| Summary: | Hyperbolic Lagrangian Coherent Structures (LCS) are time-dependent manifolds that organize tracer patterns in chaotic flow systems. In two-dimensional flow systems, LCSs take the shape of one-dimensional curves which act as the locally most attracting or repelling structures over a finite time interval. LCSs yield a description of the flow field itself by defining transport barriers which attract or repel material, without allowing for propagation through them. Generally, Lagrangian descriptions are prone to large errors and uncertainty due to non-linear and turbulent oceanic and atmospheric flow fields. Although extensive studies on LCSs have previously been conducted, few studies investigate the implications of this inherent uncertainty in chaotic flow fields on LCSs. This study investigates the sensitivity of LCSs to uncertainty in the flow field of realistic Oceanic General Circulation Models. Two flow systems are considered: 1) A simplified controlled analytical double-gyre and 2) turbulent velocity data from the Barents-2.5 EPS model, simulating realistic ocean conditions in the Barents Sea and off the coast of northern Norway. The coastal region around the Lofoten-Vesterålen islands in northern Norway is chosen as the study region due to its ecological importance. The Barents-2.5 EPS includes 24 realizations of the same scenario, each with either perturbed initial conditions or forcing that can lead to large differences in the flow field. An ensemble of the double-gyre system is also produced by perturbing the dependent variables. I develop an LCS detection software utilizing the Finite-Time Lyapunov Exponent approach. The software and resulting LCSs are verified by computing LCSs in both flow systems. I then investigate whether these correspond to independently simulated particle trajectories to study their effect on material transport. Then, LCSs are computed in all ensemble members of the double-gyre ensemble and Barents-2.5 EPS. Following variations in the velocity fields between ensemble members, ...
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