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This paper presents a novel crack size estimation method based on dilated convolution and time series fine tuning using in‐situ Lamb wave. The contributions of this proposed method are twofold: (1) a dilated convolution‐based neural network which is an effective representation learning methods with larger receptive fields for periodic signals and (2) a crack length adjustment approach based on previous estimations with a time series fine tuning method. The time series fine tuning method utilizes the monotonicity of the crack length with respect to time. A new evaluation metric has been adopted, which considers prediction errors, time errors, and monotonicity errors. The proposed method outperforms the previous feature extraction‐based methods with or without time series fine tuning in this new evaluation metric. Highlights: Crack estimation method using deep learning and time series fine tuning was proposed.The neural network using a combination of dilated convolution and long short‐term memory (LSTM) network was designed.The proposed method outperformed prior manual feature extraction‐based approaches. [ABSTRACT FROM AUTHOR]

Intense eruptions of the Tonga volcano activated prominent traveling atmospheric disturbances (TADs) at 04:05UT on 15 January 2022. Himawari‐8 satellite images depict that TADs of the tropospheric Lamb wavefront propagate with a speed of 315 m/s and arrive in Taiwan at 11:30UT. Networks of 98 barometers, 28 tide gauges, an ionosonde, and 10 magnetometers are used to study the responses of magnetic fields to TADs in Taiwan. The horizontal components in magnetic field changes of the Taiwan magnetometers all point toward and away from the Tonga volcano at 11:00–12:00UT upon the tropospheric Lamb wavefront arrival and at 22:00–23:00UT when the thermospheric Lamb wavefront with speeds of 487 m/s coming, respectively. Analyses of the raytracing and beamforming techniques on the horizontal components in magnetic field changes of 69 INTERMAGNET magnetometers show that both tropospheric and thermospheric Lamb waves efficiently activate traveling ionospheric disturbances and modify ionospheric currents of the globe. Plain Language Summary: At 04:05UT on 15 January 2022, intense Tonga volcanic eruptions induce prominent atmospheric disturbances and tsunami waves. Himawari‐8 meteorological satellite images depict the induced upper‐level tropospheric disturbances with horizontal speeds of about 315 m/s at 8.2 km altitude in the Lamb wave mode travel worldwide. Upon the traveling atmospheric disturbances (TADs) of the tropospheric Lamb wavefront arriving in Taiwan at 11:30UT, 98 ground‐based barometers register increases and reach peaks at about 11:50UT in the atmospheric pressure; 28 tide gauges record enhancements and maximums of sea level fluctuations at about 14:30–17:30UT; and a local ionosonde observes that the ionosphere reaches the highest altitude at 14:30UT. The changes of the horizontal component of the Earth's magnetic fields measured by 10 Taiwan magnetometers almost all point exactly toward the Tonga volcano upon the tropospheric Lamb wavefront arrival at 11:00–12:00UT, and away from the volcano at 22:00–23:00UT, which suggests a 487 m/s TAD (or thermospheric Lamb wavefront) at about 130 km altitude also being activated. The horizontal components in magnetic field changes of 69 INTERMAGNET magnetometers show that both tropospheric and thermospheric Lamb waves triggered by Tonga volcanic eruptions are very powerful, and can induce intense dynamo currents and electric fields on the globe. Key Points: Tropospheric and thermospheric Lamb waves of the Tonga volcanic eruption activate dynamo currents and electric fieldsTraveling atmospheric disturbances of the Tonga volcanic eruption significantly uplift the ionosphereTropospheric Lamb waves of the Tonga volcanic eruption modulate ground‐based air pressures and sea levels [ABSTRACT FROM AUTHOR]

