Improving Lagrangian Predictability by Blending Drifter Observations with Model Velocities
Helga S. Huntley, B. L. Lipphardt, Jr., A.D. Kirwan, Jr.
University of Delaware
(Abstract received 08/12/2009 for session D)
ABSTRACT
Even today’s state-of-the-art ocean models struggle with meeting desired Lagrangian predictability targets. We investigate the potential for decreasing Lagrangian prediction errors by applying a constrained normal mode analysis (NMA), blending drifter observations with model velocity fields. The energy spectrum of an unconstrained NMA and its variability are discussed, as well as the effects of parameter choices. The constrained NMA technique is initially presented in a perfect model simulation, where the “true” velocity field is known and the result can be directly assessed in both Lagrangian and Eulerian metrics. Finally, we will show results from a recent experiment in the East Asia Sea, where real observations were assimilated into operational ocean model hindcasts.
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