Assessing the Lagrangian Predictive Ability of Navy Ocean Models

Abstract

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 ocean's 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, we've 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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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2009
Accession Number
ADA526751

Entities

People

  • Albert D. Kirwan
  • B. L. Lipphardt Jr.

Organizations

  • University of Delaware

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Abstracts
  • Acoustic Detectors
  • Flow
  • Fluid Flow
  • Geographic Regions
  • Information Operations
  • Navy
  • Particles
  • Reliability
  • Standards
  • Statistics
  • Stratified Fluids
  • Tactical Decision Aids
  • Three Dimensional
  • Trajectories
  • Transport Ships
  • Uncertainty

Fields of Study

  • Environmental science

Readers

  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers
  • Systems Analysis and Design