Atmospheric waves and global seismoacoustic observations of the January 2022 Hunga eruption, Tonga.

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.

Local propagation speed constrained estimation of the slowness vector from non-planar array observations.

The estimation of the slowness vector of infrasound waves propagating across an array is a critical process leading to the determination of parameters of interest such as the direction of arrival. The sensors of an array are often considered to be located in a horizontal plane. However, due to topography, the altitudes of the sensors are not identical and introduce a bias on the estimate if neglected. However, the unbiased 3D estimation procedure, while suppressing the bias, leads to an increase of the variance. Accounting for an a priori constraint on the slowness vector significantly reduces the variance and could therefore improve the performance of the estimation if the introduced bias by incorrect a priori information remains negligible. This study focuses on measuring the benefits of this approach with a thorough investigation of the bias and variance of the constrained 3D estimator, which is not available in the existing literature. This contribution provides such computations based on an asymptotic Gaussian approximation. Simulations are carried out to assess the theoretical results both with synthetic and real data. Thus, a constrained 3D estimator is proposed yielding the best bias/variance compromise if good knowledge of the propagation wave speed is accessible.