Drifter Launch Strategies Based on Lagrangian Templates

Poje, Andrew C.; Toner, M.; Kirwan, A. D.; Jones, Christopher K. R. T.

doi:10.1175/1520-0485(2002)032<1855:dlsbol>2.0.co;2

Cited by 38 publications

(26 citation statements)

References 24 publications

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“…Behringer et al (1991), Bower (1991), Samelson (1992), Dutkiewicz et al (1993), Meyers (1994), Duan and Wiggins (1996), Rogerson et al (1999), Poje and Haller (1999), Coulliette and Wiggins (2001), Yuan et al (2001), Balasuriya and Jones (2001), Balasuriya (2001), Poje et al (2002), Waseda and Mitsudera (2002), Kuznetsov et al (2002), Miller et al (2002), and Kirwan et al (2003).…”

Section: Introductionmentioning

confidence: 99%

Computation of hyperbolic trajectories and their stable and unstable manifolds for oceanographic flows represented as data sets

Mancho

Small

Wiggins

2004

Nonlin. Processes Geophys.

115

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Section: Introductionmentioning

confidence: 99%

Computation of hyperbolic trajectories and their stable and unstable manifolds for oceanographic flows represented as data sets

Mancho

Small

Wiggins

2004

Nonlin. Processes Geophys.

115

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“…During the third year (FY 2001) an optimal deployment strategy was applied to a double gyre model. As shown in Poje et al (2002) the strategy based on dynamical systems concepts provided the best drifter dispersal and consequent reconstruction of the Eulerian velocity field.…”

Section: Work Completedmentioning

confidence: 95%

“…The templates developed in this study for optimal deployment of drifters are documented in Poje et al (2002) and the report on the LWAD experiment is in the process of being adopted by NAVO for some operational situations. The CO-PI, Dr. M. Toner, is leaving the University of Delaware to take a position there to spearhead this effort.…”

Section: Transitionsmentioning

confidence: 99%

Enhanced Ocean Predictability Through Optimal Observing Strategies

Kirwan¹,

Toner²,

Michael³

2003

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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.

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“…The expenses related to data acquisition and processing dictate that an effective method should be used for sensor deployment to ensure that the maximum amount of data is obtained from the investigation, while minimizing associated costs [10].…”

Section: Introductionmentioning

confidence: 99%

“…Depending upon the desired data, deploying sensors within, external to, or along the manifolds will be ideal for generating investigation appropriate data [10].…”

Section: Introductionmentioning

confidence: 99%

Assessing Relative Dispersion

Redd¹,

Moghraby²,

Tillman³

2017

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We assess the four point method of relative dispersion proposed by Jones and Winkler to identify the hyperbolic trajectories of a system. We sample a discrete analog to a quasi-geostrophic, single layered flow field and perform a comparison of the dispersion of neighboring points after iteration. We evaluate our method by performing a transformation to ( ) , x y space and comparing the trajectories corresponding to maximum dispersion with the ( ) , x y values of trajectories of the Standard map, derived from traditional techniques. We perform a similar evaluation using a 2D Ross by wave. We show that the method of relative dispersion is able to generate 2 nd order accurate (on the scale of the discretization) hyperbolic trajectories.

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Drifter Launch Strategies Based on Lagrangian Templates

Cited by 38 publications

References 24 publications

Computation of hyperbolic trajectories and their stable and unstable manifolds for oceanographic flows represented as data sets

Computation of hyperbolic trajectories and their stable and unstable manifolds for oceanographic flows represented as data sets

Enhanced Ocean Predictability Through Optimal Observing Strategies

Assessing Relative Dispersion

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