Abstract
This paper proposes a fuzzy number—based framework for quantifying and propagating uncertainties through a model for the trajectories of objects drifting at the ocean surface. Various sources of uncertainty that should be considered are discussed. This model is used to explore the effect of parameterizing direct wind drag on the drifting object based on its geometry, and using measured winds to parameterize shear and rotational dynamics in the ocean surface currents along with wave-driven circulation and near-surface wind shear. Parameterizations are formulated in a deterministic manner that avoids the commonly required specification of empirical leeway coefficients. Observations of ocean currents and winds at Ocean Station Papa in the northeast Pacific are used to force the trajectory model in order to focus on uncertainties arising from physical processes, rather than uncertainties introduced by the use of atmospheric and hydrodynamic models. Computed trajectories are compared against observed trajectories from five different types of surface drifters, and optimal combinations of forcing parameterizations are identified for each type of drifter. The model performance is assessed using a novel skill metric that combines traditional assessment of trajectory accuracy with penalties for overestimation of uncertainty. Comparison to the more commonly used leeway method shows similar performance, without requiring the specification of empirical coefficients. When using optimal parameterizations, the model is shown to correctly identify the area in which drifters are expected to be found for the duration of a seven day simulation.
Highlights
The ability to respond to emergencies such as marine contaminant spills and search and rescue efforts is directly linked with the ability to predict the trajectories of objects drifting at the ocean surface (Daniel et al, 2002; Breivik and Allen, 2008; Davidson et al, 2009; Butler, 2015)
During this time the dispersion of the cluster of Surface Circulation Tracker (SCT) drifters becomes comparable to the scale of the 0.67 membership level, which suggests that the size of these membership levels corresponds well with natural dispersion processes associated with unresolved high-frequency fluctuations in the forcing data
Uncertainty in surface drift trajectory predictions is of significant importance when responding to marine contaminant spills and performing search and rescue operations, along with a plethora of other applications
Summary
The ability to respond to emergencies such as marine contaminant spills and search and rescue efforts is directly linked with the ability to predict the trajectories of objects drifting at the ocean surface (Daniel et al, 2002; Breivik and Allen, 2008; Davidson et al, 2009; Butler, 2015). Drift trajectories of floating objects are governed by currents and winds at the very surface of the ocean. These remain persistently difficult to measure (Soloviev and Lukas, 2014), and the. Currents and winds used to force drift trajectory simulations are usually obtained from numerical circulation models, which introduces further uncertainty into the problem as these models are by necessity a simplification of reality. Model data and associated uncertainties will be considered in future work, since the uncertainties in observations used to verify the model data must first be established in order to accurately estimate the uncertainties in modeled data
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