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7 - Lagrangian data assimilation in ocean general circulation models

Published online by Cambridge University Press:  07 September 2009

By
Anne Molcard ,
Tamay M. Özgökmen ,
Annalisa Griffa ,
Leonid I. Piterbarg  and
Toshio M. Chin
Edited by
Annalisa Griffa ,
A. D. Kirwan, Jr. ,
Arthur J. Mariano ,
Tamay Özgökmen  and
H. Thomas Rossby
Anne Molcard
Affiliation:
LSEET, University of Toulon, France
Tamay M. Özgökmen
Affiliation:
Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, Florida, USA
Annalisa Griffa
Affiliation:
Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, Florida, USA; ISMAR/CNR, La Spezia, Italy
Leonid I. Piterbarg
Affiliation:
Department of Mathematics, University of Southern California, Los Angeles, California, USA
Toshio M. Chin
Affiliation:
Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, Florida, USA; Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
Annalisa Griffa
Affiliation:
University of Miami
A. D. Kirwan, Jr.
Affiliation:
University of Delaware
Arthur J. Mariano
Affiliation:
University of Miami
Tamay Özgökmen
Affiliation:
University of Miami
H. Thomas Rossby
Affiliation:
University of Rhode Island
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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.

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Lagrangian Analysis and Prediction of Coastal and Ocean Dynamics , pp. 172 - 203
Publisher: Cambridge University Press
Print publication year: 2007

