September 19, 2006: Optimal Spectral Decomposition for Oceanic Currents: Applications to Lagrangian Data


Leonid M. Ivanov Research Scientist, Department of Mathematics, University of Southern California, CA
Ph.: (380)-656-3257; Fax: (380)-656-3688; e-mail:
M.S. in Physics (1979), Saint-Petersburg Technical University ( Saint-Petersburg, USSR)
Ph.D. in Physics and Mathematics (1983), Marine Hydrophysical Institute ( Sevastopol, USSR)

Current Research Interests: model predictability, small sample statistics, Lagrangian fluid dynamics, statistical analysis of drifters and floats data.

A technique for mapping oceanic currents from irregularly spaced observations collected from subsurface floats and surface drifters is discussed. Our approach uses two scalar representation for 3D non-divergence flows and specially constructed basis functions to formulate a weighted least-square fitting procedure with an information constraint (the cost function). The constraint selects the optimal solution from a set of solutions corresponding to sparse and noisy data. The technique is compared to Optimal Interpolation (OI) through several test examples. We illustrate our approach through the reconstructions of: (1) the large-scale surface circulation in the Southern Ocean from the FGGE data, (2) the basin scale circulation in the Black Sea from the MHI/NPS surface drifter observations, and (3) large-scale mid-depth circulation in the North Atlantic Ocean from ARGO float data. The primary focus of all these studies is on seasonal and inter-annual variability of the reconstructed currents.


[1] Eremeev V.N., L.M. Ivanov, A.D. Kirwan, (1992): Reconstruction of oceanic flow characteristics from quasi-Lagrangian data. Part I. Approach and mathematical methods J. Geophys. Res., 97, 9733-9742.
[2] Ivanov L.M., A.D. Kirwan, T.M. Margolina, (2001): Filtering noise from oceanographic data with some applications for the Kara and Black seas. J. Mar. Sys., 28,113-139.
[3] Chu P.C., L.M. Ivanov, et al., (2003): Analysis of sparse and noisy ocean current data using flow decomposition. Part I. Theory. J. Atmos. Ocean.Techn., 478-491.
[4} Chu P.C., L.M.Ivanov, et al., (2003): Analysis of sparse and noisy ocean current data using flow decomposition. Part II. Applications to Eulerian and Lagrangian data. ibid, 492-512.
[5] Danilov A.I, Ivanov L.M., et al. (2003): Variability of the surface circulation in the Southern Ocean reconstructed from the FGGE drifter observations. Geophys. Report of Russia Academy of Scinces, 391, 3, 1-5.
[6] Collins C.A., L.M.Ivanov , O.V. Mel’nichenko, and N. Garfield (2004): California Undercurrent variability and eddy transport estimated from RAFOS float observations. J. Geophys. Res., v.109, C05028, 1-19. [6] Chu P.C., L.M. Ivanov, O.V. Mel’nichenko, and N. Wells (2006): On long Rossby Waves in the Tropical North Atlantic observed from profiling floats. J. Geophys. Res., (submitted)
[7] Ivanov L. M., and O.V. Mel’nichenko (2006): Reconstruction of oceanic currents from irregularly spaced data. Part I. Mathematical background and tests. Ocean Modeling, (submitted)
[8] Mel’nichenko O.V., and L.M. Ivanov (2006): Reconstruction of oceanic currents from irregularly spaced data. Part II. Applications to Lagrangian and HF radar data. Ocean Modeling, (submitted).