Assessment of drift prediction in ocean models using Lagrangian analysis techniques

Institution: University of Waterloo
Theme: Environmental change
Area of Vulnerability: Marine ecosystems/living resources
Project Complete

Supervisors

  • Marek Stastna
  • Simon St-Onge Drouin
  • Graig SutherlandUniversity of Waterloo
Funding Call
Partner Fund
Region
All
Years
2020, 2021, 2022
Funded By
Network Centres of Excellence (NCE)

Call

RQM/MEOPAR TReX Graduate Students & Postdoc Awards

The project is focused on the evaluation of Lagrangian techniques (i.e., the mathematics describing the motion of ocean floats) to provide insight on how to improve drift prediction in ocean forecast models. The Lagrangian techniques are (a) the computation of finite-scale Lyapunov exponents to study dispersion at different length scales and, (b) calculating finite-time Lyapunov exponents to identify Lagrangian coherent structures. The improvement of drift and dispersion models have several real-world applications including supporting search and rescue operations, planning for oil spill response, and tracking marine pollution and contaminants.

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