Multi‐Layer Evolution of Acoustic‐Gravity Waves and Ionospheric Disturbances Over the United States After the 2022 Hunga Tonga Volcano Eruption - P. A. Inchin; A. Bhatt; S. A. Cummer; S. D. Eckermann; B. J. Harding; D. D. Kuhl; J. Ma; J. J. Makela; R. Sabatini; J. B. Snively (AGU Advances, 2023)
Abstract The Hunga‐Tonga Hunga‐Ha'apai volcano underwent a series of large‐magnitude eruptions that generated broad spectra of mechanical waves in the atmosphere. We investigate the spatial and temporal evolutions of fluctuations driven by atmospheric acoustic‐gravity waves (AGWs) and, in particular, the Lamb wave modes in high spatial resolution data sets measured over the Continental United States (CONUS), complemented with data over the Americas and the Pacific. Along with >800 barometer sites, tropospheric observations, and Total Electron Content data from >3,000 receivers, we report detections of volcano‐induced AGWs in mesopause and ionosphere‐thermosphere airglow imagery and Fabry‐Perot interferometry. We also report unique AGW signatures in the ionospheric D‐region, measured using Long‐Range Navigation pulsed low‐frequency transmitter signals. Although we observed fluctuations over a wide range of periods and speeds, we identify Lamb wave modes exhibiting 295–345 m s−1 phase front velocities with correlated spatial variability of their amplitudes from the Earth's surface to the ionosphere. Results suggest that the Lamb wave modes, tracked by our ray‐tracing modeling results, were accompanied by deep fluctuation fields coupled throughout the atmosphere, and were all largely consistent in arrival times with the sequence of eruptions over 8 hr. The ray results also highlight the importance of winds in reducing wave amplitudes at CONUS midlatitudes. The ability to identify and interpret Lamb wave modes and accompanying fluctuations on the basis of arrival times and speeds, despite complexity in their spectra and modulations by the inhomogeneous atmosphere, suggests opportunities for analysis and modeling to understand their signals to constrain features of hazardous events.