Collaborative Research: Stochastic Transport Models for the Coastal Ocean

University Of California-Santa Barbara, Santa Barbara CA

Investigators

Abstract

ABSTRACT OCE-0352187 The PI's seek to determine optimal stochastic particle transport (i.e. Lagrangian) models for use in the coastal ocean which will provide a necessary link between the copious Eulerian coastal circulation data from high frequency (HF) radar systems, and transport information required by coastal resource managers tasked with identifying the fate of pollutants, larvae, and objects lost-at-sea. Specific research objectives are to (i) observe surface flow fields in two coastal regions using HF radar and high-resolution drifters, (ii) to develop accurate Lagrangian transport models to predict trajectories from the HF radar fields, (iii) to model trajectories and quantify their skill through comparisons with in-situ drifter tracks, and (iv) to compute redistribution kernel functions (RKFs), or connectivity matrices, and demonstrate their utility as simple probabilistic near-shore transport models. Existing trajectory models will be modified for consideration of flow patterns characteristic to the coastal ocean. A model with a large-scale mean component (U), a periodic component representing tidal and (near-) inertial motions (Up), and a Lagrangian stochastic component (model; LSM) for subgrid-scale motions (u) will be developed. The LSM will initially be based on high resolution drifter data. An LSM parameterization based on large-scale velocity information (e.g. integral time scales, eddy variance.) and coastal geomorphology will then be developed. This enables the trajectory models to be applied in all coastal regions with sufficient large-scale flow information. Model skill over a wide range of dynamic parameters (e.g. velocity, vorticity, eddy energy) will be quantified in the Santa Barbara (CA) and Miami (FL) coastal regions through comparisons with in-situ drifter tracks. RKFs, giving the probability that a particle released at some location x0 at time t0 will reach location x1 at t1, will be computed with modeled trajectories and evaluated as tools for predicting transport, or connectivity in the coastal ocean. An improved understanding of coastal circulation will result from subsequent identification of how and why RKFs vary spatially and temporally.