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 is the surface-guided Lamb wave ( ≲ 0.01 Hz), which we observed propagating for four (+three antipodal) passages around the Earth over six days. Based on 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 (0.01–20 Hz), long-range (~10,000 km) 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. We highlight exceptional observations of the atmospheric waves.

Morgan and Raspet [J. Acoust. Soc. Am. 92, 1180–1183 (1992)] performed simultaneous wind velocity and wind noise measurements and determined that the wind noise spectrum is highly correlated with the wind velocity spectrum. In this paper, two methods are developed for predicting the upper limits of wind noise pressure spectra from fluctuating velocity spectra in the inertial range. Lower limits on wind noise are estimated from two theories of the pressure fluctuations that occur in turbulence when no wind screen or microphone is present. Empirical results for the self-noise of spherical and cylindrical windscreens in substantially nonturbulent flows are also presented. Measurements of the wind velocity spectra and wind noise spectra from a variety of windscreens are described and compared to the theoretical predictions. The wind noise data taken at the height of the anemometer lies between the upper and lower limits and the predicted self-noise is negligible. The theoretical framework allows windscreen reduction to be evaluated in terms of the turbulent inflow properties and establishes practical upper limits on wind noise reduction for varying wind conditions.

In a previous paper [R. Raspet, et al., J. Acoust. Soc. Am. 119, 834-843 (2006)], a method was introduced to predict upper and lower bounds for wind noise measured in spherical wind-screens from the measured incident velocity spectra. That paper was restricted in that the predictions were only valid within the inertial range of the incident turbulence, and the data were from a measurement not specifically designed to test the predictions. This paper extends the previous predictions into the source region of the atmospheric wind turbulence, and compares the predictions to measurements made with a large range of wind-screen sizes. Predictions for the turbulence-turbulence interaction pressure spectrum as well as the stagnation pressure fluctuation spectrum are calculated from a form fit to the velocity fluctuation spectrum. While the predictions for turbulence-turbulence interaction agree well with measurements made within large (1.0 m) wind-screens, and the stagnation pressure predictions agree well with unscreened gridded microphone measurements, the mean shear-turbulence interaction spectra do not consistently appear in measurements.

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Measurements of the wind noise measured at the ground surface outdoors are analyzed using the mirror flow model of anisotropic turbulence by Kraichnan [J. Acoust. Soc. Am. 28(3), 378-390 (1956)]. Predictions of the resulting behavior of the turbulence spectrum with height are developed, as well as predictions of the turbulence-shear interaction pressure at the surface for different wind velocity profiles and microphone mounting geometries are developed. The theoretical results of the behavior of the velocity spectra with height are compared to measurements to demonstrate the applicability of the mirror flow model to outdoor turbulence. The use of a logarithmic wind velocity profile for analysis is tested using meteorological models for wind velocity profiles under different stability conditions. Next, calculations of the turbulence-shear interaction pressure are compared to flush microphone measurements at the surface and microphone measurements with a foam covering flush with the surface. The measurements underneath the thin layers of foam agree closely with the predictions, indicating that the turbulence-shear interaction pressure is the dominant source of wind noise at the surface. The flush microphones measurements are intermittently larger than the predictions which may indicate other contributions not accounted for by the turbulence-shear interaction pressure.