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a Idealized atmospheric pressure disturbance of 2D Gaussian shape (P0 = − 5 hPa, σx = 0.1, σy = 0.6) and the propagation of the air pressure jump along the coast of Portugal. b from south to north under incident angle between 90° and 120°; and c parallel to the continental shelf break of the northern coast with incident angle between 60° and 100°. Yellow lines denote bathymetric depth contours of 50, 100 and 150 m
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On 6 and 7 July 2010, uncommon sea waves were observed along the coast of Portugal. The Portuguese tide gauge network recorded the sea-level signals showing tsunami-like waves of heights varying from 0.14 to 0.6 m (crest-to-trough) and of periods in the range of 30 to 60 min. Analysis of both oceanic and atmospheric data revealed the occurrence of...
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Citations
... For numerical simulations of meteotsunamis, GeoClaw demonstrated good agreement with tide gauge observations, validating both local and global scales (Kim and Omira, 2021;Kim et al., 2022;Omira et al., 2022). Assuming that the pressure fluctuations propagate at a constant speed and direction, the speed and angle of the pressure jump are calculated based on meteorological observations. ...
... It is possible that these limitations may lead to inaccurate reproduction of high-frequency sea-level variations associated with local resonances. In particular, tide gauges at Peniche and Leixões are located inside the harbors (see Fig 1 of Kim and Omira, 2021), and the (see Fig 10 of Kim and Omira, 2021). Meanwhile, at Aveiro, the 20-minute rolling average results are similar to the original results in Fig. 9, which indicates that the resonance effect is minimal to this tide gauge station. ...
... It is possible that these limitations may lead to inaccurate reproduction of high-frequency sea-level variations associated with local resonances. In particular, tide gauges at Peniche and Leixões are located inside the harbors (see Fig 1 of Kim and Omira, 2021), and the (see Fig 10 of Kim and Omira, 2021). Meanwhile, at Aveiro, the 20-minute rolling average results are similar to the original results in Fig. 9, which indicates that the resonance effect is minimal to this tide gauge station. ...
In recent years, Portugal’s coastal regions have experienced an increase in the frequency and intensity of severe weather events, including tropical cyclones and extratropical storms. This paper presents an analysis of Hurricane Leslie(2018)’s impact on Portugal, with a specific focus on the complex and often underestimated meteotsunami phenomena accompanying the storm system. Our analysis examines data collected from multiple sources, and employs advanced numerical simulations, integrated within the GeoClaw framework. These simulations encompass both storm surge and meteotsunami effects. One of the findings is the significant role played by meteotsunamis in amplifying coastal sea levels during extreme weather events. The observed sea-level fluc
tuations closely align with the combined surge-meteotsunami simulations, emphasizing the importance of considering these high-frequency phenomena in coastal hazard assessments.
... The numerical package GeoClaw (Mandli & Dawson, 2014), which solves nonlinear shallow water equations, was used for the tsunami simulations. Geoclaw employs a finite-volume method with adaptive mesh refinement (AMR) and has been used in previous simulations of this tsunami event (e.g., Omira et al., 2022;Yuen et al., 2022) and other meteotsunamis (Kim & Omira, 2021). In simulations employing the commonly used nested grid system, the resolution and integration time intervals were fixed for each computational domain. ...
On January 15, 2022, at around 13:00 JST, a massive eruption occurred at Hunga Tonga-Hunga Ha’apai volcano in the Tonga Islands, South Pacific Ocean. The eruption was accompanied by rapid atmospheric pressure changes and tsunamis along the Pacific coast. Along the Japanese coast, tsunami waves were observed several hours before the expected arrival time due to the pressure change of about 2 hPa, and the subsequent tsunami heights exceeded 1 m at some stations. These are caused by the pressure waves that excited the sea surface waves, but the external force factor that can fully explain the maximum amplitude has not been clarified. This study performed tsunami simulations for the area around Japan and estimated the factors that could explain the maximum amplitude of the tsunami along the coast of Japan by comparing the results of the simulations under several patterns of external force conditions with the observed records. The results showed that a component corresponding to the resonant period caused continuous amplification in bays along the coast of the Tohoku region. On the other hand, in Amami and Shikoku, the amplification mechanism generated by the propagation on the water surface may have contributed to the amplification and to the excitation of the water surface by the external barotropic force.
