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Cluster Analysis of Thermal Icequakes Using the Seismometer to Investigate Ice and Ocean Structure (SIIOS): Implications for Ocean World Seismology
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  • Angela Marusiak,
  • Nicholas Schmerr,
  • Brad Avenson,
  • S. Hop Bailey,
  • Veronica Bray,
  • Peter Dahl,
  • Daniella DellaGiustina,
  • Erin Pettit,
  • Natalie Wagner,
  • Renee Weber
Angela Marusiak
University of Maryland

Corresponding Author:angela.marusiak@gmail.com

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Nicholas Schmerr
University of Maryland at College Park
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Brad Avenson
Silicon Audio
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S. Hop Bailey
University of Arizona, Lunar and Planetary Lab
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Veronica Bray
University of Arizona,Imperial College London
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Peter Dahl
University of Washington, Applied Physics Lab
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Daniella DellaGiustina
University of Arizona
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Erin Pettit
Oregon State University
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Natalie Wagner
University of Alaska Fairbanks
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Renee Weber
NASA Marshall Space Flight Center
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Introduction: Ocean Worlds are of high interest to the planetary community [1, 2] due to the potential habitability of their subsurface oceans [3–5]. Over the next few decades several missions will be sent to ocean worlds including the Europa Clipper [6], Dragonfly [7], and possibly a Europa lander [8]. The Dragonfly and Europa lander missions will carry seismic payloads tasked with detecting and locating seismic sources. The Seismometer to Investigate Ice and Ocean Structure (SIIOS) is a NASA PSTAR funded project that investigates ocean world seismology using terrestrial analogs. One goal of the SIIOS experiment is characterizing the local seismic environment of our field sites. Here we present an analysis of detected local events at our field sites at Gulkana Glacier in Alaska and in Northwest Greenland approximately 80 km North of Qaanaaq, Greenland (Fig. 1a). Both field sites passively recorded data for about two weeks. We deployed our experiment on Gulkana Glacier in September 2017 (Fig. 1b) and in Greenland in June 2018 (Fig. 1c). At Gulkana there was a nearby USGS weather station [9] which recorded wind data. Temperature data was collected using the MERRA satellite [10]. In Greenland we deployed our own weather station to collect temperature and wind data. Gulkana represents a noisier and more active environment: Temperatures fluctuated around 0C, allowing for surface runoff to occur during the day. The glacier had several moulins, and during deployment we heard several rockfalls from nearby mountains. In addition to the local environment, Gulkana is located close to an active plate boundary (relative to Greenland). This meant that there were more regional events recorded over two weeks, than in Greenland. Greenland’s local environment was also quieter, and less active: Temperatures remained below freezing. The Greenland ice was much thicker than Gulkana (~850 m [11] versus ~100 m [12, 13]) and our stations were above a subglacial lake. Both conditions can reduce event detections from basal motion. Lastly, we encased our Greenland array in an aluminum vault and buried it beneath the surface unlike our array in Gulkana where the instruments were at the surface and covered with plastic bins. The vault further insulated the array from thermal and atmospheric events. Event Detection and Clustering: To detect local events we filtered the data between 5-20 Hz. Using the Obspy module in python [14], we performed a short-term average/long-term average (STA/LTA) approach to determine where amplitudes spiked. For short term we used 1.5 seconds and 40 seconds and a ratio of 20 to detect events [15]. Through this approach we detect-ed 104 events at our Greenland site and 2252 events at our Gulkana site. The Gulkana site showed a strong correlation with both temperature and changes in temperature, while Greenland did not show this relationship [16]. Once we had a catalog of events, we performed a hierarchal cluster analysis to cluster events.