Abstract
Lagrangian particle-tracking models (LPTMs) were used to identify sources, destinations, and transport pathways of particles (plankton). The LPTM simulations were forced using stored fields from the Spectral Element Ocean Model simulation for a coastal upwelling system having idealized geometry, bathymetry, and simple wind forcing. Forward-in-time-trajectory (FITT) simulations are common in ocean science, although they often do not include diffusion. Results from LPTM comparisons with and without diffusion suggest that ignoring diffusion can lead to incorrect identification of source or destination regions. FITT is efficient for identifying destinations from known sources, but inefficient for identifying sources from known destinations (or receptors). Backward-in-time-trajectory (BITT) modeling from known destinations efficiently identifies sources, or particle positions, at earlier times. Although advection and some biological processes (e.g., growth) are reversible and amenable to BITT simulations, other processes, such as physical diffusion, reproduction, and mortality, are not time reversible. The reliability of BITT-derived estimates of prior particle positions was evaluated using a BITT followed by a FITT coupled approach. The results suggest that BITT approaches are valuable in identifying probability densities of prior positions. Such information is particularly useful in the ocean sciences where many of the interesting questions concern where particles (e.g., plankton, meroplankton) have been (or came from) rather than where they are headed (identifying the destination). BITT simulations provide a computationally efficient technique to examine these questions.
Comparing Eddy‐Permitting Ocean Model Parameterizations via Lagrangian Particle Statistics in a Quasigeostrophic Setting
