limitations of typical infrasound arrays. To evaluate the ability of large‐N infrasound arrays to identify weak signals hidden in background noise, we examine data from a 22‐element array in central Idaho, USA, spanning 58 days using a standard beamforming method. Our results include nearly continuous detections of diverse weak signals from infrasonic radiators, sometimes at surprising distances. We observe infrasound from both local (8 km) and distant (195 km) waterfalls. Thunderstorms and earthquakes are also notable sources, with distant thunderstorm infrasound observed from ∼800 to 900 km away. Our findings show that large‐N infrasound arrays can detect very weak signals below instrument and environmental noise floors, including from multiple simultaneous sources, enabling new infrasound monitoring applications and helping map the composition of background noise wavefields.more » « less
-
ABSTRACT Earthquakes generate infrasound in multiple ways. Acoustic coupling at the surface from vertical seismic velocity, termed local infrasound, is often recorded by infrasound sensors but has seen relatively little study. Over 140 infrasound stations have recently been deployed in Alaska. Most of these stations have single sensors, rather than arrays, and were originally installed as part of the EarthScope Transportable Array. The single sensor nature, paucity of ground-truth signals, and remoteness makes evaluating their data quality and utility challenging. In addition, despite notable recent advances, infrasound calibration and frequency response evaluation remains challenging, particularly for large networks and retrospective analysis of sensors already installed. Here, we examine local seismoacoustic coupling on colocated seismic and infrasound stations in Alaska. Numerous large earthquakes across the region in recent years generated considerable vertical seismic velocity and local infrasound that were recorded on colocated sensors. We build on previous work and evaluate the full infrasound station frequency response using seismoacoustic coupled waves. By employing targeted signal processing techniques, we show that a single seismometer may be sufficient for characterizing the response of an entire nearby infrasound array. We find that good low frequency (<1 Hz) infrasound station response estimates can be derived from large (Mw>7) earthquakes out to at least 1500 km. High infrasound noise levels at some stations and seismic-wave energy focused at low frequencies limit our response estimates. The response of multiple stations in Alaska is found to differ considerably from their metadata and are related to improper installation and erroneous metadata. Our method provides a robust way to remotely examine infrasound station frequency response and examine seismoacoustic coupling, which is being increasingly used in airborne infrasound observations, earthquake magnitude estimation, and other applications.more » « less
-
Seismic imaging and monitoring of the near-surface structure are crucial for the sustainable development of urban areas. However, standard seismic surveys based on cabled or autonomous geophone arrays are expensive and hard to adapt to noisy metropolitan environments. Distributed acoustic sensing (DAS) with pre-existing telecom fiber optic cables, together with seismic ambient noise interferometry, have the potential to fulfill this gap. However, a detailed noise wavefield characterization is needed before retrievingcoherent waves from chaotic noise sources. We analyze local seismic ambient noise by tracking five-month changes in signal-to-noise ratio (SNR) of Rayleigh surface wave estimated from traffic noise recorded by DAS along the straight university campus busy road. We apply the seismic interferometry method to the 800 m long part of the Penn State Fiber-Optic For Environment Sensing (FORESEE) array. We evaluate the 160 virtual shot gathers (VSGs) by determining the SNR using the slant-stack technique. We observe strong SNR variations in time and space. We notice higher SNR for virtual source points close to road obstacles. The spatial noise distribution confirms that noise energy focuses mainly on bumps and utility holes. We also see the destructive impact of precipitation, pedestrian traffic, and traffic along main intersections on VSGs. A similar processing workflow can be applied to various straight roadside fiber optic arrays in metropolitan areas.more » « less
-
Abstract. The International Monitoring System (IMS) was established in the late 1990sfor verification of the Comprehensive Nuclear-Test-Ban Treaty (CTBT). Uponcompletion, 60 infrasound stations distributed over the globe will monitorthe Earth's atmosphere for low-frequency pressure waves. In this study, wepresent advanced infrasound data products of the 53 currently certified IMSinfrasound stations for atmospheric studies and civilian applications. Forthis purpose, 18 years of raw IMS infrasound waveform data (2003–2020) were reprocessed using the Progressive Multi-Channel Correlation (PMCC) method. A one-third octave frequency band configuration between 0.01 and 4 Hz was chosen to run this array-processing algorithm which detects coherent infrasound waves within the background noise. From the comprehensive detection lists, four products were derived for each of the certified 53 IMS infrasound stations. The four products cover different frequency ranges and are provided at the following different temporal resolutions: a very low-frequency set (0.02–0.07 Hz, 30 min; https://doi.org/10.25928/bgrseis_bblf-ifsd, Hupe et al., 2021a), two so-called microbarom frequency sets – covering both the lower (0.15–0.35 Hz, 15 min; https://doi.org/10.25928/bgrseis_mblf-ifsd, Hupe et al., 2021b) and a higher (0.45–0.65 Hz, 15 min; https://doi.org/10.25928/bgrseis_mbhf-ifsd, Hupe et al., 2021c) part – named after the dominant ambient noise of interacting ocean waves that are quasi-continuously detected at IMS stations, and observations with center frequencies of 1 to 3 Hz (5 min), called the high-frequency product (https://doi.org/10.25928/bgrseis_bbhf-ifsd, Hupe et al., 2021d). Within these frequency ranges and time windows, the dominant repetitive signal directions are summarized. Along with several detection parameters, calculated quantities for assessing the relative quality of the products are provided. The validity of the data products is demonstrated through example case studies of recent events that produced infrasound detected at IMS infrasound stations and through a global assessment and summary of the products. The four infrasound data products cover globally repeating infrasound sources such as ocean ambient noise or persistently active volcanoes, which have previously been suggested as sources for probing the winds in the middle atmosphere. Therefore, our infrasound data products open up the IMS observations also to user groups who do not have unconstrained access to IMS data or who are unfamiliar with infrasound data processing using the PMCC method. These types of data products could potentially serve as a basis for volcanic eruption early warning systems in the future.more » « less
