Modelling acoustic propagation beneath Antarctic sea ice using measured environmental parameters

• Published in: Deep Sea Research Part II: Topical Studies in Oceanography
• Main Authors: Alexander, P., Duncan, Alec, Bose, N., Williams, G.
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: Pergamon 2016
• Subjects: Antarctic; The Antarctic; Antarc*; Antarctica; Sea ice
• Online Access: https://hdl.handle.net/20.500.11937/4608; https://doi.org/10.1016/j.dsr2.2016.04.026

Autonomous underwater vehicles are improving and expanding in situ observations of sea ice for the validation of satellite remote sensing and climate models. Missions under sea ice, particularly over large distances (up to 100. km) away from the immediate vicinity of a ship or base, require accurate acoustic communication for monitoring, emergency response and some navigation systems. We investigate the propagation of acoustic signals in the Antarctic seasonal ice zone using the BELLHOP model, examining the influence of ocean and sea ice properties. We processed available observations from around Antarctica to generate input variables such as sound speed, surface reflection coefficient (R) and roughness parameters. The results show that changes in the sound speed profile make the most significant difference to the propagation of the direct path signal. The inclusion of the surface reflected signals from a flat ice surface was found to greatly decrease the transmission loss with range. When ice roughness was added, the transmission loss increased with roughness, in a manner similar to the direct path transmission loss results. The conclusions of this work are that: (1) the accuracy of acoustic modelling in this environment is greatly increased by using realistic sound speed data; (2) a risk averse ranging model would use only the direct path signal transmission; and (3) in a flat ice scenario, much greater ranges can be achieved if the surface reflected transmission paths are included. As autonomous missions under sea ice increase in scale and complexity, it will be increasingly important for operational procedures to include effective modelling of acoustic propagation with representative environmental data.