Overview
- Researchers imaged two of three inferred magma reservoirs to depths of about 10 kilometers, finding them composed of roughly 70% crystallized rock.
- The tomography indicates mostly stalled, crystallized magma that can episodically reheat, with daily movement inferred from surface emissions.
- The team trained machine-learning models to automatically detect and classify Popocatépetl tremors, enabling higher-resolution seismic imaging.
- The deeper third reservoir remains unresolved with the current dataset, and the scientists plan energy-loss analyses and additional monitoring to investigate it.
- Core results appear in the Journal of Volcanology and Geothermal Research, with a follow-up methods paper under review at the Journal of South American Earth Sciences.