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References

Aref, H., 1984. Mixing by chaotic advection. J. Fluid Mech., 143, 1–24.CrossRefGoogle Scholar
Bauer, S., Swenson, M. S., and Griffa, A., 2002. Eddy-mean flow decomposition and eddy-diffusivity estimates in the tropical Pacific Ocean. 2. Results. J. Geophys. Res., 107, 3154–71.CrossRefGoogle Scholar
Bennett, A. F., 1992. Inverse Methods in Physical Oceanography. New York: Cambridge University Press.CrossRefGoogle Scholar
Berloff, P. and McWilliams, J. C., 2002. Material transport in oceanic gyres. Part II: Hierarchy of stochastic models. J. Phys. Oceanogr., 32, 797–830.2.0.CO;2>CrossRefGoogle Scholar
Bleck, R. and Boudra, D. B., 1986. Wind-driven spin-up eddy-resolving ocean models formulated in isopycnic and isobaric coordinates. J. Geophys. Res., 91/C, 7611–21.CrossRefGoogle Scholar
Bleck, R., Hanson, H. P., Hu, D., and Kraus, E. B., 1989. Mixed layer-thermocline interaction in a three-dimensional isopycnic coordinate model. J. Phys. Oceanogr., 19C, 1417–39.2.0.CO;2>CrossRefGoogle Scholar
Bleck, R., Rooth, C., Hu, D., and Smith, L. T., 1992. Ventilation and mode water formation in a wind- and thermohaline-driven isopycnic coordinate model of the North Atlantic. J. Phys. Oceanogr., 22, 1486–1505.2.0.CO;2>CrossRefGoogle Scholar
Cane, M. A., Kaplan, A., Miller, R. N., Tang, B., Hackert, E. C., and Busalacchi, A. J., 1996. Mapping tropical Pacific sea level: Data assimilation via a reduced state space Kalman filter. J. Phys. Oceanogr., 101, 22599–617.Google Scholar
Carter, E. F., 1989. Assimilation of Lagrangian data into a numerical model. Dyn. Atmos. Oceans, 13, 335–48.CrossRefGoogle Scholar
Chin, T. M., Mariano, A. J., and Chassignet, E. P., 1999. Spatial regression with Markov Random Fields for Kalman filter approximation in least-squares solution of oceanic data assimilation problems. J. Geophys. Res., 104, 1233–57.Google Scholar
Chin, T. M., Haza, A. C., and Mariano, A. J., 2002. A reduced-order information filter for multi-layer shallow water models: profiling and assimilation of sea surface height. J. Atmos. Ocean. Tech., 19(4), 517–33.2.0.CO;2>CrossRefGoogle Scholar
Davis, R. E., 1983. Oceanic property transport, Lagrangian particle statistics, and their prediction. J. Mar. Res., 41, 163–94.CrossRefGoogle Scholar
Davis, R. E., 1991. Observing the general circulation with floats. Deep-Sea Res., 38, 5531–71.CrossRefGoogle Scholar
Davis, R. E., 1996. Comparison of Autonomous Lagrangian Circulation Explorer and fine resolution Antarctic model results in the South Atlantic. J. Geophys. Res., 101, C1, 855–84.CrossRefGoogle Scholar
Davis, R., 1998. Preliminary results from directly measuring mid-depth circulation in the Tropical and South Pacific. J. Geophys. Res., 103, 24619–39.CrossRefGoogle Scholar
Evensen, G., D. P. Dee, and J. Schroter, 1998. Parameter estimation in dynamical models. In Ocean Modeling and Parameterization, ed. Chassignet, E. P. and Veron, J.. Dordrecht: Kluwer Academic Publishers, 373–98.CrossRefGoogle Scholar
Fratantoni, D. M., 2001. North Atlantic surface circulation during the 1990s observed with satellite-tracked drifters. J. Geophys. Res., 106, 22,067–93.CrossRefGoogle Scholar
Garraffo, Z. D., Mariano, A. J., Griffa, A., Veneziani, C., and Chassignet, E. P., 2001. Lagrangian data in a high-resolution numerical simulation of the North Atlantic. 1. Comparison with in situ drifter data. J. Mar. Sys., 29, 157–76.CrossRefGoogle Scholar
Ghil, M. and Malanotte-Rizzoli, P., 1991. Data assimilation in meteorology and oceanography. Adv. Geophy., 33, 141–266.CrossRefGoogle Scholar
Griffa, A., 1996. Applications of stochastic particle models to oceanographic problems. In Stochastic Modeling in Physical Oceanography, ed. Adler, R., Muller, P., Rozovskiim, B.. Cambridge, MA: Birkhauser Boston, 113–28.CrossRefGoogle Scholar
Hansen, D. V. and Maul, G. A., 1991. Anticyclonic current rings in the eastern tropical Pacific Ocean. J. Geophys. Res., 96, 6965–79.CrossRefGoogle Scholar
Hansen, D. V. and Poulain, P.-M., 1996. Quality control and interpolations of WOCE/TOGA drifter data. J. Atmos. Oceanic Tec., 13, 900–9.2.0.CO;2>CrossRefGoogle Scholar
Hernandez, F., Traon, P. Y., and Barth, N. H., 1995. Optimizing a drifter cast strategy with a genetic algorithm. J. Atmos. Ocean Tech., 12, 330–45.2.0.CO;2>CrossRefGoogle Scholar
Holland, W. R., 1978. The role of mesoscale eddies in the general circulation of the ocean. J. Phys. Oceanogr., 22, 1033–46.Google Scholar
Ide, K. and Ghil, M., 1997a. Extended Kalman filtering for vortex systems. Part I: Methodology and point vortices. Dyn. Atm. Oceans, 27, 301–32.CrossRefGoogle Scholar
Ide, K. and Ghil, M., 1997b. Extended Kalman filtering for vortex systems. Part II: Rankine vortices and observing system design. Dyn. Atm. Oceans, 27, 333–50.CrossRefGoogle Scholar
