About the project
Sea ice is vital for global climate, and coverage is reducing with global warming; current sea-ice thickness measurements have large uncertainties. We will develop robust ice quantification methods using seismo-acoustic measurements from autonomous vehicles traversing under the ice, which can be used to ground truth satellite data.
We will develop physics based model for improved measurements of sea ice thickness and physical properties from seismo-acoustic measurements. Critical to efficacy of this model is the detailed understanding of elastic wave propagation in sea ice and the establishment of well-defined relations between seismo-acoustic and physical properties of interest, including ice thickness, composition (ice, brine, air content and structure), anisotropy and mechanical properties.
We will use National Oceanography Centre Southampton's (NOCS) and the University of Southampton's world-leading geophysics and geomechanics laboratories and related facilities to conduct a range of experiments on synthetic sea ice, including X-ray CT imaging and quantification of ice structure, to establish a comprehensive database for both compressional and shear waves. This database will inform the development of bespoke theoretical models of elastic wave propagation in poro-visco-elastic media suitable for sea ice remote sensing. We will test these models with real data from the Arctic using a specially designed sonar mounted on an autonomous underwater vehicle (AUV) in collaboration with NOCS' Marine Autonomous Robotic Systems. Ultimately, we will develop suitable inversion algorithms for use in operational deployments of under ice sonars.
The output will include development of a novel database of the seismo-acoustic and mechanical properties of sea ice relevant to a wide range of Arctic oceanographic (e.g. ocean acoustics, ice dynamics modelling) and engineering (e.g. air strips and seafloor structures) applications. We expect this study to underpin the implementation of an operational autonomous underwater sonar system for sea ice thickness calibrations and mapping in finer detail than is currently possible.
You will also be supervised by other organisations, including Dr Sourav Sahoo (lead supervisor), Professor Angus Best, Dr Gaye Bayrakci, and Dr Oliver Sanford.