... The numerical package GeoClaw (Mandli & Dawson, 2014), which solves nonlinear shallow water equations, was used for the tsunami simulations. Geoclaw employs a finite-volume method with adaptive mesh refinement (AMR) and has been used in previous simulations of this tsunami event (e.g., Omira et al., 2022;Yuen et al., 2022) and other meteotsunamis (Kim & Omira, 2021). In simulations employing the commonly used nested grid system, the resolution and integration time intervals were fixed for each computational domain. ...
The 2022 Hunga Tonga-Hunga Ha’apai eruption generated tsunamis that propagated across the Pacific Ocean. Along the coast of Japan, nearshore amplification led to amplitudes of nearly 1 m at some locations, with varying peak tsunami occurrence times. The leading tsunami wave can generally be reproduced by Lamb waves, which are a type of air-pressure wave generated by an eruption. However, subsequent tsunamis that occurred several hours after the leading wave tended to be larger for unknown reasons. This study performs multi-scale numerical simulations to investigate subsequent tsunami waves in the vicinity of Japan induced by air pressure waves caused by the eruption. The atmospheric pressure field was created using a dispersion relation of atmospheric gravity wave and tuned by physical parameters based on observational records. The tsunami simulations used the adaptive mesh refinement method, incorporating detailed bathymetry and topography to solve the tsunami at various spatial scales. The simulations effectively reproduced the tsunami waveforms observed at numerous coastal locations, and results indicate that the factors contributing to the maximum tsunami amplitude differ by region. In particular, bay resonance plays a major role in determining the maximum amplitude at many sites along the east coast of Japan. However, large tsunami amplification at some west coast locations was not replicated, probably because it was caused by amplification during oceanic wave propagation rather than meteorological factors. These findings enhance our understanding of meteotsunami complexity and help distinguish tsunami amplification factors.
... For numerical modeling, we used the Boussinesqtype extension of GeoClaw (Kim et al. 2017b) with atmospheric pressure forcing. To account for the air-pressure jump as a trigger and driver of meteotsunami propagation, the GeoClaw code was equipped with atmospheric pressure forcing terms following the governing equations presented in Kim and Omira (2021). The atmospheric pressure terms are handled by the flux splitting method (f-wave method) which is based on the momentum balance (Mandli and Dawson, 2014). ...
... Further details on the interpolation process can be found at Kim and Omira (2021). The propagation of the meteotsunami waves is then simulated over a uniform bathymetric grid spacing of dx = dy = 20″ (~ 500 m). ...
... Despite the minimal coastal impact of the 2009 event, this study helps to extend the hazard posed by meteotsunamis in the Yellow Sea. The analysis of sea-level and air-pressure data, both available with high temporal resolution, allows building a robust numerical model for the 2009 meteotsunami, based on a Boussinesq-type code equipped with atmospheric forcing terms (Kim et al. 2017b;Kim and Omira 2021). Although propagation metrics of the meteotsunami-driven atmospheric instability are uncertain, the conducted numerical tests enable estimating the speed and direction of the observed air-pressure jumps to 11-13 m/s and 340-350º, respectively. ...
The Yellow Sea is recognized as a meteotsunami “hot-spot”, with a relatively high rate of
events’ occurrence. The March 2007 and May 2008 meteotsunami events attracted large
attention due to their deadly and high impact on the west coast of the Korean Peninsula.
However, other small size meteotsunamis remain less known because of their insignificant
coastal effect. Yet, a better understanding of meteotsunami hazard in the Yellow Sea can be achieved through investigation of both large and small events. This paper reveals the occurrence of a meteotsunami on 11–12 June 2009 in the eastern Yellow Sea, and addresses the analyses of the sea-level and air-pressure data, the meteotsunami genesis mechanism by the atmospheric forcing, and the numerical modeling of meteotsunami propagation. Analysis results evidence that a moving air-pressure jump of about 3 hPa disturbed the sea surface and induced a meteotsunami with wave height up to 0.45 m (crest-to-trough) which were observed at the Janghang (JH) station. Both meteorological observations and numerical modeling support a speed of 11–13 m/s for the atmospheric disturbance propagation, which is smaller than the optimal condition for Proudman resonance of meteotsunamis in the eastern Yellow Sea. Here, we demonstrate that the Greenspan resurgence was responsible for the tsunami-like waves. This study unravels new insights into the formation, amplification, and hazard extent of small size meteotsunamis in the eastern Yellow Sea.
