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Lagrangian predictability of high-resolution regional models: the special case of the Gulf of Mexico
1Naval Ocean Analysis and Prediction Laboratory, Department of Oceanography, Naval Postgraduate School, Monterey, California, 93943, USA
2Marine Hydrophysical Institute, the Ukrainian National Academy of Sciences, Kapitanskaya 2, Sevastopol, 99011, Ukraine
3University of Colorado, Boulder, Colorado, 80309, USA
Abstract. The Lagrangian prediction skill (model ability to reproduce Lagrangian drifter trajectories) of the nowcast/forecast system developed for the Gulf of Mexico at the University of Colorado at Boulder is examined through comparison with real drifter observations. Model prediction error (MPE), singular values (SVs) and irreversible-skill time (IT) are used as quantitative measures of the examination. Divergent (poloidal) and nondivergent (toroidal) components of the circulation attractor at 50m depth are analyzed and compared with the Lagrangian drifter buoy data using the empirical orthogonal function (EOF) decomposition and the measures, respectively. Irregular (probably, chaotic) dynamics of the circulation attractor reproduced by the nowcast/forecast system is analyzed through Lyapunov dimension, global entropies, toroidal and poloidal kinetic energies. The results allow assuming exponential growth of prediction error on the attractor. On the other hand, the
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Citation: Chu, P. C., Ivanov, L. M., Kantha, L. H., Margolina, T. M., Melnichenko, O. V., and Poberezhny, Y. A.: Lagrangian predictability of high-resolution regional models: the special case of the Gulf of Mexico, Nonlin. Processes Geophys., 11, 47-66, 2004. Bibtex EndNote Reference Manager
