The Parcels v2.0 Lagrangian framework: new field interpolation schemes

Delandmeter, Philippe; Sebille, Erik van

doi:10.5194/gmd-12-3571-2019

Cited by 262 publications

(196 citation statements)

References 47 publications

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“…org (last access: 1 August 2019). The Elipot et al (2016) Global Drifter Program drifter data are available at ftp://ftp. aoml.noaa.gov/phod/pub/buoydata/hourly_product/v1.02/ (last access: 1 August 2019).…”

Section: Conclusion and Discussionmentioning

confidence: 99%

“…There is some observational data on pathways into the Galápagos region from satellite-tracked surface drifters in the real ocean. However, of the more than 30 000 drifters in the Global Drifter Program (GDP) (Elipot et al, 2016), only 40 crossed the Galápagos Archipelago region, defined as between 91.8-89 • W and 1.4 (Fig. 1).…”

Section: Introductionmentioning

confidence: 99%

“…1 of Onink et al, 2019), but because Stokes drift has large spatial coherence patterns its long-term effect on particle transport can be significant (Fraser et al, 2018). (Elipot et al, 2016). Panel (a) shows drifter trajectories before they arrive in the Galápagos region.…”

Section: Introductionmentioning

confidence: 99%

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Basin-scale sources and pathways of microplastic that ends up in the Galápagos Archipelago

et al. 2019

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Abstract. The Galápagos Archipelago and Galápagos Marine Reserve lie 1000 km off the coast of Ecuador and are among the world's most iconic wildlife refuges. However, plastic litter is now found even in this remote island archipelago. Prior to this study, the sources of this plastic litter on Galápagos coastlines were unidentified. Local sources are widely expected to be small, given the limited population and environmentally conscious tourism industry. Here, we show that remote sources of plastic pollution are also fairly localised and limited to nearby fishing regions and South American and Central American coastlines, in particular northern Peru and southern Ecuador. Using virtual floating plastic particles transported in high-resolution ocean surface currents, we analysed the plastic origin and fate using pathways and connectivity between the Galápagos region and the coastlines as well as known fishery locations around the east Pacific Ocean. We also analysed how incorporation of wave-driven currents (Stokes drift) affects these pathways and connectivity. We found that only virtual particles that enter the ocean from Peru, Ecuador, and (when waves are not taken into account) Colombia can reach the Galápagos region. It takes these particles a few months to travel from their coastal sources on the American continent to the Galápagos region. The connectivity does not seem to vary substantially between El Niño and La Niña years. Identifying these sources and the timing and patterns of the transport can be useful for identifying integrated management opportunities to reduce plastic pollution from reaching the Galápagos Archipelago.

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Section: Conclusion and Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Basin-scale sources and pathways of microplastic that ends up in the Galápagos Archipelago

et al. 2019

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“…To investigate oceanographic larval dispersal from the identified spawning periods, particle tracking experiments were run using an offline Lagrangian particle tracking model, PARCELS “Probably A Really Computationally Efficient Lagrangian Simulator” (Delandmeter & Van Sebille, 2019; Lange & Van Sebille, 2017), described below. These simulations used the velocity fields from a Regional Oceanographic Modelling System (ROMS 3.4) configuration of the East Australian Current System (Kerry & Roughan, 2020a).…”

Section: Methodsmentioning

confidence: 99%

Multiple spawning events promote increased larval dispersal of a predatory fish in a western boundary current

Schilling

Everett

Smith

et al. 2020

Fisheries Oceanography

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Transport of larvae by ocean currents is an important dispersal mechanism for many species. The timing and location of spawning can have a large influence on settlement location. Shifts in the known spawning habitat of fish, whether due to climate or the discovery of new spawning stock, can influence the distribution of juveniles and our understanding of connectivity. The globally distributed species; Pomatomus saltatrix, is one such example where a previously unrecognised summer spawning event and a more southern latitudinal extent was recently reported for the southwest Pacific population. Although restrictions are in place to protect the traditional spawning event, the importance of the newly recognised summer spawning event is uncertain. Here, we investigate larval dispersal of P. saltatrix using particle tracking simulations to identify the contributions of the different spawning events to settlement. By modelling dispersal of larvae released in northern and mid‐latitude regions over the Austral spring and summer, we show that the newly recognised mid‐latitude summer spawning event contributes over 50% of the larvae reaching southern latitudes. This is due to a reduced (1–2 days) pelagic larval duration (associated with temperature), resulting in reduced larval mortality, and the seasonal (summer) strengthening of the East Australian Current (EAC) transporting particles ~50 km further south. These findings demonstrate that in dynamic boundary current systems such as the EAC, the final settlement location of larvae that are transported by ocean currents can vary considerably depending on the timing and location of spawning and that multiple spawning events are important for maximum dispersal.

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“…Our dataset starts on January 5, 2000, and has a temporal resolution of 5 days. We use the Parcels framework version 1.1.0 [23] (http:// oceanparcels.org) for the particle advection with the C-grid interpolation scheme described in [24]. Trajectories are integrated with the 4th-order Runge-Kutta method, with a time step of 10 minutes.…”

Section: Methodsmentioning

confidence: 99%

Mixing of passive tracers at the ocean surface and its implications for plastic transport modelling

Wichmann

Delandmeter

Dijkstra

et al. 2019

Environ. Res. Commun.

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The tracking of virtual particles is one of the main numerical tools to understand the global dispersion of marine plastic debris and has been successful in explaining the global-scale accumulation patterns of surface microplastic, often called 'garbage patches'. Yet, the inherent inaccuracies in plastic input scenarios and ocean circulation model results produce uncertainties in particle trajectories, which amplify due to the chaotic property of the surface ocean flow. Within this chaotic system, the subtropical 'garbage patches' correspond to the attractor. These facts make the large scale surface ocean circulation a mixing dynamical system, which means that the information of a particle's initial location is lost over time. We use mixing entropy and Markov chain mixing of the transfer operator associated with surface ocean transport to quantify the time scales of mixing for the global surface ocean in each subtropical basin. In the largest parts of all basins we find mixing times in the order of or below 10 years, which is lower than typical simulation times for surface plastic transport simulations. Maximum mixing times of more than 10 years are found in some parts of the North and South Pacific. Our results have important implications for global dispersion modelling of floating materials on the basin scale: precise initial information has little relevance for long term simulations, and there is a temporal limit after which the backtracking of particles is not meaningful any more.

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The Parcels v2.0 Lagrangian framework: new field interpolation schemes

Cited by 262 publications

References 47 publications

Basin-scale sources and pathways of microplastic that ends up in the Galápagos Archipelago

Basin-scale sources and pathways of microplastic that ends up in the Galápagos Archipelago

Multiple spawning events promote increased larval dispersal of a predatory fish in a western boundary current

Mixing of passive tracers at the ocean surface and its implications for plastic transport modelling

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