Advances in Infrasonic Remote Sensing Methods

Assink, Jelle; Smets, Pieter; Marcillo, Omar; Weemstra, Cornelis; Lalande, Jean-Marie; Waxler, Roger; Evers, Läslo

doi:10.1007/978-3-319-75140-5_18

Cited by 29 publications

(17 citation statements)

References 70 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Pioneering works on the exploitation of infrasound to probe the atmosphere include Groves (1956), Donn and Rind (1972) and Rind et al (1973). More recent publications report on the development of inversion approaches to retrieve corrections to wind and temperature model profiles using using atmospheric infrasound recordings (Le Pichon et al, 2005b,a;Drob et al, 2010;Lalande et al, 2012;Assink et al, 2013Assink et al, , 2019. Moreover, several works report on monitoring the stratospheric polar vortex and the evaluation of sudden stratospheric warming forecasts using atmospheric infrasound datasets, see Smets et al (2019Smets et al ( , 2016 and the references therein.…”

Section: Introductionmentioning

confidence: 99%

Estimating tropospheric and stratospheric winds using infrasound from explosions

Blixt

Näsholm

Gibbons

et al. 2019

The Journal of the Acoustical Society of America

View full text Add to dashboard Cite

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.

show abstract

Section: Introductionmentioning

confidence: 99%

Estimating tropospheric and stratospheric winds using infrasound from explosions

Blixt

Näsholm

Gibbons

et al. 2019

The Journal of the Acoustical Society of America

View full text Add to dashboard Cite

show abstract

“…These data have been used to directly measure gravity waves in the atmosphere (de Groot‐Hedlin et al., 2014), phenomena that occur at sufficiently fine spatiotemporal scales that they are not resolved in state‐of‐the‐art atmospheric models. The observation of atmospheric ground motions thus can provide direct information on the state of the atmosphere, through measurements of gravity waves and of infrasound waves, which can be used to probe the atmosphere at altitudes that are poorly sampled with other technologies (Assink et al., 2019). At very dense spatial resolutions, the study of a nodal seismic data set at Sage Brush Flats in California has related spatial variations in wind‐generated ground motions to effects of vegetation and structures (C. W. Johnson et al., 2019).…”

Section: Science Enabled By Big Data Seismologymentioning

confidence: 99%

Big Data Seismology

Arrowsmith

Trugman

MacCarthy

et al. 2022

Reviews of Geophysics

View full text Add to dashboard Cite

The discipline of seismology is based on observations of ground motion that are inherently undersampled in space and time. Our basic understanding of earthquake processes and our ability to resolve 4D Earth structure are fundamentally limited by data volume. Today, Big Data Seismology is an emergent revolution involving the use of large, data‐dense inquiries that is providing new opportunities to make fundamental advances in these areas. This article reviews recent scientific advances enabled by Big Data Seismology through the context of three major drivers: the development of new data‐dense sensor systems, improvements in computing, and the development of new types of techniques and algorithms. Each driver is explored in the context of both global and exploration seismology, alongside collaborative opportunities that combine the features of long‐duration data collections (common to global seismology) with dense networks of sensors (common to exploration seismology). The review explores some of the unique challenges and opportunities that Big Data Seismology presents, drawing on parallels from other fields facing similar issues. Finally, recent scientific findings enabled by dense seismic data sets are discussed, and we assess the opportunities for significant advances made possible with Big Data Seismology. This review is designed to be a primer for seismologists who are interested in getting up‐to‐speed with how the Big Data revolution is advancing the field of seismology.

show abstract

“…In addition to prospective numerical weather prediction improvements, the suggested vespagram-based approach may be applied in multi-technology studies of atmospheric dynamics, for example initiatives building on the Atmospheric dynamics Research InfraStructure in Europe (ARISE) projects (Blanc et al, 2018(Blanc et al, , 2019. These aim at harvesting from synergies between ground-based infrasound observations, radar and lidar systems, as well as airglow and satellite observations to monitoring the middle atmosphere (Chunchuzov et al, 2015;Le Pichon et al, 2015;Blanc et al, 2018;Hupe et al, 2019;Smets et al, 2019;Hibbins et al, 2019;Assink et al, 2019; Le Pichon et al, 2019).…”

Section: 2)mentioning

confidence: 99%

Microbarom radiation and propagation model assessment using infrasound recordings: a vespagram-based approach

Vorobeva

Carlo

Pichon

et al. 2020

Preprint

View full text Add to dashboard Cite

Abstract. This study investigates the use of a vespagram-based approach as a tool for multi-directional comparison between simulated microbarom soundscapes and infrasound data recorded at ground-based array stations. Data recorded at the IS37 station in northern Norway during 2014–2019 have been processed to generate vespagrams (velocity spectral analysis) for five frequency bands between 0.1 and 0.6 Hz. The back-azimuth resolution between vespagrams and a microbarom model is harmonized by smoothing the modelled soundscapes along the back-azimuth axis with a kernel corresponding to the frequency-dependent array resolution. An estimate of similarity between the output of a microbarom radiation and propagation model and infrasound observations is then generated based on the image processing approach of mean-square difference. The analysis revealed that vespagrams can monitor seasonal variations in the microbarom azimuth distribution, amplitude, and frequency, as well as changes during sudden stratospheric warming. The vespagram-based approach is computationally inexpensive, can uncover microbarom source variability, and has potential for near-real-time stratospheric diagnostics and atmospheric model assessment.

show abstract

Advances in Infrasonic Remote Sensing Methods

Cited by 29 publications

References 70 publications

Estimating tropospheric and stratospheric winds using infrasound from explosions

Estimating tropospheric and stratospheric winds using infrasound from explosions

Big Data Seismology

Microbarom radiation and propagation model assessment using infrasound recordings: a vespagram-based approach

Contact Info

Product

Resources

About