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Searching for Glacier-related Seismic Events in Greenland with Waveform Similarity and Machine Learning

Enhanced calving at the marine terminus has contributed to ice loss from the Greenland Ice Sheet at an accelerated rate over the past three decades. However, the characteristics, frequency, and scales of these calving events are poorly resolved, largely due to their challenging observational conditions. Glacial calving events can cause seismic signals, which are termed glacial quakes. Identifying glacial quakes through continuous seismic records enables remote, uniform monitoring of their occurrence, complementing intermittent field campaigns and remote sensing. Seismic signals of glacial quakes often differ from tectonic earthquakes, lacking high-frequency radiation, and conventional detection methods may fail in identifying these events. In this study, we analyze continuous waveform data recorded by regional seismic stations in Greenland in 2019 and search for events using waveform similarity and machine-learning methods. Waveform similarity is particularly useful in this context because many glacial quakes occur at the same locations with similar failure processes. We estimate event locations using back-projection techniques and classify detections into different types and families. Preliminary results suggest that the detected signals include glacial calving events and tectonic earthquakes, as well as additional waveform families that require further analysis to determine their physical origins. Many detections appear to be previously undocumented. The workflow developed here is readily transferable and can be adapted to other cryoseismic study regions. We aim to identify abundant and diverse glacier-related (and other) seismic signals in continuous records in Greenland, expanding and refining existing catalogs with new detection approaches.

Session: Cryoseismology: Advances in Technology and Scientific Discovery - I

Type: Oral

Room: Ballroom F

Date: 4/15/2026

Presentation Time: 02:15 PM (local time)

Presenting Author: Fengzhou Tan

Student Presenter: No

Invited Presentation: No

Poster Number:

Additional Authors