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Title: Lagrangian ocean analysis: Fundamentals and practices

Lagrangian analysis is a powerful way to analyse the output of ocean circulation models and other ocean velocity data such as from altimetry. In the Lagrangian approach, large sets of virtual particles are integrated within the three-dimensional, time-evolving velocity fields. A variety of tools and methods for this purpose have emerged, over several decades. Here, we review the state of the art in the field of Lagrangian analysis of ocean velocity data, starting from a fundamental kinematic framework and with a focus on large-scale open ocean applications. Beyond the use of explicit velocity fields, we consider the influence of unresolved physics and dynamics on particle trajectories. We comprehensively list and discuss the tools currently available for tracking virtual particles. We then showcase some of the innovative applications of trajectory data, and conclude with some open questions and an outlook. Our overall goal of this review paper is to reconcile some of the different techniques and methods in Lagrangian ocean analysis, while recognising the rich diversity of codes that have and continue to emerge, and the challenges of the coming age of petascale computing.
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  1. Imperial College, London (United Kingdom); Utrecht Univ. (Netherlands)
  2. National Oceanic and Atmospheric Administration (NOAA), Princeton, NJ (United States)
  3. Columbia Univ., New York, NY (United States)
  4. Scottish Association for Marine Science, Oban (United Kingdom)
  5. Imperial College, London (United Kingdom)
  6. GEOMAR Helmholtz Centre for Ocean Research, Kiel (Germany)
  7. National Centre for Scientific Research (CNRS), Brest (France)
  8. Florida State Univ., Tallahassee, FL (United States)
  9. Univ. of Miami, FL (United States)
  10. Catholic Univ. of Louvain (Beligium); Delft Univ. of Technology (Netherlands)
  11. Stockholm Univ. (Sweden)
  12. Princeton Univ., NJ (United States); Massachusetts Inst. of Technology (MIT) and Woods Hold Oceanographic Inst. Joint Program in Oceanography, Cambridge, MA (United States)
  13. Univ. of Southampton (United Kingdom)
  14. Univ. of New South Wales, Sydney, NSW (Australia)
  15. British Anarctic Survey, Cambridge (United Kingdom); Univ. of Oxford (United Kingdom)
  16. GEOMAR Helmholtz Centre for Ocean Research, Kiel (Germany); Abilene Christian Univ., TX (United States)
  17. Univ. of Oxford (United Kingdom)
  18. National Oceanograhy Centre, Cambridge (United Kingdom)
  19. Plymouth Marine Lab., Plymouth (United Kingdom)
  20. Sukkur Inst. of Buisness Adminstration (Pakistan); Delft Univ. of Technology (Netherlands)
  21. Yale Univ., New Haven, CT (United States)
  22. California Inst. of Technology (CalTech), Pasadena, CA (United States)
  23. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  24. Imperial College, London (United Kingdom); Univ. of New South Wales, Sydney, NSW (Australia)
Publication Date:
Report Number(s):
Journal ID: ISSN 1463-5003
Grant/Contract Number:
AC52-06NA25396; SC0012457
Published Article
Journal Name:
Ocean Modelling
Additional Journal Information:
Journal Volume: 121; Journal Issue: C; Journal ID: ISSN 1463-5003
Research Org:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org:
USDOE Office of Science (SC). Biological and Environmental Research (BER) (SC-23); USDOE
Country of Publication:
United States
58 GEOSCIENCES; Mathematics; Planetary Sciences
OSTI Identifier:
Alternate Identifier(s):
OSTI ID: 1411342