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The Lagrangian prediction skill (model ability to reproduce Lagrangian drifter trajectories) of the now- cast/forecast system developed for the Gulf of Mexico at the University of Colorado at Boulder is examined through com- parison with real drifter observations. Model prediction error (MPE), singular values (SVs) and irreversible-skill time (IT) are used as quantitative measures of the examination. Di- vergent (poloidal) and nondivergent (toroidal) components of the circulation attractor at 50 m depth are analyzed and com- pared with the Lagrangian drifter buoy data using the empir- ical orthogonal function (EOF) decomposition and the mea- sures, respectively. Irregular (probably, chaotic) dynamics of the circulation attractor reproduced by the nowcast/forecast system is analyzed through Lyapunov dimension, global en- tropies, toroidal and poloidal kinetic energies. The results al- low assuming exponential growth of prediction error on the attractor. On the other hand, the q-th moment of MPE grows by the power law with exponent of 3q/4. The probability density function (PDF) of MPE has a symmetrical but non- Gaussian shape for both the short and long prediction times and for spatial scales ranging from 20 km to 300 km. The phenomenological model of MPE based on a diffusion-like equation is developed. The PDF of IT is non-symmetric with a long tail stretched towards large ITs. The power decay of the tail was faster than 2 for long prediction times. whole spectrum of ocean motions, including meso- and submesoscale eddies, various waves, inertial and semi- diurnal motions, and provide invaluable resources to estimate the nowcast/forecast skill of high-resolution regional ocean models in terms of model ability to simulate from synoptic

Lagrangian predictability of high-resolution regional models: the special case of the Gulf of Mexico