To better predict explosive, fiery volcanic activity, Cornell geologists have proposed a new classification system to discern the stages of a volcano’s unrest – as seen from smart, perceptive satellites.
“This proposal will enable us to quickly analyze the type of geologic behavior being produced at each active volcano and identify other volcanoes that produce a similar behavioral pattern,” said Kevin Reath, postdoctoral researcher in earth and atmospheric sciences, and lead author of research published Jan. 5 in Geochemistry, Geophysics, Geosystems, a journal of the American Geophysical Union.
“Using satellite data and physical trends,” Reath said, “we can compare information on multiple volcanoes to better predict volcanic activity.”
More than 800 million people around the world live within 60 miles of an active volcano, according to the researchers. To mitigate the peril, the scientists on this paper suggest to more fully utilize long‐term volcanic monitoring from satellites, to complement labor-intensive ground monitoring for deformation, outgassing and other thermal signals that may precede an eruption.
Currently, ground‐based monitoring is essential for tracking volcanic activity, but those instruments are available at fewer than half of the world’s potentially active volcanoes, Reath said.
Finding a consistent, accurate way to monitor active volcanoes from multiple satellites would be ideal, Reath said. The group applied new models to satellite observations at 47 of the most active volcanoes in Latin America. Among those active volcanoes, he said, 44 had a dataset robust enough to classify and cluster them into groups.
The proposed new schematic suggests classifying volcanoes in one of three ways: open, closed or eruptive. An example of an open system was Isluga, a volcano in Chile near the Bolivian border. After a period of volcanic unrest 10 years ago, the volcano calmed in 2015, when outgassing and thermal output – two of the three parameters considered – decreased.
As an example of a closed system, the Sierra Negra volcano in Ecuador, was classified based on a third parameter: surface deformation measurements.
“In looking at our first 47 volcanoes, we wanted to understand the data available and to see if this idea was feasible or not,” said Reath. “Now, we’re now developing conceptual models based on the observed unrest.”
Reath’s said next steps will be to develop quantitative models to more precisely determine the volcanic activity occurring below the volcanoes’ surfaces, as well as the factors that are influencing this activity.
Said Reath: “It’s really promising for the future to better understand what’s happening to the volcanoes with sensors from above.”
Other contributors included: Matt Pritchard, professor in the Department of Earth and Atmospheric Sciences; Juliet Biggs, University of Bristol, United Kingdom; Benjamin Andrews, Smithsonian Institution; Susanna K. Ebmeier, University of Leeds, U.K.; Marcos Bagnardi, Társilo Girona and Paul Lundgren, all of the Jet Propulsion Laboratory, California Institute of Technology; Taryn Lopez, University of Alaska, Fairbanks; and Michael Poland, U.S. Geological Survey.
This work was supported by funding from NASA and the U.S. Geological Survey.