In 2022, the Hunga volcano eruption in Tonga generated atmospheric pressure waves that propagated globally and produced tsunamis in all the world's oceans. The largest pressure wave, with an amplitude of several hundred pascals, is the Lamb wave. Standard Lamb wave models, incorporating the sound‐speed as a function of temperature, satisfactorily explain observations in the near‐field but not in the far‐field. We show that an augmented Lamb wave model that includes the effects of wind and topography accurately reproduces the wavefronts observed by satellites and barometers, including those close to the antipode. Winds, first suggested to explain the travel times of Lamb waves from Krakatau in 1883, are now shown to also play a major role in shaping their waveforms; temperature and topography play smaller, but still detectable, roles. Our augmented model provides a significant advance for the development of early warning and hazard assessments for the meteotsunamis these waves produce. Plain Language Summary: The January 2022 explosive eruption of the Hunga volcano in Tonga produced a pressure wave (of a type known as a Lamb wave) in the atmosphere, which was detected worldwide. This wave circled the Earth more than once, and generated tsunami in unexpected times and places. We have derived a mathematical description that allows us to quickly and accurately model the observations of this atmospheric wave. The description includes the effects of winds, temperature, and topography. The wave modeled using this description reproduces satellite and ground observations much better than simpler models, notably the complex pattern of the wave near the antipode of the eruption. Our model clearly identifies global winds as the crucial influence on global‐scale Lamb‐wave propagation, and provides modeling tools for possible future occurrences of such waves and the global tsunamis created by them. Key Points: A augmented model is proposed to simulate the propagation of planetary scale Lamb waves, incorporating wind, temperature and topographyWinds play a primary role shaping Lamb waves in the far field, especially near the antipode of the sourceThe augmented Lamb wave model will help better assess far‐field volcanic tsunami hazards [ABSTRACT FROM AUTHOR]

High‐resolution Whole Atmosphere Community Climate Model with thermosphere/ionosphere extension is used to simulate the responses to the Hunga‐Tonga volcano eruption on 15 January 2022. Global propagation of the Lamb wave L'0 and L'1 pseudomodes are reproduced in the simulation, with the exponential growth of wave amplitudes with altitudes. The wavefront is vertical up to the lower thermosphere, and tilts outward above. These features are consistent with theoretical results. With simulated surface pressure perturbation agreeing with observations (∼100–250 Pa), thermospheric wind perturbations over 100 ms−1 are comparable with reported satellite and ground‐based observations. Traveling ionospheric disturbances in the total electron contents from the simulation show good agreement with observations, including magnitude and propagating speed and evidence of conjugacy in the first 1–2 hr after eruption. Conjugacy in E × B drift, on the other hand, is more persistent. Plain Language Summary: As one of the most powerful volcano eruptions on record, the Hunga Tonga‐Hunga Ha'apai Volcano produces waves that ripple through the atmosphere and near‐space environment. These wave signals have been recorded by observations from instruments on the ground and from satellites, and they propagate around the Earth multiple times. This event provides a rare opportunity to study the strong and direct connection of the whole atmosphere system. The challenge is for a model to be able to represent the key processes in the whole atmosphere system and to have sufficient spatial and temporal fidelity to gain a realistic global picture of the event. This is achieved in the study by using the high‐resolution Whole Atmosphere Community Climate Model with thermosphere/ionosphere extension. The model is able to simulate the global propagation of the waves, and the model results compare favorably with observations from the surface to the thermosphere and ionosphere. Key Points: High‐resolution Whole Atmosphere Community Climate Model with thermosphere/ionosphere extension simulation of Hunga eruption shows whole atmosphere responsesSimulated wave amplitude growth and phase structure are consistent with the theoretical predictionSimulation results are comparable with thermospheric and ionospheric observations [ABSTRACT FROM AUTHOR]

