Supervisors: Alberto Naveira Garabato (lead, UoS), Eleanor Frajka-Williams (UoS), Rob Hall (UEA), Kurt Polzin (WHOI)
Case support: Rockland Scientific Instruments
Ocean turbulence—tiny millimeter scale eddies in the ocean—varies by several orders of magnitude with both space and time. Inadequate representation of the variability of ocean turbulence in numerical models is one of the leading causes of uncertainty in climate projects. However, quantifying these tiny fluctuations within all the larger-scale flows and fluctuations in the ocean is a challenge. Traditional measurements requiring sensitive probes sampling 512 times a second on quiet, free-falling instruments which is time consuming and requires continuous ship support by expensive research vessels. As a consequence datasets are sparse and rarely capture the sporadic nature of spatially- and temporally-varying ocean turbulence.
Turbulence sensors have recently been deployed on autonomous underwater vehicles including gliders (Creed et al. 2015; Palmer et al., 2015) and higher-powered vehicles (Kimura et al., 2016). These platforms offer a transformative approach to making measurements of spatially- and temporally-varying ocean turbulence, enabling measurements at scales not accessible by traditional methods (longer timescales, full time-depth resolution, etc.). However, uncertainties in how the turbulence sensors behave on these new platforms (e.g., associated with the glider flight model, variable flight speed and attack angle, vibrational and acoustic noise) can affect the measurements made at millimetre scale. In order to enable more widespread adoption of these new platforms, further development is needed.
This studentship will focus on a multi-platform comparison between turbulence measurements using both existing datasets and data to be collected. Existing datasets include from the Autosub Long Range (aka, Boaty McBoatface) expedition in the Southern Ocean as part of the DynOPO project (Dynamics of the Orkney Passage Outflow). New datasets will be collected using a MicroPods on a Seaglider east of the Bahamas as part of the MerMEED project (Mechanisms responsible for Mesoscale Eddy Energy Dissipation). These observations include both traditional and novel measurements, and will enable the student to develop the methods for using autonomous platforms for turbulence measurements.
The aims of the project will be to
Potential additional developments will include further developing a processing suite of software for microstructure measurements from autonomous platforms.
This project is ideal for a student with an interest or background in marine autonomous platforms, sensors and electronics, with experience in geospatial data analysis, time series analysis methods and software development, and an interest in oceanography and/or climate change.
The NEXUSS CDT provides state-of-the-art, highly experiential training in the application and development of cutting-edge Smart and Autonomous Observing Systems for the environmental sciences, alongside comprehensive personal and professional development. There will be extensive opportunities for students to expand their multi-disciplinary outlook through interactions with a wide network of academic, research and industrial / government / policy partners. The student will be registered at the University of Southampton and hosted at the University of Southampton/NOC, but will also spend time at University East Anglia.
The student will work in collaboration with scientists, technologists and the industry partner. They will gain experience in the measurement of ocean turbulence, and the use of autonomous platforms for Earth observation. Training will be provided in ocean glider piloting, numerical data analysis including spectral methods, hydrodynamic models, and optimization procedures, and seagoing experience in the Bahamas as part of the MerMEED project.
Support from CASE partner Rockland Scientific will be used to supplement the student stipend by £1000/year.
Background Reading:
Beaird et al. (2012) Dissipation of Turbulent Kinetic Energy Inferred from Seagliders: An Application to the Eastern Nordic Seas Overflows. Journal of Physical Oceanography.
Creed et al. (2015). Integration of a RSI microstructure sensing package into a Seaglider. Oceans 2015.
Frajka-Williams et al. (2011) Determining vertical velocities from Seagliders, Journal of Oceanic and Atmospheric Technology.
Kimura et al. (2016) Ocean mixing beneath Pine Island Glacier ice shelf, West Antarctica. Journal of Geophysical Research, 121:8496—8510.
To apply for this project, use the: apply for a NEXUSS CDT studentship