• A
  • A
  • A
  • ABC
  • ABC
  • ABC
  • А
  • А
  • А
  • А
  • А
Regular version of the site

Russian Scientists Assess Dangers of Internal Waves During Underwater Volcanic Eruptions

Russian Scientists Assess Dangers of Internal Waves During Underwater Volcanic Eruptions

© iStock

Mathematicians at HSE University in Nizhny Novgorod and the A.V. Gaponov-Grekhov Institute of Applied Physics of the Russian Academy of Sciences studied internal waves generated in the ocean after the explosive eruption of an underwater volcano. The researchers calculated how the waves vary depending on ocean depth and the radius of the explosion source. It turns out that the strongest wave in the first group does not arrive immediately, but after a significant delay. This data can help predict the consequences of eruptions and enable advance preparation for potential threats. The article has been published in Natural Hazards. The research was carried out with support from the Russian Science Foundation (link in Russian).

Layers of water with varying temperature, density, and salinity form in an ocean column. Internal waves arise at the boundaries of these layers due to external forces such as wind, currents, earthquakes, and volcanic eruptions, which cause the upper and lower layers to shift relative to each other. The boundary starts to oscillate, attempting to return to its original position under the influence of buoyancy forces. Since the density difference between the layers is small, internal waves have a larger amplitude (usually 5–20 metres but sometimes up to 150 metres) compared to surface waves, where the density contrast between water and air is much greater.

Although the speeds of internal waves are relatively slow (typically only a few dozen centimetres per second), they can still pose a serious threat to hydraulic structures, underwater gas and oil pipelines, and can also lead to the erosion of the ocean floor. Disasters involving at least three submarines have been attributed to the effects of internal waves: the two American atomic submarines, USS Thresher in 1963 and USS Scorpion in 1968, and the Indonesian diesel submarine KRI Nanggala-402 in 2021.

‘During underwater volcanic eruptions and earthquakes, the primary danger comes from surface tsunami waves, which can have amplitudes of up to 30 meters on the coast and can be highly destructive. Internal waves are typically not considered in such cases. However, a recent article by Chinese colleagues reported for the first time the observation of internal waves during a volcanic eruption in the Tonga Archipelago in 2022. This sparked our interest in studying the characteristics of internal waves,’ explains co-author of the study Ekaterina Didenkulova, Leading Research Fellow at the International Laboratory of Dynamical Systems and Applications at HSE University in Nizhny Novgorod.

Le Mehaute’s parabolic cavern was chosen as a source of tsunami waves. This model is commonly used to calculate surface tsunami waves generated by underwater explosions, volcanic eruptions, and meteorite impacts in water. It was considered that the curves connecting points with the same seawater density (isopycnals) bend over an underwater volcano in the same way as the water surface.

Geometry of the problem
© Talipova, T., Pelinovsky, E. & Didenkulova, E. Internal waves generated by explosive eruptions of underwater volcanoes and their effect on the sea surface. Nat Hazards 121, 661–675 (2025). https://doi.org/10.1007/s11069-024-06851-3

Calculations reveal that internal waves generated by the eruption of an underwater volcano form frequency-modulated groups, with the first group exhibiting the largest amplitude. The characteristics of internal waves depend on the ratio of layer thicknesses, the source radius, and the distance from the source. Even at relatively small distances from the source, the wave amplitudes change gradually, allowing the source of a tsunami to be identified from internal waves using remote sensing of the sea surface. This approach makes it possible to obtain additional information about the tsunami and mitigate potential damage caused by the disaster.

'The amplitudes of the waves in the remote zone are a percentage of their height at the source, but when translated into real numbers, they can correspond to several metres. Thus, the eruption site of the Krakatoa volcano in 1883 had a height of 200 metres and a radius of three kilometres. Our calculations indicate that the height of an internal wave at a distance of 300 kilometres can be around 10 meters, which could still pose a danger,' comments Efim Pelinovsky, Chief Research Fellow at the International Laboratory of Dynamical Systems and Applications at HSE University in Nizhny Novgorod. 

