A dataset of direct observations of sea ice drift and waves in ice.

Variability in sea ice conditions, combined with strong couplings to the atmosphere and the ocean, lead to a broad range of complex sea ice dynamics. More in-situ measurements are needed to better identify the phenomena and mechanisms that govern sea ice growth, drift, and breakup. To this end, we have gathered a dataset of in-situ observations of sea ice drift and waves in ice. A total of 15 deployments were performed over a period of 5 years in both the Arctic and Antarctic, involving 72 instruments. These provide both GPS drift tracks, and measurements of waves in ice. The data can, in turn, be used for tuning sea ice drift models, investigating waves damping by sea ice, and helping calibrate other sea ice measurement techniques, such as satellite based observations.

Inversion of surficial sediment thickness from under-ice acoustic transmission measurement.

The under-ice acoustic transmission experiment of 2013, conducted under ice cover in the Fram Strait, was analyzed for bottom interactions for the purpose of developing a model of the seabed. Using the acoustic signals, as well as data from other sources, including cores, gravimetric, refraction, and seismic surveys, it was deduced that the seabed may be modeled as a thin surficial layer overlaid on a deeper sediment. The modeling was based on the Biot-Stoll model for acoustic propagation in porous sediments, aided by more recent developments that improve parameter estimation and depth dependence due to consolidation. At every stage, elastic and fluid approximations were explored to simplify the model and improve computational efficiency. It was found the surficial layer could be approximated as a fluid, but the deeper sediment required an elastic model. The full Biot-Stoll model, while instrumental in guiding the model construction, was not needed for the final computation. The model could be made to agree with the measurements by adjusting the surficial layer thickness.

Measured and modeled acoustic propagation underneath the rough Arctic sea-ice.

A characteristic surface duct beneath the sea-ice in the Marginal Ice Zone causes acoustic waves to be trapped and continuously interact with the sea-ice. The reflectivity of the sea-ice depends on the thickness, the elastic properties, and its roughness. This work focuses on the influence of sea-ice roughness on long-range acoustic propagation, and on how well the arrival structure can be predicted by the full wave integration model OASES. In 2013, acoustic signals centered at 900 Hz were transmitted every hour for three days between ice-tethered buoys in a drifting network in the Fram Strait. The experiment was set up to study the signal stability in the surface channel below the sea-ice. Oceanographic profiles were collected during the experiment, while a statistical description of the rough sea-ice was established based on historical ice-draft measurements. This environmental description is used as input to the range independent version of OASES. The model simulations correspond fairly well with the observations, despite that a flat bathymetry is used and the sea-ice roughness cannot be fully approximated by the statistical representation used in OASES. Long-range transmissions around 900 Hz are found to be more sensitive to the sea-ice roughness than the elastic parameters.

Identification and quantification of soundscape components in the Marginal Ice Zone.

Acoustic experiments using an integrated ice station were carried out during August 2012 and September 2013 in the Marginal Ice Zone (MIZ) of Fram Strait. The two experiments lasted four days each and collected under-ice acoustic recordings together with wave-in-ice and meteorological data. Synthetic aperture radar satellite data provided information on regional ice conditions. Four major components of the under-ice soundscape were identified: ship cavitation noise, seismic airgun noise, marine mammal vocalizations, and natural background noise. Ship cavitation noise was connected to heavy icebreaking. It dominated the soundscape at times, with noise levels (NLs) 100 km from the icebreaker increased by 10-28 dB. Seismic airgun noise that originated from seismic surveys more than 800 km away was present during 117 out of 188 observation hours. It increased NLs at 20-120 Hz by 2-6 dB. Marine mammal vocalizations were a minor influence on measured NLs, but their prevalence shows the biological importance of the MIZ. The 10th percentile of the noise distributions was used to identify the ambient background noise. Background NLs above 100 Hz differed by 12 dB between the two experiments, presumably due to variations in natural noise sources.