... • user-defined surface pressure fields based on meteorological observations (e.g., meteorological network, weather radar, and satellite) characterized by constant air pressure oscillations, such as waveform, duration, source location, speed, and direction (Bechle and Wu, 2014;Kim and Omira, 2021;Ličer et al., 2017;Linares et al., 2016;Perez and Dragani, 2021;Rabinovich et al., 2021;Š epić et al., 2015a;Wang et al., 2021); • spatially and temporally varying surface pressure fields after simulation using an atmospheric model, which is commonly used in realtime operating systems Denamiel et al., 2019;Shi et al., 2019;Tojčić et al., 2021); • adjusted surface pressure field after simulating an atmospheric model (Huang et al., 2021). ...
A traveling air pressure disturbance of several hPa over a short period (5–10 min) can generate tsunami-like waves in coastal areas owing to a multi-resonant mechanism. Pressure-forced meteotsunamis have been reported over the Korean Peninsula on a regular basis in recent years. However, the Korean meteotsunami early warning system does not always provide sufficient lead time. The early warning system comprises two-segmented zones for tracking intensity and propagation of air pressure disturbances via 89 meteorological stations in precaution zones (offshore islands) and warning zones (coastline and inland areas). To address the lead-time problem in the current observation-based monitoring system, we used an atmospheric model with a horizontal resolution of 1.5 km, the Korea Meteorological Administration's local data assimilation and prediction system (LDAPS). The ability of the LDAPS to detect air pressure disturbances was tested for a widespread and destructive meteotsunami event that occurred on March 4, 2018. The detection capability of significant air pressure disturbances (>1.5 hPa/10 min) was 67% in the precaution zone, and the propagation pattern (direction, speed, and spatial scale) was reasonably consistent with the monitoring results. Based on the LDAPS prediction and the established observation-based monitoring system, monitoring operators can determine the potential meteotsunami risk from the open Yellow Sea beyond the observation system with sufficient lead time. This case study contributes to the development of observation- and atmospheric model-based early warning systems for meteotsunami mitigation. In the near future, it is expected that an early warning of tsunamigenic disturbances in the Korean Peninsula can be provided with the LDAPS-based modeling system using a high-resolution atmosphere–ocean coupled model.
... The northern mid-latitude synchronicity is more widely documented, both through statistics (quoted above) and through case study analyses. For example, a meteotsunami was observed along the Portuguese coastline in June 2010, propagating from south to north (Kim and Omira, 2021) over hundreds of kilometres. More recently, in 2017, the meteotsunami struck tourist beaches along the 500 km stretch of the coasts of the English Channel and North Sea (Sibley et al., 2021). ...
This paper provides global climatology of high-frequency (T < 2 h) sea-level oscillations of atmospheric origin. Sea-level series with a temporal resolution of 1 min from 331 tide gauges in the world ocean and spanning between 1.5 and 12 years were analysed to determine the typical ranges, seasons and characteristics of moderate and extreme manifestations of nonseismic sea-level oscillations at tsunami timescales (NSLOTTs). Variances in these oscillations reach 6.6 cm² on average, but their region-averaged extreme (99.99th percentile) ranges may exceed half a metre or more at individual hotspot locations. The NSLOTTs are the highest in the mid-latitudes and decrease towards polar and tropical regions. Moderate oscillations show clear winter maxima at the majority of stations, while a less pronounced pattern is evident for the most extreme oscillations, which may occur throughout a year. A total of 3080 of the most prominent NSLOTT events were selected from 308 stations and compared to background oscillations, revealing the substantial capability of energy amplification during extreme events. Synchronicity in extreme NSLOTT events between neighbouring stations (up to 250 km) in mid-latitudes has been detected for 20–32% of all episodes, suggesting possible connectivity between the episodes.
... To investigate the generation, amplification and propagation properties of meteotsunamis in the Balearic Sea, Ličer et al. (2017) applied nested ocean modelling system (ROMS) forced by synthetic atmospheric gravity waves, and quantified the contribution of Mallorca shelves and Menorca Channel to meteotsunami intensity, and analyzed subcritical and supercritical propagation conditions. Kim and Omira (2021) identified meteotsunami hazard hot spots along the coast of Portugal using a series of idealized numerical simulations with comparison to observed data. ...