The 2022 volcanic eruption in Tonga caused an unusually large tsunami around the Pacific. It travels with a faster apparent velocity and has larger amplitudes at long distances than what would be expected from a conventional tsunami from the volcanic source. This tsunami was generated by the moving atmospheric Lamb wave and traveled at the speed of the Lamb wave (0.31 km/s). Japanese data showed the amplitude of this first tsunami becomes small when approaching the coast, due to the weaker air‐sea coupling at the shallow depth. This wave split when passing the continental slope, and traveled at the speed of the ocean gravity wave. Therefore, the tsunami observed at the coast is delayed by thousands of seconds from the passage of the Lamb wave. Tsunamis generated by this atmospheric mechanism have not been previously observed by modern digital recording systems and should be considered in the tsunami warning systems. Plain Language Summary: A tsunami is usually generated by the sudden changes of the water heights, and caused by offshore earthquakes, coastal landslides, and submarine volcanic eruptions. The generated vertical displacement of the water propagates as a very long wave, and the tsunami waves become compressed with increased heights as they approach the coast. The 2022 volcanic eruption in Tonga caused an unusually large tsunami, which cannot be explained by conventional sources. The speed and amplitude are very different from theoretical values: the speed is about 0.31 km/s, whereas the average tsunami speed in the Pacific is 0.2 km/s. These data suggest that the tsunami from the Tonga eruption was excited by a pulse of atmospheric pressure as it traveled from the volcano. This source of the tsunami in the atmosphere needs to be considered for the tsunami warning system in the future. Key Points: Lamb wave produced by the volcanic eruption excites the sea surface as it travels across the Pacific and generates a tsunami pulseThe effect of the air‐sea coupling becomes weaker as the Lamb wave approaches the coastThe tsunami wave splits when passing the continental slope of Japan causing more complex waves [ABSTRACT FROM AUTHOR]

The explosive eruption of the Hunga‐Tonga volcano in the southwest Pacific at 0415UT on 15 January 2022 triggered gigantic atmospheric disturbances with surface air pressure waves propagating around the globe in Lamb mode. In space, concentric traveling ionosphere disturbances (CTIDs) are also observed as a manifestation of air pressure waves in New Zealand ∼0500UT and Australia ∼0630UT. As soon as the air pressure waves reached central Australia ∼0800UT, conjugate CTIDs appeared almost simultaneously in the northern hemispheres through interhemispheric coupling, much earlier than the arrival of the surface air pressure waves to Japan after 1100UT. Combining observations over Australia and Japan between 0800 and 1000UT, both direct and conjugate CTIDs show similar horizontal phase velocities of 320–390 m/s, matching with the dispersion relation of Lamb mode. The arrival of atmospheric Lamb wave to Japan later created in situ CTIDs showing the same Lamb mode characteristics as the earlier conjugate CTIDs. Plain Language Summary: The Hunga‐Tonga volcano eruption on 15 January 2022 has created the impulsive Lamb wave propagation on the surface air pressure that has been observed globally. The Lamb wave, typically moving near the ground at the sound speed of ∼340 m/s, traveled 6 hr to reach Japan. However, the Lamb wave signature in the Earth's ionosphere, the ionized component of the atmosphere, arrived 3‐hr earlier than expected, thanks to the property of the ionospheric plasma being controlled by the Earth's magnetic field. As soon as the surface Lamb wave reached Australia, the ionosphere above showed concentric wave shape of the traveling ionospheric disturbances (CTIDs), and the effect was mapped to Japan in the northern hemisphere along the conductive magnetic field lines. The much faster appearance of the ionosphere disturbances to the northern hemisphere through the magnetic field lines is beyond expectations. This is the first time such concentric waves from a volcanic eruption have been observed simultaneously in both hemispheres. Monitoring the ionospheric disturbances could be a robust early warning tool for diagnosing such explosive events on the planet Earth. Key Points: Concentric traveling ionospheric disturbances (CTIDs) driven by volcano excited Lamb wave are observed simultaneously in Australia and JapanDue to magnetic conjugate effect, the northern hemisphere CTIDs appear 3‐hr prior to the arrival of the surface Lamb waveBoth direct and conjugate CTIDs match with the theoretical dispersion relation of the atmospheric Lamb and gravity modes [ABSTRACT FROM AUTHOR]

