Predicting volcanic eruptions could soon mirror weather forecasts, powered by recent breakthroughs in volcanology, a study published in Nature Communications, and advanced seismic monitoring.
Challenging the Soda Bottle Model with Gas Resorption
A study published in Nature Communications challenges long-held assumptions about volcanic eruptions. It reveals that gas resorption—rather than exsolution—may be the critical driver behind catastrophic events.
Researchers analyzed data from Japan’s Aso-4 eruption, which is 86,000 years old. They found that gases dissolving back into magma, instead of escaping, create the necessary eruption pressure.
Contrary to what was previously thought, it appears that the buoyancy of magma, influenced by its temperature and chemical makeup, is a critical factor in causing eruptions,
noted Dr. Catherine Booth, a key author of the study.
This theory contradicts the traditional “soda bottle” model. That model posited that gas bubbles forming in magma drive eruptions.
The new research shows that in large magma systems, resorption reduces compressibility. This makes the magma rigid and sensitive to new influxes of magma.
When gas is resorbed into the melt, the magma compressibility decreases significantly,
explained the study’s team. This change in state modulates how the volcano responds to recharge, which is the arrival of fresh, hot magma from deeper in the Earth.
Mapping Magma Buoyancy and Eruption Severity
Another study, led by researchers from Imperial College London and the University of Bristol, emphasizes the role of magma buoyancy in eruption severity.
We expanded our research deeper than most prior studies, focusing on magma’s origin point where extreme heat transforms solid rock into liquid magma deep below,
Booth explained.
The research found that magma buoyancy—determined by temperature and composition—determines whether an eruption is explosive or effusive.
As magma becomes lighter than the surrounding rock, it becomes buoyant—rising and breaking through the Earth’s surface to unleash its fiery power,
the study stated.
Longer magma storage at shallow depths can lead to less violent eruptions. Meanwhile, larger magma reservoirs may dissipate heat, reducing eruption intensity.
Our study not only advances our understanding of volcanic processes but also enhances the models that help predict these events,
Jackson said. However, the team acknowledged that current models still lack data on water and carbon dioxide content, which are critical to magma behavior.
Seismic Sensors and Machine Learning in the Field
Scientists are deploying advanced technologies to monitor volcanic activity with unprecedented precision. As part of this work, hundreds of seismometers and fiber-optic cables are being used to detect even the smallest earthquakes.
Machine learning algorithms analyze seismic data to identify hidden magmatic pathways. These programs have been used to process a huge volume of data far more proficiently and efficiently than scientists can manage alone,
the sources noted.
In Iceland, the Krafla Magma Testbed is described as the world’s first direct magma observatory.
It aims to drill into magma chambers to study processes in situ.
Drill all the way down to where there is some magma sitting at depth, and really see these processes in situ, rather than just seeing the results of them,
said Winder.
The Gap Between Instrumentation and Forecasting
Despite these advances, major challenges remain.
You would like to think, ‘OK, volcanoes are pretty well monitored.’ But they’re not,
said Roman.
Researchers are focusing on expanding monitoring to diverse volcanoes and refining models to include three-dimensional magma flow dynamics.
There’s no reason we can’t think that, at some point in the future, we can have volcano forecasts that are like weather forecasts,
Poland said. Achieving this, however, will require decades of consistent data collection across multiple eruption cycles.
