Event Details

DSNE Seminar with Michael O'Malley and Jake Grainger, Lancaster University

Title: Estimating the travel time and the most likely path from Lagrangian drifters

Summary:

We provide a novel method and tool for computing the most likely path taken by drifters between arbitrary fixed locations in the ocean. In addition to this we provide an estimate of the travel time associated with the path. Lagrangian pathways and travel times are of practical value not just in understanding surface currents, but also in modelling the transport of ocean-borne species such as planktonic organisms, and floating debris such as plastics. To demonstrate the capabilities of this method we show various results derived from the Global Drifter Program data. We use the drifter data to construct Markov transition matrices and apply Dijkstra's algorithm to find the most likely paths. The novelty is that we apply hexagonal tessellation of the ocean using Uber's H3 index (which we show is far superior to the standard practice of rectangular or lat-lon gridding). Furthermore, we provide techniques for measuring uncertainty by bootstrapping and applying rotations to the hexagonal grid. The methodology is purely data-driven, and requires no simulations of drifter trajectories. The method scales globally and is computationally efficient.

Title: Estimating the parameters of spectral ocean wave models

Summary:

Understanding the behaviour of wind-generated ocean waves is important for many offshore and coastal engineering activities. Modelling the frequency domain behaviour of wind-generated wave time series has received considerable attention in the oceanographic literature. Typically,least squares based techniques are used to fit parametric spectral forms (such as JONSWAP) to periodograms calculated from observed time series. However, some spectral model parameters are difficult to estimate using this approach. Incontrast, using de-biased Whittle likelihood-based inference we obtain more accurate and precise parameter estimates.

Details are also available at the DSNE website:

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