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Assessing the Lagrangian Predictive Ability of Navy Ocean Models

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Our long-term goal is better understanding of the processes that influence ocean transport at all scales. We focus on the sub-mesoscale and mesoscales because they represent the greatest challenge both for modeling and observing the ocean, since the oceans response at these scales is both nonlinear and episodic. Our recent efforts emphasize the application of Lagrangian analysis tools to ocean velocity archives for studying transport processes. With prior ONR support, we have quantified many Lagrangian properties of synoptic ocean data archives, including both regional ocean models and coastal HF radar measurements. We have also explored the application of dynamical systems tools to study the Lagrangian properties of these archives. More recently, as we have compared observed near-surface drifter trajectories with those predicted from Navy ocean models, weve found that the typical Lagrangian prediction horizon for these models is no more than 24-48 hours. As Navy operators begin integrating Lagrangian forecasts into tactical decision aids for acoustic problems, the fidelity of these forecasts becomes crucial. Thus, we are motivated to quantify the uncertainty in Navy Lagrangian forecasts and develop new analysis products that communicate this uncertainty to fleet operators in an accessible way.

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  • Physical and Dynamic Oceanography
  • Active and Passive Radar Detection and Equipment
  • Fluid Mechanics

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