Ide, K., Kuznetsov, L., and Jones, C. K. R. T., 2002. Lagrangian data assimilation for point-vortex system. J. Turbulence, 3, 053.CrossRefGoogle Scholar
Ishikawa, Y. I., Awaji, T., and Akimoto, K., 1996. Successive correction of the mean sea surface height by the simultaneous assimilation of drifting buoy and altimetric data. J. Phys. Oceanogr., 26, 2381–97.2.0.CO;2>CrossRefGoogle Scholar
Kamachi, M. and O'Brien, J. J., 1995. Continuous assimilation of drifting buoy trajectories into an equatorial Pacific Ocean model. J. Mar. Sys., 6, 159–78.CrossRefGoogle Scholar
Kuznetsov, L., Toner, M., Kirwan, A. D., Jones, C. K. R. T., Kantha, L. H., and Choi, J., 2002. The Loop Current and adjacent rings delineated by Lagrangian analysis of near-surface flow. J. Mar. Res., 60, 405–29.CrossRefGoogle Scholar
Lorenc, A. C., 2000. A Bayesian approach to observation quality control in variational and statistical assimilation. Proceedings of Aha Huliko Hawaiian Winter Workshop, 249–63.Google Scholar
Malanotte-Rizzoli, P. and Holland, W. R., 1988. Data constraint applied to models of the ocean general circulation. Part 2. The transient, eddy resolving case. J. Phys. Oceanogr., 18, 1093–107.2.0.CO;2>CrossRefGoogle Scholar
McClean, J. L., Poulain, P.-M., and Pelton, J. W., 2002. Eulerian and Lagrangian statistics from surface drifters and a high-resolution POP simulation in the North Atlantic. J. Phys. Oceanogr., 32, 2472–91.CrossRefGoogle Scholar
Molcard, A., Griffa, A., and Özgökmen, T. M., 2005. Lagrangian data assimilation in multi-layer primitive equation ocean models. J. Atmos. Ocean. Tech., 22, 1, 70–83.CrossRefGoogle Scholar
Molcard, A., Piterbarg, L. I., Griffa, A., Özgökmen, T. M., and Mariano, A. J., 2003. Assimilation of drifter positions for the reconstruction of the Eulerian circulation field. J. Geophys. Res., 108, C3, 3056.CrossRefGoogle Scholar
Niiler, P. P., Maximenko, N. A., Panteleev, G. G., Yamagata, T., and Olson, D. B., 2003. Near surface dynamical structure of the Kuroshio extension. J. Geophys. Res., 108, C6.CrossRefGoogle Scholar
Oschlies, A. and Willebrand, J., 1996. Assimilation of Geosat altimeter data into an eddy-resolving primitive equation model of the North Atlantic Ocean. J. Geophys. Res., 101/C6, 14,175–90.CrossRefGoogle Scholar
Owens, W. B., 1991. A statistical description of the mean circulation and eddy variability in the northwestern Atlantic using SOFAR floats. Prog. Oceanogr., 28, 257–303.CrossRefGoogle Scholar
Özgökmen, T. M., Molcard, A., Chin, T. M., Piterbarg, L. I., and Griffa, A., 2003. Assimilation of drifter positions in primitive equation models of midlatitude ocean circulation. J. Geophys. Res., 108, C7, 3238.CrossRefGoogle Scholar
Poje, A. C., Toner, M., Kirwan, A. D. Jr., and Jones, C. K. R. T., 2002. Drifter launch strategies based on Lagrangian templates. J. Phys. Oceanogr., 32, 1855–69.2.0.CO;2>CrossRefGoogle Scholar
Poulain, P. M., 1993. Estimates of horizontal divergence and vertical velocity in the equatorial Pacific. J. Phys. Oceanogr., 23/4, 601–7.2.0.CO;2>CrossRefGoogle Scholar
Poulain, P. M., Luther, D. S., and Patzert, W. C., 1992. Deriving inertial wave characteristics from surface drifter velocities – frequency variability in the Tropical Pacific. J. Geophys. Res., 97(C11), 17947–59.CrossRefGoogle Scholar
Richardson, P. L., 1993. A census of eddies observed in North Atlantic SOFAR float data. Prog. Oceanogr., 31, 1–50.CrossRefGoogle Scholar
Reverdin, G., Niiler, P. P., and Valdimarsson, H., 2003. North Atlantic Ocean surface currents. J. Geophys. Res., 108, C1, 3002.CrossRefGoogle Scholar
Samelson, R. M., 1992. Fluid exchange across a meandering jet. J. Phys. Oceanogr., 22, 431–40.2.0.CO;2>CrossRefGoogle Scholar
Samelson, R. M., 1996. Chaotic transport by mesoscale motions. In Stochastic Modeling in Physical Oceanography, ed. Adler, R. J., Müuller, P., and Rozovskii, B.. Cambridge, MA: Birkhäuser Boston, 423–38.CrossRefGoogle Scholar
Smith, R. D., Maltrud, M. E., Bryan, F. O., and Hecht, M. W., 2000. Numerical simulation of the North Atlantic ocean at 1/10°. J. Phys. Oceanogr., 30, 1532–61.2.0.CO;2>CrossRefGoogle Scholar
Toner, M., Poje, A. C., Kirwan, A. D., Jones, C. K. R. T., Lipphardt, B. L., and Grosch, C. E., 2001. Reconstructing basin-scale Eulerian velocity fields from simulated drifter data. J. Phys. Oceanogr., 31, 1361–76.2.0.CO;2>CrossRefGoogle Scholar
Veneziani, M., Griffa, A., Reynolds, A. M., and Mariano, A. J., 2004. Oceanic turbulence and stochastic models from subsurface Lagrangian data for the North-West Atlantic Ocean. J. Phys. Oceanogr., 34(8), 1884–906.2.0.CO;2>CrossRefGoogle Scholar
Zhang, H.-M., Prater, M. D., and Rossby, T., 2001. Isopycnal Lagrangian statistics from the North Atlantic Current RAFOS floats observations. J. Geophys. Res., 106, 13, 817–36.CrossRefGoogle Scholar

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