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Abstract Records of pressure variations on seismographs were historically considered unwanted noise; however, increased deployments of collocated seismic and acoustic instrumentation have driven recent efforts to use this effect induced by both wind and anthropogenic explosions to invert for near-surface Earth structure. These studies have been limited to shallow structure because the pressure signals have relatively short wavelengths (<∼300 m). However, the 2022 eruption of Hunga Tonga–Hunga Ha’apai (also called “Hunga”) volcano in Tonga generated rare, globally observed, high-amplitude infrasound signals with acoustic wavelengths of tens of kilometers. In this study, we examine the acoustic-to-seismic coupling generated by the Hunga eruption across 82 Global Seismographic Network (GSN) stations and show that ground motion amplitudes are related to upper (0 to ∼5 km) crust material properties. We find high (>0.8) correlations between pressure and vertical component ground motion at 83% of the stations, but only 30% of stations show this on the radial component, likely due to complex tilt effects. We use average elastic properties in the upper 5.2 km from the CRUST1.0 model to estimate vertical seismic/acoustic coupling coefficients (SV/A) across the GSN network and compare these to recorded observations. We exclude many island stations from these comparisons because the 1° resolution of the CRUST1.0 model places a water layer below these stations. Our simple modeling can predict observed SV/A within a factor of 2 for 94% of the 51 non-island GSN stations with high correlations between pressure and ground motion. These results indicate that analysis of acoustic-to-seismic coupling from the eruption could be used to place additional constraints on crustal structure models at stations with collocated seismic and pressure sensors. Ultimately, this could improve tomographic imaging models, which rely on methods that are sensitive to local structure. 

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.

 

Characteristics of atmosphere‐generated seismic noise below 0.05 Hz are investigated when surface pressure is large. In this paper, large pressure means pressure power spectral density exceeding 100 Pa²/Hz (at 0.01 Hz). We discuss three main points. The first point is existence of two frequency ranges that show high coherence between co‐located pressure and vertical seismic data. The lower frequency (LF) range is broad and its upper bound is about 0.002 Hz. The higher frequency (HF) range is bounded between about 0.01 and 0.05 Hz. Phase difference between pressure and vertical displacement is different for the two ranges. The LF range shows phase difference of zero, and the HF range shows phase difference of 180°. The second point is on the excitation mechanism in the HF range. Using theory and data, we show that seismic noise in the HF range is primarily excited by wind‐related pressure. When pressure is high, wind speeds become high, and wind directions become unidirectional. In such a case, a deterministic, moving pressure‐source by Sorrells (1971,https://doi.org/10.1111/j.1365-246X.1971.tb03383.x) captures the characteristics of data better than stochastic source models. The third point is on the cause of phase differences between the LF range and the HF range. The root cause is that, even after removing the instrument response, vertical seismic data contain effects from gravity and Earth rotation. Gravity effects become significant for frequencies below 0.005 Hz and create discrepancies between deconvolved vertical displacements and true vertical ground displacements. Phase‐difference results are naturally explained by it.

 

Although microseisms have been observed for more than 100 years, the precise locations of their excitation sources in the oceans are still elusive. Underwater Distributed Acoustic Sensing (DAS) brings new opportunities to study microseism generation mechanisms. Using DAS data off the coast of Valencia, Spain, and applying a cross‐correlation approach, we show that the sources of high‐frequency microseisms (0.5–2 Hz) are confined between 7 and 27 km from the shore, where the water depth varies from 25 to 100 m. Over time, we observe that these sources move quickly along narrow areas, sometimes within a few kilometers. Our methodology applied to DAS data allows us to characterize microseisms with a high spatiotemporal resolution, providing a new way of understanding these global and complex seismic phenomena happening in the oceans.