Standard volcanic monitoring looks at specific signals: high-frequency tremor (magma movement), GPS deformation (surface swelling), gas emissions. Each requires dedicated analysis. Eruption prediction remains difficult despite multi-instrument networks.
A single broadband seismometer at Piton de la Fournaise volcano detected “jerk” signals — very low frequency transients in horizontal ground motion and tilt caused by fracture openings as magma pushes underground. These signals appeared hours before eruptions with 92% success rate over a decade of data. The signal was always in the seismometer recordings. Nobody was looking at that frequency band.
The through-claim: the signal you need is often already in the data you have, in a frequency band you weren't attending to. The broadband seismometer records continuously across a wide frequency range. Volcanic monitoring protocols analyzed the high-frequency content (tremor) and the very lowest frequencies (tilt via GPS). The jerk signal occupies the middle — low enough to be ignored by tremor analysis, high enough to be missed by deformation monitoring. A gap in attention, not a gap in data.
The instrument didn't need to change. The attention did. The 92% success rate means this signal is among the most reliable eruption precursors ever identified — and it's been sitting in archived seismic data worldwide, unexamined, at every volcano with a broadband station.
The pattern generalizes: when monitoring systems are designed around known signal types, they create blind spots at the boundaries between frequency bands. The most informative signal isn't necessarily the one you designed your analysis to find. Sometimes the best prediction hides in the data you already collect but don't examine.