Meteotsunami Observed by the Deep‐Ocean Seafloor Pressure Gauge Network Off Northeastern Japan

Kubota, Tatsuya; Saito, Tatsuhiko; Chikasada, Naotaka Yamamoto; Sandanbata, Osamu

doi:10.1029/2021gl094255

Cited by 21 publications

(19 citation statements)

References 55 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…2A). We then simulated the generation and propagation of ocean waves driven by the atmospheric pressure waves (11,12) using global bathymetry data (13). We finally calculated the ocean-bottom pressure changes (pbot) as the sum of the atmospheric pressure (patm) and the sea-surface height changes η (peta = ρwg0η, ρw: seawater density, g0: gravity acceleration, 9.8 m/s 2 ): pbot = patm + peta (12,14).…”

Section: Main Textmentioning

confidence: 99%

“…Because the pressure change at the ocean's bottom caused by this leading wave is a superposition of the pressure changes caused by the Lamb wave and tsunamis, pbot = patm + peta (12,14), the ocean-bottom pressure does not directly represent the tsunami height, whereas the coastal tide gauges observe only the sea height changes but not the atmospheric pressure. This makes it difficult to accurately calculate the tsunami height from global ocean-bottom pressure gauges.…”

Section: Fig 4 Schematic Illustration Of the Generation Mechanism Of ...mentioning

confidence: 99%

“…After the numerical simulation of the atmospheric pressure wave, we simulated the generation and propagation of the tsunami excited by the atmospheric pressure wave. Similar to the simulation of the atmospheric pressure wave, the following two-dimensional long-wave tsunami equation was solved (11,12):…”

Section: Modeling Of Tsunami Generation and Propagationmentioning

confidence: 99%

“…The external force term, including the atmospheric pressure patm, drives the tsunami. After the calculation, we calculated the ocean-bottom pressure pbot by the sum of the pressure changes due to the atmospheric pressure change patm and because of the sea-surface height change peta = ρwg0η (12,14), expressed as:…”

Section: Modeling Of Tsunami Generation and Propagationmentioning

confidence: 99%

See 3 more Smart Citations

Global fast-traveling tsunamis by atmospheric pressure waves on the 2022 Tonga eruption

Kubota¹,

Saito²,

Nishida³

2022

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

Section: Main Textmentioning

confidence: 99%

Section: Fig 4 Schematic Illustration Of the Generation Mechanism Of ...mentioning

confidence: 99%

Section: Modeling Of Tsunami Generation and Propagationmentioning

confidence: 99%

Section: Modeling Of Tsunami Generation and Propagationmentioning

confidence: 99%

See 2 more Smart Citations

Global fast-traveling tsunamis by atmospheric pressure waves on the 2022 Tonga eruption

Kubota¹,

Saito²,

Nishida³

2022

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…To investigate the direction-of-arrival of the P1 and P2 phases, a semblance analysis (e.g., Neidell and Taner 1971;Honda et al 2008;Kubota et al 2021) was conducted on arrays consisting of three or more near-trench stations with similar waveforms and water depths. Here, the bandpass-ltered waveforms in the period of 360-3600 s were analyzed with a time window of 1800 s and a sliding interval of 600 s. Assuming a plane-wave incidence, we estimated the apparent velocity and the direction of arrival.…”

Section: Array Analysis In S-netmentioning

confidence: 99%

Ocean-wave phenomenon around Japan Island due to the 2022 Tonga eruption observed by the wide and dense ocean-bottom pressure gauge networks

Kubo

Kubota

Suzuki

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

Ocean-bottom pressure gauges of wide and dense ocean-bottom observation networks in Japan, S-net and DONET, observed ocean waves due to the Tonga eruption that occurred at approximately 13:00 JST (UTC + 9) on January 15, 2022. We scrutinized their waveform records to clarify the nature of the arriving ocean waves, and found two significant disturbances between 20:00–21:00 and after 22:00. The first disturbance with a positive-polarity pulse and significant long-period components (1000–3000 s) arrived at S-net and DONET stations between 20:00–21:00 from the southeast, corresponding to the direction of the great circle of Tonga as seen from Japan. This arrival was much earlier than expected for a direct tsunami from the volcano and can be explained by assuming the propagation along the great circle path between Japan and Tonga at a velocity of approximately 300 m/s. After 22:00, significant phases dominated by relatively shorter period components (< 1000 s) arrived from the southeast direction in both observation networks. In DONET, another phase arrived from the south-southeast direction at approximately 23:30 with significant shorter period components (approximately 500 s). Most of the near-trench S-net stations recorded a peak amplitude during the first disturbance, whereas the near-coast S-net stations and DONET stations observed their peak after 22:00. The amplitudes of ocean-bottom pressure change were amplified as the water depth decreases. This amplification behavior differed between the first and second disturbances, and it may have been caused by differences in the dominant period of the arriving ocean waves, as well as differences in their generation mechanisms. This study also found several arrivals of air-wave disturbances that were correlated with the ocean-wave phases, which implies that the multiple disturbances of ocean-bottom pressure were generated by the interactions of several atmospheric pressure waves following the 2022 Tonga eruption with ocean waves.

show abstract

Prospects for meteotsunami detection in earth’s atmosphere using GNSS observations

et al. 2023

View full text Add to dashboard Cite

We study, for the first time, the physical coupling and detectability of meteotsunamis in the earth’s atmosphere. We study the June 13, 2013 event off the US East Coast using Global Navigation Satellite System (GNSS) radio occultation (RO) measurements, Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) temperatures, and ground-based GNSS ionospheric total electron content (TEC) observations. Hypothesizing that meteotsunamis also generate gravity waves (GWs), similar to tsunamigenic earthquakes, we use linear GW theory to trace their dynamic coupling in the atmosphere by comparing theory with observations. We find that RO data exhibit distinct stratospheric GW activity at near-field that is captured by SABER data in the mesosphere with increased vertical wavelength. Ground-based GNSS-TEC data also detect a far-field ionospheric response 9 h later, as expected by GW theory. We conclude that RO measurements could increase understanding of meteotsunamis and how they couple with the earth’s atmosphere, augmenting ground-based GNSS TEC observations.

show abstract

Meteotsunami Observed by the Deep‐Ocean Seafloor Pressure Gauge Network Off Northeastern Japan

Cited by 21 publications

References 55 publications

Global fast-traveling tsunamis by atmospheric pressure waves on the 2022 Tonga eruption

Global fast-traveling tsunamis by atmospheric pressure waves on the 2022 Tonga eruption

Ocean-wave phenomenon around Japan Island due to the 2022 Tonga eruption observed by the wide and dense ocean-bottom pressure gauge networks

Prospects for meteotsunami detection in earth’s atmosphere using GNSS observations

Contact Info

Product

Resources

About