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7 - Lagrangian data assimilation in ocean general circulation models
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- By Anne Molcard, LSEET, University of Toulon, France, Tamay M. Özgökmen, Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, Florida, USA, Annalisa Griffa, Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, Florida, USA; ISMAR/CNR, La Spezia, Italy, Leonid I. Piterbarg, Department of Mathematics, University of Southern California, Los Angeles, California, USA, Toshio M. Chin, Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, Florida, USA; Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
- Edited by Annalisa Griffa, University of Miami, A. D. Kirwan, Jr., University of Delaware, Arthur J. Mariano, University of Miami, Tamay Özgökmen, University of Miami, H. Thomas Rossby, University of Rhode Island
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- Book:
- Lagrangian Analysis and Prediction of Coastal and Ocean Dynamics
- Published online:
- 07 September 2009
- Print publication:
- 10 May 2007, pp 172-203
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Summary
Introduction
In the last 20 years, the deployment of surface and subsurface buoys has increased significantly, and the scientific community is now focusing on the development of new techniques to maximize the use of these data. As shown by Davis (1983, 1991), oceanic observations of quasi-Lagrangian floats provide a useful and direct description of lateral advection and eddy dispersal. Data from surface drifters and subsurface floats have been intensively used to describe the main statistics of the general circulation in most of the world ocean, in terms of mean flow structure, second-order statistics and transport properties (e.g. Owens, 1991; Richardson, 1993; Fratantoni, 2001; Zhang et al., 2001; Bauer et al., 2002; Niiler et al., 2003; Reverdin et al., 2003). Translation, swirl speed and evolution of surface temperature in warm-core rings, which are ubiquitous in the oceans, have also been studied with floats by releasing them inside of the eddies (Hansen and Maul, 1991). Trajectories of freely drifting buoys allow estimation of horizontal divergence and vertical velocity in the mixed layer (Poulain, 1993). Also, data from drifters allows investigation of properties and statistics of near-inertial waves, which provide much of the shear responsible for mixing in the upper thermocline and entrainment at the base of the mixed layer (Poulain et al., 1992). Drifters have proved to be robust autonomous platforms with which to observe ocean circulation and return data from a variety of sensors.
8 - Dynamic consistency and Lagrangian data in oceanography: mapping, assimilation, and optimization schemes
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- By Toshio M. Chin, Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, Florida, USA, Kayo Ide, University of California at Los Angeles, Los Angeles, California, USA, Christopher K. R. T. Jones, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA, Leonid Kuznetsov, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA, Arthur J. Mariano, Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, Florida, USA
- Edited by Annalisa Griffa, University of Miami, A. D. Kirwan, Jr., University of Delaware, Arthur J. Mariano, University of Miami, Tamay Özgökmen, University of Miami, H. Thomas Rossby, University of Rhode Island
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- Book:
- Lagrangian Analysis and Prediction of Coastal and Ocean Dynamics
- Published online:
- 07 September 2009
- Print publication:
- 10 May 2007, pp 204-230
-
- Chapter
- Export citation
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Summary
Introduction
As illustrated throughout this book, Lagrangian data can provide us with a unique perspective on the study of geophysical fluid dynamics, particle dispersion, and general circulation. Drifting buoys, floats, and even a crate-full of rubber ducks or athletic shoes lost in mid-ocean (Christopherson, 2000) may be used to gain insights into ocean circulation. All Lagrangian instruments will be referred to as “drifters” hereafter for simplicity. Because movement of a drifter tends to follow that of a water parcel, the primary attributes of Lagrangian measurements are (i) horizontal coverage due to dispersion in time, (ii) that many of the observed variables obey conservation laws approximately over some lengths of time, and (iii) their ability to trace circulation features such as meanders and vortices at a wide range of spatial scales. Due mainly to inherently irregular spatial distributions, the Lagrangian measurements must first be interpolated for most applications. As we will see, the design of interpolation and mapping schemes that can preserve the Lagrangian attributes is often non-trivial.
To observe finer dynamical details of oceanic and coastal phenomena and to forecast drifter trajectories more accurately (for search-and-rescue operation, spill containment, and so on), Lagrangian data afford a particularly informative and novel perspective if they are combined with a dynamical model, rather than mapped by a standard synoptic-scale interpolation procedure which can smear some details at smaller and faster scales. Data assimilation can be viewed as a methodology for imposing dynamical consistency upon observed data for the purpose of space-time interpolation.