Instead of employing simulated data from the past decades using ocean models driven by reanalysed surface fluxes, we utilise an up-to-date description of simulated surface velocities which includes the assimilation of direct observational data. Here, we provide insights on surface drift simulations of objects for quasi-real-time applications. However, given the high spatial and temporal variability of real-world surface flows resulting from features such as mesoscale eddies, the results of such studies must be interpreted in a probabilistic context, often with large uncertainties. The model data generally stem from simulations that, to a large extent, faithfully represent the large-scale upper ocean circulation of the past decades. Such assessments require model data that allow for the connection between the coastal environment (as primary source of anthropogenic litter or pollution) and the open-ocean, and thus span wide spatial and temporal scales.

Supplementing these observations, simulations of pathways of floating objects in the marine environment are routinely undertaken, in particular for assessing the dispersion and accumulation of marine litter and pollution (e.g.

Since the latter part of the twentieth century, satellite-tracked drifting buoys continuously provide a wealth of information on ocean circulation and in-situ properties (Lumpkin etВ al. Most notably, NansenвЂ™s observations of ice drift in the Arctic led to the formulation of Ekman theory, which plays a central role in understanding the dynamics of ocean gyres, fronts, and upwelling, among others. The results have implications for other drift simulation applications.Дrift observations of objects near the surface of the ocean have led to fundamental advances in the understanding of ocean dynamics. Given the uncertainties associated with the timings of the debris sightings, we show that at least 5 items are required to achieve an optimal most probable crash-site region. The differences between the tracking approaches provide a measure of uncertainty which can be minimised by simulating a sufficiently large number of virtual debris. We consider: (1) How important is the influence of surface waves on the drift? (2) What are the relative benefits of forward- and backward-tracking in time? (3) Does including information from more items refine the most probable crash-site region? Our results highlight a critical contribution of Stokes drift and emphasise the need to know precisely the buoyancy characteristics of the items.

We use ocean currents simulated by an operational ocean model in conjunction with surface Stokes drift to determine the possible paths taken by the debris. Some of these items were recovered around the western Indian Ocean. The aircraft is assumed to have crashed in the Indian Ocean, leaving floating wreckage to drift on the surface. One pertinent example is Malaysia Airlines flight MH370. Modelling the drift of marine debris in quasi-real time can be of societal relevance.

Drifting lands unique items