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Researchers:
- 1RSMAS, Miami Sponsors: Publications: -Veneziani M., A. Griffa and P.M. Poulain 2006: Historical drifter data and statistical prediction of particle motion: a case study in the Adriatic Sea, J. Atmos. Ocean Tech, in press, (PDF) - Veneziani, M., A. Griffa, A.M. Reynolds, Z.D. Garraffo, and E.P. Chassignet, 2005: Parameterizations of Lagrangian spin statistics and particle dispersion in presence of coherent vortices., J. Mar. Res., 63, 1057-1083, (PDF). - Veneziani, M., A. Griffa, Z.D. Garraffo, and E.P. Chassignet, 2005: Lagrangian spin parameter and coherent structures from trajectories released in a high-resolution ocean model. J. Mar. Res., 63, issue 4, 753-788, (PDF). - Maurizi A., A. Griffa, P.M. Poulain and F. Tampieri, 2004: Lagrangian turbulence in the Adriatic Sea as computed from drifter data: effects of inhomogeneity and nonstationarity. J. Geophys. Res., 109, C04010, doi:10.1029/2003JC002119 - Veneziani M., A. Griffa, A.M. Reynolds and A.J. Mariano, 2004: Oceanic turbulence and stochastic models from subsurface Lagrangian data for the North-West Atlantic Ocean. J. Phys. Oceanogr., 34, (8), 1884-1906. - Reynolds, A.M. and M. Veneziani, 2004: Rotational dynamics of turbulence and Tsallis statistics. Phys. Lett. A, 327, 9-14. - Bauer, S., M.S. Swenson and A. Griffa, 2002: Eddy-mean flow decomposition and eddy diffusivity estimates in the tropical Pacific Ocean. 2: Results. J. Geophys. Res., 107, (C10), 3154-3171. - Garraffo, Z., A. Mariano, A. Griffa, C. Veneziani and E. Chassignet, 2001: Lagrangian data in a high resolution model simulation of the North Atlantic. 1: Comparison with in-situ drifters. J. Mar. Sys., 29, 157-176. - Garraffo, Z., A. Griffa, A. Mariano and E. Chassignet, 2001: Lagrangian data in a high resolution model simulation of the North Atlantic. 2: Mean flow reconstruction and sampling effects. J. Mar. Sys., 29, 177-200. - Falco P., A. Griffa, P.M. Poulain, E. Zambianchi, 2000: Transport properties in the Adriatic Sea as deduced from drifter data. J. Phys. Oceanogr., 30, (8), 2055-2071. |
Lagrangian data provide information on ocean currents in terms of velocity and transport. Extensive data sets are available today, both at and below the ocean surface, thanks to a number of extensive field experiments. The data have been analyzed by a number of authors, providing significant contributions to our knowledge of the ocean circulation and transport. Dispersion and Parameterizations We have analyzed data sets of surface drifters in the Adriatic Sea(Maurizi et al.,2004) and the Topical Pacific (Bauer et al.,2002) and a set of subsurface floats in the North Atlantic (Veneziani et al.,2004). Our focus is characterizing dispersion processes and testing suitable transport parameterizations, in particular in terms of Lagrangian Stochastic (LS) models. In the following, we provide some specific information on the North Atlantic study. The historical data set provided by 700 m acoustically-tracked floats has been analyzed in different regions of the north-western Atlantic Ocean. (Fig. 1, Fig. 2). In the Gulf Stream recirculation and extension regions, the autocovariances and crosscovariances of the Lagrangian velocity exhibit significant oscillatory patterns on time scales comparable with the Lagrangian decorrelation time scale. They are indicative of the presence of significant coherent structures and of sub- and super-diffusive behaviors in the mean spreading of water particles. Our main result is that the properties of the Lagrangian statistics can be considered as a superposition of two different regimes associated with looping and non-looping trajectories (Fig. 3), and that both regimes can be parameterized using a simple first-order Lagrangian stochastic model with spin parameter. The non-looping regime corresponds to an approximately homogeneous "background" flow, while the looping regime is characteristics of the coherent structures. The spin parameter couples the zonal and meridional velocity components, reproducing the effect of rotating vortices. It is considered as a random parameter whose probability distribution is approximately bi-modal, reflecting the distribution of loopers (finite spin) and non-loopers (zero spin). The simple model is found to be very effective in reproducing the statistical properties of the data (Fig. 4). Supplementary analysis has been performed using a synthetic data set of trajectories released in a high resolution Miami Isopycnic Model (MICOM) (Fig. 5). The goal is to investigate the relationship between Langrangian and Eulerian statistics, and in particular to verify whether the spin parameter can be interpreted as a relative vorticity estimate of the coherent structures (Fig. 6).
Transport processes in
coastal flows
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