The major eruption of volcano Hunga Tonga‐Hunga Ha'apai in Tonga on 15 January 2022 generated atmospheric Lamb waves that propagated over the world. This seemed the first volcanic Lamb wave event that was clearly captured by the state‐of‐the‐art geostationary meteorological satellites. This paper provides visualization of the waves using thermal infrared images from geostationary satellite Himawari‐8. The second time derivatives of 10‐min interval images clearly illustrated the waves propagating at about 310 m s−1. The waves could be tracked for more than a week while they propagated five times round the earth. Automated wavefront identification illustrated nonuniform propagation speed. The signals in the satellite images well matched the surface pressure observations in Japan. Plain Language Summary: The major eruption of volcano Hunga Tonga‐Hunga Ha'apai in Tonga on 15 January 2022 generated atmospheric pressure pulses that propagated over the world. This seemed the first event that was clearly captured by the state‐of‐the‐art geostationary meteorological satellites, such as Himawari‐8. Taking the time difference of Himawari‐8's 10‐min interval images twice, the waves that propagated at about 310 m s−1 could be tracked for more than a week while they propagated five times round the earth. This was not possible with the previous‐generation geostationary meteorological satellites. Visualized waves also illustrated how the propagation speed changes in space and time. The signals in the satellite images well matched the surface pressure observations in Japan. Key Points: Lamb waves from an eruption were clearly visualized by the second time derivative of satellite infrared images every 10 minThe waves could be tracked for more than a week while they propagated at least five times round the earth at a speed of about 310 m s−1The signals in the satellite images matched the surface pressure changes quantitatively [ABSTRACT FROM AUTHOR]

On 15 January 2022, around 4:30 UTC the eruption of the Hunga‐Tonga volcano, in the South Pacific Ocean, generated a violent underwater explosion. In addition to tsunami waves that affected the Pacific coasts, the eruption created atmospheric pressure disturbances that spread out in the form of Lamb waves. The associated atmospheric pressure oscillations were detected in high‐frequency in‐situ observations all over the globe. Here we take advantage of the similarities in the propagation and characteristics between atmospheric Lamb waves and long ocean waves and we use a 2DH ocean numerical model to simulate the phenomenon. We compare the outputs of the numerical simulation with in‐situ atmospheric pressure records and with remote satellite observations. The signal in the model matches the observed atmospheric pressure perturbations and reveals an excellent agreement in the wave arrival time between model and observations at hundreds of locations at different distances from the origin. Plain Language Summary: The underwater explosion of the Hunga‐Tonga volcano in the South Pacific Ocean generated atmospheric pressure disturbances, known as Lamb waves, that propagated and surrounded the globe several times. In this study, we exploit the similarities between atmospheric Lamb waves and long waves in the ocean (e.g., tsunamis) to simulate their propagation using an ocean numerical model. The comparison of our results with remote satellite data and in‐situ atmospheric pressure records reveals that our model correctly reproduces the propagation of the atmospheric disturbances generated by the volcano explosion. Key Points: The underwater Hunga‐Tonga volcano exploded generating Lamb waves that traveled around the Earth several timesWe simulate these waves using a hydrostatic shallow water equation oceanic modelThe results closely follow the observations of atmospheric pressure perturbations [ABSTRACT FROM AUTHOR]

Honeycomb sandwich composites are extensively used in military shelters, aerospace structures, ground transportation structures, auto‐racing bodies, ship panels, and other special purpose structures requiring lightweight construction materials. But debondings at the face‐sheet‐to‐core junctions frequently occur due to the variable operating and loading conditions, which may menace the safety and overall integrity of the structural assembly. This paper aims to effectively identify such hidden debonding regions in these advanced structures, using Lamb wave‐based monitoring technique. A semianalytical analysis of Lamb wave dispersion in a healthy sandwich structure is carried out to identify various Lamb modes and to study their propagation phenomenon. A combined finite element‐based simulation and experimental analysis of Lamb wave propagation in sandwich panels (healthy and with debonding) are then carried out using piezoelectric transducer networks. It is observed that the presence of debonding significantly reduces the propagating Lamb wave mode amplitudes. A debonding detection algorithm, which uses the differential changes in Lamb mode amplitudes, is applied to efficiently identify single and multiple debonding regions in the structure. [ABSTRACT FROM AUTHOR]