Although relatively rare, meteotsunamis are capable of causing coastal infrastructure damage and casualties. Analyses of water level and meteorological data in the U.S. show that meteotsunamis occur more frequently than expected, and therefore, it is important to include meteotsunami assessment in coastal hazard mitigation efforts. In this study, we conducted numerical experiments to investigate the generation and propagation of meteotsunami waves and assessed hazards on a broad scale in the northeastern Gulf of Mexico (GOM). The numerical experiments used a simple 2D depth-averaged hydrostatic shallow water model forced by an idealized atmospheric pressure disturbance on a set of trajectories and directions (1260 runs) covering the whole Florida GOM shelf. Results show that bathymetry pattern has control over the direction of major meteotsunami waves and that forward speed has more influence on maximum water level than the trajectory location. Maximum water level anomaly tracking and Proudman length analysis both demonstrate that Florida’s wide and long straight continental shelf in the northeastern GOM is favorable for producing large meteotsunamis. Statistical analysis indicates that pressure disturbances coming from southwest–west direction result in higher water level near south Florida region, while east direction in the Florida panhandle region. The forward speed distribution shows that 20–25 m/s have the most potential. These results can help identify vulnerable coastal regions and pressure disturbance scenarios that most likely generate higher meteotsunami waves.
... In other coastal areas, with no available atmospheric data, these records were interpolated to estimate the air-pressure disturbances. Details on the interpolation process can be found in Kim and Omira (2021). The propagation of the meteotsunami waves is then simulated over a uniform bathymetric grid spacing of dx = dy = 20" (~ 500 m) (Fig. 1). ...
The Yellow Sea is recognized as a meteotsunami “hot-spot”, with a relatively high rate of events’ occurrence. The March 2007 and May 2008 meteotsunami events attracted large attention due to their deadly and high impact on the west coast of the Korean Peninsula. However, other small size meteotsunamis remain less known because of their insignificant coastal effect. Yet, a better understanding of meteotsunami hazard in the Yellow Sea requires thorough investigation of both large and small events. This paper reveals the occurrence of a meteotsunami on 11–12 June 2009 in the eastern Yellow Sea. It addresses the analyses of both the recorded sea-level and air-pressure data, the correlation between the atmospheric forcing and the meteotsunami formation, the numerical modeling of meteotsunami propagation, and the resonance effects on the recorded waves. Analysis results evidence a moving air-pressure jump of about 3 hPa that disturbed the sea surface and caused a meteotsunami with wave height up to 0.45 m (crest-to-trough). Both meteorological observations and numerical modeling suggest a speed of 11 to 13 m/s for the atmospheric disturbance propagation, which is much smaller than the optimal condition for Proudman resonance of meteotsunamis in the eastern Yellow Sea. Here, we demonstrate that the Greenspan resonance was responsible for amplifying the incident waves. Despite the insignificant coastal impact of the 11 June 2009 event, its investigation unravels new insights into the formation, amplification, and hazard extent of small size meteotsunamis in the Yellow Sea.
... Additionally, various theoretical models must be quantified to obtain the expected added value (e.g., [9][10][11]). The topics and use cases range from the analysis of impacts in the case of prevalent ex-post assessment of tsunami hazards and related damages [12] to the maximum earthquake magnitude scenario [13], analysis of historical events such as the 1755 CE Lisbon earthquake and the largest historical tsunami ever impacting the Europe's Atlantic coasts [14], or confirming the existence of low-level tsunamis [15]. ...
Various organizations and institutions store large volumes of tsunami-related data, whose availability and quality should benefit society, as it improves decision making before the tsunami occurrence, during the tsunami impact, and when coping with the aftermath. However, the existing digital ecosystem surrounding tsunami research prevents us from extracting the maximum benefit from our research investments. The main objective of this study is to explore the field of data repositories providing secondary data associated with tsunami research and analyze the current situation. We analyze the mutual interconnections of references in scientific studies published in the Web of Science database, governmental bodies, commercial organizations, and research agencies. A set of criteria was used to evaluate content and searchability. We identified 60 data repositories with records used in tsunami research. The heterogeneity of data formats, deactivated or nonfunctional web pages, the generality of data repositories, or poor dataset arrangement represent the most significant weak points. We outline the potential contribution of ontology engineering as an example of computer science methods that enable improvements in tsunami-related data management.
... A case study of a meteotsunami that occurred in June 2010 along the Portuguese coastline was conducted by Kim and Omira (2021), who analysed both oceanic and atmospheric data and constructed a high-resolution ocean model to quantify the meteotsunami hazard. The authors demonstrated that meteotsunamis present a real threat for the densely occupied Portuguese coast and identified "hot spots"-specific coastal sites, where the meteotsunami energy is focused. ...
