Uncertainties in the finite-time Lyapunov exponent in an ocean ensemble prediction model
<p>Lagrangian coherent structures (LCSs) are transient features in the ocean circulation that describe particle transport, revealing information about transport barriers and accumulation or dispersion regions. The method of finite-time Lyapunov exponents (FTLEs) uses Lagrangian data to approxi...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2025-02-01
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| Series: | Ocean Science |
| Online Access: | https://os.copernicus.org/articles/21/401/2025/os-21-401-2025.pdf |
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| Summary: | <p>Lagrangian coherent structures (LCSs) are transient features in the ocean circulation that describe particle transport, revealing information about transport barriers and accumulation or dispersion regions. The method of finite-time Lyapunov exponents (FTLEs) uses Lagrangian data to approximate LCSs under certain conditions. In this study FTLEs are used to characterize flow field features in a high-resolution regional ocean forecast system. Generally, trajectory simulations, such as Lagrangian trajectories, inherit uncertainty from the underlying ocean model, bearing substantial uncertainties as a result of chaotic and turbulent flow fields. As the FTLE characterizes the flow, which may impact particle transport, we aim to investigate the uncertainty of FTLE fields at any given time using an ensemble prediction system (EPS) to propagate velocity field uncertainty into the FTLE analysis. In addition, velocity fields often evolve rapidly in time, and we therefore also evaluate the time variability of FTLE fields. We find that averaging over ensemble members can reveal robust FTLE ridges, i.e., FTLE ridges that exist across ensemble realizations. Likewise, time averaging can reveal persistent FTLE ridges, i.e., ridges that occur over extended periods of time. In addition, large-scale FTLE ridges are more robust and persistent than small-scale ridges. Averaging of FTLE fields is thus effective at removing short-lived and unpredictable structures and may provide the means to employ FTLE analysis in forecasting applications that require the ability to separate uncertain from certain flow features.</p> |
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| ISSN: | 1812-0784 1812-0792 |