1. What are the common applications of Lagrangian particle tracking in oceanography?
Lagrangian particle tracking is commonly used in various oceanographic applications such as pollutant dispersion, oil spills, harmful algal blooms, planktonic larvae, marine plastics, and search-and-rescue operations. It is a valuable tool for studying ocean transport features and is frequently employed in post-processing of existing oceanographic model runs. The tracking of particle trajectories can be performed 'online' along with velocity fields in ocean circulation models or 'offline' using stored hydrodynamic model output. Several offline particle tracking software packages have been developed for multiple applications in oceanography, including OceanParcels, Ichthyop, TRACMASS, PaTATO, OceanTracker, and Deft3D-PART 30. However, comparing different particle tracking models can be challenging due to the development of tracking codes for separate ocean models or forcing file formats. To address this, a well-established circulation model, LiveOcean, was utilized to evaluate the performance of popular particle tracking software packages in a uniform testbed. This evaluation included offline particle tracking codes like LTRANS, OpenDrift, and Particulator, as well as online passive dye experiments. The model, LiveOcean, is built using ROMS and simulates ocean circulation and biogeochemistry for the coastal and estuarine waters of the northern California Current System. It is widely used by stakeholders concerned with the effects of ocean acidification, hypoxia, harmful algal blooms, and larval transport on fisheries. The model's offline particle tracking code, Tracker, has been used to identify estuarine inflow sources and track harmful species trajectories to assist resource managers in decision-making. The evaluation of Tracker and other particle tracking codes aims to provide practical guidance for researchers in choosing the appropriate code for their specific needs.
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2. How does Tracker prevent particles from accumulating in low-diffusivity areas?
Tracker prevents particles from accumulating in low-diffusivity areas by implementing random displacement (as a modified random walk) in the vertical. This is achieved using a 4th-order Runge-Kutta solver for particle advection. The vertical particle position at time step n after advection is calculated using the equation 80, where R is a normal distributed random function with a mean of 0 and a standard deviation of 1. The vertical diffusivity, evaluated at (North et al., 2006), is used in the equation. The vertical profile of eddy diffusivity is smoothed using a 3-point Hanning window prior to calculating the vertical derivatives, similar to the smoothing technique applied in North et al., (2006). Additionally, the surface and bottom are adjusted to be equal to the values one grid point in to prevent particles close to the top or bottom from using near-zero diffusivity. Tracker also uses pre-computed nearest-neighbour search trees to find velocities and other fields, such as diffusivity, temperature, and salinity, used for moving each particle forward, speeding up computation for the large grid size of the model domain. To ensure trustworthy results, Tracker tests the preservation of vertical well-mixed conditions and the similarity to the dispersion of an inert dye.
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3. What dynamic settings were selected for WMC tests?
Six sites in different dynamic settings were selected for WMC tests, ranging from the deep 95 ocean to the Salish Sea. These sites were chosen to perform the well-mixed condition tests using LiveOcean's hydrodynamic output. The selected sites provided a diverse range of environments for testing the well-mixed condition in Tracker with specific parameters, such as horizontal and vertical advection turned off and a random displacement model implemented for the z direction. The tests aimed to evaluate the uniformity of particle distribution under different diffusivity profiles and timestep conditions.
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4. What are the applications of LTRANS particle tracking software?
LTRANS is a well-documented tool written in Fortran 90, specifically for output from ROMS. It has broad applications in studying larvae transport, oil spills, coastal connectivity, plastics, algae, and more. For instance, North et al. (2008) used LTRANS to study larvae transport, while Testa et al. (2016) utilized it for oil spill analysis. Li et al. (2014) employed LTRANS for coastal connectivity research, and Liang et al. (2021) used it to study plastics. Additionally, Wang et al. (2022) applied LTRANS to study algae. These examples demonstrate the versatility and wide-ranging applications of LTRANS in various fields of research.
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