See also:

First Digital Adult Reading Test Available on RuStore

HSE University's Centre for Language and Brain has developed the first standardised tool for assessing Russian reading skills in adults—the LexiMetr-A test. The test is now available digitally on the RuStore platform. This application allows for a quick and effective diagnosis of reading disorders, including dyslexia, in people aged 18 and older.

Low-Carbon Exports Reduce CO2 Emissions

Researchers at the HSE Faculty of Economic Sciences and the Federal Research Centre of Coal and Coal Chemistry have found that exporting low-carbon goods contributes to a better environment in Russian regions and helps them reduce greenhouse gas emissions. The study results have been published in R-Economy.

Centre for Language and Brain Begins Cooperation with Academy of Sciences of Sakha Republic

HSE University's Centre for Language and Brain and the Academy of Sciences of the Republic of Sakha (Yakutia) have signed a partnership agreement, opening up new opportunities for research on the region's understudied languages and bilingualism. Thanks to modern methods, such as eye tracking and neuroimaging, scientists will be able to answer questions about how bilingualism works at the brain level.

How the Brain Responds to Prices: Scientists Discover Neural Marker for Price Perception

Russian scientists have discovered how the brain makes purchasing decisions. Using electroencephalography (EEG) and magnetoencephalography (MEG), researchers found that the brain responds almost instantly when a product's price deviates from expectations. This response engages brain regions involved in evaluating rewards and learning from past decisions. Thus, perceiving a product's value is not merely a conscious choice but also a function of automatic cognitive mechanisms. The results have been published in Frontiers in Human Neuroscience.

AI Predicts Behaviour of Quantum Systems

Scientists from HSE University, in collaboration with researchers from the University of Southern California, have developed an algorithm that rapidly and accurately predicts the behaviour of quantum systems, from quantum computers to solar panels. This methodology enabled the simulation of processes in the MoS₂ semiconductor and revealed that the movement of charged particles is influenced not only by the number of defects but also by their location. These defects can either slow down or accelerate charge transport, leading to effects that were previously difficult to account for with standard methods. The study has been published in Proceedings of the National Academy of Sciences (PNAS).

Electrical Brain Stimulation Helps Memorise New Words

A team of researchers at HSE University, in collaboration with scientists from Russian and foreign universities, has investigated the impact of electrical brain stimulation on learning new words. The experiment shows that direct current stimulation of language centres—Broca's and Wernicke's areas—can improve and speed up the memorisation of new words. The findings have been published in Neurobiology of Learning and Memory.

Artificial Intelligence Improves Risk Prediction of Complex Diseases

Neural network models developed at the HSE AI Research Centre have significantly improved the prediction of risks for obesity, type 1 diabetes, psoriasis, and other complex diseases. A joint study with Genotek Ltd showed that deep learning algorithms outperform traditional methods, particularly in cases involving complex gene interactions (epistasis). The findings have been published in Frontiers in Medicine.

Cerium Glows Yellow: Chemists Discover How to Control Luminescence of Rare Earth Elements

Researchers at HSE University and the Institute of Petrochemical Synthesis of the Russian Academy of Sciences have discovered a way to control both the colour and brightness of the glow emitted by rare earth elements. Their luminescence is generally predictable—for example, cerium typically emits light in the ultraviolet range. However, the scientists have demonstrated that this can be altered. They created a chemical environment in which a cerium ion began to emit a yellow glow. The findings could contribute to the development of new light sources, displays, and lasers. The study has been published in Optical Materials.

Genetic Prediction of Cancer Recurrence: Scientists Verify Reliability of Computer Models

In biomedical research, machine learning algorithms are often used to analyse data—for instance, to predict cancer recurrence. However, it is not always clear whether these algorithms are detecting meaningful patterns or merely fitting random noise in the data. Scientists from HSE University, IBCh RAS, and Moscow State University have developed a test that makes it possible to determine this distinction. It could become an important tool for verifying the reliability of algorithms in medicine and biology. The study has been published on arXiv.

'The Six Handshakes Rule Applies to Social Media'

Ivan Samoylenko specialises in graph theory; in his third year of university, he developed an idea that later became the foundation of a highly cited academic article. In this interview with the HSE Young Scientists project, he speaks about the Watts-Strogatz small-world model, being a performer in the Bolshoi Children's Choir, and making the choice between science and industry.