ALBERT

Description: We present new results from a multiyear effort to record environmental signals in the Beaufort Sea using distributed acoustic sensing (DAS). We collected seafloor DAS data on a 36-km long segment of telecom dark fiber for eight one-week intervals in 2021 and 2022. The eight data collects comprise two samplings of each Arctic “season” (ice bound, ice free, and partial ice coverage during freezing and breakup). We recorded icequakes, floating sea-ice collisions, ice grounding events, ice flexural-gravity waves excited by winds, currents, and hovercrafts, ocean gravity waves, earth microseisms, and submarine soil/permafrost resonance. We have used these signals to characterize both sea ice extent and sea-ice thickness in the Beaufort Sea. Sea ice-extent is determined by clustering ambient noise data in 30-minute windows using a convolutional neural network. The presence or absence of ocean gravity waves is the dominant factor in the ice/no-ice clustering. Sea ice thickness is estimated from the inversion of ice flexural-gravity wave dispersion curves. This novel application has the added benefit of simultaneously inverting for snow thickness on the ice sheet, a confounding factor in other remote sensing methods. Ocean gravity wave parameters will also be presented. Comparison with wave buoys purposefully deployed above the fiber indicates that DAS can capture low-frequency waves with high spatial resolution during both open water and partially ice-covered periods. SNL is managed and operated by NTESS under DOE NNSA contract DE-NA0003525