Volcanologists Pursue a Better Way to Forecast Eruptions
In spite all the harm and havoc volcanic eruptions can wreak—even the nonfatal ones—scientists still cannot reliably forecast them. Although they have had success predicting dozens of eruptions, they lack a standard method.
“The field of volcanology is quite a long way behind fields like meteorology, in terms of developing forecasts,” says David Pyle, a volcanologist at the University of Oxford.
Volcanoes have complicated, unpredictable behavior—and, of course, much of their activity takes place underground, which makes them significantly harder to study and develop models for than, say, weather systems. “The real challenge at the moment is that for volcanoes where we have no observations of prior eruptions and where it’s not currently densely observed, it can be very difficult to anticipate what will happen next,” Pyle says.
He adds that the methods scientists use for eruption forecasts today “are pretty qualitative.” But a team of researchers at the University of Savoy Mont Blanc is attempting to develop a more reliable, accurate and data-driven approach to anticipate eruptions like the one at Eyjafjallajökull—and potentially create a daily or even hourly volcano forecast—using satellites and a method called data assimilation.
Data assimilation is widely used in fields like meteorology—our weather forecasts depend on it. The method combines a model for systems such as weather or climate with real-world data points to develop predictions about the future. The strength of this technique is that the model is continuously fine-tuned—it compares its predictions against the real-world data and self-corrects in near-real time.
In a new study published Wednesday in Frontiers in Earth Science, the Savoy researchers applied data assimilation to a volcano model to see if the technique could accurately predict an important parameter for volcanic eruptions: magma overpressure. This is the excess pressure created by the volcano’s magma pushing outward, relative to the inward pressure created by the overlying rock.
“For each volcano, there’s a critical overpressure value,” says Mary Grace Bato, lead author of the study and a Ph.D. fellow at the Institute of Earth Science in France. “If this value is attained, then you would know that in a few days or months, there might be an eruption.” Being able to predict how this element of the system changes could help volcanologists make better forecasts.
For their study, the team created a simplified model based on the Grímsvötn volcano, also in Iceland. They then used synthetic satellite data, on how the volcano’s exterior ground deformed, to inform the model over time and make predictions.
Bato offers a simple way to think about the relationship between ground deformation and magma overpressure: “Imagine that the volcano’s magma chamber is like a balloon. If you continuously fill this balloon with magma, the balloon inflates and causes the ground on top of it to deform. We can measure the deformation by using GPS or radar satellite data, and then we can infer the magma overpressure.”
The team can also use that satellite data to fine-tune their model’s predictions for magma overpressure in the future. Current practices do not use this type of physics-based technique, explains Daniel Dzurisin, a research geologist at the U.S. Geological Survey’s Cascades Volcano Observatory. He says today’s eruption forecasting relies on combining monitoring data with information from global volcanic databases, local knowledge of a volcano’s past behavior and scientific insight based on experience.
When the researchers compared their predictions to a simulation of the volcano, they found data assimilation was able to accurately forecast the shifts in magma overpressure. In addition to the technique’s forecasting strength, it also helped constrain the volcano’s underground features.
“It shows that scientists can use data assimilation to better understand various components and behaviors occurring inside the volcano,” such as the geometry of its magma chamber and the rate of magma flow inside that reservoir, Bato explains. “These are the parameters that are very difficult to infer since they are buried at huge depths, greater than 10 kilometers.”
Read full story at Scientific American