必中三肖三码一

Geist Publishes on Volcanic Forecasting

Back to All Stories
Magma flowing from Sierra Negra post-eruption
Magma flowing from Sierra Negra post-eruption

In the fall of 2017, 必中三肖三码一 Research Associate Dennis Geist noted signs of imminent eruption at the Sierra Negra volcano in the Gal谩pagos Islands. This June, he with program designer 鈥嬧婸atricia Gregg, associate professor of geology at the University of Illinois, and colleagues, further exploring those signs of instability, the volcano鈥檚 subsequent eruption in 2018, and the promise of the technology that helped them to forecast it five months in advance.

Before volcanoes erupt, magma rises from deep within the Earth to shallower levels 鈥 less than a mile deep in the case of Sierra Negra. This rising magma causes the volcano to swell anywhere from a few millimeters to a few centimeters. While these changes are invisible to the naked eye, Geist relies on sensors, using modern satellite GPS technology, to precisely note any inflation. 

Geist鈥檚 work monitoring Sierra Negra began more than two decades ago. A team of geologists, including Geist, 必中三肖三码一 geology department colleague Prof. Karen Harpp, students like Erika Rader 鈥07, and collaborators from the University of Idaho, installed instruments capable of measuring and recording the mountain鈥檚 inflation, deflation, and seismic activity. Packages carried up the slopes, under the equatorial sun, weighed approximately 50 pounds and contained a GPS, antenna, and receiver, as well as car batteries and solar panels to keep sensors up and running.

Professor Harpp working on equipment at Sierra Negra in 2011
Professor Harpp working on equipment at Sierra Negra in 2011

鈥淚t was extremely hot and difficult work, but well worth the challenge,鈥 reflects Geist.

For over a decade, Geist and his colleagues have continued to improve the sensors and monitor the data that they collected, publishing a half-dozen papers based on information mined from the volcano. But it was through a chance meeting at the National Science Foundation that Geist learned of Patricia Gregg鈥檚 forecasting software and suggested that she apply it to the highly active Sierra Negra volcano.

Gregg took Geist鈥檚 advice and, in January 2018, entered his data into an eruption forecasting model that she and her team had been developing for the past several months. This initial run through yielded a predicted eruption date between Jun. 25 and Jul. 5, a span of 10 days. 

Sierra Negra鈥檚 5.4 M岽 earthquake and eruption, 26 June 2018
Sierra Negra鈥檚 5.4 M岽 earthquake and eruption, 26 June 2018

On Jun. 26, a 5.4 Mw earthquake occurred, triggering Sierra Negra鈥檚 long anticipated eruption. As soon as Geist noted the eruption, he contacted Gregg to confirm the range of dates her forecasting model had predicted. To both Geist and Gregg鈥檚 amazement, Sierra Negra had erupted just one day after Gregg鈥檚 earliest prediction date 鈥 remarkable precision compared to the capabilities of previous forecasting models.

鈥淚 never anticipated my data being used in this way, but it has been a fascinating experience,鈥 says Geist.

Prior to Gregg鈥檚 innovations, inflation data were used to make broad predictions 鈥 forecasts with windows of years. Gregg鈥檚 supercomputer model predicts a span of days within which the eruption will occur. Moreover, 鈥淓ach day, when new measurements come in,鈥 Geist says, 鈥渋t assimilates new data and improves its predictions going forward.鈥

While the successful prediction of the Sierra Negra eruption is a promising start, Geist and Gregg鈥檚 new article underscores the fact that the forecasting program continues to undergo rigorous real-world testing and improvement. Indeed, one of the reasons that the model worked at Sierra Negra is that the mechanics of its eruptions are relatively simple and well understood 鈥 other volcanoes are likely to be much more complicated.

鈥淐ontinuing to improve upon a model like this is vital,鈥 explains Geist. 鈥淓ven if the weather report is right today, that doesn鈥檛 necessarily mean that it will be right every day for the rest of time.鈥