Lagrangian data in a high-resolution numerical simulation of the North Atlantic I. Comparison with in situ drifter data

A model/data comparison was performed between simulated drifters from a hig h-resolution numerical simulation of the North Atlantic and a data set from in situ surface drifters. The comparison makes use of pseudo-Eulerian stat istics such as mean velocity and eddy kinetic energy, and Lagrangian statis tics such as integral time scales. The space and time distribution of the t wo data sets differ in the sense that the in situ drifters were released in homogeneously in space and time while the simulated drifters were homogeneo usly seeded at the same time over a regular 1 degrees grid. Despite this di fference, the total data distributions computed over the complete data sets show some similarities that are mostly related to the large-scale pattern of Ekman divergence / convergence. Comparisons of eddy kinetic energy and root mean square velocity indicate t hat the numerical model underestimates the eddy kinetic energy in the Gulf Stream extension and in the ocean interior. In addition, the model Lagrangi an time scales are longer in the interior than the in situ time scales by a pproximately a factor of 2. It is suggested that this is primarily due to t he lack of high-frequency winds in the model forcing, which causes an under estimation of the directly forced eddy variability. Regarding the mean flow , the comparison has been performed both qualitatively and quantitatively u sing James' statistical test. The results indicate that over most of the do main, the differences between model and in situ estimates are not significa nt. However, some areas of significant differences exist, close to high-ene rgy regions, notably around the Gulf Stream path, which in the model lies s lightly north of the observed path, although its strength and structure are well represented overall. Mean currents close to the buffer zones, primari ly the Azores Current, also exhibit significant differences between model r esults and in situ estimates. Possibilities for model improvement are discu ssed in terms of forcings, buffer zone implementations, turbulence and mixe d layer parameterizations, in light of our model/data comparison. (C) 2001 Elsevier Science B.V. All rights reserved.