## 1. Introduction

[2] Regional coastal ocean observing systems exist in part to provide stakeholders with the best possible information for addressing a wide variety of applied coastal problems. Many applications are inherently Lagrangian, requiring trajectories to determine the “fate and transport” or “connectivity” of tracers. For example, coastal water quality management, ecosystem management, spill remediation, and search-and-rescue operations all require knowledge of dispersion from water parcel trajectories.

[3] Lagrangian applications in the turbulent ocean require statistical approaches, and thus a large number of observations. Probability distributions of water parcel location as a function of initial position and advection time (hereafter “Lagrangian PDFs”) are the required quantities. Direct observations with water following drifters are too sparse for computation of meaningful Lagrangian PDFs for more than a few combinations of initial position and advection time. Trajectories computed from numerical circulation models must therefore be relied on. In a recent study, *Mitarai et al.* [2009] determine Lagrangian PDFs with millions of trajectories computed from the Eulerian output of *Dong and McWilliams*' [2007] Southern California Regional Ocean Modeling System (ROMS) simulations. Results of the work by *Mitarai et al.* [2009] are a part of the planning process for designation of Marine Protected Areas in Southern California.

[4] Southern California ROMS simulations, the basis of *Mitarai et al.*'s [2009] Lagrangian PDFs, compare favorably with observations in a Eulerian sense [*Dong et al.*, 2009]. Comparisons show agreement in the first two statistical moments and lead *Dong et al.* [2009] to conclude, “The model results resemble the observations in terms of the spatial structure and magnitude of the mean, interannual, seasonal, and intraseasonal variations”. Eulerian agreement is not necessarily indicative of accuracy in trajectories, dispersion, or Lagrangian PDFs. Various Eulerian flow patterns can yield similar low order statistical moments, relatively small errors in Eulerian velocity statistics can become substantial when integrated and eddy structures can manifest themselves differently in Eulerian and Lagrangian frames [*Ohlmann and Niiler*, 2005].

[5] This paper uses *in situ* drifting buoy data to assess dispersion distributions from modeled trajectories in a purely Lagrangian sense. Such an assessment is necessary prior to using modeled trajectories and their derived products in applied problems. The analysis gives a spatially continuous distribution of model skill that can elucidate an improved understanding of both model performance and ocean circulation beyond that offered in a Eulerian assessment. Limited densities of Lagrangian observations typically preclude such studies.