The 15 January 2022 climactic eruption of Hunga volcano, Tonga, produced an explosion in the atmosphere of a size that has not been documented in the modern geophysical record. The event generated a broad range of atmospheric waves observed globally by various ground-based and spaceborne instrumentation networks. Most prominent was the surface-guided Lamb wave (≲0.01 hertz), which we observed propagating for four (plus three antipodal) passages around Earth over 6 days. As measured by the Lamb wave amplitudes, the climactic Hunga explosion was comparable in size to that of the 1883 Krakatau eruption. The Hunga eruption produced remarkable globally detected infrasound (0.01 to 20 hertz), long-range (~10,000 kilometers) audible sound, and ionospheric perturbations. Seismometers worldwide recorded pure seismic and air-to-ground coupled waves. Air-to-sea coupling likely contributed to fast-arriving tsunamis. Here, we highlight exceptional observations of the atmospheric waves.

Researchers monitor southwest Greenland’s ice sheet mass changes by measuring seismic velocity variations in Greenland’s crust.

SUMMARY. Using ambient seismic noise for imaging subsurface structure dates back to the development of the spatial autocorrelation (SPAC) method in the 1950s.

We conducted two-dimensional continuous multi-offset georadar surveys on Bench Glacier, south-central Alaska, USA, to measure the distribution of englacial water. We acquired data with a multichannel 25 MHz radar system using transmitter–receiver offsets ranging from 5 to 150 m. We towed the radar system at 5–10 kmh^–1 with a snow machine with transmitter/receiver positions established by geodetic-grade kinematic differentially corrected GPS (nominal 0.5 m trace spacing). For radar velocity analyses, we employed reflection tomography in the pre-stack depth-migrated domain to attain an estimated 2% velocity uncertainty when averaged over three to five wavelengths. We estimated water content from the velocity structure using the complex refractive index method equation and use a three-phase model (ice, water, air) that accounts for compression of air bubbles as a function of depth. Our analysis produced laterally continuous profiles of glacier water content over several kilometers. These profiles show a laterally variable, stratified velocity structure with a low-water-content (~0–0.5%) shallow layer (~20–30 m) underlain by high-water-content (1–2.5%) ice.

Time-shift estimation between arrivals in two seismic traces before and after a velocity perturbation is a crucial step in many seismic methods. The accuracy of the estimated velocity perturbation location and amplitude depend on this time shift. Windowed cross-correlation and trace stretching are two techniques commonly used to estimate local time shifts in seismic signals. In the work presented here we implement Dynamic Time Warping (DTW) to estimate the warping function – a vector of local time shifts that globally minimizes the misfit between two seismic traces. We compare all three methods using acoustic numerical experiments. We show that DTW is comparable to or better than the other two methods when the velocity perturbation is homogeneous and the signal-to-noise ratio is high. When the signal-to-noise ratio is low, we find that DTW and windowed cross-correlation are more accurate than the stretching method. Finally, we show that the DTW algorithm has good time resolution when identifying small differences in the seismic traces for a model with an isolated velocity perturbation. These results impact current methods that utilize not only time shifts between (multiply) scattered waves, but also amplitude and decoherence measurements.