OpenDrift v1.0: a generic framework for trajectory modeling

Abstract

Abstract.OpenDrift is an open-source Python-based framework for Lagrangian particle modeling under development at the Norwegian Meteorological Institute with contributions from the wider scientific community. The framework is highly generic and modular, and is designed to be used for any type of drift calculations in the ocean or atmosphere. A specific module within the OpenDrift framework corresponds to a Lagrangian particle model in the traditional sense. A number of modules 5 have already been developed, including an oil drift model, a stochastic search and rescue model, a pelagic egg model, and a basic module for atmospheric drift. The framework allows for the ingestion of an unspecified number of forcing fields (scalar and vectorial) from various sources, including Eulerian ocean, atmosphere and wave models, but also measurements or subjective estimates of the same variables. A basic backtracking mechanism is inherent, using sign reversal of the total 10 displacement vector and negative time stepping. OpenDrift is fast and simple to set up and use on Linux, Mac and Windows environments, and can be used with minimal or no Python experience.It is designed for flexibility, and researchers may easily adapt or write modules for their specific purpose. OpenDrift is also designed for performance, and simulations with millions of particles may be performed on a laptop. Further, OpenDrift is designed for robustness, and is in daily operational 15 use for emergency preparedness modeling (oil drift, search and rescue and drifting ships) at the Norwegian Meteorological Institute.

Modeling Environmental DNA Transport in the Coastal Ocean Using Lagrangian Particle Tracking

“…The open-source particle tracking software OpenDrift (Dagestad et al, 2017) was used to track eDNA transport in MB. We chose to simulate eDNA transport using Lagrangian particle tracking due to the extensive literature modeling larvae and plankton using Lagrangian particle tracking (Hunter, 1987;Huret et al, 2007;Edwards et al, 2008;Lett et al, 2008;Navas et al, 2011;Thygesen, 2011;Drake et al, 2013;Robins et al, 2013;Dagestad et al, 2017). OpenDrift uses the Eulerian velocity fields generated by the ROMS model simulation and a second-order Runge-Kutta scheme to transport particles within the domain.…”

The Fate of Marine Litter in Semi-Enclosed Seas: A Case Study of the Black Sea

“…Experiments were carried out offline using the surface velocity and Stokes drift data from the Copernicus circulation and wave models, respectively. The Lagrangian model is the freely available open-source model OpenDrift (Dagestad et al, 2017), which uses a second-order Runge-Kutta method neglecting vertical velocities (it is emphasized that we simulate FML, that is, particles, which are at the surface at all times). The coefficient of horizontal diffusion is considered a function of grid size l:…”

Circulation of the European Northwest Shelf: A Lagrangian perspective

“…In one class of experiments (#1 and 4-6 in Table 2), the particles were seeded at 1 m (surface particles), as well as in the grid cells just above the seafloor (bottom particles). In the second experiment (#2 in Table 2) named CR-V, particles were released in a 100 km wide stripe extending oceanward from the 150 m isobath starting in the Bay of Biscay and ending north of the Shetland Islands at 61.7° N; in this experiment, particles were seeded vertically every 20 m. In a third experiment (#3 in Table 2) named CR-B, the particle tracking process was carried out offline; for this purpose, the freely available open-source model OpenDrift (Dagestad et al, 2017) was used, in which the particles were advected by a 2 nd -order Runge-Kutta scheme. The offline calculation was performed backward in time at a constant depth with a velocity input time step, a model time step and an output time step of 1 h. The particle release depth in this experiment was 1 m.…”