LONG-TERM GOALSThe primary long-term goal of our research is to develop optimal deployment strategies for drifter releases using templates derived from dynamical systems theory and to apply these to operational scenarios. The second goal is to improve current understanding of basic mesoscale and submesoscale oceanic processes. Both goals contribute to improved predictive capability of the marine environment. This research effort was initiated as a component of the DRI, Predictability of the Ocean and Atmosphere, and has contributed to the goals of that program by developing effective observation strategies for improved now-casts and forecasts of oceanic conditions. OBJECTIVESThree objectives were identified as important to achieving our long-term goals. First, integrate Lagrangian methods developed from dynamical systems theory into oceanographic applications. Second, use these methods to design optimal observing strategies with special emphasis on drifter deployments that achieve the maximum geographic coverage with the fewest units. Finally, apply the methodology to operational situations, specifically applications to data assimilating ocean models. APPROACHThe technical approach taken in this project builds on results obtained by the PI from prior ONR support as well as collaboration with investigators at other institutions. The approach has three basic components. The first is to objectively reconstruct Eulerian velocities either from data assimilating models or from synoptic current maps in a format that can be used for the Lagrangian analysis. Here we have adapted methods initiated by Rao and Schwab (1981) and used by Eremeev et al. (1992a,b) and Lipphardt et al. (2000) as well as others for rendering these velocity fields. The second part is to calculate the critical material curves from the velocity archives by Lagrangian analysis. Our approach is adapted from that used by Miller et al. (1997) and Poje and Haller (1999). Since then a number of new developments have occurred that may improve this approach in future applications.
The long-term goals of this research are to develop the requisite technology to design effective observation strategies that will maximize the capacity to predict mesoscale and submesoscale conditions so as to understand the physical processes responsible for these conditions and to provide the best possible now-casts and forecasts of oceanic conditions. OBJECTIVES There are three tightly integrated objectives. The first is to focus both oceanographic and dynamical systems approaches on developing optimal observing strategies. The common thread linking both approaches is Lagrangian analysis, and so this phase of the work addresses the question of how best to utilize Eulerian current maps constructed from disparate data and how to use the information contained therein to design optimal observing systems. The second objective will be to design an optimal observing strategy from a synthetic database. Here we will use primitive equation model simulations as the control. The last objective will be to apply this technology to the Gulf of Mexico where both high-resolution numerical model results and drifter data are available. APPROACH We approach the objectives in this effort by combining the oceanographic methodology of objective Eulerian current reconstruction initiated by Rao and Schwab (1981), Eremeev et al. 1992 and Chao et al. 1998 with dynamical systems techniques of invariant manifold calculations as presented in Poje and Haller (1999). During the first phase of the study, we shall utilize model flows where the Lagrangian
The long-term goal of this research is to develop the requisite technologies for effective observation strategies that provide the best possible now-casts and forecasts of oceanic conditions. This research contributes to the effort to predict mesoscale and submesoscale conditions and to understand the physical processes responsible for these conditions.
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