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SSF-Svalbard Science Forum

The CalvingSEIS experiment

Alternative title: CalvingSEIS: Dynamisk istapp kvantifisert gjennom seismikk øyene

Awarded: NOK 0.40 mill.

About 40% of global glaciers and ice caps, excluding ice sheets of Greenland and Antarctica, loose mass through iceberg calving. This dynamic ice loss is a sensitive component of the mass transfer from glaciers to oceans through a number of feedback processes with climate. Current models are currently not equipped to realistically predict dynamic ice loss, mainly because long-term continuous calving records are inexistent. CalvingSEIS aims to produce continuous calving records using combined passive seismic/acoustic strategies; the only technique able to capture rapid calving events, continuously, and back through time over decades. CalvingSEIS will focus on the glaciers in Kongsfjord, Svalbard because the research village of Ny Ålesund houses a passive seismic instrument since 1994 and is only 15 km from one of the fastest flowing and most heavily studied glaciers in Svalbard, Kronebreen. Through innovative, multi-disciplinary monitoring techniques combining fields of seismology and bioacoustics, individual calving events will be detected and located autonomously. CalvingSEIS will generate a catalogue of calving events using state-of-the-art terrestrial remote sensing techniques to measure calving ice volumes, velocities, and ice-ocean interactions. This forms the basis for scaling the calving record to mass loss and will invoke process-based understanding at the transition zone between glacier and ocean. Underwater bio-acoustic sensors will collect not only glacier sounds, but record the entire fjord soundscape instigating studies between biotic, abiotic and anthropogenic components; e.g. marine animal interaction with glacier sounds from calving and melting. The dynamic ice loss timeseries can reveal fine scale processes and key climatic-dynamic feedbacks between glacier calving, climate history, topographic setting, terminus evolution and fjord conditions and form an unprecedented dataset for developing, calibrating and validating glacier dynamic models.

About 40% of global glaciers and ice caps (excluding Greenland and Antarctica) loose mass through iceberg calving, while current models (e.g. in the IPCC) are currently not equipped to realistically predict dynamic ice loss, mainly because long-term continuous calving records are inexistent. Combined seismic/acoustic strategies are the only technique able to capture rapid calving events, continuously, and back through time over decades. CalvingSEIS aims to produce high temporal resolution, continuous calving records for the glaciers in Kongsfjord, Svalbard, and in particular for the Kronebreen glacier laboratory. Through innovative, multi-disciplinary monitoring techniques combining fields of seismology and bioacoustics, individual calving events will be detected and located autonomously and methods to quantify calving ice volumes directly from the seismic and acoustic signals will be developed. Scaling seismic/acoustic signals to calving ice volumes require calibration. CalvingSEIS will generate a detailed catalogue of calving events employing state-of-the-art terrestrial remote sensing techniques to measure calving ice volumes, velocities, and ice-ocean interactions. Experimental terrestrial remote sensing observations and investigations will further invoke process-based understanding at the transition zone between glacier and ocean. The underwater bio-acoustic sensors will collect not only glacier sounds, but record the entire fjord soundscape instigating studies between biotic, abiotic and anthropogenic components; e.g. marine animal interaction with glacier sounds from calving and melting. The main project goal to generate a dynamic ice loss timeseries will reveal fine scale processes and key climatic-dynamic feedbacks between glacier calving with climate history, topographic setting, terminus evolution and fjord conditions. This timeseries will form an unprecedented dataset for developing, calibrating and validating glacier dynamic models.

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SSF-Svalbard Science Forum